From 238b7df16126830ab7dffc80fcd143a04e88511f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sat, 20 Sep 2025 20:16:04 +0900 Subject: [PATCH 01/16] did week 1 update book/ate/did.ipynb with new version --- book/ate/did.ipynb | 1256 +++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 1235 insertions(+), 21 deletions(-) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index 5feb084..9537da1 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -2,6 +2,7 @@ "cells": [ { "cell_type": "markdown", + "id": "2fa76ef6", "metadata": {}, "source": [ "# Difference-in-Difference (DiD)" @@ -9,48 +10,1219 @@ }, { "cell_type": "markdown", + "id": "8a671f4c", "metadata": {}, "source": [ - "- Basic DiD (2X2 with 사전평행)\n", - "- Control과 함께 DiD, DML을 이용한 DiD\n", - "- Staggered DiD, 2WFE\n", - "- DDD, Event Study\n", - "- 사전 평행 추세에 대한 통계적인 검정을 확인할 수 있는 파이썬 코드 필요. (matheus facure 책에서 쉽게 찾기 어려운 것 같습니다)" + "- 출처\n", + " - 실무로 통하는 인과추론 with 파이썬" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "plaintext" + "execution_count": 1, + "id": "f1cc97bd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: toolz in /Users/kimsieun/대학원/가짜연구소/11기/fack_cl/lib/python3.10/site-packages (1.0.0)\n", + "\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m25.1.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.2\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" + ] + } + ], + "source": [ + "!pip install toolz" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "ac5e48f1", + "metadata": {}, + 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"\n", + "from cycler import cycler\n", + "\n", + "color=['0.0', '0.4', '0.8']\n", + "default_cycler = (cycler(color=color))\n", + "linestyle=['-', '--', ':', '-.']\n", + "marker=['o', 'v', 'd', 'p']\n", + "\n", + "plt.rc('axes', prop_cycle=default_cycler)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "d17c7963", + "metadata": { + "ExecuteTime": { + "end_time": "2024-01-20T14:39:09.589128Z", + "start_time": "2024-01-20T14:39:09.554340Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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datecityregiontreatedtaudownloadspost
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" + ], + "text/plain": [ + " date city region treated tau downloads post\n", + "0 2021-05-01 5 S 0 0.0 51.0 0\n", + "1 2021-05-02 5 S 0 0.0 51.0 0\n", + "2 2021-05-03 5 S 0 0.0 51.0 0\n", + "3 2021-05-04 5 S 0 0.0 50.0 0\n", + "4 2021-05-05 5 S 0 0.0 49.0 0" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import pandas as pd\n", + "import numpy as np\n", + "\n", + "mkt_data = (pd.read_csv(\"./data/short_offline_mkt_south.csv\")\n", + " .astype({\"date\":\"datetime64[ns]\"}))\n", + "\n", + "mkt_data.head()" + ] + }, + { + "cell_type": "markdown", + "id": "d7b53c33", + "metadata": {}, + "source": [ + "처치 개입 전후 기간 확인" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "3d6cdba1", + "metadata": { + "ExecuteTime": { + "end_time": "2024-01-20T14:39:09.608185Z", + "start_time": "2024-01-20T14:39:09.594150Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_14638/2583971365.py:4: FutureWarning: The provided callable is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"min\" instead.\n", + " .agg({\"date\":[min, max]}))\n", + "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_14638/2583971365.py:4: FutureWarning: The provided callable is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n", + " .agg({\"date\":[min, max]}))\n" + ] + }, + { + "data": { + "text/html": [ + "
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downloadsdate
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delta_ytreated
city
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1930.1666670
1950.4206350
1960.1190480
1971.5952381
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" + ], + "text/plain": [ + " delta_y treated\n", + "city \n", + "192 0.555556 0\n", + "193 0.166667 0\n", + "195 0.420635 0\n", + "196 0.119048 0\n", + "197 1.595238 1" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pre = mkt_data.query(\"post==0\").groupby(\"city\")[\"downloads\"].mean()\n", + "post = mkt_data.query(\"post==1\").groupby(\"city\")[\"downloads\"].mean()\n", + "\n", + "delta_y = ((post - pre)\n", + " .rename(\"delta_y\")\n", + " .to_frame()\n", + " # add the treatment dummy\n", + " .join(mkt_data.groupby(\"city\")[\"treated\"].max()))\n", "\n", - "# comment" + "delta_y.tail()" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "31be6542", + "metadata": { + "ExecuteTime": { + "end_time": "2024-01-20T14:39:09.665299Z", + "start_time": "2024-01-20T14:39:09.659783Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(0.6917359536407155)" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(delta_y.query(\"treated==1\")[\"delta_y\"].mean() \n", + " - delta_y.query(\"treated==0\")[\"delta_y\"].mean())" + ] + }, + { + "cell_type": "markdown", + "id": "3d9eee06", + "metadata": {}, + "source": [ + "DID 모형에 따른 실험군과 대조군의 추세 및 실험군의 가상적(반사실적) 추세" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "ff0261df", + "metadata": { + "ExecuteTime": { + "end_time": "2024-01-20T14:39:09.877683Z", + "start_time": "2024-01-20T14:39:09.666729Z" + }, + "tags": [ + "hide-input" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "did_plt = did_data.reset_index()\n", + "\n", + "\n", + "plt.figure(figsize=(10,4))\n", + "\n", + "sns.scatterplot(data=did_plt.query(\"treated==0\"), x=\"date\", y=\"downloads\", s=100, color=\"C0\", marker=\"s\")\n", + "sns.lineplot(data=did_plt.query(\"treated==0\"), x=\"date\", y=\"downloads\", label=\"Control\", color=\"C0\")\n", + "\n", + "sns.scatterplot(data=did_plt.query(\"treated==1\"), x=\"date\", y=\"downloads\", s=100, color=\"C1\", marker=\"x\")\n", + "sns.lineplot(data=did_plt.query(\"treated==1\"), x=\"date\", y=\"downloads\", label=\"Treated\", color=\"C1\",)\n", + "\n", + "plt.plot(did_data.loc[1, \"date\"], [did_data.loc[1, \"downloads\"][0], y0_est], color=\"C2\", linestyle=\"dashed\", label=\"Y(0)|D=1\")\n", + "plt.scatter(did_data.loc[1, \"date\"], [did_data.loc[1, \"downloads\"][0], y0_est], color=\"C2\", s=50)\n", + "\n", + "plt.xticks(rotation = 45)\n", + "plt.legend()\n" + ] + }, + { + "cell_type": "markdown", + "id": "7d388983", + "metadata": {}, + "source": [ + "### 선형회귀를 이용한 이중차분법(Regression DID)" + ] + }, + { + "cell_type": "markdown", + "id": "b8dd4569", + "metadata": {}, + "source": [ + "#### 개입 전/후 기간을 하나의 블록으로 집계한 데이터" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "bead249f", + "metadata": { + "ExecuteTime": { + "end_time": "2024-01-20T14:39:09.887639Z", + "start_time": "2024-01-20T14:39:09.879115Z" + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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citypostdownloadsdatetreated
05050.6428572021-05-010
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" + ], + "text/plain": [ + " city post downloads date treated\n", + "0 5 0 50.642857 2021-05-01 0\n", + "1 5 1 50.166667 2021-05-15 0\n", + "2 15 0 49.142857 2021-05-01 0\n", + "3 15 1 49.166667 2021-05-15 0\n", + "4 20 0 48.785714 2021-05-01 0" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "did_data = (mkt_data\n", + " .groupby([\"city\", \"post\"])\n", + " .agg({\"downloads\":\"mean\", \"date\": \"min\", \"treated\": \"max\"})\n", + " .reset_index())\n", + "\n", + "did_data.head()" ] }, { "cell_type": "markdown", + "id": "6cb1e2e6", "metadata": {}, "source": [ - "### 질문이나 의견을 남겨주세요.\n", - "" + " `statsmodels`와 `pyfixest`\n", + "\n", + "DID 분석을 회귀 모형으로 구현할 때,\n", + "- **statsmodels (smf)** 은 파이썬에서 가장 널리 쓰이는 범용 회귀 패키지라 기본 구현을 설명하기에 적합하다. \n", + "- 그러나 DID는 본질적으로 **패널 데이터 + 고정효과(FE) + 클러스터 표준오차**가 중요하다. \n", + " 이를 편리하게 지원하는 패키지가 바로 **pyfixest**이다.\n", + "\n", + "따라서 \n", + "- statsmodels로는 DID의 기본 원리를 쉽게 보여줄 수 있고, \n", + "- pyfixest로는 실제 실증연구에서 사용하는 **FE-DID, TWFE, robust SE**를 더 직관적으로 구현할 수 있다." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "54757217", + "metadata": { + "ExecuteTime": { + "end_time": "2024-01-20T14:39:09.896935Z", + "start_time": "2024-01-20T14:39:09.889021Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(0.6917359536407082)" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import statsmodels.formula.api as smf\n", + "\n", + "smf.ols(\n", + " 'downloads ~ treated*post', data=did_data\n", + ").fit().params[\"treated:post\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "463a35ef", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DID estimate: 0.6917359536407451\n" + ] + } + ], + "source": [ + "import pyfixest as pf\n", + "\n", + "model = pf.feols(\"downloads ~ treated*post\", data=did_data)\n", + "\n", + "# DID 추정치 (treated:post 계수)\n", + "coef = model.coef()[\"treated:post\"]\n", + "print(\"DID estimate:\", coef)" + ] + }, + { + "cell_type": "markdown", + "id": "48ef6933", + "metadata": {}, + "source": [ + "### 블록디자인을 바탕으로 한 이중차분법\n", + "- DID를 추정할때 처치 전후로 각 값들을 그룹화하여 하지 않고 각 시점의 데이터를 모두 활용하는 방법\n", + "- 사전 평행 추세를 검정할 수 있다는 장점이 있음\n" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "d1eed2c4", + "metadata": { + "ExecuteTime": { + "end_time": "2024-01-20T14:39:11.143922Z", + "start_time": "2024-01-20T14:39:09.915271Z" + }, + "tags": [ + "hide-input" + ] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_14638/2621860921.py:7: FutureWarning: The provided callable is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n", + " .assign(treated=lambda d: d.groupby(\"city\")[\"treated\"].transform(max))\n", + "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n" + ] + }, + { + "data": { + "text/plain": [ + "(array([ 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5,\n", + " 11.5, 12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5, 20.5, 21.5,\n", + " 22.5, 23.5, 24.5, 25.5, 26.5, 27.5, 28.5, 29.5, 30.5, 31.5]),\n", + " [Text(0.5, 0, '2021-05-01'),\n", + " Text(1.5, 0, '2021-05-02'),\n", + " Text(2.5, 0, '2021-05-03'),\n", + " Text(3.5, 0, '2021-05-04'),\n", + " Text(4.5, 0, '2021-05-05'),\n", + " Text(5.5, 0, '2021-05-06'),\n", + " Text(6.5, 0, '2021-05-07'),\n", + " Text(7.5, 0, '2021-05-08'),\n", + " Text(8.5, 0, '2021-05-09'),\n", + " Text(9.5, 0, '2021-05-10'),\n", + " Text(10.5, 0, '2021-05-11'),\n", + " Text(11.5, 0, '2021-05-12'),\n", + " Text(12.5, 0, '2021-05-13'),\n", + " Text(13.5, 0, '2021-05-14'),\n", + " Text(14.5, 0, '2021-05-15'),\n", + " Text(15.5, 0, '2021-05-16'),\n", + " Text(16.5, 0, '2021-05-17'),\n", + " Text(17.5, 0, '2021-05-18'),\n", + " Text(18.5, 0, '2021-05-19'),\n", + " Text(19.5, 0, '2021-05-20'),\n", + " Text(20.5, 0, '2021-05-21'),\n", + " Text(21.5, 0, '2021-05-22'),\n", + " Text(22.5, 0, '2021-05-23'),\n", + " Text(23.5, 0, '2021-05-24'),\n", + " Text(24.5, 0, '2021-05-25'),\n", + " Text(25.5, 0, '2021-05-26'),\n", + " Text(26.5, 0, '2021-05-27'),\n", + " Text(27.5, 0, '2021-05-28'),\n", + " Text(28.5, 0, '2021-05-29'),\n", + " Text(29.5, 0, '2021-05-30'),\n", + " Text(30.5, 0, '2021-05-31'),\n", + " Text(31.5, 0, '2021-06-01')])" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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kfvrTn4Y///nPcWD0nnvuGX7/+9832YWpIa4DIUmSpEo0rATrQJQ0gGgrBhCSJEmqRMOqcSG5tpKFhaiKlW6W9tV0i5em6RY3XReSy166WdpX0y1emqZb3HSztK9ZTreqB1FLkiRJKm8GEJIkSZLyZgAhSZIkKW8GEJIkSZLyZgAhSZIkKRvTuI4YMSLcdddd4e233w7LLrts6NevX7jgggtCnz59at/DytQsOPfMM8/EtSD22muvcOWVV4bVV18977/jNK6SJEmqRMNKMI1rSVsgxo8fH4YMGRJeeOGF8Nhjj4X58+eHPfbYI8yZMyf+nK/8f6mllgpPPvlkePbZZ8PXX38dV69etGhRKXddkiRJqkolXQfi4YcfrvP/UaNGhdVWWy1MmjQp7LTTTjFgmDp1anjllVdC586d43tuvPHGsPLKK8eAYuDAgXn/rSzMI1+sdLO0r6ZbvDRNt7jpug5E9tLN0r6abvHSNN3ippulfc1yulU9BmLmzJnxa9euXeNXuizR+tCxY8fa93Tq1CksvfTSsUuTJEmSpCoNIOiSdOqpp4YddtghbLbZZvG1b33rW2H55ZcPZ511Vpg7d27s0sR4iIULF4Zp06Y1mA5Bx5dffllnW7BgQRt/GkmSJKkylU0AwViIN954I4wePbr2tW7duoUxY8aE++67L6ywwgqhS5cuYcaMGWHrrbeOrRCNDczmfbnbhAkT2vCTSJIkSZWrLAKIk046Kdx///3hqaeeCj179qzzMwZRMxPT9OnTw6effhpuuumm8NFHH4V11123wbSGDh0au0Llbv3792+jTyJJkiRVtpIOomYG2ZNPPjmMHTs2jBs3LvTu3bvR96666qrxK4OnCSb222+/Bt/HeIncMRNo376kH1OSJEmqGCVdB+LEE08Mt956a7jnnnvqrP1AtyPWhcANN9wQNt5449id6fnnnw+nnHJKOPLII8Mll1yS999xHQhJkiRVomElWAeipFXzI0eOjF8HDBhQ53WCBoIETJ48OXZL+vzzz8M666wTfvnLX4bTTjutJPsrSZIkVbuSd2FakvPPPz9urZWFeeSLlW6W9tV0i5em6RY3XdeByF66WdpX0y1emqZb3HSztK9ZTrcqB1FLkiRJygYDCEmSJEl5M4CQJEmSlDcDCEmSJEl5M4CQJEmSlI11IJjGlW3q1Knx/5tuumn49a9/HQYNGhT//9VXX4Wf/vSnYfTo0WHevHlhzz33DL///e/D6quv3qy/4zoQkiRJqkTDSrAORElbIHr27BmnaJ00aVKYOHFi2HXXXcP+++8f/va3v8Wfs97DfffdF8aMGRPGjx8fPv7443DggQeWcpclSZKkqlbSFoiGdO3aNVx00UXhu9/9blx9mpWq+R5vv/12XJWaFam/9a1vNasFIgvzyBcr3Sztq+kWL03TLW66rgORvXSztK+mW7w0Tbe46WZpX7Oa7rBqa4HItXDhwthVac6cOWH77bePrRLz588PAwcOrH3PRhttFHr16hUDCEmSJElVthI1Xn/99RgwMN5hhRVWCGPHjg2bbLJJePXVV0OHDh3CSiutVOf9jH/45JNPGk2PsRJsuRYsWFC0/ZckSZKqSclbIPr06RODhRdffDGccMIJYfDgweHNN99scXojRowIXbp0qbNNmDChoPssSZIkVauSBxC0Mqy//vphm222iYX/vn37hssvvzx07949fP3112HGjBl13v+vf/0r/qwxQ4cODTNnzqyz9e/fvw0+iSRJklT5Sh5A1Ldo0aLYBYmAYplllglPPPFE7c8mT54c3n///djlqTEdO3YMnTt3rrO1b1/ynlqSJElSRShpyZrWAtZ8YGD0rFmz4oxL48aNC4888kjsenT00UeH008/Pc7MRCBw8sknx+ChOTMwSZIkSaqQaVwJEGhhmDZtWgwYtthii3DWWWeF3Xffvc5Ccn/+85/rLCTXVBemhriQnCRJkirRsBJM41p260AUgwGEJEmSKtGwEgQQVTM4IAsLURUr3Sztq+kWL03TLW66LiSXvXSztK+mW7w0Tbe46WZpX7Ocbqj2QdSSJEmSypcBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJysY0rk8//XS46KKLwqRJk+JaEGPHjg0HHHBA7c9nz54dfv7zn4e77747fPbZZ6F3797hJz/5STj++OOb9XecxlWSJEmVaFgJpnEtaQvEnDlzQt++fcNVV13V4M9Zhfrhhx8ON998c3jrrbfCqaeeGk466aRw7733tvm+SpIkSSrxOhCDBg2KW2Oee+65MHjw4DBgwID4/+OOOy5cc8014S9/+UvYb7/9mvW3sjCPfLHSzdK+mm7x0jTd4qbrOhDZSzdL+2q6xUvTdIubbpb2NcvptrWyHgPRr1+/2Nrw0UcfBXpaPfXUU+Hvf/972GOPPUq9a5IkSVJVKuuVqK+88srY6tCzZ8/Qvn37sPTSS4drr7027LTTTo3+zrx58+KWa8GCBW2wt5IkSVLlW7rcA4gXXnghtkIw0PqSSy4JQ4YMCY8//nijvzNixIjQpUuXOtuECRPadL8lSZKkSlW2AcR//vOf8Itf/CJceumlYd999w1bbLFFHEB96KGHhosvvrjR3xs6dGiYOXNmna1///5tuu+SJElSpSrbLkzz58+PG92WcrVr1y4sWrSo0d/r2LFj3HLR/UmSJElSxteBYJ2HKVOmxO+32mqr2Nqwyy67hK5du4ZevXrF2Zc+/fTT8L//+79h7bXXDuPHjw8nnHBCfB9f8+U6EJIkSapEw0qwDkRJq+YnTpwYA4bcdR/A1K2jRo0Ko0ePjl2SDj/88PD555/HIOLcc89t9kJykiRJkioggKCFoakGkO7du4cbbrihIH8rC/PIFyvdLO2r6RYvTdMtbrquA5G9dLO0r6ZbvDRNt7jpZmlfs5xuWyvbQdSSJEmSyo8BhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJysY6EPn46KOPwllnnRUeeuihMHfu3LD++uvHmZm23XbbvNNwHQhJkiRVomHVtg7EknzxxRdhhx12iGtFEEB069YtvPPOO2HllVcu9a5JkiRJVamsA4gLLrggrLXWWnXWgujdu3eL0srCPPLFSjdL+2q6xUvTdIubrutAZC/dLO2r6RYvTdMtbrpZ2tcsp9vWynoMxL333hu7Kh188MFhtdVWC1tttVW49tprS71bkiRJUtUq6wDiH//4Rxg5cmTYYIMNwiOPPBJOOOGE8JOf/CTceOONjf7OvHnzwpdffllnW7BgQZvutyRJklSpyjqAWLRoUdh6663DeeedF1sfjjvuuHDssceGq6++utHfGTFiROjSpUudbcKECW2635IkSVKlKusAokePHmGTTTap89rGG28c3n///UZ/Z+jQoWHmzJl1tv79+7fB3kqSJEmVr6wHUTMD0+TJk+u89ve//z2svfbajf5Ox44d45arffuy/piSJElSZpT1OhAvvfRS6NevXxxhfsghh4S//OUvsQvTH/7wh3D44YfnnY7rQEiSJKkSDSvBOhBl3YXpG9/4Rhg7dmz485//HDbbbLNw9tlnh8suu6xZwYMkSZKkwin7vj3f/va349ZaWZhHvljpZmlfTbd4aZpucdPN0r6abvHSNN3ippulfTXd4qVpuv9V6PQqogVCkiRJUnkxgJAkSZKUNwMISZIkSXkzgJAkSZKUNwMISZIkSXkzgJAkSZKUvYXkzj///DB06NBwyimnxLUe8O6774YzzjgjPPPMM2HevHlhr732CldeeWVYffXVm5W2C8lJkiSpEg2r1oXkWHH6mmuuCVtssUXta3PmzAl77LFHWGqppcKTTz4Znn322fD111+HfffdNyxatKik+ytJkiRVq5IvJDd79uy4svS1114bzjnnnNrXCRimTp0aXnnlldC5c+f42o033hhWXnnlGFAMHDiwWX8nawuCuIhLdaebpX013eKlabrFTTdL+2q6xUvTdIubbpb2NcvpVl0LxJAhQ8I+++yzWEBAlyVaHzp27Fj7WqdOncLSSy8duzRJkiRJqrIWiNGjR4eXX345dmGq71vf+lZYfvnlw1lnnRXOO++8wFCNn//852HhwoVh2rRpjaZJ4MGWa8GCBUXZf0mSJKnalKwF4oMPPogDpm+55ZbYslBft27dwpgxY8J9990XVlhhhdClS5cwY8aMsPXWW8dWiMaMGDEivjd3mzBhQpE/jSRJklQdShZATJo0KUyfPj0GBO3bt4/b+PHjwxVXXBG/p6WBQdTMxMT7Pv3003DTTTeFjz76KKy77rqNpstMTjNnzqyz9e/fv00/myRJklSpStaFabfddguvv/56ndeOOuqosNFGG8VuS+3atat9fdVVV41fGTxNMLHffvs1mi5jJnLHTYCARJIkSVIFrQOBAQMGhC233LJ2HYgbbrghbLzxxrE70/PPPx+7PB155JHhkksuaVa6rgMhSZKkSjSsBOtAlHXV/OTJk2OXpM8//zyss8464Ze//GU47bTTSr1bkiRJUtUqqxaIYqEFImvz+ToHc3Wnm6V9Nd3ipWm6xU03S/tqusVL03SLm26W9jWr6Q6r1pWoJUmSJGWDAYQkSZKkvBlASJIkScqbAYQkSZKkvBlASJIkScreLEznn39+nLKVtR5YB2Lq1Kmhd+/eDb739ttvDwcffHDeabsOhCRJkirRsGqdhemll14K11xzTdhiiy1qX1trrbXCtGnT6mwEAiussEIYNGhQSfdXkiRJqlYlX0hu9uzZ4fDDDw/XXnttOOecc2pfb9euXejevXud944dOzYccsghMYhorizN51vodLO0r6ZbvDRNt7jpZmlfTbd4aZpucdPN0r6abvHSNN3/KnR6mWmBGDJkSNhnn33CwIEDm3zfpEmTwquvvhqOPvroNts3SZIkSWXUAjF69Ojw8ssvxy5MS3LdddeFjTfeOPTr16/J982bNy9uuRYsWNDqfZUkSZJUwhaIDz74IA6YvuWWW0KnTp2afO9//vOfcOutt+bV+jBixIjQpUuXOtuECRMKuOeSJElS9SpZAEGXpOnTp4ett946tG/fPm7jx48PV1xxRfx+4cKFte+94447wty5c8MRRxyxxHSZyWnmzJl1tv79+xf500iSJEnVoWRdmHbbbbfw+uuv13ntqKOOChtttFE466yz4iDq3O5L++23X+jWrdsS0+3YsWPcchGQSJIkSaqgdSAwYMCAsOWWW8Z1IJIpU6aEDTfcMDz44INhr732alG6rgMhSZKkSjSsWteBaMr1118fevbsGfbYY49S74okSZJU9cqqBaJYaIHI2ny+zsFc3elmaV9Nt3hpmm5x083Svppu8dI03eKmm6V9zWq6w2yBkCRJklTODCAkSZIk5c0AQpIkSVLeDCAkSZIk5c0AQpIkSVLeDCAkSZIkZWMa15EjR8Zt6tSp8f+bbrpp+PWvfx0GDRoUPv/88zgt1aOPPhref//9uAr1AQccEM4+++zQpUuXZv0dF5KTJElSJRpWgmlc24cSYoG4888/P2ywwQaBOObGG28M+++/f3jllVfi/z/++ONw8cUXh0022ST885//DMcff3x87Y477ijlbkuSJEnVq6bMrLzyyjV//OMfG/zZ7bffXtOhQ4ea+fPnNyvN4cOH08pS0I00s5JulvbVdLO3r6abvX013eztq+lmb19NN3v7mtV0S6GkLRC5Fi5cGMaMGRPmzJkTtt9++wbfM3PmzNC5c+fQvn3Z7LYkSZJUVUpeEn/99ddjwPDVV1+FFVZYIYwdOzZ2Warv008/jeMfjjvuuCbTmzdvXtxyLViwoOD7LUmSJFWjks/C1KdPn/Dqq6+GF198MZxwwglh8ODB4c0336zzni+//DLss88+MbAYPnx4k+mNGDEiDrLO3SZMmFDkTyFJkiRVh5IHEB06dAjrr79+2GabbWLhv2/fvuHyyy+v/fmsWbPCXnvtFVZcccXYOrHMMss0md7QoUNjV6fcrX///m3wSSRJkqTKV/IuTPUtWrSotgsSLQ977rln6NixY7j33ntDp06dlvj7vJctl2MmJEmSpApYB4LWAtZ86NWrV2xpuPXWW8MFF1wQHnnkkbDddtuFPfbYI8ydOze2PCy//PK1v8eaEO3atcv777gOhCRJkirRsGpbB2L69OnhiCOOCNOmTYtjFbbYYosYPOy+++5h3LhxcVwE6OKU67333gvrrLNOifZakiRJql4lDSCuu+66Rn82YMCAuJhcoSxp8HVL08tCulnaV9MtXpqmW9x0s7Svplu8NE23uOlmaV9Nt3hpmu5/FTq9zAyiliRJkpQdBhCSJEmS8mYAIUmSJClvBhCSJEmS8mYAIUmSJCkb60CMHDkyblOnTo3/33TTTcOvf/3ruDZELnZx7733Dg8//HBcE+KAAw5o1t9xHQhJkiRVomElWAeipC0QPXv2DOeff36YNGlSmDhxYth1113D/vvvH/72t7/Ved9ll10WllpqqZLtpyRJkqT/U1NmVl555Zo//vGPtf9/5ZVXatZcc82aadOm0VJSM3bs2GanOXz48Pi7hdxIMyvpZmlfTTd7+2q62dtX083evppu9vbVdLO3r1lNtxRKupBcroULF4YxY8aEOXPmhO233z6+Nnfu3PD9738/XHXVVaF79+6l3kVJkiSp6pU8gHj99ddjwPDVV1+FFVZYIY5x2GSTTeLPTjvttNCvX7/YrSlf8+bNi1uuBQsWFHy/JUmSpGpU8gCiT58+4dVXXw0zZ84Md9xxRxg8eHAYP358mDJlSnjyySfDK6+80qz0RowYsdig6Z133rnAey1JkiRVp5JP49qhQ4ew/vrrh2222SYW/vv27Rsuv/zyGDy8++67YaWVVgrt27ePGw466KAwYMCARtMbOnRoDEZyt/79+7fhJ5IkSZIqV8lbIOpbtGhR7IJEK8IxxxxT52ebb755+N3vfhf23XffRn+/Y8eOccuVgg9JkiRJGV4HgtYC1nzo1atXmDVrVrj11lvDBRdcEB555JGw++67L/Z+pnJ1HQhJkiSpdOtAlLRqfvr06eGII44I06ZNC126dAlbbLFFo8GDJEmSpNIraQBx3XXXNev9rWksGT58eIt/t6n0spBulvbVdIuXpukWN90s7avpFi9N0y1uulnaV9MtXpqm+1+FTi8zg6glSZIkZYcBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqRsLCSX6/zzz48Ly51yyinhsssui6/9+Mc/Do8//nj4+OOPwworrBD69esXF5rbaKONmpW2C8lJkiSpEg0rwUJyZdEC8dJLL4VrrrkmLiSXa5tttgk33HBDeOutt+ICc8Q6e+yxR1i4cGHJ9lWSJEmqZiVdSA6zZ88Ohx9+eLj22mvDOeecU+dnxx13XO3366yzTvx53759w9SpU8N6663XrL+TtQVBXMSlutPN0r6abvHSNN3ippulfTXd4qVpusVNN0v7muV0q64FYsiQIWGfffYJAwcObPJ9c+bMia0RvXv3DmuttVab7Z8kSZKkMmmBGD16dHj55ZdjF6bG/P73vw8/+9nPYgDRp0+f8Nhjj4UOHTo0+v558+bFLdeCBQsKut+SJElStSpZC8QHH3wQB0zfcsstoVOnTo2+j+5Nr7zyShg/fnzYcMMNwyGHHBK++uqrRt8/YsSI0KVLlzrbhAkTivQpJEmSpOpSsgBi0qRJYfr06WHrrbcO7du3jxtBwhVXXBG/TwOlCQA22GCDsNNOO4U77rgjvP3222Hs2LGNpstMTjNnzqyz9e/fvw0/mSRJklS5StaFabfddguvv/56ndeOOuqoOEXrWWedFdq1a7fY7zALE1v9Lkq5OnbsGLdcBCSSJEmSKmgdCAwYMCBsueWWcR2If/zjH+G2226L07Z269YtfPjhh3GtiGeffTZO67raaqvlna7rQEiSJKkSVe06EA1hXARjF/bee++w/vrrh0MPPTSsuOKK4bnnnmtW8CBJkiSpcMqqb8+4ceNqv19jjTXCgw8+WLC0szafr3MwV3e6WdpX0y1emqZb3HSztK+mW7w0Tbe46WZpX7Ocblsr2xYISZIkSeXHAEKSJElS3gwgJEmSJOXNAEKSJElS3gwgJEmSJGVjHYiRI0fGberUqfH/m266afj1r38dBg0aFF/r3bt3g793++23h4MPPjjvv+M6EJIkSapEw0qwDkRJp3Ht2bNnXBxugw02iCtM33jjjWH//fcPr7zySlyRetq0aXXe/4c//CFcdNFFMcCQJEmSVAI1ZWbllVeu+eMf/9jgz7bccsuaH/3oR81Oc/jw4bSyFHQjzaykm6V9Nd3s7avpZm9fTTd7+2q62dtX083evmY13VIomzEQCxcuDKNHjw5z5swJ22+//WI/nzRpUnj11VfD0UcfXZL9kyRJklQGK1G//vrrMWD46quvwgorrBDGjh0bNtlkk8Xed91114WNN9449OvXr8n05s2bF7dcCxYsKPh+S5IkSdWo5C0Qffr0iS0LL774YjjhhBPC4MGDw5tvvlnnPf/5z3/Crbfemlfrw4gRI0KXLl3qbBMmTCjiJ5AkSZKqR8kDiA4dOoT1118/bLPNNrHw37dv33D55ZfXec8dd9wR5s6dG4444oglpjd06NAwc+bMOlv//v2L+AkkSZKk6lHyLkz1LVq0aLEuSHRf2m+//UK3bt2W+PsdO3aMW6727cvuY0qSJEmZVNJ1IGgtYErWXr16hVmzZsVuShdccEF45JFHwu677x7fM2XKlLDhhhuGBx98MOy1114t+juuAyFJkqRKNKza1oGYPn167JbEeg+MVdhiiy3qBA+4/vrr43oRe+yxRyl3VZIkSVKpWyDaCi0Qw4cPL2iaKb0spJulfTXd4qVpusVNN0v7arrFS9N0i5tulvbVdIuXpun+F+mVogWi5IOoJUmSJGWHAYQkSZKkvBlASJIkScqbAYQkSZKkvBlASJIkScqbAYQkSZKkbEzjOmLEiHDXXXeFt99+Oyy77LKhX79+cSG5Pn361L7nk08+CWeeeWZ47LHH4mJz/OyXv/xlOOigg/L+Oy4kJ0mSpEo0rNqmcR0/fnwYMmRIeOGFF2KAMH/+/Lhg3Jw5c2rfw0JzkydPDvfee294/fXXw4EHHhgOOeSQ8Morr5Ry1yVJkqTqVFNGpk+fTmtIzfjx42tfW3755Wv+9Kc/1Xlf165da6699tq80x0+fHhMt5AbaWYl3Sztq+lmb19NN3v7arrZ21fTzd6+mm729jWr6ZZCWY2BmDlzZvzatWvX2tfo1nTbbbeFzz//PCxatCiMHj06fPXVV2HAgAEl3FNJkiSpOrUPZYLg4NRTTw077LBD2GyzzWpfv/3228Ohhx4aVlllldC+ffuw3HLLhbFjx4b111+/wXTmzZsXt1wLFiwo+v5LkiRJ1aBsWiAYC/HGG2/EFoZcv/rVr8KMGTPC448/HiZOnBhOP/30OAaC8RCNDczu0qVLnW3ChAlt9CkkSZKkylYWAcRJJ50U7r///vDUU0+Fnj171r7+7rvvhv/93/8N119/fdhtt91C375940jzbbfdNlx11VUNpjV06NDYFSp369+/fxt+GkmSJKlylbQLEzPInnzyybFL0rhx40Lv3r3r/Hzu3Lnx69JL141z2rVrF7s8NaRjx45xy0XXJ0mSJEkZXwfixBNPDLfeemu455576qz9QLcj1oVgWtdNNtkk9OjRI1x88cVxHMTdd98d14WgxWLvvffO6++4DoQkSZIq0bBqWwdi5MiRsYsRMyoRJKSNWZewzDLLhAcffDB069Yt7LvvvmGLLbYIf/rTn8KNN96Yd/AgSZIkqYK6MC3JBhtsEO68885W/63hw4e3Oo2G0stCulnaV9MtXpqmW9x0s7Svplu8NE23uOlmaV9Nt3hpmu5/FTq9TA2iliRJkpQNBhCSJEmS8mYAIUmSJClvBhCSJEmS8mYAIUmSJCkb60DkOv/88+Mq0qecckq47LLL4mt/+MMf4joRL7/8cpg1a1b44osvwkorrdTstF0HQpIkSZVoWLWtA5G89NJL4ZprronrPNRfiXqvvfYKv/jFL0q2b5IkSZLKZB0IzJ49Oxx++OHh2muvDeecc06dn5166qnx67hx41r9d7I2n69zMFd3ulnaV9MtXpqmW9x0s7Svplu8NE23uOlmaV+znG7VtUAMGTIk7LPPPmHgwIGl3hVJkiRJxWiBGDx4cDj66KPDTjvtFFpj9OjRcXwDXZgKZd68eXHLtWDBgoKlL0mSJFWzFrVAzJw5M7YYbLDBBuG8884LH330UbPT+OCDD+KA6VtuuSV06tQpFMqIESNCly5d6mwTJkwoWPqSJElSNWtRAHH33XfHoOGEE04It912W1hnnXXCoEGDwh133BHmz5+fVxqTJk0K06dPD1tvvXVo37593MaPHx+uuOKK+P3ChQtbsmtxJicCnNytf//+LUpLkiRJUoHGQHTr1i2cfvrp4a9//Wt48cUXw/rrrx9++MMfhjXWWCOcdtpp4Z133mny93fbbbfw+uuvh1dffbV223bbbeOAar5v165di/arY8eOoXPnznU2AhJJkiRJZbAOxLRp08Kf/vSncMMNN4QPP/wwHHTQQbF1gtaECy+8MAYT+RowYEDYcssta9eB+OSTT+I2ceLEcOyxx4ann346rLjiiqFXr16ha9eueafrOhCSJEmqRMOysg4E3ZTuvPPO8O1vfzusvfbaYcyYMXHK1Y8//jjceOON4fHHHw+33357+O1vf9uqnbv66qvDVlttFYMHMGib/997772tSleSJElSC9W0wCqrrFKz8sor15x44ok1r7zySoPv+eKLL2rWWWedmnIwfPhwWlkKupFmVtLN0r6abvb21XSzt6+mm719Nd3s7avpZm9fs5puKbRocMDvfve7cPDBBzc5e9JKK60U3nvvvZbGNZIkSZLKUIu6MD311FMNzrY0Z86c8KMf/agQ+yVJkiSpUgIIxjn85z//Wex1XmNAtSRJkqTK1KwuTF9++SVjJuI2a9asOl2YWLfhwQcfDKuttlox9lOSJElS1gIIxjUstdRScdtwww0X+zmvO2WqJEmSVLmatQ4Eazvw9l133TVO45q7FkOHDh3ilK4sJFduDGokSZJUiYaVYB2IZrVA7LzzzvErsyuxmBstDq0xcuTIuE2dOjX+f9NNNw2//vWvw6BBg+L/33333XDGGWeEZ555JsybNy/stdde4corrwyrr756q/6uJEmSpCIHEK+99lrYbLPNwtJLLx1mzpwZXn/99Ubfu8UWW+SVZs+ePcP5558fNthgg9iyweDs/fffP7zyyithnXXWCXvssUfo27dvePLJJ+P7f/WrX4V99903vPDCC3E/mmP48OHNen++6WUh3Sztq+kWL03TLW66WdpX0y1emqZb3HSztK+mW7w0Tfe/Cp1ewQOILbfcMnzyySdxkDTf0/rQUO8nXmdAdT4IBnKde+65sUWCAOGjjz6KLRMEE507d44/J8BYeeWVY0AxcODAfHddkiRJUlsHEHRb6tatW+33hUbQMWbMmLiWxPbbbx+7LxGMdOzYsfY9zPpEywNdmgwgJEmSpDIOIBggndx6661xHEL9ReOuv/768O9//zucddZZee8AXaEIGL766quwwgorhLFjx4ZNNtkkBivLL798TOu8886LrR0///nPY6Axbdq0RtNjrARbrgULFuS9P5IkSZIKvJDcNddcEzbaaKPFXmcQ9NVXX92stPr06RNeffXV8OKLL4YTTjghDB48OLz55psxgKBF4r777ouBRZcuXcKMGTPC1ltv3eT4hxEjRsT35m4TJkxoyceUJEmSVIgAgrEQPXr0WOx1Cv1NtQ40hOlf119//bDNNtvEwj+Dpi+//PL4MwZR05Vp+vTp4dNPPw033XRTHBux7rrrNpre0KFD4yDv3K1///4t+JSSJEmSWjWNa7LWWmuFZ599NvTu3bvO67zW2nUgFi1atFgXpFVXXTV+ZfA0wcR+++3X6O8zZiJ33ATat2/Rx5QkSZLUmoXkkgsvvDBuF110UVxUDk888UT42c9+Fn7605/GVoB88D7WfGBNiVmzZsWxFRdccEF45JFHwu677x5uuOGGsPHGG8eWjeeffz6ccsop4cgjjwyXXHJJs/bXheQkSZJUiYaV+0JyyZlnnhk+++yzcOKJJ4avv/66doYkBjznGzyA1oQjjjgidntirALrR6TgAZMnT47pff7553FdiF/+8pfhtNNOa8kuS5IkSSpVC0Qye/bs8NZbb4Vll102LgZXv+tQuaAFImsLgriIS3Wnm6V9Nd3ipWm6xU03S/tqusVL03SLm26W9jWr6Q7LSgtEwuxI3/jGNwq3N5IkSZIqbxYmSZIkSdXJAEKSJElS3gwgJEmSJOXNAEKSJElS28zC1FqsPH3XXXeFt99+O87k1K9fv7gORJ8+feLPp06duthidcntt98eDj744Lz+jutASJIkqRINK8EsTCVtgRg/fnwYMmRIeOGFF8Jjjz0W5s+fH/bYY48wZ86c2hWvWSMidyMYYPYnFqCTJEmSlKFpXFvr4YcfrvP/UaNGhdVWWy1MmjQp7LTTTqFdu3ahe/fudd4zduzYcMghh8QgojmyNJ9vodPN0r6abvHSNN3ippulfTXd4qVpusVNN0v7arrFS9N0/6vQ6WVyDMTMmTPj165duzb4cwKLV199NRx99NFtvGeSJEmSSt4CkWvRokXh1FNPDTvssEPYbLPNGnzPddddFzbeeOM4VqIx8+bNi1uuBQsWFHx/JUmSpGpUNi0QjIV44403wujRoxv8+X/+859w6623LrH1gYHZXbp0qbNNmDChSHstSZIkVZeyCCBOOumkcP/994ennnoq9OzZs8H33HHHHWHu3LnhiCOOaDKtoUOHxq5QuVv//v2LtOeSJElSdSlpFyZmkD355JPjwOhx48Y1OmVr6r603377hW7dujWZZseOHeOWq337sumpJUmSJGVaSdeBOPHEE2O3pHvuuad27QfQ7Yh1IZIpU6aEDTfcMDz44INhr732avbfcR0ISZIkVaJh1bYOxMiRI2MXowEDBoQePXrUbrfddlud911//fWxaxNrREiSJEmq4i5M+TjvvPPi1hpZm8/XOZirO90s7avpFi9N0y1uulnaV9MtXpqmW9x0s7SvWU63KgdRS5IkScoGAwhJkiRJeTOAkCRJkpQ3AwhJkiRJeTOAkCRJkpSNdSDaiutASJIkqRINq7Z1IPIxYsSI8I1vfCOsuOKKYbXVVgsHHHBAmDx5cql3S5IkSapKJV0HIh/jx48PQ4YMiUHEggULwi9+8Yu4oNybb74Zll9++bzTydp8vs7BXN3pZmlfTbd4aZpucdPN0r6abvHSNN3ippulfc1yum2t7AOIhx9+uM7/R40aFVsiJk2aFHbaaaeS7ZckSZJUjcq+C1N9M2fOjF+7du1a6l2RJEmSqk7Zt0DkWrRoUTj11FPDDjvsEDbbbLMG3zNv3ry45aLrkyRJkqQqa4FgLMQbb7wRRo8e3eSg6y5dutTZJkyY0Kb7KUmSJFWqzAQQJ510Urj//vvDU089FXr27Nno+4YOHRq7OeVu/fv3b9N9lSRJkipV2XdhYpmKk08+OYwdOzaMGzcu9O7du8n3d+zYMW652rcv+48pSZIkZULZLyR34oknhltvvTXcc889oU+fPrWv0zVp2WWXzSsNF5KTJElSJRrmQnKLGzlyZOyGNGDAgNCjR4/a7bbbbiv1rkmSJElVp+z79hSqgSRrC4K4iEt1p5ulfTXd4qVpusVNN0v7arrFS9N0i5tulvY1y+m2tbJvgZAkSZJUPgwgJEmSJOXNAEKSJElS3gwgJEmSJOXNAEKSJElS5awDkev888+PK02fcsop4bLLLsv791wHQpIkSZVomOtANO6ll14K11xzTdhiiy1KvSuSJElS1Sr7dSAwe/bscPjhh4drr702nHPOOS1KI2vz+ToHc3Wnm6V9Nd3ipWm6xU03S/tqusVL03SLm26W9jXL6ba1TLRADBkyJOyzzz5h4MCBpd4VSZIkqaqVfQvE6NGjw8svvxy7MOVj3rx5ccu1YMGCIu2dJEmSVF3KugXigw8+iAOmb7nlltCpU6e8fmfEiBGhS5cudbYJEyYUfV8lSZKkalDWAcSkSZPC9OnTw9Zbbx3at28ft/Hjx4crrrgifr9w4cLFfodZmmbOnFln69+/f0n2X5IkSao0Zd2Fabfddguvv/56ndeOOuqosNFGG4WzzjortGvXbrHf6dixY9xyEWxIkiRJqrJ1IDBgwICw5ZZbug6EJEmSqt4w14GQJEmSVM4y17dn3LhxLfq9rM3n6xzM1Z1ulvbVdIuXpukWN90s7avpFi9N0y1uulna1yyn29ZsgZAkSZKUNwMISZIkSXkzgJAkSZKUNwMISZIkSXkzgJAkSZJUOetArLPOOuGf//znYq+feOKJ4aqrrsorDdeBkCRJUiUaVoJ1IMp+GteXXnopLFy4sPb/b7zxRth9993DwQcfXNL9kiRJkqpR2QcQ3bp1q/P/888/P6y33nph5513blY6WZvP1zmYqzvdLO2r6RYvTdMtbrpZ2lfTLV6aplvcdLO0r1lOt61lagzE119/HW6++ebwox/9KCy11FKl3h1JkiSp6pR9C0Suu+++O8yYMSMceeSRjb5n3rx5ccu1YMGCNtg7SZIkqfJlqgXiuuuuC4MGDQprrLFGo+8ZMWJE6NKlS51twoQJbbqfkiRJUqXKTADBTEyPP/54OOaYY5p839ChQ8PMmTPrbP3792+z/ZQkSZIqWWa6MN1www1htdVWC/vss0+T7+vYsWPccrVvn5mPKUmSJJW1TLRALFq0KAYQgwcPNhiQJEmSSqjsF5LDo48+Gvbcc88wefLksOGGGzb7911ITpIkSZVomAvJNWyPPfYIGYhzJEmSpIqXiQCiELK2IIiLuFR3ulnaV9MtXpqmW9x0s7Svplu8NE23uOlmaV+znG5by8QYCEmSJEnlwQBCkiRJUt4MICRJkiTlzQBCkiRJUt4MICRJkiRVzjoQs2bNCr/61a/C2LFjw/Tp08NWW20VLr/88vCNb3wj7zRcB0KSJEmVaFgJ1oEo+xaIY445Jjz22GPhpptuCq+//npcE2LgwIHho48+KvWuSZIkSdWnpozNnTu3pl27djX3339/nde33nrrml/+8pd5pzN8+HBaWQq6kWZW0s3Svppu9vbVdLO3r6abvX013eztq+lmb1+zmm4plHULxIIFC8LChQtDp06d6ry+7LLLhmeeeaZk+yVJkiRVq7JeiXrFFVcM22+/fTj77LPDxhtvHFZfffXw5z//OTz//PNh/fXXb/B35s2bF7f6gYgkSZKk1ivrFggw9oFx3muuuWbo2LFjuOKKK8Jhhx0Wll664V0fMWJE6NKlS51twoQJbb7fkiRJUiUq+wBivfXWC+PHjw+zZ88OH3zwQfjLX/4S5s+fH9Zdd90G3z906NAwc+bMOlv//v3bfL8lSZKkSlTWXZhyLb/88nH74osvwiOPPBIuvPDCBt9HKwVbrvbtM/MxJUmSpLJW9utAECywi3369AlTpkwJZ555ZhxUTbekZZZZJq80XAdCkiRJlWiY60Asji5IQ4YMCRtttFE44ogjwo477hiDinyDB0mSJEmFU/Z9ew455JC4tdbw4cMLsj/108tCulnaV9MtXpqmW9x0s7Svplu8NE23uOlmaV9Nt3hpmu5/FTq9immBkCRJklQ+DCAkSZIk5c0AQpIkSVLeDCAkSZIk5c0AQpIkSVI21oF4+umnw0UXXRQmTZoUpk2bFsaOHRsOOOCA2p/fdddd4eqrr44///zzz8Mrr7wSttxyy2b/HdeBkCRJUiUaVm3rQMyZMyf07ds3XHXVVY3+nHUfLrjggjbfN0mSJElltg7EoEGD4taYH/7wh/Hr1KlTW/23sjafr3MwV3e6WdpX0y1emqZb3HSztK+mW7w0Tbe46WZpX7OcbltzDIQkSZKkylmJurnmzZsXt1wLFiwo2f5IkiRJlaTiWiBGjBgRunTpUmebMGFCqXdLkiRJqggVF0AMHTo0zJw5s87Wv3//Uu+WJEmSVBEqrgtTx44d45arffuK+5iSJElSSZS0ZD179uwwZcqU2v+/99574dVXXw1du3YNvXr1ims/vP/+++Hjjz+OP588eXL82r1797hJkiRJqqKF5MaNGxd22WWXxV4fPHhwGDVqVNyOOuqoBhfMaM60VS4kJ0mSpEo0rAQLyZU0gGgrBhCSJEmqRMNKEEBUzeCArC0I4iIu1Z1ulvbVdIuXpukWN90s7avpFi9N0y1uulna1yyn29YqbhYmSZIkScVjACFJkiQpbwYQkiRJkvJmACFJkiQpbwYQkiRJkipnGtenn346XHTRRWHSpElh2rRpYezYseGAAw5oVhpO4ypJkqRKNKwE07iWfQvEnDlzQt++fcNVV11V6l2RJEmSql7ZrwMxaNCguLVW1ubzdQ7m6k43S/tqusVL03SLm26W9tV0i5em6RY33Szta5bTbWtl3wIhSZIkqXyUfQtEc82bNy9uuRYsWFCy/ZEkSZIqScW1QIwYMSJ06dKlzjZhwoRS75YkSZJUESougBg6dGiYOXNmna1///6l3i1JkiSpIlRcF6aOHTvGLVf79hX3MSVJkqSSKPt1IGbPnh2mTJkSv99qq63CpZdeGnbZZZfQtWvX0KtXr7zScB0ISZIkVaJhJVgHouyr5idOnBgDhuT000+PXwcPHhxGjRpVwj2TJEmSqk/ZBxADBgwIhWgkydp8vs7BXN3pZmlfTbd4aZpucdPN0r6abvHSNN3ippulfc1yum2t4gZRS5IkSSoeAwhJkiRJeTOAkCRJkpQ3AwhJkiRJeTOAkCRJkpSNdSCefvrpcNFFF4VJkyaFadOmhbFjx4YDDjig9udHHnlkuPHGG+v8zp577hkefvjhZv0d14GQJElSJRpWgnUgStoCMWfOnNC3b99w1VVXNfqevfbaKwYXafvzn//cpvsoSZIkqUzWgRg0aFDcmtKxY8fQvXv3Vv+trM3n6xzM1Z1ulvbVdIuXpukWN90s7avpFi9N0y1uulna1yyn29bKfgzEuHHjwmqrrRb69OkTTjjhhPDZZ5+VepckSZKkqlXWK1HTfenAAw8MvXv3Du+++274xS9+EVssnn/++dCuXbsGf2fevHlxy7VgwYI22mNJkiSpspV1APG9732v9vvNN988bLHFFmG99daLrRK77bZbg78zYsSIxQZN77zzzkXfV0mSJKkalH0XplzrrrtuWHXVVcOUKVMafc/QoUPDzJkz62z9+/dv0/2UJEmSKlVZt0DU9+GHH8YxED169Ghy0DVbrvbtM/UxJUmSpLJV0nUgZs+eXduasNVWW4VLL7007LLLLqFr165xoyvSQQcdFGdhYgzEz372szBr1qzw+uuvLxYkNMV1ICRJklSJhpVgHYiSVs1PnDgxBgzJ6aefHr8OHjw4jBw5Mrz22mtxIbkZM2aENdZYI+yxxx7h7LPPblbwIEmSJKlCAogBAwaEphpAHnnkkYL9razN5+sczNWdbpb21XSLl6bpFjfdLO2r6RYvTdMtbrpZ2tcsp9vWMjWIWpIkSVJpGUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJysZCck8//XS46KKLwqRJk8K0adPC2LFjwwEHHPDfnVtqqQZ/78ILLwxnnnlm3n/HheQkSZJUiYaVYCG5krZAzJkzJ/Tt2zdcddVVDf6coCJ3u/7662NQwerUkiRJkqpsIblBgwbFrTHdu3ev8/977rknrly97rrrNvtvZW1BEBdxqe50s7Svplu8NE23uOlmaV9Nt3hpmm5x083SvmY53aoKIJrjX//6V3jggQfCjTfeWOpdkSRJkqpWZgIIAocVV1wxHHjggU2+b968eXHLtWDBgiLvnSRJklQdMjMLE+MfDj/88NCpU6cm3zdixIjQpUuXOtuECRPabD8lSZKkSpaJAIIAYPLkyeGYY45Z4nuHDh0aZs6cWWfr379/m+ynJEmSVOky0YXpuuuuC9tss02csWlJOnbsGLdc7dtn4mNKkiRJZa+k60DMnj07TJkyJX6/1VZbhUsvvTTOstS1a9fQq1ev+PqXX34ZevToES655JJw/PHHt+jvuA6EJEmSKtGwEqwDUdKq+YkTJ8aAITn99NPj18GDB4dRo0bF70ePHh2IcQ477LCS7ackSZKkMmiBaCu0QGRtPl/nYK7udLO0r6ZbvDRNt7jpZmlfTbd4aZpucdPN0r5mNd1h1bYStSRJkqRsMYCQJEmSlDcDCEmSJEl5M4CQJEmSlDcDCEmSJEnZmIVpxIgR4a677gpvv/12WHbZZUO/fv3CBRdcEPr06VP7nq+++ir89Kc/jdO5zps3L+y5557h97//fVh99dXz/juuAyFJkqRKNKzaZmEaP358GDJkSHjhhRfCY489FubPnx/22GOPMGfOnNr3nHbaaeG+++4LY8aMie//+OOPw4EHHljK3ZYkSZKqV00ZmT59Oq0hNePHj4//nzFjRs0yyyxTM2bMmNr3vPXWW/E9zz//fN7pDh8+PP5OITfSzEq6WdpX083evppu9vbVdLO3r6abvX013ezta1bTLYWyGgMxc+bM+LVr167x66RJk2KrxMCBA2vfs9FGG4VevXqF559/vmT7KUmSJFWr9qFMLFq0KJx66qlhhx12CJtttll87ZNPPgkdOnQIK620Up33Mv6BnzWEcRJsuRYsWFDEPZckSZKqR9m0QDAW4o033oiDpVs7MLtLly51tgkTJhRsPyVJkqRqVhYBxEknnRTuv//+8NRTT4WePXvWvt69e/fw9ddfhxkzZtR5/7/+9a/4s4YMHTo0doXK3fr371/0zyBJkiRVg5IGEMwgS/AwduzY8OSTT4bevXvX+fk222wTlllmmfDEE0/UvjZ58uTw/vvvh+23377BNDt27Bg6d+5cZ2vfvmx6akmSJEmZVtJ1IE488cRw6623hnvuuafO2g90O2JdCJxwwgnhwQcfDKNGjYrBwMknnxxff+655/L+O64DIUmSpEo0rATrQJS0an7kyJHx64ABA+q8fsMNN4Qjjzwyfv+73/0uLL300uGggw6qs5CcJEmSpFBdAUQ+jR+dOnUKV111VdxaY/jw4a36/cbSy0K6WdpX0y1emqZb3HSztK+mW7w0Tbe46WZpX023eGma7n8VOr1MDaKWJEmSlA0GEJIkSZLyZgAhSZIkKW8GEJIkSZLyZgAhSZIkKW8GEJIkSZKysZDciBEjwl133RXefvvtuHBcv379wgUXXFC7qNznn38eF8d49NFH4+rT3bp1CwcccEA4++yz42Jz+XIhOUmSJFWiYSVYSK6kLRDjx48PQ4YMCS+88EJ47LHHwvz588Mee+wR5syZE3/+8ccfx+3iiy8Ob7zxRlyN+uGHHw5HH310KXdbkiRJql41ZWT69Om0htSMHz++0ffcfvvtNR06dKiZP39+3ukOHz48plvIjTSzkm6W9tV0s7evppu9fTXd7O2r6WZvX003e/ua1XRLoazGQMycOTN+7dq1a5Pv6dy5c2jfvqSLaEuSJElVqWxK4YsWLQqnnnpq2GGHHcJmm23W4Hs+/fTTOP7huOOOazSdefPmxS3XggULCr6/kiRJUjUqmxYIxkIwzmH06NEN/vzLL78M++yzT9hkk03C8OHDmxyYzQDr3G3ChAlF3HNJkiSpepRFAHHSSSeF+++/Pzz11FOhZ8+ei/181qxZYa+99gorrrhiGDt2bFhmmWUaTWvo0KGxm1Pu1r9//yJ/AkmSJKk6lLQLEzPInnzyyTEoGDduXOjdu3eDLQ977rln6NixY7j33ntDp06dmkyT97HlcryEJEmSVAHrQJx44onh1ltvDffcc0/t2g+g2xHrQhA8MK3r3LlzY5Cx/PLL176HNSHatWuX199xHQhJkiRVomElWAeipFXzI0eOjF8HDBhQ5/UbbrghHHnkkeHll18OL774Ynxt/fXXr/Oe9957L6yzzjptuLeSJEmSSt6FqSkEFoVqIGlq4HVr0stCulnaV9MtXpqmW9x0s7Svplu8NE23uOlmaV9Nt3hpmu5/FTq9TA2iliRJkpQNBhCSJEmS8mYAIUmSJClvBhCSJEmS8mYAIUmSJCkb60CMGDEi3HXXXeHtt9+O6z7069cvXHDBBXXWhGAmpvHjx9f5vR//+Mfh6quvzvvvuA6EJEmSKtGwEqwDUdIWCAKDIUOGhBdeeCE89thjYf78+XHhuDlz5tR537HHHhumTZtWu1144YUl22dJkiSpmpV0HYiHH364zv9HjRoVVltttTBp0qSw00471b6+3HLLhe7du7fqb2VtPl/nYK7udLO0r6ZbvDRNt7jpZmlfTbd4aZpucdPN0r5mOd2qHgMxc+bM+LVr1651Xr/lllvCqquuGjbbbLMwdOjQMHfu3BLtoSRJklTdStoCkWvRokXh1FNPDTvssEMMFJLvf//7Ye211w5rrLFGeO2118JZZ50VJk+eHMdONGTevHlxy7VgwYKi778kSZJUDcomgGAsxBtvvBGeeeaZOq8fd9xxtd9vvvnmoUePHmG33XYL7777blhvvfUaHJhdf9D0zjvvXMQ9lyRJkqpHWXRhOumkk8L9998fnnrqqdCzZ88m37vddtvFr1OmTGnw53RxoitU7ta/f/+i7LckSZJUbUraAsEMsieffHIYO3ZsGDduXOjdu/cSf+fVV1+NX2mJaEjHjh3jlqt9+7JpaJEkSZIyraTrQJx44onh1ltvDffcc0+dtR+6dOkS14WgmxI/33vvvcMqq6wSx0CcdtppsZWi/toQTXEdCEmSJFWiYSVYB4JWgJLhzze03XDDDfHn77//fs1OO+1U07Vr15qOHTvWrL/++jVnnnlmzcyZM4uyP1999VXNsGHD4tdqTTdL+2q6xUvTdIuXpukWN90s7avpFi9N0y1uulnaV9MtjpK2QJSbL7/8MrZ+MG6ic+fOVZlulvbVdIuXpukWL03TLW66WdpX0y1emqZb3HSztK+mW8GDqCVJkiRlgwGEJEmSpLwZQEiSJEnKmwFEDqZ/ZSR7/WlgqyndLO2r6RYvTdMtXpqmW9x0s7Svplu8NE23uOlmaV9NtzgcRC1JkiQpb7ZASJIkScqbAYQkSZKkvBlASJIkScqbAYQkSZKkvBlASJIkScqbAYQkKW8DBgwIp556aql3Q5JUQgYQkqSiGDduXFhqqaXCjBkzSr0rkqQCMoCQJEmSlDcDCElSg+bMmROOOOKIsMIKK4QePXqESy65pM7Pb7rpprDtttuGFVdcMXTv3j18//vfD9OnT48/mzp1athll13i9yuvvHJsiTjyyCPj/xctWhRGjBgRevfuHZZddtnQt2/fcMcdd5TgE0qSWsIAQpLUoDPPPDOMHz8+3HPPPeHRRx+NXZJefvnl2p/Pnz8/nH322eGvf/1ruPvuu2PQkIKEtdZaK9x5553x+8mTJ4dp06aFyy+/PP6f4OFPf/pTuPrqq8Pf/va3cNppp4Uf/OAH8W9JksrfUjU1NTWl3glJUnmZPXt2WGWVVcLNN98cDj744Pja559/Hnr27BmOO+64cNllly32OxMnTgzf+MY3wqxZs2KrBQEHrRBffPFFWGmlleJ75s2bF7p27Roef/zxsP3229f+7jHHHBPmzp0bbr311jb8lJKklmjfot+SJFW0d999N3z99ddhu+22q32Ngn+fPn1q/z9p0qQwfPjw2AJBkEDXJLz//vthk002aTDdKVOmxEBh9913r/M6f2urrbYq2ueRJBWOAYQkqUXjI/bcc8+43XLLLaFbt24xcOD/BANNtWzggQceCGuuuWadn3Xs2LHo+y1Jaj0DCEnSYtZbb72wzDLLhBdffDH06tUrvkYrw9///vew8847h7fffjt89tln4fzzz4/jHVIXplwdOnSIXxcuXFj7Gi0TBAoEG6QjScoeAwhJ0mIYw3D00UfHgdSMhVhttdXCL3/5y7D00v9/7g2CCgKEK6+8Mhx//PHhjTfeiAOqc6299tpx9qX7778/7L333nHGJWZsOuOMM+LAabo87bjjjmHmzJnh2WefDZ07dw6DBw8u0SeWJOXLWZgkSQ266KKLQv/+/cO+++4bBg4cGAv722yzTfwZXZZGjRoVxowZE1sVaIm4+OKL6/w+XZR+85vfhJ///Odh9dVXDyeddFJ8nUDjV7/6VZyNaeONNw577bVX7NLEtK6SpPLnLEySJEmS8mYLhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkiRJypsBhCRJkqS8GUBIkrQEo0aNCksttVSYOnVqqXdFkkrOAEKScvztb38LP/jBD8Kaa64ZOnbsGNZYY41w+OGHx9db47zzzgt33313qAbFOoaFNmDAgBgULGkbPnx4qXdVksrKUjU1NTWl3glJKgd33XVXOOyww0LXrl3D0UcfHXr37h1rnK+77rrw2WefhdGjR4fvfOc7LUp7hRVWCN/97ndjTXYlK+YxLLTHHnss/Otf/6r9/0svvRSuuOKK8Itf/CJsvPHGta9vscUWYdNNNw3z58+PARFBhSRVMwMISQohvPvuu7Gg2KtXr/D000+Hbt261f7s008/Df379w8ffPBBeO2118K6667b7PSrIYAo9jFsqTlz5oTll19+ie+74447wsEHHxyeeuqp2DohSWqYXZgkKYRw0UUXhblz54Y//OEPdQq+WHXVVcM111wTC6IXXnhh7etHHnlkWGeddRZLiy4vubXUfM/v3njjjbXdYvjd5KOPPoq19XT1oYabWvsTTjghfP3117Xv+cc//hELt9TsL7fccuFb3/pWeOCBB+r83XHjxsW0b7/99vCb3/wmdiFaccUVY+Ayc+bMMG/evHDqqaeG1VZbLQY0Rx11VHytvptvvjlss802Ydlll41/73vf+14s+Bf6GFJgZ3/Hjx+/WFq8l5+98cYbta+9/fbb8bOwT506dQrbbrttuPfeexscq0CaJ554YvysPXv2DMUYA8G5//a3vx2PO/vC8dp8883j/1NrDP9nXzmer7zyymLp5vOZJKnctC/1DkhSObjvvvtigZBa8obstNNO8ef1C+35uOmmm8IxxxwTvvnNb4bjjjsuvrbeeuvFrx9//HF8fcaMGfFnG220UQwoKFxTGO/QoUPsZtOvX7/4/5/85CdhlVVWicHIfvvtF99Xv0vQiBEjYmH25z//eZgyZUq48sorwzLLLBOWXnrp8MUXX8QA54UXXoiFYoKVX//617W/e+6554Zf/epX4ZBDDon7/O9//zv+Pp+fAvBKK61UsGO4zz77xECGgGfnnXeu897bbrstdhvabLPN4v8ZP7HDDjvEoIjPRYsCv3fAAQeEO++8c7FjQPBAEMNnI2gpFo7v97///fDjH/84jvu4+OKLw7777huuvvrq2BWK/UjnhGM6efLkeB5a8pkkqWzQhUmSqtmMGTPoylmz//77N/m+/fbbL77vyy+/jP8fPHhwzdprr73Y+4YNGxbfl2v55ZeP76/viCOOqFl66aVrXnrppcV+tmjRovj11FNPjelNmDCh9mezZs2q6d27d80666xTs3DhwvjaU089Fd+32Wab1Xz99de17z3ssMNqllpqqZpBgwbVSX/77bevs/9Tp06tadeuXc25555b532vv/56Tfv27Rd7vRDHkH1bbbXVahYsWFD7nmnTpsVj8tvf/rb2td12261m8803r/nqq6/qHJ9+/frVbLDBBrWv3XDDDTH9HXfcsU6a+RgzZkz8XY5jfSnd9957r/Y1jh2vPffcc7WvPfLII/G1ZZddtuaf//xn7evXXHPNYmnn+5kkqdzYhUlS1Zs1a1b8SnefpqSff/nllwX5u4sWLYozM1FjTdeV+lI3qAcffDC2Uuy44461P6PmnhYLutS8+eabdX7viCOOiC0OyXbbbUc0E370ox/VeR+v0zVpwYIFtV1u2CdqyhmzkLbu3buHDTbYII4NKPQxPPTQQ8P06dNru/2AVhX2g5/h888/D08++WTcL/5O2i8GZe+5557hnXfeia02uY499tjQrl27UGybbLJJ2H777escU+y6665xLEj91+mK1tLPJEnlwi5MkqpeKtSmQnBrC8n5onsQBenUTacx//znP2sLoLnSTEH8PDeN3IIrunTpEr+utdZai71OQZ3xEXSLotBKoEGw0JDcoKRQx3CvvfaK+0GXpd122y2+xvdbbrll2HDDDWu7CbFfdK1iawhBCF2BErpmtYXmHGvQhayln0mSyoUBhKSqR+GuR48ecXagpvBzCnSdO3eO/29sOs+FCxeGUmqs5r2x19NkfAQTfKaHHnqowffS6lHoY8igcfr8jx07Nvz+97+P4z2effbZuG5Gwn7hjDPOiLXzDVl//fXr/J8xIOV+rJv7mSSpXBhASFIIcTada6+9NjzzzDN1ugolEyZMiN2FGCybrLzyynHwc320CNTXULDBIF8K0rkzDTVk7bXXjoNvG5rBJ/28EBjYTQGX2vtU+1/sYwi6KjEo/IknnghvvfVW3IfUfQlpyldaQAYOHBgqQSV+JknVwzEQkhRCOPPMM2OtNYVb+qHnor/68ccfH6dP5X25BW66/+TWuk+bNi3WptfHDDv1gw1m46H2ndmLJk6c2Ght9d577x3+8pe/hOeff772Z8wsxHSpzGpEP/xCOPDAA2PNOVPA1l8iiP/XPy6FOIagAM00pnRdYmO8R24XJKZiZV0Gpnbl+DbUFSxrKvEzSaoetkBIUgix3z+14Icffnicu7/+KsoMcP3zn/9cO/0qWB/hrLPOitNtMr0q06yOHDky1t6//PLLddJnHYDHH388XHrppXG9B9JmXANddR599NE4jSmDohnXQIFyzJgxsSafaVOZ4pO/PWjQoPh3KGyzr++9916c7jNNC9pafLZzzjknDB06NH5ughvGKvB3CIrYP7rcFPIYplp4ghdWqSYwYirU+q666qrYqkG6DJCmBp/uTgRVH374YfjrX/8asqYSP5OkKlHqaaAkqZy89tprcWrRHj161CyzzDI13bt3j/9nKtOGPProo3Ha1A4dOtT06dOn5uabb25wGte33367ZqeddorTe/Kz3Cldme6T6Vy7detW07Fjx5p11123ZsiQITXz5s2rfc+7775b893vfrdmpZVWqunUqVPNN7/5zZr777+/zt9I07gyHWlDU5DWnyo27ee///3vOq/feeedcRpUpp5l22ijjeL+TJ48uSjHEI899ljcF6ab/eCDDxp8D8eA40R6pLvmmmvWfPvb36654447lvhZizWN6z777LPYe3kfxysXv8frF110UbM/kySVm6X4p9RBjCRJkqRscAyEJEmSpLwZQEiSJEnKmwGEJEmSpLwZQEiSJEnKmwGEJEmSpLxV/DoQixYtCh9//HGcy7yhlWAlSZKkLKqpqQmzZs2K6wsVak2gfFR8AEHwsNZaa5V6NyRJkqSi+OCDD0LPnj1DW6n4AIKWh3RgO3fuXOrdkSRJkgriyy+/jBXlqbzbVio+gEjdlggeDCAkSZJUaZZq4276DqKWJEmSlDcDCEmSJEl5M4CQJEmSlLeKHwMhSZKkyrFw4cIwf/78UA2WWWaZ0K5du1BuDCAkSZKUiTUPPvnkkzBjxoxQTVZaaaXQvXv3slrPzABCkiRJZS8FD6uttlpYbrnlyqpAXayAae7cuWH69Onx/z169AjlwgBCkiRJZd9tKQUPq6yySqgWyy67bPxKEMFnL5fuTA6iliRJUllLYx5oeag2y/3fZy6ncR8GEJIkScqESu+2lJXPbAAhSZIkKW8GEJIkSZLyZgAhSZIklcCRRx4ZDjjggJA1BhCSJEnKtAEDBoRTTz21Tf7WkRkt9FdMADF8+PA4MCR322ijjeq85/nnnw+77rprWH755UPnzp3DTjvtFP7zn/+UbJ8lSZKUvTUVFixYUOrdqBglb4HYdNNNw7Rp02q3Z555pk7wsNdee4U99tgj/OUvfwkvvfRSOOmkk8LSS5d8tyVJklQGaBEYP358uPzyy2srpEeNGhW/PvTQQ2GbbbYJHTt2jGXMRYsWhREjRoTevXvHNRb69u0b7rjjjjrrTRx99NG1P+/Tp09MN7fy+8Ybbwz33HNP7d8aN25c/NkHH3wQDjnkkLhydNeuXcP+++8fpk6dWift008/Pf6ctSx+9rOfxcAmi0q+kFz79u3j8twNOe2008JPfvKT8POf/7z2NU5kU+bNmxe35Msvvyzg3kqSJKmcUMD/+9//HjbbbLPw29/+Nr72t7/9LX6lDHnxxReHddddN6y88soxeLj55pvD1VdfHTbYYIPw9NNPhx/84AehW7duYeedd44BRs+ePcOYMWNiIf+5554Lxx13XFwFmuDgjDPOCG+99VYsX95www3xbxAssEbDnnvuGbbffvswYcKEWL4955xzYkX4a6+9Fjp06BAuueSSGNhcf/31YeONN47/Hzt2bOxpkzUlr8p/5513whprrBFP7OGHHx7ef//92hX3XnzxxbjqXr9+/cLqq68eT2xuC0VDuDC6dOlSu6211lpt9EkkqbDmzJlTW8PF95KkxVHeo4DOgmtUSrOlFZsJKHbfffew3nrrxe7w5513XizAU9in7EnrBQHENddcE9+/zDLLhN/85jdh2223ja0QlE2POuqocPvtt8efr7DCCrFlghaN9Lf427fddlsMPv74xz+GzTffPAYIBBiUa1MLxWWXXRaGDh0aDjzwwPhzghj2PYtK2gKx3XbbxUiMVgW6L3HC+vfvH954443wj3/8o7apiMhxyy23DH/605/CbrvtFn9O1NgQTgzNQwkRokGEJElS9SEQSKZMmRLmzp0bA4pcX3/9ddhqq61q/3/VVVfFIIPCP+Nu+Tnl0Kb89a9/jemvuOKKdV7/6quvwrvvvhtmzpwZy7qUfRNaKdi/LHZjKmkAMWjQoNrvt9hii3hQ11577RjlEZnhxz/+cYz8wMl94okn4kmlpaEhRIRskiRJqm60OiSzZ8+OXx944IGw5ppr1nlfKjuOHj06dlOiexHdkQgILrrootgrpimzZ8+OYy1uueWWxX5G96hKU/IxELkYVLLhhhvGCC71B9tkk03qvIfAInVzkiRJkuhGxCDlplCmJFCgHEm3+IY8++yzsev8iSeeWPsaLQhL+ltbb7117MZE13tmDW0I4ygIRJhRFMwKNWnSpPi7WVPyMRD1ozdOEgd4nXXWiWMjJk+eXOc9DJKhlUKSJEkC5UYK58x69Omnn8bxCPXRmkDrApP0MJMSZc6XX345XHnllfH/oIv8xIkTwyOPPBLLnL/61a/iLKD1/9Zrr70Wy6j8LQZQM1Zi1VVXjTMvMYj6vffei2MfmAzoww8/jL93yimnhPPPPz/cfffd4e23345ByowZM0IWlTSA4CQy7RYnm1Hu3/nOd+Kgl8MOOywOGjzzzDPDFVdcEafXolWCk8gBZ3otSZIkKZUpKUPSykCXocZ6q5x99tmxPElXeHq1MEsSXZoYMJ26zjPI+dBDD41d6z/77LM6rRE49thj4/hdxi/wt2i1YAA3Mzr16tWrdpA05VXGQKQWiZ/+9Kfhhz/8YRg8eHBt9yjKvlm0VE0JR25873vfiwebk8MJ2HHHHcO5554bR8onRGoMZvn888/jXL0XXnhhfF++GETNCHcGrzTWpCRJ5YgpqdOkEJdeeqnjuyRVLQri1OpT0O/UqVOoJl818dlLVc4taQDRFgwgJEmSss0A4r2yCiDKagyEJEmSpPJWVrMwSZL+iwZiBuiBwXmMDZMkqdQMICSpTLHgEVMCplnqcuczlySpVOzCJEmSJClvBhCSJEmS8mYAIUmSJClvBhCSJEmS8mYAIUmSJClvBhCSJEmS8mYAIUllqn379mHw4MFx43tJUrZdddVVYZ111okrSm+33XbhL3/5S8gin0iSVKY6duwYRo0aVerdkCQVwG233RZOP/30cPXVV8fg4bLLLgt77rlnmDx5cu2aP1lhACFJkqTMqqmpiQtvtrXlllsuLLXUUnm//9JLLw3HHntsOOqoo+L/CSQeeOCBcP3114ef//znIUsMICSpTOU+FJv7oJKkakE+ucIKK7T53509e3ZYfvnl83rv119/HSZNmhSGDh1a+9rSSy8dBg4cGJ5//vmQNY6BkKQyfyiylaJ2TZJUGJ9++mlYuHBhWH311eu8zv8/+eSTkDW2QEiSJCmzaKGlNaAUf7daGUBIkiQps+jemW9XolJZddVVQ7t27cK//vWvOq/z/+7du4essQuTJEmSVEQdOnQI22yzTXjiiSdqX1u0aFH8//bbbx+yxhYISZIkqchOP/30uK7PtttuG775zW/GaVznzJlTOytTlhhASJIkSUV26KGHhn//+9/h17/+dRw4veWWW4aHH354sYHVWWAAIUmSJLWBk046KW5ZZwAhSWWKAXff/e53a7+XJKkcGEBIUpnq1KlTGDNmTKl3Q5KkOpyFSZIkSVLeDCAkSZIk5c0AQpLKFNP7sUASG99LklQODCAkSZIk5c0AQpIkSVLeDCAkSZIk5c0AQpIkSVLeDCAkSZIk5c0AQpIkSSqyp59+Ouy7775hjTXWiLPr3X333SGrXIlakspUu3btwt577137vSQpu+bMmRP69u0bfvSjH4UDDzwwZJkBhCSVqU6dOoUHHnig1LshSWWtpqYmfP31123+dzt06BBbEvI1aNCguFUCAwhJkiRlFsHDT37ykzb/u1dccUXo2LFjqEaOgZAkSZKUN1sgJKmM+8uuttpq8fvp06eH5ZdfvtS7JEllh65EtAaU4u9WKwMISSpjc+fOLfUuSFJZYxxCtXYlKhW7MEmSJEnKmy0QkiRJUpHNnj07TJkypfb/7733Xnj11VdD165dQ69evUKWGEBIkiRJRTZx4sSwyy671P7/9NNPj18HDx4cRo0aFbLEAEKSJEkqsgEDBsQ1KyqBYyAkSZIk5c0WCEkqU0svvXTYeeeda7+XJKkcGEBIUpladtllw7hx40q9G5Ik1WGVliRJkqS8GUBIkiQpExYtWhSqzaIy/Mx2YZKkMjVnzpywzjrrxO+nTp0all9++VLvkiSVRIcOHeJYsI8//jh069Yt/p8VqCtZTU1N+Prrr8O///3v+Nn5zOXCAEKSytinn35a6l2QpJKjAN27d+8wbdq0GERUk+WWWy4uNFdOk2kYQEiSJKnsUQNPQXrBggVh4cKFoRq0a9cutG/fvuxaWwwgJEmSlAkUpJdZZpm4qXTKpy1EkiRJUtkzgJAkSZKUNwMISZIKPHPKzJkzw/z580u9K5JUeQHE8OHDY1+23G2jjTZqMDMeNGhQ/Pndd99dkn2VpLbGjBvbbrtt3Mpp9g01be7cueHDDz+MUy9KUiUq+SDqTTfdNDz++OO1/2ekeX2XXXZZ2Y0+l6RiW3bZZcNLL71U6t1QM1Dh9dlnn4Wvvvoqfu3cuXNYYYUVSr1bklRZAQQBQ/fu3Rv9+auvvhouueSSMHHixNCjR48lpjdv3ry4JV9++WXB9lWSpCUt/jdjxozQpUuX2BIxffr0GAgyFaMkVYqSt4m/8847YY011gjrrrtuOPzww8P7779f+zMy3+9///vhqquuajLIyDVixIiYcadtrbXWKuLeS5L039YHFv7jK1NMrrjiinEsxBdffFHqXZOkygkgtttuuzBq1Kjw8MMPh5EjR4b33nsv9O/fP8yaNSv+/LTTTgv9+vUL+++/f95pDh06NGbYafvggw+K+AkkqXioRFlnnXXixvcqb7Nnz47PndRliXErnTp1imMh6NIkSZWipF2YGBidbLHFFjGgWHvttcPtt98eunXrFp588snwyiuvNCvNjh07xk2Sso6a7H/+85+136t8LVq0KI55YLxe7li+5ZZbLnz++ecxiOjZs6fj+SRVhJJ3Ycq10korhQ033DBMmTIlBg/vvvtufI3MOGXIBx10UBgwYECpd1WSpMVaH5ZffvnFfkZXJoIIx+RJqhQlH0RdPwMmaPjhD38YDjnkkHDMMcfU+fnmm28efve734V99923ZPsoSVL91gfGPtRvfUgYD0F3JgZUE2A09B5JypKS5mJnnHFGDAbotvTxxx+HYcOGxZkqDjvssNiFqaGB07169Qq9e/cuyf5KklQf4/bYaGloTGqFoJvT6quv3qb7J0kVFUCw0A7BAhkqAcOOO+4YXnjhhfi9JElZGvvQ1FSt/JzWB8ZCEEwwNkItw3ggx5JIVRxAjB49ulnvdxChJJU3uqJS086A4WpYPZuWB8Y2sGDckjAj03/+85/YlYnW9Go4PoVGOeCjjz6Ks1pxPNnoIpY2uocZXEjFZ0dMSSpTFIQ22WST2u+zgOCBwcSrrLJKgwOKK8nChQvj2AdaHvJdKI5AIy00t/LKKxd9HysNwRotPgQKTG3MOQDHP024wsJ99QMLtqzcQ1IWGEBIUpmim8vf/va3kBUU6Agevv7661jQq/QAgs9IC0Q+rQ8JBV0Ks2lAdYcOHYq6j5Vk/vz54V//+lc8hmmtjYRAYsGCBXFj4b4UWNDKkwILggqCixRQcOx53ZYgqfkMICRJBUHwQAGOwIda9lVXXTUW1CoRBdRUE55v60NC4EAhl9aLNdZYo2j7WGk43nSR69q162I/S61A9deBYoxKCiwI+DjuaQxFbmDBxu+mblB8be55lZYUAFO5UikVKwYQkqRW48FI4Sx1H+H7OXPmxLV8Krn1oSWfj8IrNegUiGm9qF+brsVxLTEAncJXc7oi0bpAS0P9lp7cwCKt4ZHGWabuUAQUuYFFbnAhNff6nTZtWrwe11133VAJDCAkqYy7BH3jG9+I37/00ktlPXMPBWoGtlI7nGYkSn39K63veRr7kNZ3aAkKtJxfuuQQdFnb3TgK+wQPfKVAXwiNBRYEESmwYMA7QSJ/N13TqQtaarVI3aBScGF3KNVHPshSBQQRDbWeZZUBhCSVKQozb775Zu335d6dh5raFCxQKKbwRVDB95WE2mpqrVvbupIGVDPw3OnLG8cxokWLYLTYuH5Ta0N9aZwFXVEILggsuC/rj7NIgUUKKvjewKJ6F5j85JNPYuBZzhVALWEAIUlqFQIFClS5BTwKTRSy+VklBRAUIKkNL0ShkN+nsJnWhihU7XqldY2jlYbjXepWmuaMs8j9Hc7rWmut5fmtIvPnz4+BAwEEgQPnnvywkhgSS5JajMITNegUlOoXqCn0UXucZsSplNYHuiIUaiAkhQsKyQQR5dzKVAocD2arIjgt54GnqTsU55JWJabnZaOFiuCZgiOFyUq6D9Q4rtf3338/3tNcD5UaOBpASJJajH78tDI01DzPazxMKXBXSq0iNYq5XbUKgUHUBGHUXuu/uK44LrTOZHEcTeoORcscrRK0pBgkVrYvv/wyTJ06NV67BJF0YatUBhBlhpoo+gxLUhbQwkChqKEHZWqRqJSCMa0PBEyFrg1PU4ZS206Qov8/3oDjgayvlZHWraBGmvtFlTvQ/5///Ge8dml9qvRxL5X96TJ28VFD8d5774UPP/ww/l+SyhmtCxSImhocSPM9AcS8efNClhWr9SGhgEmtJYPR9f/XfOC6ofWhEqTZmpjKkyBUlWPBggVxlqWPPvooVgZktcWsuQwgygAtDgQNRK48pNLAQ0nVjYfQ2muvHbdyfCClVafrDyrNxc8IHrLejYkKHgp+xZpJhfNLywZBStaPVSEC0zT4tJJqcQkSecZT2LSlqXLKb++//35sLeP8VtKEEUtSOXdmhgcf0uqQ+nmykWFS+2IrhFTdKEDRn5at3KYApACUFo7Lpx84eVxW8zSCJPJkPmsxAzlaa+j+kNY8qOauIASdlVgYY1AtLSuMh6jWc1wpZs+eHSt+qUhhvEO1LTBoAFHiUfps9B/OHWyTmrIrbcovSZWjOWs88B5q77PadYNuWm21ngWVSPy9au0rn6ZBpaBdiagg5LPRwkJQreyhzPb555/Hih0CXcpvldRSlq/q+8QllmqX/vGPf8QHBBlJ/QF5aa5rLlBnbJBUrgvH0a87nxp5Kkf4nSx2zUytD7QOtEU3srTSMTXU/O1qQqsWn5tjUMmz13B+6drH1K5WFGYL+RjjWD744IN4nTLDVjl2L20LBhBtiH6tNHdx4RGtErU2tjAOrRDUxFR7X1ip2lsqv/GNb8SN78sFhR7ypuZ0q6L2nkqTrPX9piKHY9+W3WmoVOJvVtvaENTK00rF86/Sce/QhYnxENUWKGYV54nyG0HucsstV3bdStta5Yb4ZVhbxyCbNL3XklbUpPaFBwdNuTxMqjXClaoZBYyJEyfWfl8OUr5EJUhzmu2pwef3CD6oPMkCui0RQFBQaMs8mL9FVyaeG7RSV8pMRE0hICWAqKbnHeeWe4Ia7Z49e5Z8pW0Q4FNOKdZsY1m+Pgn2yL9odWhXBueq1AwgioyLjWiV1gQeQs15EPB+auy6du1a1qtwSqoeTS0c1xQKIzx0GXBIJUoWCicU7ggiVllllTb/23QPoxWCiieOdSUXWAiO06Dipmb0qjTcAxRGUxe51VdfveSFZIKZtPJ36mLdVt33yhEVJpTDOC5M10rlR7Uei/oMIIo8ZzgbF2BLFhXhAUIAklohJKnUeJhSQ9mSGUcoCDdn8HU5tD6UMu+lwon8n/3o1q1bqORrisCSwnS1ITDkGiOAoqBeimNQv5CcJj3gnNAbgv9ThuH+ZR+rZcAwAS0BPOeG41CN12dTDCCKcCPygOSC4yt9OVtTo0LGwo1NDVi5P3AlVTYK1eRHLc2LCDrIF9nKPT+j0E6f51L2x6egxnFiLESlzjHPLDY8L3lOVnIrS1MolKf1ITgO/L/UheS0+jf7xTmi738KJlLLBN9XajDB52aQe+pWV00tY/kygCggHjZcbGT23FR0PWptUxcXLc2K+cy3Xkk3Lg9vjl+1zasslbO0onRrCtXkaeRnVIqUa4GRLhylbn1IqPVlX3iu0E++kgpsVLjxuQhMszIupli4pwjOCSJYOLIt7g2etbQ60IWqsUIyz+D0HKZ1gnPFisvsX2oxScFEsfeZYId9YL/Txv4UY6IB8jkqOvh8lTwjWGt4VAqAi5emPiJ4Cvs0O6fovRByx0K0Zc1EKR8oHEuCr9VWW63UuyTp/woPFGRbmwdR0CC/JK8s17n+KVDxectl8HIabMtXupJUCgpoHGuOc7X3K0/jITjP3GM9evQo6jGhixLBCueA6yqfQjLvSZUHdGMk0CYAYT9zg4nWjtkhUMgNEqicJVBg475kS5NK8HeKcZzSTJmVFLAXmgFEAaJUCrxkglzIhWh1qI8bk/R56FZ6AEENJ8eTY0lrDhlbpX9mqSmrrrpqKAcUNCgwtLammAcyeST5WTkGEBSsKMS1ZopGClcUcgrV7YGCG3kiXU0ooFVCyyzHh8/D9VAJn6cQOBYEUzwDee5RnigG7r00fWxLxmeC6zE3mKBwnxtMcG/zc+6jxoITfo8AgWuBfWkoUKBSMU3AQDpUzpKmBfvSM4BoIaJfbkL6yHGxc9MXMxOk1o7aPx7ehWzdKCdkHrQ8pJU6+bxsa6yxRql3reKOMxlzoXHeDPYKi8IihYlyyO+oxCCPK0QFCflZ6g5Vbn2LyXO4P1oa3FDgGT16dCxM/fCHPyzYzDoUxghsqFghqKQwleVae44zQWkltagUAs/31P+ee6OQ3ei4j7l+SJsCeaGOfRoIzsbfoExEcEjexeehZSIFG9xb3PdURvCV/xNIcN/wDCGt1D0q69d4pTOAaCG6FKVBRW0xrVcKIAhaKnE2DjIPMhy6NaQaTjIjCi2pWVStR6bNYobFWLiIwmWvXr08VxUoLRxXqC49FCpIj3TLKYBI481aM8aD5wL3GO69995w1FFHFaQPNc8Y7i0Kf+xjGtBKQSv1U09buRe60iJ5lTwItzU4zzzrCUIZD1GIysm0yjfHPc2mVAycz7TIWgom+Js831NrAvhMBApcAwYK2WQA0Yqa8tz+gMWWmgUpUFNrUGlNvmSW9fvCUrDwQVM41PTwQCJDL8Z0dKn7meeqsqQpHlM3gkIgLfIwCsLl0s+Yz0klDbWhrWnl/ctf/lL7PffDhAkTwi677FKQfSRP5Lilbh8cP/YXHEOeSWw8K7gPU0DB5+H1cjjOadYfPkM1rDjdUqkVnoBxzTXXbNW54zlKlyXy6HzHOxQ6mEgDnQ0UKocBRDNxE9AEyA1ZrP6JS5qNg0ygFAsbFQvNmGSSZGr1AyMeMAQXaTYEta6Fh4JgsQpsnqvCI58ZNGhQ/P6hhx4qyUxs7APntdB/m/RogWDMQTkUJGl94P5ozb5QoP/73/8evx8wYEAYN25ceP7558P6668f1lprrYLsJ/cugUT9lps0Qw0bzwj2JdX4ptpeAgu2FIikPLctZ8PiWmLfymWAelYWmWtpzwOuBWZN4jnb0vEOhWDgUHkMIJqJB16pZo3g75Hxp1aIcp0CsSW1UY0Nzky1Zmke9Er4zKXAA5tjyHVbrAeI56o498f48eNrvy/lwnGFHnvF9cJnooBT6gAitT6wP61p3Z04cWL8uu6664Z+/frFvPr1118P999/fzj66KOLOn6Ne4/06/+N3MCC5xcF+FQbzD3K5+W5QkBXiBl0mkKrA/l9Cl7UtNSaRAUbX5sTdKVxS/wuZYesrP6u7Ch9e2aG8BBN/fhKNZCZzJ2aMh66lYDCCZkczaqNZW4ULqjV5sGn5uN6oetS6spQTJ6ryuuuyT1arP7SaUpXCpbl0PrQmvE7dA3861//Gr//5je/Gb/uvvvutVOwPvHEE6EUUmDBs4MCKAVJKmv4mlqVUh7xj3/8I7zzzju13V0KPdkClQu0ODlOKn/pHHFOaEXIB+eN99PyQL7vNLkqBgOIZkiDmEvZ9JqmvKPQnfq+ZhUPXMaSpP65S3oAErwVY/BvJeN4UTDgWmmLh3bqXuG5qgwUIrlPixVAkC7pUzNe6m6pfG1N6wPBA9c8MyT17t279vPts88+8ftXXnklFtDLReraRAGVZxpdcgl2UnfHFExQCOU6aG2Ql1rvyYcszDYP54fAK+XlTeF+ev/99+M5rNTVy1UeDCDyVE6DecmAyYxL+dBtLZpX0xS4+RRseU9aHVb5H2MCtLRQUFuhptNzlX0UVCjwERAWq8CXBmbndqtpa6lbT2u6UXGvpe5L3/jGN+ocL4KJbbfdNn5PVybujXKVBr3SQkH/ez4HwRXBxJQpU8KHH37Yohaj3Nb7cpp1K2vjIdKK5I3dKwR6zADGOeIcVtpkKyovBhB5Phy4aWk+bM3iQoWS5krm4V6qftGtRUZIs36+g23JQDn2fOZyfgCXEx78aTG+tqzx81xVBgJPaj2LneeRPn+LyoS2lvrkozV98hk4nQaab7bZZov9nFmYqOEnWHn00UdDFvCc4fPQ1Sn1n+eeTi0T1HLT7Suflkbe19ogrdqlhduoFKrfhZmAgnOTpugul5nNVNm8wvLAw43CbjmtmkqNPPuVxVYICiVkgjTvN2ewHu/ngU9GWarayqzgAcMxTnNstzXPVbZRMUGQ3xZTf1JLSp9t8rO2RK043XMKsSJ2mrp1q622arDWl9f23XffWAj/29/+Ft56662QJex3CiYonJJv80x87733YssEBVf+31Af/bSoGC0PTqzQOhxD7knGN6TKGa5jujaldanausJI1csAIs/FV9Iy6uUiZcQ85LNUQCOzo+sSBYaW1GxSA8NnZtCfGsYDmwcKStn/1XNVGGke9bYO8inQt9XfpWCUu6ZBWwRI3CP8zdZObUlhjq49pJG6KjWEufy33377+P3DDz+cycqf3DWJUjDBc5EgbOrUqTGY4Cv3PflQGl/C94W6lqiUePrpp8Nrr71WOz1pNSFf5TNz/ZK3EjjwTE0zaKk8zZo1K163zMpWKcqnRFymyKzI6Nt6zYfmzLtPJpKVpmGOJ83ZPHxaItXupdU0baZtOECjdqqlx7hQ0rmi9tFz1TIUCkoRgFGwRltVmqTZmPisxW7pTYOE07TGra0VT60Pm2yyyRLz4f79+4d33303Vko9+OCD4eCDD850bXGaWpyN40r3mdRinwZo8/ws1CxAVDyNGTNmsfFVpM/gdTbWSErfV2qBmq6/qcUnre9g6055mjlzZlwLhkkWeD7TBZDWyEo4XwYQTeBhxkOmXGeNSA93MtNy3cdcPEh4cLKvrbl5UuBEN51SF5LLSSoYcT2Uy5zfnCvOUxrUp/JXrIXjmkJwyVaI7kRLwv2R8qHWDjLl2n777bfrTN3aFPI9Cg833HBDrK2nFr1v376hEuQGEyCYoCUrrYZdCC+88EI8f1ybq622Wm0FH0ELG12qchFA5AYUaSNfKof8saW4V7hPUvCQ5c9Sqb744ovw3HPPxRaHNFa1R48eYccdd6yYyjQDiCUMnOZrsaYwLAQegjx0ySTLeW5tao54aFPIbe3xTN3J0oJl5dS1rJS4DtLUfeVSu5HOFd0YqCX0XJW/NMtOW09XTb5Q7Glj+Wx0OWJa6ELMBjRp0qT4jGCV6e7du+f1OxR8d9ppp/DUU0+Fxx57LKy99toVWRHS0KJ2rUHg8Oyzz8bv99xzz9jiA66XNGEEAUX6nnNNAMNGN59cnPv6gQX/z1JhvJCBmQrn008/jYEDY51S93Lu8R122CFeYwS/WbnGlsSneSPoZtOcWYJKhQyEGhj2tZwDCAr7hayF5rOmc9StW7dQ7ag1pk8sBfRymybRc9VyFI4OOuig+P2dd95Z9MoMAgfOUykqTbhuycto+S3G3ydt+synqUpbixp21nbIt/Uh13bbbRdnMmLsBFO7Hn744RVTqCgGCmKPPPJI7ALCtLgbb7xx7c+4Vnr27Bm3+ueHoCMFFGlLXX8IJNlykdb6668fNtpoo/h3LKArX9OnTw/PPPNMbYsk1ltvvRg4pGszq+OeGmMA0QAyHmrLszJrBA9DCmgpui031CqScVMzXqimO9IhsyddgrxSrQxeDij0ETzwUCzHbkK554pm93ILcMoZBSb6yqfviy21AJTqOkqDqQs9DSUBNsEDLaGFqhR644034rGi1nqDDTZo1u/y2ejK9Mc//jFOh/rSSy81OwipJsxaRfcknse0PuQTbPFMoFWofssQ1wDXWG5QQcsFG+eT88rG71MAJJjgazU/Y9S4jz/+OLaMUSGQbLjhhjFwoMtSJTOAaKQfeSkfoi156FJrR6ZYbgFEmsWqGAsI8VnTg2CNNdYI1bxYHK075dwNgnNFbSAP6Wo9V+WOAIVzREGpVLXhXCdp/YlCTQxBhRDBQyEnFiA/S4OnWTiuJcEOz5fddtstzshEd6Z11103dqVRXTyL6eqFfv36tXpCE1ppaQmt3xpKXkqL0OTJk2MtMtchgQsbv8P5IZighaKcuzWrbXzwwQcxcMhdXZ6WMQIHuilWAwOIesg0eIhmbZAVrRAUpslcyyVz4yFL1yWa7YoRjHF+6B5DoZSCQaXOuNGUFEDRX72cB2ZxrrinqvlclbvUfag1NfTc8xS+eIDSItpc1DCTBi0hhQggqG2mhpB8nTyoUHk6MynxnKBSZIsttmhxOqwbwSJ0FELuu+++cMQRR2Si1bstMfUl1yXPtjQNbjGQf/bq1StuAwcOjK26XMtstPBznth4H92b+vTpE2uazcuqB3kTa57QVen999+Pr5GnbLrppjG4rbYKAAOIejVwaVXSrDVXEjTwQCOjy3cwX7FRCEgDnYsVjPEAp7aSQjQDGbMU9BWiwMeUrRyDLPTVreZzlYUHI8Fomg2ppShsjR07NgYhxx9/fIsKw+RltKhRQ9ya6zp3rQf2p5DXW2p9YAal1rSssk/77LNPuPbaa+O+MviSqV71/3FMGKgOui611SQMnBdaStlYRZxyQQomqAQhgGR76KGHYsBBywQBRVamU1fz80eCfFocaKXC0ksvHSsPCGqz0lul0AwgcpAxUOjN6sWQuvRQU1PqAIhuAxRuKUAUe1/ItNOCUOW0Wnixjy8PV2pYy7nrUn3VeK6ygMCOvK+1tampYE0AwCwkLamdJ4DgGmlNyyUPfPKfNO6mkLX6FCZZLI1CZlMLx+WL1kMKx/fcc08soNBFptL7TucbAFJA51xSw0utfylwnldfffW47bzzzvGaIpCgqxPdR6mRZmOQN4NlUzBR7hOwaMm49mh14r4kPwF5yZZbbhm+9a1vVf05NoD4P/SPzfriZOnBSytEKfvgpXEkqdm52KilJJNPa3ZUehcAHqxkZnTLKMcFDptSbecqK8g3uK5aU+PPOAO2hMWTNt9882bX/PN+aprTgpMtaTng+qJwV4xpnhnwDLqvFCp4Z0rS1Pf+3nvvDT/60Y8y0apYTC+//HJtCytjRcoF3VSYy5+N+yadt7QiOdvjjz8eg0ACCQKKrOXT1Y68kHNK4EBeAu5Huhwyg1pbT3FdrgwgctZ8oFY3yzd6WsiHlhRq7kr1AOLBzz5Q89dW3VTS4nJsWT6H+UizhhS6W0ZbIfPlGqmGc5WVQaqci0K1PlBookaWa5TCFQWo5korGFOx09z9olBHwZM0Ct36SaUIM/SgkLMmcR/vtddecWAmx238+PGxH361onJk3Lhx8fsBAwaUbdcgnrPURLPRgpeCCc4jLcRsfA5alZiO2QqT8kcAyMx3PGdBHrLNNtvE+72cp8ovBQOI/+urz0OnErpUpMHUfKaWDGIsRGGEhze1fm0ZwKSuUgSCFFArtfaO80rNKuc5q4uy0cJXDeeqEHhgpcWIinlNMQVwawppBCBp/nMGE1Iz/+KLL8Y+/QQUzQ10uSYoRBJENCeA4LNQE8y9UYwZ6agVZ6wctcv11x1oLT7n3nvvHcaMGRODMaaGZQGqakQNPhV6jEGg1jcLKD8wIxcb1y1dXwgo6O7GquNPPPFE2GOPPUq9m2oE1xvB3sSJE2t7dNBFkfNZbrNblots9tUpwjSjacXcrONBTeGM6Jn+8W3dkpOmwC1FpM7fTNPZViKOKzVanONymWmrpSr9XGUp/2PyhdZeTwx0JdChwEs+mlYdpzKBAlRr1oTId/0LxnHQhYp8qBj5D/kpAQSojSxG6x9BAwOzwQJzBHbVhsGqTJ2aWmWy2KWYYHzrrbcOhx12WPjud78bX6Ngyrgglec1x0QGKXig6yWTQLBivMFD47J3ZxYYBe1CzjleDqjJSoMi2xLdUiiMtGXXpVz8TT4755TCdiWhEEVhrFKu1Uo+V1lCLX9LugnVr7l79dVXawvWaRwW8+aDVoiW4MHNvuWzeisFbYIH9qVYLclvvvlmDHoJjlrSLStfdF2ieyKtOtRaV1tAy2BkUPtbLjMKtjYopFUOdI1JfepVeuQvBOqjR4+O9xt5x/e+9724yKPT8y5ZVQcQPAwowFBblcW+5I2hxoYuABTm22L12nQjUsCl9aOULTkUOihMpP6LlSANSi/GdJSlVInnqtAIrg4++OC4FTrQoqaePCINbG+p1157rXbhTaa0JHjg4Us3JvIixkPkDq7OF7/LfvFgX1Khk/Rbu4ZFvgvH0R+6mH3ZaXn59re/Hb8nMKP7S7Vg4D35HEEatb+Vgs9C6xzX6l133RUDXZUWXS7/8Ic/xPwrBazHHntsbcWHlqxqA4i0gi9fC71CcjkgKKLmjhrGtjqWZIrlMMgoTRWaT81lFlAgI4Dgc1XaILxKO1eFRgXAHXfcEbdCVgZQIOaebe3UraSTmv1T329aydJU0muuuWarWyHIwxoLnjgmdOvjHilmcE0QxD2YZmIpNgqbaZD2Aw88EI9ppWPwOAEEdt9994p6LhMMH3DAAbWLadISUeyxTWoYedSdd94ZAzkqHRgr+sMf/jCOT6mka64tVG0AkWaBqdTpuMiwKGySWVHALyb+RjkNQqfgwmemZrvYn73YKDhQQKJVp9RrexRDJZ2rLOF4E0CQ/7UmKKV2PI2hYM0H8lUK8WwEEWll1nfeead2kc7m4IFOxURDAWaquEirmxezr3yaupW+0W3VJ5o1ByjcUMhJ3XoqFYXphx9+OAaE6623Xhx4X2moXPvOd74Tr1O6w6XAW213jdHaQKsDg9vJo+hadvTRR8eFTdV8VRlA0G2CBw8Pp0qr0W2oFaKYtbs83CgY8FAtp2OZpnVtixaYYqG5m+CBr5Uw7qGSz1WWEOxzXVHob21Qmrr1sLASD2QK86lFg/yAbk1pTZpUu9xc7COBSW6ASWGAvuTkPa0NgpaEAIkAKLWytBVaO/bbb794XBlUXMkDcClQ08pDRQk1wZXSTbM+Cqq77rpr/J7xLS3p2qfmI/9gnAPjHWjNZGwNa60wRXAlTJ5TlQHE8OHDa2ur0pYGp5Fpn3zyybEmgsIpfWt/8pOfLLE/7JKkBw8XUaUPkuGhyjHlWLa2dpffpyaQgIGbkWP4/vvvxzmTmZ2k3GYqIFOgpof9bKtxIIXE9cl0lHQxKZeWnWLJ+rnKEoI0rivyhtbes2kVXvIYxgU0NCCba5cVfFMhsSWzbrGf5Du53Xhy13oo9jTAqfWBmvG2nhqb6WJ32GGH+D2tEJUYZHPNPPbYY/F7PmtLVx/PCoJQyjk8U1M3GhUHx5j7lxmW3nvvvfis2WWXXcKRRx5Zmy+p5UoeerFEPXM+Jyka5CHHdvHFF8dVOnlQMa0Wr9EfuKXIgKklo9aqUms56rdCEHSl2UPyueGo8U4bQQOFWTYCBbYUjHCuKIiUawGXmm2CHbZSrInREhxbCkcUzmgp49hmcRrDajhXWUMBnICfa6wQ92wqWFMYYvxBmq4193olj2UcBH+X6/qFF14IgwYNatbfIY+h4odgOrVWUXNLy0SxpzMm30uDLAu5cFxzUKimqxgBE+MhDj300Ip6drFoHtcm9z0LslU6zt0+++wTW8+o3GPlcc5pNeTzbd1Nk/sltfLQ+sM6Kz5fKiiAoBDa0FRtm222WRzoklD7c+6554Yf/OAHsRDbkmYnfo+bNs1SVA3SceLhzcM3PXio6a0fKFATRKE1BQo8tHl/WiODBza1i1nJ6NhPuqmlbg7lPoaAh2iabYmCUTWt0py1c5U1udOcFmKmIrpFpi41FKzJT3hgN9SqwWssusZ1TWG8f//+ze6Sx/2QVsumEilNA1xszIJE/titW7ewzjrrhFIg/2Vayeuvvz7OV89aFLT4VAKuybS2Bms+lFM32GIir2Nl6lGjRsWa8QkTJsQxL2o98iIqKp555pn4Pc8SWh1Yl6OSAu9yUPIAgr6lrDbJA2L77bcPI0aMiN2VGpLm6W0qeOBBmbv4Tu5aCET7tEAw4K6apFYIjjGBAbVqKVDgBkuBAseVjffxtRJutrQyN+e+XOcU5xzQKkYXHs4JBbxqeZDWP1ecp3I+V1mUO80peV8h7uu0IjOtC2y0HKXZlxpC4ZsWCvJfxk2kfuD5Ik9KLXN8nrbIw2mpyZ1hqpT5IQEM/bXpN09XJlokdtxxx9pZrrKI48vA6TQ4vdpW3eac0hpHC8Szzz4bg2wqStVyjO2i1SFN2MDx5BiXay+JrCtpVfJ2220XI3AykZEjR8ZInNqphvp5Urt19tlnh+OOO67JNAlAKIClLY2up3adAhq1YVmpQS+U1NpCIYIbi2PBw5BjwYOYhz79Tqn5TX2KKyF4QKqppIDO5y431ORSsKKLB0ED56Mag4d0rgh2y/VclQLXbpoIoSU17sWY5jR3ReY0qJiKGgqEjV27VEj07t27dtXq5p5f9puaRCo+irXWQ0PzxKdpbmkRLzVaephClmPx7rvvhhtvvDHceuutsXtvFhGcERASHDY3oKwUXFfUjINAgvtUzUelwpNPPhnLk2lSFyYgOOSQQwweimipmjKajJibh1qISy+9NE6tlZCJMy80BV1usqa6HzXUAkEQQdM5D9NKH6ClhlGrzZSS1PKUQ3BEhkdQnKYvrZaxDlk8V1nFdUW/eTYK3YWabeSvf/1rrOXjmj3xxBPrdPVp6mHN/jBYlpYKFtaiBr2cUUCn0oX9LKdFzbg/mNHq9ddfrx2PxjOOsRIEaVm4Z6gkvOaaa2KXOmqI22JtjXJFQH7TTTfFQJ9B86xJ4MxA+SOAfuihh+J9AcbMUl4shzWp6qMiiIC50C1NlHPT6vVtGTCV1VVK7euGG25YZ+VNMhr6RlI7Pnbs2CWOXaBvYUOLgXBguTlV3ohnGVTPVzKBQj0MuX7oAsE1Vsq1P/hcXNPUvPGVvuAuXlOe5yrLuM4ITtOYkkIVSHJXZGblVoJeHl6pe1RTeO/6668fK3NIgxr1ch3rQuDARotKqiEuF1SkMQiXgIG+3gR0H3zwQZymku7AvM5xLudAgkCS4IEuWEwBXM24Nw888MA4xoUggmPT3IkGqgUtl7RQp8o3epXQcwU8SykrUoZUFQYQRGc0zRKBgwfTnnvuGQtYtDy0ZsYNAg+j+vJHrVqa3YU+ooWqmeL8U/ihNpYHF90SuJ7a8iHL3yXDI+OjMEVBoJwf8qWSzhXHilqk1rbMNDazGOe/3KfyozX1xz/+cfyeGtt8g8201gNN+YUspNPdjvPCOerbt29tPp3vxBbUkP/973+Px/+VV16J3VjLUQqSqM0s1zVYCNgoMKVAguPJAPMxY8bEtTd4nRmyyi2PoYKQ7mHsFwXlctu/UqD2mC43t912WzyPtL4yLqQakfdTIZEbKKStsSlvCULpBlfsWdlUV0lL1GeccUacXYJuS2R8w4YNizU+hx12WHwosaAMzd0333xz/H8aEE3Bsrn9xMu1pkv/xblmkGDy1FNPxdqEQjVF0rRHBsT6FRR20hgQvhZzbAwFWFrAqA3mM1IgKdX1SMGN8RYUMMq5byi15tzvHLd8ux3mM7NYkmrOubbKtYAI9pmuNLjqqqvyCiD4XNSeU8gv9AM1BfesOs09k1YRT3+H4OK0006LYyNOOeWUxX6f4849TSsEhV5aMcptzA/XHAXcUk7d2tx7hdZaJiEh8GF8CnkNLfZMWUkgQSBUDl0kuS8fffTR2mObFhnU/x/wS3c5Zg+iSw6VG5V8fNLUzPUDhSWNgeN6p4tr2mjFquTjVM5KGkBQkCFY4IIhKODm4aHC9+PGjQsvvvhifB/NsblosirVlHrFRAGIjJ+bodweqm2Bc07GwfnnYUc3HwZGEWQWAmmmLjE8yChY0vSfZp6iFoiWiUJOVUuBnUIV/TP5OxSGS1XjRmY9efLk2ApD9ykKFeXafSpNHcyxq98Fh0J1bqDAeWzJzGIpqCu3VdRbgwCZ4CENSC8k8unUvTQNniYgpuU4BaN0P+R9TIxBft7QdKPk3RTQ2VdqWwkiygmDvLl+qNgq9xaqXATC1MKylgKBHoOUORe03jNNaL9+/eKg3VJe68w2xFhHrhcmTFFd3DPcv5RxWGTuqKOOatM8mgoB/n5uZUuhkFfnBgt8TyVPY3hWEiAQBKdgge/L9ZlVjUoaQNBnszFMWVdG47uLhpuKzIIHKg9nCkLURDB7QDU17VKQZyAmaJanAE/NK12aqO0s9BR/1M6m8TRpalsyTv5uCiYogBFMtOSBS0bMg5IgiLSXNP1wsZFhM2UyQTmFPgIaPtsGG2xQFjWTjRWI6IqTuswQIBBgcs/ktiiw/2lRw3S+8rl30qJklbJ4XWpd4vgUY6ai1PrANZOmayUo5e+le4kCYkKXK1pN6o9b4/yQButIMBiYMQblcg1SoEn5UGtbH7he+ext/dm4B1hTgO5hBEO0SnAfMfCd2m0CDLqftXV+RB5EBSFoMbFXwOK4Vvbff/84HoI8+v7774/jI4pdFqDShVZB7se2nAkqdeWtHyjwWinX6uLZwvXKc7st1pvJKgcFlOghxVgPgga+1o/CeY2MvlpqaMi80nzgPNjS1LuMf6CGkp8dc8wxRas540GaurGwLxTE6D+eFjcjE+HnZCT5PHQp5BI4kBHzkCxlqwOBDJ+FIJVFqAgeQLBE6w77l6bXLDdpqmH2n+9ToMDWnEChMfx+WryOYDHL/WfTWg+c32LMNMc1TTCf2/pABQ+1iKlGkJYt8i7OE/cLlQL33XdfLAA1NhaCljDu8XJZGI1CFPc/x7B+y3dzzwctLFyfhVp7o7m4num+xPmiWxOVBwTMrCNBoEcgQR7bFgU1rhXycfIjgkcHujaOvO073/lOnJmJFmMC92J1paOgTMBMYJe6iHPdFGPyCvLtFCykgIH7rBxbf3kmcOw5FvSIoFcIx6SaKnXzYQDRRngopcFjFORymwgpoPbp0yduqaaIJmf69q277rqh0pFBpjU6WDEytxWKm5hCChkcD8NiIzOjMMnGw47zRmbCRkGJTISNTL7+g5fgg1oj3pumtCxl5sg1xngPCnLUhlI7DVq4CCi41u65555Y41WuQUQan1LshQapbeJ+y+IDguuO4CGNFynGZ0jTtPIgTa2BBBUEAKmrVGp9YPAn9/Fll10Wx69xH9dfYI57h+uQ/JBaTwZBlrogQSG3UAvHEcgROHAPcl5KuXgplQQECwRpqbDIeaO72XPPPRdbKmgFKmbXkDfeeCPmRZx3xjZm8T5rS+RFAwcOjONFGBfIDJKpYq0QqLQkcOdaSAOTuY9TUFnNrUPpWZme8eStVI4Q8NClkXu5XFpMS80Aooh4iFDLRiGYAluasxs86AkYmCWDzCFlqKzCzQVLRk/h7kc/+lGbLZxUCjxcCZaw22671WkupOBIJppW6qTPfluu40EmkcZEcO7IWFIfTjJYalkJJsh4KVzR6sDnYb9LPTCXwIdAlYyPQIaHRep/TpcwHkY8PLhGmbWFGUC4FqsN9x3nkPPKcSrngeVNtTARuBbrwUaAkgrW1ISmvIoaS+6JdE+mAIK+9nRRoSKEbnMs7nT66acvli6VI/ycdMjvSt0KQQUPx5FaR+6R1pwTNo4L+QTz1PMZS31tURgiMKKASGsSwQP5FZNVEMTRMpBbO1yo64lAk2Al9fGv5OdZIXE/UJB9880344B4ygKtfa5wv9KtjdaoNFCZ65LAgSDemSpDfI4zrqt79+61reBpBkUqB7mv+dnKK69c0m5W5cCrpcC48AgYqFmjxiV3HAcZcwoaqMlrrBaGGpq0ABQZB9Palrp2rliY85rCNwXahqat23TTTeM85zyEqY0p1dgQHqSpNpxzSkZMzTUFDjIRCgy8Xg61ExRWCB7YN64zjh+BAoFOOsZkftQS8yDhfQzY4/88SKqtdjD1U+fhkG83tXLA9cY+82ArZmsXeVlqaSCITwi60gOUoPqtt96qDSA4niwyx4xM3ON77733YgEqNd4EtHR74jrkXi9lN7I0dSsFqdbUwFIwS5UIXEvUJtMKSE1vOSxuxT4RRBAkMQ6FQII8IHVRS7ie6g9gTf3Tm3OtEaBwTPjdLMxqVS7Ih7lvKNByr1GhyKQzLXm+cPypBKC1n8ol8KziXuWZUKnli+biOcmMoOSnuc9B8gO6MlGZwvOV+6Zz584xkOC+yHL319bIxpOyzFGLk4KG1E0kocmLByeBAxlocxeW4WKm9ob1MCoNrTNsZIgMnG6o4Mpr/OyPf/xjLGhwnEtdU84+kWGwUYijdoLXyqHZl4IcwQMPCTI3glCCL9BNIbdwzP5TI0jrBAUcHvQUSHloVVvNCoU9xqykoKtcENBwTtL3uShUULigUFqs88X1nQZP514/FEjSNLigBhsbb7xxbT7HfUpLBAHEyJEjw+9+97vFCj/UenO9cuwJdEu1LgTHkfuE+7i1LSFULhA0pGNFQYMF3rjHUnBRDig0EkQwM1NqrcydISfNCpiuv4RzSAVECigoWPE9W/3rkOdhGpTOmg8WVJuHZ8pBBx0UW/G4PsePH1+nm++SELSmGbnSWEsCQLoDE7CXurKr3HAPEEQ0tugw1y/XfloQdvLkyTEPpJzHvVDqngdtzQCihXjg0bTIBUQXglw8PNKYhpZ2uaF2gG4lt99+e2xyZGEZbvhKQWaW5gOn0MBDqDE8mKgZp4sEv0N//XKZyo0CRznsS+5gaTI5jicFmdR1iQGhDQWwvJcCExkfATA1KxQevvvd75a8y0UpWpiozU8D5svl+mro3iD/4Xxz7RXz+qM7JZUY9Vdk5uFJkJq6o6TuS/XHKR155JFxQggqCggk6leEcMzptknhiGuVoKMUXVxSkNTav0++RuBQfxAqzwHGQ6TVrcuhsqH+CuG5g8bTLHINzdHPZ+QrG+e1/nMrt7UiterkTo5RLBTq0pZahFN3svSZ0uv135P7uxSwy+n8cByp1Ln77rtjoE75YkmD0OkJkRYXpIUf5CNpcUEDh8VRIUKems94JfLlzp07x/ucgIPnLvkk5yqtsVQNx9gAogWoraFgnzImLiYyxxQ0FKrgRYZOEyNNzA8++GC8MJsqaGcJhQpuWB7W1IIvCceBgI1uQ08//XSs2dTig6XTAHAehNT8EUSQyeV2PamP65eHCg9NjjG1MLR+UfNV7Id+OaEwy/VFjSuF2nJ9AFA44GGVgp5iSgVAaqlzu9+kdU24dihopu4v9QMICmOHH354bEG84YYb4s/r19JRGCKAIE0G27IgWlsee44ngTNa28UmzYLV0HmhcMG9msYllXNXuTS9JhutREmqea2/QnBa/ItrgS2tF4L6k2O0FgViCnqcN1pJ2BoLBuoHC7kbuH5zuxnzPlpuefaWUxBB/k1rDi0JzGzGeIiGKid5phJkkPdzXMDn4RnLeay27qn54hrgmuL+bE6eutT/rbfDlmZv5P7mvknjJFKrW24wWynKNwcrU1wc9BfnQqAmgCbgQq6WXN9OO+0UCwtTp06Nf5cavXKo8W4NCmhpkUBqJPPpfsF7eC9rh5CJ0m+TG7TakWlR+0HGRaaVrg0eNlw3ZHD5rvZLyw4FBwJkuuXdcsst8ZjTX7paEGxRACKwbcsB+40hAEwDkC+99NI6Cz0Vu6Y+dc3Mnbo17RPHKOV51HSyX8yq1NA9SUsqU4cS4N56663huOOOq/NzAgryUj4XAQSFt7ZcwI0pTilssQ9sLZU7Dqoh3It8rjTHPOcva116Us0rW+4MgXxugqfcgIKvFGgJHgrVokfwwrOQlkK6YLI/aYrntH9peuf6r/N9er2xgjTXAc94lFsQwSQj5PPcJ5QFjjjiiNpnJxUfBA5MQ5wKqfRaIGDnPBk4NC2t2dSa2dI6/V+3ZvJHrn3OFXlkmpCAZzOVBlkvv+UygGjmA/W2226LTbgM/jv00EOL/gDIXViGTJmWiAMOOCCzGUKaD5yvtNY0Z651MkL6WDNYkzTIQMu1lrgt8DBlXAgPj9zVy6kJpD85aFnIN1PkmuKhw0Mp9Ql/6KGH4gOVgf1ZK+y0BBk8nz+tDVHqAgSFzd///vfx+3POOae2prctpgUlUOc+Ja/LHReSui+lltbGui8lHM8f//jH4X/+53/ijGoEpfUXhqQShoIRn4+udOmB2xbHlwCifpDUEhSgKSg3VZlEfkX/agqq3LelXCOmkHJrYgu96CcoFBM0EDxw7eXmd4VEmqRdjkEE+8b6ENddd13Mn+nOS9deeigQeKeWFI4/9yJfK+HaKrZUKYPmnOuF/9fylVrB0vHnHif/SpOt8CxJZUbGQpVySudCq97SVzPx0Kb2m0FJdCNikHNbFajIlMk4uDApPKcpFbOIgi2149yoLemGxLSuFCyoXU+D86pRmvWGGj5qNdO1SKZFgYhmfgonzV2wKS32Qxee1J2DfrTUHKf5wisd9xuflWNcTqjRovDeFguT8eBrbEVmuhql2ly6kaT3NdUVkXE2dE3iQXv11VfX6TYCPlNqdWBq1/RALzbuFQr+BEOtnZyBQkI+MxRxj1GQSK1d9Y+FGl94FcUKHhoKIhpa6LWUuE6pQEzPUlZ7p/sg1xAVbMzYSJdBCqsGD/lJ43kaanHmuJJncQ0QuPJcIM9j+/rrr2MAkcY80UWRPIxWWCoJqIwjAKWilG5RjBeiS2hu976sM4DIs5bqjjvuiBcZFwotD209bRcX46677hq/Z2GZ+rM9ZQE3HzP9gFW2WzJWhONPty6QFjdyNdaW8DDluiSYzX1Q0J2JGg8KeBTaWtJCQ2bHQzQN5CfYo/sJfdhTzVwl43jSrYb7vZyuLwqbbbWqMV0hCCIoENM1KeGhyX6kLik8ELkOGSuzpPEyxx57bGyNIOCg1rS+FOymmmZafIuZFzEoNa1PQDe/1rRmUrjgPsl3BV/eS3cp7rW0ArAan6yE/Idrn2cGhToq9DiHhd643zmXXAsEEQTt5RZE0NV05513rnPfHHXUUeF73/teVY1ZK4Q0sQFBQO6YJF7nWuCaSOeevIvrr36g0KNHj9hNKS0wSwVn6kaX2yJBi1Dqvlgp7MK0BGRWDFoiA+PCIHgo1ew0NLFzsVPznBaWKYd5xZs7HzgZc2u6C1AwptaFwizBFF28qnWwdC4yPJqy06DXhgozFNzomsQA6aaaa8nwaCYnQ6SrGH1uqXn+05/+FPbZZ5+KmhGsIdzraRXyFFCVQhoICc5nW3TZI0htbEVmrjHu4TSZA5MhIJ+JEHjQMrvXn//853DttdfGQntuN6U0ew+BG9c5+UShPzP5OQVSun/wOfhstLC0dvB0Wucg9/MQCLH/jVU2cV0RRPBZOa7VNgVkPrPKkVdxD6RFvcB9mabTLHQwzd9NwQR/g3OaZlmkNrlcprdmUhHuD8bRlNO001lDYZ7nWu6YK6631EWT5x/XAcFFIfKh9mU8cUJL2AKxBE8++WQssHPxUOgq5c2aFpbhIUtXBhaWycqofh6S1Gqm+cBbczPyu6QBZk+h1r3SkaHRtYOaWR4a9YMHCkZM90vmx0Mvd4AjeJ2+s2effXYMAm688ca8pg8lSKNwNHjw4FgTTRDDdcd9kZVrr6VSFxP6qpcCx5quem398KGJnc9Mwbf+4o4cj3R9cE1yzTU1/qE+FoLk+iQ4pVW3sVYIfk7BjUJ4oVDTz6rrXL8pCGJSCgantiY/4t7ieOT2bSYIonsU08PWX0ehoQHk3Et0pdL/D8bI6+jyQYGd6yUFCnTNJK8jeOD+5PgVcqPQSGGSa4O/nWax4z7kvkhTopYax4NZlQweWo6WBSpkCRLS/c99SD5x5ZVXhksuuSS2glLRVs1jLZviUWkCmX+aLejb3/527FdYatRwMf6CzI3C5IQJE0K54wHLoGcwo08+M52k1TKbqs1MCz4xwwuFrUpFsEiXJQrzPDAaGlzKAzdNrclxya2Zo2BC4JBbYKNFIRX+GpO6MVELSI3cwQcfHPuxp5l3mMp4SeepUtaGaOvPSUGFboqc07aWpm7lXs1tpUrN72maQ/JHHsLUDtcPWBtDUHLMMcfE77l+CBRyUXgjQCbP4LhT8UAhrjXSuKA//OEPsRDIdU03SFpwG1swqjnSKu+pWxf7zt9hvymMcJyYzaqxwieflzERHMvWftasI/CihYgCOxVlua0yFO44PhyvYq7Twn3P3+VaJL/leuf88rwlqCmXIEKtQ2BPgJB6lKSZxChTMVU8rZT0OKG3h+OUGmYA0QgyfBY+woABA2KXkHJB7QgtEWkGlHIflEMQRsGDTJ9j2RQeEhScaK2gq05Ttdz0AyVjp5CVVsKtxAdqQ4Olc5EJ8tAF0wrnPlwpoP30pz+N54Cg82c/+1nYd99948+oYUk1yo3h4cnvpdWtmZKRLmMEKrzGCqmV1KezPo4ln5vCbFs9RCigUDNGK0Bbd5ckSKXQnsbQ1A9kqR1OrV+5sy/lBqwUoHlvYyi807JBgZlWsVykk1ohOAZcn60ZUE3ewHTEVGDw96i8IHCgy1UhuqWllegZK5JqKdlfWk9SP2kKo7SU0i2ssdYsfp/3E6hXYwGV4JSKCvIxggSORW53oVS4S60EbYHzybVOEJH6urOPdBOt5IqTakA+xn3K9ZTyrtSlkVZKcN65H88999wwZMiQOq3B+v8MIBpAAZZm7lQLl2pdywl90NMDnqkRl1QQLBX2K/WTZgalphZpSbNtUJvOA4XvCY4aG8BGbWaayYm+/aWorS0mCiEEDw0Nlk4IsGhJ4AFLYYXZkxIKLaecckqsOaPJ/8ILL4wBwNFHHx0HdFGYYW2BJRWMqfEjcyVgYF+49hgXwYOcY04QwTmrVHRh4HO2xWDXFDzw91JXNWrE2Npi4obcFZnrF9TSoGYKVtyTqaWifvcl7nmuF7aGcB2fcMIJMR0+V/3Z1Cjk87k5Fml12OYOqOa+oJWMBewIiCiMklcwS00hF+OkIEmelmrKKXBwL7D/qctZ6qZEEMox4z7KHduSjklaKJTgq/7PKxnHjBZW8nuOW0NjG7iWuP75WVt3J0mBBK1EzKiTWkmoOKnklu9KRp7CdZfuW4JT7tfx48fH88qzlFb6U089Nbb4c98ySJ3gotK77jaHAUQ9ZA5cJGQMDJpizvKGCm6pRoTMnoccDzgKZDz4SYOHBU1k1OhxsRK9EpjwMKPPPpklzaFknBT0GBTMg5Smdl7PpymbvrtkajzEuNjLLTPjGKXuRRRYmxp4mx4itDpQG8eDgq8cM15vbDYc1oVgVgoeuPytSmlq5NpKBZ+mFjQjwEj9NAl207VK69nPf/7z+DO6l1x++eW101SSIZ511lkxbQqMBKBNIU26E3A9c35SsMLMH8z6QWGSe4Ya6Uo5/rk4ThQi+PzFrB3mOHJ8yUPoOkYNOX83zXBU7IJTUysyc3+Rr6UKAKb2pVDHdUGhqv7noCDc1BSl3LMMxgfTuuYWmHNbIajxTd258n1w0+pGUMs4HfIeup4yAxQDwgt9DMl7CfS4//isBAc8D+rfsxROCCK4lph+k7y+fitNWiOC3+XYVXpBhePFPcU1x7WVugvVx/WUxpiUchAq54dzzarQqVWS80QeW27PXjWdz1EuSzPapVm3CFBprQTdLPn/D37wgziF+ZZbbhmfyRdccEGs/MjiLJjFYABRrxDLQnE8GMnImW+5oQdOGuTFQ5QHQdrodsNGMECmSOGOwi/doQgKCBoIHigkEFCQeZJxkgGl6ePIiLg4U8GwKWSmrA9BpssNkbpclQs+N5+ZY9hYIAaOAceLAIym69Tvmoct/+f1VONTH2mSNoUtji3HrRIerFwDXGdNNddz3LiuQAZHhpcGS9OywLVE7TBdlerXulKAS33RqaVd0kD0NOsJ124a2Eqt3Pe///2w9dZbx/9Te0N/0XKa8rCQrRAU+DjmxcAx45xzz3OcSzHrEy1ZFFqZMpqKiVxpSsPUPS63+1JuHkkexnVI/skxa6rVhtYArm+ChPvvv7/Oz2hJIx3S429zzS1pQDXXO9dgmm6Y3ydIOeyww4qyeBOBDecprQjO/vFZGmstBO/l2HAf0a2wfjdN0iPQ4H2VvEYE1zvBFvk1n7+xtR3SHPycv6Zar9sSzyeCUu4HKvq4J7hGOV/V2P0sS7ifKHtxTXE9pbUcqKxktk0qb8j/GPOaUPnJ+Kkzzjgj5inkk7RGjB49uuKD/CUxgPg/XEgM6ktzrTNbSP1pLrlYKPQTIPCwT82t1MLx0CATpMCbtob+n5qp05SFqbadv8lDg4cutbs8eCk003rR1EXK76RpTAlo2LdyQMaaAhq6gPF5GxvvkNtNp37Alubj5kGSWijqHw+OIdPagb+Z9f6pBEwUgJpqeeB4pUHQ1E5T6KCGhNWK02BpMrlf/OIXjXZ9YSwENc2kdf755y/xuJFOGryfWoR46O+11161M2txjpjlqVy71LV2pV2C2ELPlsO9wnVN8EA+kHsPkC+dd955cStmYEbBp6kVmdk37jvON9dLGnNUv/sSx4Y8ic/Bdck11Vh3HPI6ZvfCzTffXOea4RgwywyohOC64xg11jJLPkLgTGDDftIqctxxx4W+ffsWbd0MAny6QFCA5PjR3ZK/taSCLp+FY5MGd1PplHtN8fPUjasS14jgM5HnE2yl515D0noPBJn5rq/RVigbEGSTT1OxQMBLfs3+ch1XYiVKJSAfowzHuSIfS8Ep1xrPLZBv1G/pIj9KQQPTT5OvXXzxxbFlk+u4WhlA/F9BlkWFKKyT+TPyvv40mWTwPCDI+NK81GnBkLQqa6GkKTRJmxpmamqaypDoosLCbHjooYeanDawrdC3Oa2amwr3jY134JgvaU7vVAPV2LgIghQCCWqFqIXMKjI1CkpcU02t00CLDZ+VQj0Dp9Ngafp9p8HSFM6a6rLB8T7ttNPisae7FC0RS8J54CFJi0VubRvdp1gBlcIU1x+1wAQalYRjzfnh8xWq5okHEec73Sv1zxd/j9ovtmJ2k+B64rxSmKvfJYnPSuCUAlEKvASQvLd+t0TuSypGUh7G902NTaL1kOmBSa/+1MLU8nIPpHn5KXgyPiS3Vp6/R6UBD39ah8i3maWOKbeLua4C+8D5SN0gOIcUJpszvoL8iooV7iW6EvL76bNxrFOXp6YGpGcJ1xG1v1xrFORyW5sbwvVIns91Vo6rKrPvtCZx/ihEUiagZZfzyn1NRZCBRPldf6kihHOUFiekmxL5C+ePPKkxtE78/ve/j92Dl1tuudgdkVZ4KkCqadxSUvUBROqnT6GUqJOpKnno1W91YOYFHl6ptaAtMjRqXfhbFO6o2W3qQcKsIgQSPNQYD1HKWngKs2kwJjdj/cV3csc7cKzznZKP9zU2LoJzl258aubT4j9Zw7GjINRU6wPXI0ElGEjPtctgr/qDpfPB9UXTLB544IG8ZrPinNFdI42HSKhVZYYbHqQ8/FkwjOugkrph8LBJ/Z5bi3uUa7mx4KGtcH7SgOiGVmRurPsSQXtutxNaB6hU4RilhzQPXPLKxloOeA99ikE+nDsYn3s6rYJNRUrqQpcqSCi4sSBdymsIpKk9TGN9iikVblM3Le5BCrrN7XpGoMB9QwUVn4MKqnSsCIYIIjg/HP8s41rnGHEeOUYNtTbn4hjwc855OS++lYII8mN6DHD9c83zLCY45HMTQFf79LzlgICO5xb5U2rZ4p7l/k1jH3784x8v8R7mumRBzNtuuy1st9128dxedtllsUtwNaxJlavqAwgKTHT9AV2BuPkTMnUeaKmfZv2p5doqg8odB8DDs6ECGQ/p/fbbr3ZmHAqDpSi48TdpBeErD/JUAGhsvENzj2dT4yKoPUg1ouxD1voncr1RoKTmtLGHKzVaqasJn5faYAZEU6itP1g6X4xhoMYWv/vd75Y4LSsZLIFc7niIhOuPvu2cB64BaocffPDBihlkyGfnGuQ+bE3tIg8wjh+F82KsqNscBJ6cc/IauvzUxz5y/vjc1LKlILP+6tMUcjn/acA1XwmMKGA1tRgf1woBL9fLyJEj69y3XNMUIHnIc41TaGdsFWNtCFAJ5CgE0L2Afstt1U+egmEaq0LhkXu3peMs0gxM/D4VI0z3mu5BjidBBK19We2ayfOIvJoKOPKNJXVH4lpj4/g2tOYNkz4QKP7kJz8J//M//xMrTK655pp4PTCWhtZvaoa5rvnbxc57coMInm38PYI/yhI8/wiWmpqVTMVHXsT1x3OVe4nzkyptaD0g76LL5K677pp3mj169Aj/+7//G69B0qP7OK3wTOBQKc+7JSnf0L4N0Kowbty4+D1T/KWmex5gaUAcDwYyvVIuYZ/GAfCwTDXv9LmsXzNDDSHN9zTn85ClVpEIuS0RjNFMSKaapljNbT4kU0+fp6XS71OgILijqwMPWV5nZipquugOQEGbGtUsDZzmeqMGvzEEDGkufj5fmrOabmJnnnlmi6f6pLsTD12OHX076XPfVA0hD3b+FjUuqSY24V4hmCXQe+qpp2K6FIiK3a2krXDsKRDzmeoPNm5O8JAKnaXunpFaH6jBr3/9pLwwvc79xmfnPPL+XNTEkVemfsWpmxPHiICClpbGCo+0XBGYkD7XDPdx7oBVrkvyNGbGI49J3ee4v1lbpqmuMIXG5yPvpXCf1s0oxIrA5N8UOglOOScUaPjsqb82+eeSujaWgzR2IQ0sTi1G5AdLuta53vhdrp/63Yg57hdddFEMHltybDlfqdaZ65Cv9V+jwN+SBWM5J+TbqWWYdaO4Rvi7bOSX5O/kjeXcolKpyKvJgzgXPK/Ipwj+CTAZ14Djjz++2a3ASy21VJxsh9ZY1otgOnmCCmaA+/Wvfx3zq0rWoiuZRXl4gKQaqKuuuio2JTO9Gd831f2iXFCQTTN/UMhOAwd5qKf+rDw0eTCU+gGfkMlRC8W+s5/UztXv/sPDmoI73QG4iImSc9cGKCYeGCkgY5G3VFgg42efqQEgsy7UKqKpPz7jIvhKxs91SYGCz8++EBSW2wC8pgZOk7E1huPHtZkCiSeeeCJ+T+0rtf6t6QLDg42WjJNOOikW+O+8887Yna8pnEsKBwQRtHrkFmy4Z771rW/F+4fxRez79ddfH5t+W1LoLid8Nq4zHkgcg+YERSl/Sf1vS5238GDl/mls8HSaqjrdQ6n7EnlmbqUKwUMaZE/Bj+4bFKy591PBmACAnzV0nfJ+Zkti7AyDoXkgp3yChzAFMx72Kdjhb3F9sbV1168U+PF36ZLDZ26oprwlKNSQZ3PMqdHkM5OHcXwIIsgjeA6UWyGU80z+z8Y+c4y4Jvg83B/5tAylqdFT7XDuvUEQy7gujgmvE3ByTVGpRusUxyt9n6ZV5zW2lC4bx68ppE2XTsZBNhfXQAoiSIeWtXSe6PaZpn4ljy/1fV9NuDbTYpQpeEjnhXFXlB0ou7LAZUutvvrqsfWfnh/MekiLG1PA0q3pyCOPLLv7tVBa9Kmo6WQ+XHBDM3jz9NNPjzVHfOUhUM4o9FBAoraDdQRotkpjHXjo0ZzFDV/KVofGpKCGwksKIurPcESXFGo7aE6l8EZm2xY1vwQsZJJkommRO44lBRQKKuxnoY8pGQI3J5+Xv83xYEAv1yU1do8//nic6racpal7m6pd5LOlBbcosBM8cCwZ+9CcZtem8ECmPzr9OclY6c6S5uNvDOeUcRvcN9Te1X8wcj7IQGkp4Zq96aab4oxN9Wuvs4bzxIOHz841mE/fd+6FdJ2Wy8DQNH6A89xQxQ8FMGr70zoH1LA1NPsSn40gg2uYvJPPx4M6dY3iAZvmzW8sSKYmj8Cf+5buKCx4CI4vlSBUQqQ1Iriu0irVjCFoKzwnOA4UcNkfruli/H2OZZqem8IwQQSBBXkFx7TUQQTHIQ1up/KDQjvXNceGgnSaobA5+H2ulfqLxVGhQfDAsea4UNPb0MQcjXVdIahJgUUKLnL/n17j+qSFn1YO/hZ5YXPv0RRE8MzjdymYcp74PLxOUMXfa2zmqUpFWYXzQPmlrVYST9KaXJSbyHvSM5bX04yFLTnX9fH7dKOkcmXEiBHh6aefjmvcUC4aNmzYYpNTVIIW5UAUYLgxQEGcg0aXB7pU7L333qGccfMy+IUbmYyfqSzTol2pMNBUF5JykAahpS48zFNMF55UiOFCppDG5+FhQxDBTAHFrKnjYUqXMDCtJ3+LTDi1DlCAKNbfT+Mi+KxE/hQu2AcCWY4PBWFeK1fpPPEZGsJDmeCBmhTOOcEDD9lf/epXMQAupD322CMOQqcfMZUEV155ZZMtRqnASEGOILWhe4dMmyCCvsuMKaLlj89MN5VSDRwuBAoznA9qXJc0+04KHsh3yiV4IN9L0z431PrAdcd1mWrXqW3nQUwhIK39kfC5aFnKnTWH64KCWVobgvyWSg0CkoYqEniwM4iRhy15FpMipDFpdAnh+qIQkApfaQ0Jrs/ciS+KfczStK08B7m2i3UNU/Dk83ON8WylhZVxTxxb8tbU2tNW11JakyONR+FYpHPJMeF+aOm+pC5p5GupgMf1x4QgFOgJnKigoHtlcwK2tE5HPgV2/h6tXxT6aC3lGA8dOrTZgVoKIuh2hxREcJwIAnlWkh/U76JVabheuFbIQ7heUj5AZQDHoS3WuuFvcp9yfVLZldtFk3NMvkX5gJbMQunWrVtshaAyhGuXfPOII46IC6+mKfcrRYtyPm7wNG81NbwUOkBmWs7zVnMxETxQq8YDh/ECRKEUfCnQsP9tHR23FBk1mS2ZUFrVOneQFueIPud8JTgq5tSmZO50awMtD2Seues78NAvdkExd70I/i4PpNQKwo1crgv85DNwmvPHrFJ8Nu43ChK0EhQ6eEjX1cknnxwzQWqCeZguCdcYBcc0ywr3VP0BxjxU6b6Uuj1S803f00KvqdCW0uqlfN6mBrhS6OIc8h7yl+YUskj/0UcfjVtLx7c0hqCU+5PAtaFujuQn5JX1Z19i7ZDcLjuca/5PASm35ZZrgv9zjimckb+mCRAaQ9oEM+wXA2PTRBCkyZiA3IIg+8U5SIOY2wKflX2gUELhoy26R9LaQZ5KsJTWfuE19oUWCj57MSaM4BwQAJIPEGimdYbogsfPuJbZL84x57qlwQP5Gscyt3srn42WBmpy+VsDBw6MFULFbG1i/+lywqBYrqt77rkntny0ZPB6bhBBpVYaVMvzmsIzz6NKnOKVz0R+SHdFrhfKVlSwcH3wuXlWUInEz9tiZrE0yx2BeG5FGM/TNJamEK0P9ZEelZisLUYPAa5xpknn2VoJi90mS9W0YKoeBkhyodCMffbZZ8fMlBpwHnL0oU6r45aD1FxIgYUZYYj+uYlZKI6omAyY/2ehn3xjcpu1KVzmdhHgYk03Su4Cdnxly+0P2FLPPPNMbK7jOBJlc0wLPd6hOSj48OAjoKC2ngIc1yrjMsoJtx6ZKceqsVYv9p37igyJlWs5nnQhLPZsM2T8jImgYMJXxpUsSRo4ye+kKXfTrCu5Nc50E2DVTx6iFIQILAoxCLVUKBBzT6UpS3NxPChw8VnLqdsCBTYK6OwfrbCbb775Yu+hUoXCD9cm1yqFKwqTzIGeey/x+Skw0URPIT+3G15acZgHKEEyf49CKO9pLG/gfmBAI/karRFN1Q6yX7SKkJcxDqeY3Xo4ZpxH7j3GIHFcGuuSSSsbn5OaR56NhcBnTV1X+ZzcZxRuue/SgF2OK1uq8eYrNb1pvaLUnSa9lruOUf3Bz6nWmHPH+eVz87WQha00RS3XBvcQ+8L5pOBOHsTfGjJkSJzkoS1b7Rg/98tf/jKec7pbMjtdS+5fjh/3EeN40ursHEMKsGmx0Cy3woJ7gnIWgQIb1xCfiXNKpUf985ZmaeNn9J4oVgUjZQACbq4rWkdz94MFV2nlpMKCdR2K7fHHH48t+uSVnHPyuEI+w1M5l8/clpXgLQogqE078cQT44ORqdRSX1UWpeLiuOKKK0K5SAeWlXZ5kJG50jSelqEvRAG6HHAauXm5SbgpuWHSTUlmmPouN9aSkQKKFFzwNZ/ZPvibDKDnvKc1H1o73iGtd9GaoI5Mjf1I057yoKQA1FZdHfLBseMhyfXZ0LGmoEAXQTJiHjZkOBRIWpPZclzIvPmbS8rAmM2LvugEhkyO0FgXq/pSQYR7jO/5O1wPXGdkbpwLCgn0P6WQwnVCIbYt5u8vBo4pn5XgPbeQwXVMHsm9UU4tm6lrCLWA7C/dhhrKAwkeuEa5Z6gkIs/nXNFylFv459qkcERXgIYCYdJIqw5z7fL8oGaW9zZWKKR7AeNmeA+BTlN5EceX6ym3i08xcK1yL3BOyVfqjz1LqBRgOkcK+BQWmXKU/xfyOcNnZiPI4tpLhX3OD5+fn3Ge6z/e+VkKGtKWpibmd7hv0+Bn7tt8x/e0FHkc55bKLY4PrWJUWKTxDnSNZkB9KbAvlGm4j+kCS7mmJd2b0+DptEo5eQF5YZoeuS1a6AuN/U5d2XjOct3w+bg/8m2N4rjye+QdtCwVskDNtczYGf4GXchy94f7l0or3kM+09B4vBT4cV0WqhL0iy++iIELlS+/+c1vQiFlKoDIknRg6YNNZp5qs7Le6tAYHiZkTAQQBBKpq0EaJMbNnqY042tTC9xw3HJbK1JgkW50Lh26hBGYUctGAZAbj/e1NEOk7z21PaAWqjV9E9MUlBSU+LwcD8aClEP/czJgCmhcnw0FNew3/XGp1aWAygMnd1rcluDckOGTKZJ+Wu28MWSwtHbQikUmzHzrzS1MpMGWqXsdwRDXB4VJCgzUAlG4BK1EzIRRDuenuXhQca9RiKUwxnml+by1wQMFVYI3UBNbiCk8acmiZY57lIC0oVmxOF8UoFLNM3Ols9gS9yOtArn7xzVFdzpaMRrqZsUxIABJizfxOwTO5D2NrZ1AwfLYY4+NwQd595JmxSEt8jjyoHwD3ebgM3CO2XcKIHT5aug6JU9kvzl2PGNSNw1aZn7xi1802NJTyAJdqnxprBDH/vFZuC9TkJH+n36vraaJ5ZzxdylAc51RWcIYhzTegX7kuesylQKBLpWkBKhcV4wJa+l4Oj4r1zX3AXlxWtuDe4bAhOuFwmpDtfblgP3PHXCerm32uaVjcVKFFvkCz+e0in1r95N7lI3rp/4EMkyvytpEPG+YOakh5N3pOcnvt3SNl/ooc/FZCx0Ul30A0ZyxDeVU25YbQBBpcoFWSqvDkmrf+ZzUyDXW9MqpJ9hIQUVuYNFUn+I0TSMZB4VLCiKMN2jJzBu5+0yBmX6nSZquj7EcrclUaC5m+kcyln322afBxbLaGk2YBDYNDS7nvAwfPrx2LnHek++sI41JM6ak1im6GXKul9R1iNplap556DEtHTWpLUVBJU2nmJq4uR8pTFJblApadJEs1LSYbd0CmAYS8wDitdZWUnCs0oQVBJytrQ2j9p9AgH2jxTCNE6qPAhMDntPc/fQTpvsnM+7RHz23Vo1zydiWprrq8GDj9znnXNOkT97RVF7M7CUMQuRaoJVzSQPVKTxzjTF9ZqGfQaRNYY/7gbQbGwDLNI4EWBQCaWEj36GQwufnOFLzSSBYjFnxUstfGriexqWUI84T+8j9z35SOUFlAri+KOSVovtrQzjn9F0nCObcU8FViGcIzyPyDJ5PaeX21LUvjW9MAUWpWijYL8oIKWjI7aLKVojWKa5bKiEIHCnws7U0iE35MOeM64vnXS7OId3XeR8zAjY0jjBVtDGbEs9M8l2Q/7Q2uPm0WgOI1E8y38yhXKQDS79dZg6pxFaHhqQZVHiAUCua7yxI/B4ZBA9MMgwKmWmjsNDQwCeaHynktDTDpzBBUzUFarD+AH+HWgJQ887YmtbUjFFIpWtBWnyKlW9L9XBNs99wP9W/HtPqzRxrPi+ZAYOwWpNxkRlyTxJMpr6gnF+OCQ+AJd0TTM/MA57rh69pte/WSF0vKPBwHthH9odrj+CUglZTa2KUo1SrmLtWRGsVMoDg4U+TPV85hwRqjV1X3ItpbAHBELXqXCt0acu9XvgZNbI8EJvqgsB5JXjhAUdtHv9nLAx5VGOBAfcCc/LzuRmDQ9eWJSE99o+CQaGC0JSXpm5CdLloCMeVyg7ySoIExoOBe5lJDwguwDHlczELWTFqmrnXU2tE6kJYTjXaadwDeRv5AOeVe5/8heNGq1g57S8493RnIt/mumJwd2vWDaifNtcI54njwTVG6wzHiWcAAQT3DNd1WgitGAFF6vKWAlGuIfKAFJjzdwlqitWljc9M4Z98n4J/SyojyV/Yd8ZqUeapnwcwqxbPV57/VE40hDyNv0+QyHVIVyauT+7v1s4e9Wm1BhC5s/hQk0SBnFr9dCBYRZS547mxGPBULtKBZQaHQk3PysOPz8vFUGjUxtFNoFB99VM/Q2oHeXCx72RSqQk7zYBBwYfX+ZqatNOWmrpza5FJk42bicJIS2eImThxYiyUsp8UuKjh5PPz95j28w9/+EPcB/4Gs2O0tCmRNBhQReYArglaI1qy6mixBk5zDNjHNEsNx5opklt6bFNtDNcUXQLqF9TIZGmJ4FpbUoscXQvo9kKLBV1qClmDmsYQ8LDi2NBNhAcnU0KnwnNWcA55uBdqisZCBRBc/7feemssxJMPkHc3FpCTHzCDSppdi5lEyD+pgGFmnITzxDmj9SGf8SucY7o78lBnI2+mQJb62jfVhYRrmQc+rXJN4X3UPpLf0ZpViIIW+Ry1xGnNh8buFbrcEGDRvYlxIvWPLxN58HzkHIDjRjfNYi2smFojuIbSIn/lgOuA/SEPpFtX6sJCJVIhp9MsNAr2lHuYNITnHvteiGk5uTc5BhRQc7sCcS2nbk5svC/dk2nlbO6j3IJ/embn/j/39fTMT9+n13n2576fe5u/zXlin9rq2knPLHCvcR/n21uEvJdjR7mMY1n/+cqzLnVh5j5taJXodM9Qrs2twOI1WmTJW7hfW3o8Pq3WACIXNScMSGXl0Fw8oCjwpdWIy0E6sAwIXVITeD7I9KhNSmseFAOFM2pi8pn5Jh9kBtyUPEzzHVSX+3r6fyGRedGVggct+5T6CNe/6SlQ89DloUONAl17WlPop9BM4ShNobflllvGGv5CT5HZnIHTZNoUnKmR5Xv2jcIiD6uWDizjmKb+mwQPDQVe/C1qmqlhWVK/cQohXJNkoNS8sW/FqCXkfqWglbpMEjiS2Rai+TiLChVA0IpEpQfXHDXjTVVQ8JDjGiVY5JhTgOf6pBtH7jo/aZE4Xss3oOT+S1Nmg4CCMTCpq1RD6HdOa2QayLqkGsDUr5oCQiGm/WSfCSDS4NfGAh2695Gvsb+NFRAIzkaNGhUDMgpt5DsMYudZWoxutWnsBvcTeUIpu8MgTYnKlMB0BWL/OE9UUJR6vEM+OGcE0cwiB7r20c22tXkT6abpr5u6x3MDCo5dOpfpuZ5m02oIP2NLv5N6ldTf0mxdbTUWpiEU5NN4PVoDllQopnzA84yCPV0jaSn4f+2dB7RdRfm354ZAAgkhtBBROkoPBAREAWkKBAOKFA1NQAVBJTQRG4IlSJciTV0iRZRi6EJoUUGQGqQ3aQIGRAgpECD7W8/8fe+37+GUvffZc86ee3/PWodcbnnPnNlT3jpTO59wTuII59oBjNUs0YfaNrFHkwZVtLj6VRkQ/1c0Q84ySl+thYdCVqWz3csyIJiseMSJsrAJsBCTClP2YkzhDwMUqNZHaSsr7YpHXQUljIWBI83sZmUiAZxU0mjBok/IK2YTR6FGeeX4taKw+HIyE4oMoPxwZnOrW5dDFE7bJVFMfDNQWeTaMSAZq2xGvAfGQzNvOHMVZZGx0WrhwdhgEUY+N863W9TdCOQzNsxTS7soJicntUr1VbEYEKzLduMqt7K3uj8EZRilmfWSOUK0gnUDB1HaECUSzXrPc8m6rjD3MBr4fT4L/8+RqM3GH3MDhxVeRY53zeL1tSgpn7WdaC4KG55H2lnPYwm0nfULx0Sz1Ig0rPE4Rpj7wNqDA6VVhKUotN+iEXbUa6dh/cOYwXFk6VysIdQ7hD6Wukx43hz9iREI5NSzLrab2sN4Zd22WoisbYEq7OutyKtqsg/gcMMoIKqHc7GevoU+xoufs9ZhTNTqesxhMmP4eyKq9ZyQFn2g3rCRo4AxzHvgUBleoLi6vxkQhVweeHUoaiP1JA0XZYS86KVboMDiLbELQLBOJ06cGOTGagYoJxuxWaNIotyxOI0dO7Zt2VVYZPg8HKmLh5Dw60EHHeQ33do+YKNjU2HxYEwR9cHzg7JBFIKjg7kIsMhnwvgjVI6ixEaOYoKChbKBdyLUDaF247RdeIc3g4WIhZXPifeDjRWFseidFXiw6Fs8MHhsW+WBo8ThcaEt1t+NQInfY489vAeVDZR2lnXGfRo2UNJlWJxJcbGoBC/ej+dEW6p0r0InKHJZGOlw5i3lgrZWxoNFK81QseOfiQSlN0s2W5Qc5mbei/GsroLxZjfTsrY2yq/mObP5kzpnxy5Sz9MM2o9SgbHC+xSN3OC0wMjHEG/Edddd540H5hprdRZoP8fT8mwoskYpITIUqsiafuZ5WTQCJStULn2jsWvRe9aaKtc7tMLupsAwJW0NhZQ5c8wxx7RlmPE8mGOs33ZHR5a2VB32N+Yi+3re8cY8YKzaZb92SEUaZLLfoTNggNWLZNmFqERLG2Uw0O/8rFntBVEN1lDWqoceesincMZ8h1FXIhCEkykWwyOD9wk4bQJliKPY0mHumCMQKHmcl061vl0ghCds2223DT5x8fbiyWLRBbxubDCxnU5Te/Y8CgCbCYoHF/XUnpKQzpFFSUnnhLIAobiyYZv3irSKovmIli/NwoQ31QoOkYvCVOYzThdOW445hgugFNsFccAmi4KcFyt8YwFlIcyaEsHzwJhCqWt2Nr/NCTylGHJEINlAQ+bHMhbwhtM2FLk0bBr0E/n3sRVcF4lAcEIZnuqs3lrWLNY9xjdjghSbVkoJihDP1tKXKPZlo6z1/KNYo0ARPczreaVdKPbMZxQExhTvgfes0d0KjFEcBxiRrB2kMrVKO2z3kjmMKd4PpbCRwZIunOa0MtJZihh5OKjs0Aj2Kfq93cMTWh15y9xi7obeU3gO1LrxGfmsMdQ7ZIVLPomgMJYx0Nmz2zH+rAaAdbzo0ahVgTnLWGN+M1drLxTNu2Ywl+lb9M50NMJSs0nR5D1r9wKi2ehtrFPop/UMDNZZjGsiA1mLt/+dKq5O37s1kCIQhe+BYEM/88wze73yWGVsMlWLQBQ1IMjLPemkk3pv1ea4Q3KBO2ltEnbmaFNuNQX6FiWzNnWs6jDB6EsmOJCaQ1/WU4SskBvlhMlgi49RW1xNyB9DpGhxtZ2wwvuiRFthPB5H0prK8HLzHshmTCEf5QnYuEkBQREmJQjPHEcYZvVi1jtmEsOBBTKvpwfjAyXOboduBl4elCWeKydmFVGais5l+pH3RWFLw9xGSeSFwhjzxpsGowmDmY2Y+c94xOjO8hmJZpFqinFKxC5LKiRjk4gr6xyKDEf3Mn7T66edqLTJJpsUPpELRZL5YBcLtrpU0fqC09h49kQKORWnFe1cModDjAgla0yjNrUqnM4DTjjSmuh/oH8psm506lNZx3PaCTuhTvb54x//6B1HsdU75Hlu7MsYZBj4GLeNDOEssBfZHU1VOcq2XcOBz1HG+GLus1cxl9GDTIdgruKgq3c/CzVG1FKSvomuUA/mHBH7epfKNeONnMXVMiAiI68BweTlBlRSiPgaLwBHGLJhdUspwQtm3hs2WzyJ5F2GvCG0LFD4SD1iguEBZDLjtWzUl2xqTAAMCLujgkWo9rPi0WKzxXPQbnE1U4CFicnPe7LYsPihDJBeRTpNO88e5YgL8lDO7EI1lEBTTOy8exZD0gDzetMZF3wGjJ5mxai16Se1fYphgEOgmRJnUATJrZq8F8+3jBS7PPUd5rlGwbPokUH/mTGRpT+qCmMbo5IxaQoJGwRGXqvz0jEcMCD47F/4whdapvwA6x2RMbu/AscFaUNEeYiKGbQB7zwnhBW99wUlg+fGZ2O8mZFtUbBGEB3hKEb+HuW6Nv2xrEvmaBcX7jGWGjnFshZO54G2kltPmqAVWeOY4xmGKLLmOdI3fN6ih2XUUyEsuovHl/WtzHoHuyXYFFLabHUdrOH8S191ct4zT3GKsdYTUWY8oMy2Mw4wfPkMsWQdMCd5NlaszxoSwjC154+OwNqEjoZzkmdfqzyjO1Hozs8wZOutLRZ9oPahiCNyzpw5ft9kPcPx0mx8y4Co6Xg8UXaijZHXiquKAYEygkfpqaee8v9PoS4pMu14E8r8HHg2UNws4kOYO9QRgO3CsLr++ut9yhEKDxML679ZobIdJWvnN1t0AM9OvboExh7F1WxUZRRX20lVjBNyv+3IVxQI0vKKFGOyMLFwmSw8MSjbFsliMSS8igGT5cbdNNY/LNYYD1naZyd48LcslulNlu8x9unXVqlM6dNxeF8UzU7VJLBR2Xn/eDTZHOwUK+Zw+h4a2oTiyEbDxh6LMcGmRPTTTiJJt9vOS0d5r5ezy+bKYQ/MJWppuHE1qyGKgs7ztGMqMSiIMBFpsr4nfQkDuN17DFjTeF52TCT7Ce/PHGwWLbFbsZnzjMEsdTh5LpnjM6IQkD7aKPpQpHA6D/QLaT7IB9ZN1s8y7mBpdEMyRkS9gzYaPePatYN1gyiSvSxKWGa9AwoSzxJvMWsoc4G5QtvtpnD2kfR9LHaiUNrICLEOsMYTIeNf5iS1Le0cQ20ONPbCKl98a0fBWwowczd92hfefRR81rLPfvazpWRx2CmDvDfrI2mutQYbv0PklTWFfdVShMuKPjQqrubzN9oLZUD8z1NJPr7losdwkVwzA4LFhsJlQtC0He8mVisbQ5UUDh4V3hyUcjvbm02MVJsqtRMFFYXyxhtv9P+PUo+x0yqFwryRaQ+8eWJYjOpt5DxfPOFWX4AyTqiyaH+wyJk3n4WF4y8ZHyhUHF9KzU/WC/lQaJkjdnQhMtlQ0psB45IUCBR2iiqzpkCw6TMPWSxQorMsGpZfywLOZouM2nxd+puQLJtyq0gInwuvG/3Egvj973+/Y+MwbTwRyjYlmvbjGabvMYZY2A3GH4oYBgVGYTePs2wGShA1UHabPCl7QA2ChcgbnZfOMyFdhHHMuEDxz/pMSCkyLxrziqNFGSOkUZqjgnHB+5KG2KywOAt8BsaOGUOA8sVG3OziS9ZoohDMeT4jTp8s88bmS6tL5vg9TkdiTtrFi7UwrxnvyMHLHuJADfreiqx5HrSDyDMRiW5fiMozQFminzByeNXWKDFWMcBYk61WsihWzwI8PwzY2vFhxbrpF/MhbVzYK21cWNTC/m1nXcBo4mAQO5QCw7JorQefB6OefsXIrtp6ZbeJQ9pwYI0gQ+COO+7wjjir4wTmH46J9G327WCF0/U8/zhbeRbMUerH6jmCcU7yYv8qmgadfl6soZyWx9iqZyjJgHDOh23pKMLabCR4WPF6ocixmJOiEosBgbJBfr4dncqDxYtQ5aJM+pp+ZgM1BZ1ToYqmE5QJCgApLSgiLHicnsLJIq0WP7vADsWhVhlgAUXJQNmtt5nztxhVf/rTn/z/b7311t7jVbRgizGDTBQkFiXkWt0CigLju1kqBJsV0Rern2Hx58jf2jHFc8QAZEPjkrysnmI7M5zxTBuz5smyUNJ//A1fM4fp09p+oq8xIvhZq0JVlHTGHm0iPQ0lt5PGrJ1YgiJZO795hrQPZdwuqDPoMw5DKFKsHhLaTFuJqjHGaDMGMbDO1j4POy+dzRGliqJO/p41j8hB1nQR5h5pTzxHFAHkkDaJZw5nALBV8F6MFxSAdjdcUwCYW8jks/H58V7z/WZrMBsxc5y5yphDqW6FpdWQ+sV4qbcm0d+sq3xODNN6c6uMwuk8MB/Za63IGlBOLI0NAzL9b9knOKWPoDaDgcJU1pA0KGqcUEjKJ1HWdi4YrX1vol6MNxwwRTzYdilb2rDgXzMu+Jpnz798jnbunaFf8HZTG8HadPTRR3snXxHMUcR8qEpRtUUcwG6ntigDLzz+accNfcC4oK9tT2TtJQUxlCHM8ybiRSSRkwMxJOpBu9kP11prrdLe+99NiqtlQPzv9BMsOhRXGou1iWcPTxlHu3JTY9UNCBYLPL8cwcYk5XMQdSDkX4VJ2grajEJhubK0n0lCHl+3+POf/+w3OpQajBlSirKGBetFH2oLIe0krHowjCdPnuxrCKy4GqW8aFqNFSWjQLEIsCAQUeF7jA8WAG6STUcTaANKGDc2s8Dye3iG2VDr1atQw0Gf0UccbZtl3Fn6CnLJa88TscCbRZjXbiTHM8SCxrOqTUew2oJmnmCDcUhROyCfeiFOkOmUQYuyxxhhI2iUesUc4TNhTLCJ8Rx5dqSNVeUYPtqIwcNzoU2MGdrZzIBIn5dOGB9lnL9j88xTfMvGw9hl/vH3pAaiALH5cnsrmDcXQwVjtyyPKMohL97bbpLFgGX8NHMC0D7aCeTWZ9mUW10yx5jHe2zRh3qfEYcTNXJlFE7ngZoMPNq0sRko2mZM1BoYtWmLjeBZ8wzMYEApNG+zgeLIIRAYCxwyQmSv7BPZLN+d9Q7jIZTCacYF6z5rBGslz79o6hDyGJsY4kAdJfOoSPvRVSxdp5v3ZbA+2b5Gmxgf1AsyLi0aavC80EWIvuA8Y6zw9+zPdhKj1S5yelXZcJkxWQ/0F3ppvb2ozOhDvfU0ffSszQsZEP8LQ7GgkH/LZsJiyobCBo3XoeoXybFA4F3DA2unXeBJKnsQdQL6nE3FIigUquEJDnWXQaPFkjQHjErAmsd4yBrFYTGyBaXRZsyYwoioV1BdWzSFMs7vowSwQNU7KjYLlheMos4GzP+zIaBgAJ+PaAQbMxsOaQ22uTPW+BsWj3qficUFLxUKCnncGCpZ2sMGh+LCZ8pTRM/f4Vnjfezv6HfGDc+vdmOz27D5u1Y1QJbmQtGueaZ4DxwMGBNsIKFzeM3g41mxeTVTbtmIcRzw2XmGVTgemT7EeMAjRn/bhpPFgAAUDHPcoNQRGc5zggvvSzSWOcOmStEuGz7npzPW2Cb4PuOCzS9LUXZWkMln5z1Yt+xmdqIFrYw77iPieGi87kRKshiDjS6ZY69gXjI+mLf1nA/pwmlq0ho5bCzawTMoszYIuSgJRHp58dzS/9YqcrXQv2mjwl58XmoYMBh42YlsafgcFl3gXyI0IQ/ySNc7ECnslKHGmo/nmv5kfBTdSxnH6Bk4KoG5i+edtMK8l5YyZlE+LeWqk7AO0CeMfeYHBqVFEgwUddZ51gZezU7jRHfE4Le6QAwroollrcH0O+mXrClEB9HtOhV9SMMawx7KvEIfoI9kQPzvQiLSlUgV2X777b3ijTeVBZULuawIuWoGBP9ypwMbDoOMdjNw8STHDBswn4tcXB4nijjWd6hbTdOg1FPsh1EG5Oji/cyzsbA48SyaeazT52O3CtFjGGI42AaOMVPUy2F3K6BEWd4tBgQpShbCZ3PD88uGywLPeOJ9+Vz1CpsZe0SLWJApzqZQvxW0AeXcIiJ5vL8oO/w9Bn+tkcyCg9FDe+uljqFIsPBl8XzRH0RU0kYW8FwpuMW4bedkkqzPKouBxYaMJ4zf5/kVvZSwDOxEIl6Ml/RzyGJA8Lmp1WF8mHKI0kMfsHG1Giu8P9EH/p41Eu8dN8Uji8iS3V3C+KZt1AKV7WxhY2WjZazQXhRHUon4vM3GHm1irUOhwUNNBDzL2oPBjyKGw4uxb4XTeAxpQz1nBmsQzhkU7FaF03YgA3OPscZzKCOdJ8scrDUu7GvW6jzbPYYshoIZDRiNncjDt3oHxh1RjXr1DqGx9EfGFYpt0YNU+Cw4Vtif03oRKT0YEqyLWQ0C1mrGFfOhEycwMmZwyLE2MBftBEEDI8gMBj5PHsOGOUG2AroYsK/96Ec/KiWllP2HOgv0BKIP9RRq9mY+D20PefjHuzXF1YyrAW9AcAoGHUP4nxAW+X0MbBZcUmrynCQTGutY0llom1m9eOjIm+1Pt9kyyamNYBNk8aX2gHPcy/DcMEyYdDxnNnvSAPB6EnVgs2eycn9B3oIxjB8zemwBYjPnuTER0hsHk4/PBq28FUwkajHoE2RQyMcJEEWURJQnFA4UMzZRFm8WHwraWVwNFFcMApQ+DCqUhnoLPcYHiydKHiHdZsqYFdLxGfCWFEm3sUWF9tUrPCT1hX61FJI0KHUYOpZSkxWMuClTpvh0rnRxJQoBUQmU0BBRMntWluLVbFPjc+NYYLyxkbdb6NlOITEGKOOgdly3MiBoO5EH5iPPmBRMjFieOX1BGhPPvZnyylzDK8jf0184hyhAZB1njbfoA2ODeYrXvWyFDkWbPqDNFg1jDKF0tToRjPQn6tZQSoicUHfVitpL5ljTMCAwJngO9Qx/aqHYR3hGOMoapYixN5KGRloPxgifi3nE/OH9unWiDn3LmE9HLWgn//J95rgZDLwwIDttVJdR71AWjBHagheZ8c84LPrskIXnniPi2TfsoBnWXPYlHBitCvGZ68xz9uEQ9RDMH2pb0OkwknHApeGZoPiyx7NWlnE6JWsXhgOfi75FJyNtsqiBxPhh3WLtQBb7fj2YjxhAIU41a1ZczbNDjxjQBkSj88otv7pKWMcaTFg8vv3hFsx6sNBxmg/Km1n2pMo0uyMBJR6lywyD9IvvYTTwtaWn1EIoG4s/70kkppiwyZoSjZHAos0Cyc9q81AxVmhTlotpkEVaAwo7YOgSziwSAqaP6AM2VfrU2kQaDLnYLEakjmBY2IlQ9fJd+UwsaijV5MWycTTrH4w0PE7pk4bytttSexpFbugnvN/8Xu3iY8WTdpxoXvh7vFh4hegnNkFACSNSgzFBCLnMzZDPwxhBwcPoamZAU79F23h/jO1OXoRpxhsGmp2ZXksrA4Kxxt8zHvGKp58xz565a5fP1TMQgTZg8DJ/eT+UcOY6qXXUCpiRT7+iFJeZvpSGMcY4tMvlrKCZf1tFPIh8EQXPcy+J1Vaxb9FPjFXGCkZS7bNIF05TK8fxkI1A8WKuEvVkrTFjBWMIQ53PxzOpUq1dveNbO02n6h3yglKGcck8YWy0G0libWIu431nfQf2MpwqRCVI/Wz0LOwADeZE0UvmWIMZ+7wYk1YUzxpQr/gZXQmFl+hAiEgQugdzlsgn8J4Unhe5bJC7a8g+YH7h3Ky353Uq+tCouBrdpmz9M1oDwv6824tPFgOCk0M49aYqC1NI8CCSUsbnR7kgz5BNuNYw4F9+JytMSIxElBG8dBgmXChVJMphBol5dizCYbU1lhPOz80za6dSsABk8WDXFlezOJF/WWTxNcUUowYjol6KQ6vLsKgVwHvJJslN7s2MGZQOxi5KXNGTVViceV6t7kBgDOAloZ9rveCWG05b2znhhWeL9w2F3W7bBRR90puYn0WMlGbKIZ+d/mv0vO1mczt1ipzZEKfYNFI0CW8zjhu1r5kBgfcYowzwCNa7E8ZOTkIxqHf5HD9HScewZX2wCwJRlLjQjDHDvLSL+4g+hCqOtxuu02s2zxADlrWmlfeX9Y46JNqH4yBLO+2SOT4bn58xXu/gAHLZuXsCA5Mjvxutd8hjjUAJrF0DWD94ZqwROEIsL1p0r94hKyjspKHw7JivZcwB5uTUqVN9VAJHhsHehyHBvlpvLWJNsKPNm0XizVBI/8vcYr5jMPCqPXqXNcTSkqhp6NRayDqE8s8t5axFrIdkNJAin1W3pD8x8pljOIkbRSI7GX2oN85xuJd9u3x0BgShf3JAmVTAA8HTTfipSljHMhjLOns4FlDYOEPclIxmsDmbYcC/bNi1L35WVh6vRR+QyfPBqGFhZPPAa0x7WLTx/GBI0CYzGGwBzVNQRh9QXI3hwXsQNi1iSJoHCOWAdqYXcPobRbvRTc54sMihRgYelmaX3tE3KBx454su4nxWNg425SyKip2GY3noaex8/rypTM3uyMCQYAO13Fo2ClIniErgoWlXiWDDZJygGBLBadSPjDPSG1H88EZjbIfOuWYM4fHjMzYbhzw/jBtgw7O+R9nCY8dYwkBqVQjInMGYZL6la2EwDkjDo29oCzUE1FMQGSNCZgccMM8Y1yHSl9LQHqJ6rDO0x2oTWB9aGZco7xwpTBSDccQcz9JW/o7fo494j9rnkbVw2uYJRhoRkEbvzdy2tCY+H3OqyheF9fd6hzxt5fli0DIv2APKaivjAUOCo3qtts6KrqkrZP1Kw/xnTrD/0HfpqIKpdKwVdiABc5y0JL5Oq3y8B5EyizJgIHfTGYzyTwTBLlAkJZMLFLMcyEJEh3pMdBWchvX2PNYX5jmftZOKdmiiMiA4xo5LdMg7tbPryWXD64P36uCDD3Yx3kSdB7v9kgUk/WLS1n7dzQnJ4yV3F88vVn2tUWBGA4Ouk+204+B4JnbbJgpS7cVNdmERylb6hkeUdSZLnlxQZDBuWXxRogibFrnvgzahANJ/LOwsVJbqw3hrdCP0Mccc48/JJg0E5aZRu+0EFxTDokXHVjtBfza7syINnwHly7zRtZ+Z/rNLe8qCxZy1A2PC7jUBnjUpORgT7VxYZmlgjBP6s1EqDGMQI8JOGeK9Q8HYpS95/kVC6Oa5tLFGKlgWRQZlwop7URQYG/QNCjoeMT47p5fgIaOWijQSO16ZfzluuN3L47I8L5QI2mVzk3nO2OAZtnJgEEXjgALWF07XQvnKgqVp1ea5pwunqZvDQ9oI5g39hDLWal1BLgogxokd9tAoxay/UqV6hzwwh1jrMXzS0fEyYAwRReOUOLt7CEiPJSrB8diWFkc72MtM37Abt1nLqGMgdZTIRu2pmDh7zWAgIl+1aA97DXW2ROgZI8wLao9I8WoE8x2nB2lCOItZxxqtDxiq7dwQXkVmxGRAkAOLB5XTdtKcd9553nq0I0X7owFhm7AVFAKeYl4MdgsV2suKpdLdzN/yMgOj1uhgIaiqF6bM6ANKIv+ycWA8NAoLWxESnliLlNDXLBb0cZ6oCHKo1+AZojSRN51VwU5jqVS0GSOCUHCzwmk8Krwvz5VL75odLYssNiVO0Sq6uKPI0FdEH/LUfJgHmPet7Vd+RoSFzxAiDZAIDbU7vFCuDCI1XDpUtOjaNlv6AyOiUZ0WSgGeK+AAgrxHLWaBBZ7oC+tC1jQIjCz+jnHKZ0E5IAWMMYJCkTcqiEKBPOYd45jnSlvsXgWMEtZL2mgbOL8TMn2p1jlj91mYF5H/x7htVVCdPqSAcUqUPIuywDrExlur+KcLp/EQ10sTA54LEQWim3lSI+hfxj1OEp5JOtLan6lqvUOe9jOPrWan7Fx6xhNGK2OOiKDpEcxNK7pmr7HL70hHYv7ioGIcpsFAI8XRCqCrVqfaCCLeOPzs9CpSOXFO10v35D4WjHvWNFI96xl1/TX6EJ0BwYaFIsFmnIZFkFB67YUz/cWASN/6igevdjOlK9OhRDMm2CTS3+f/zeiwV9rwoP/YRBrdvBw7dhMoCgIeTTwCWVNsGHf8vZ1Xj7el1d0Q9eSgzOP5Y0Em7FnE02/ebTY/Kz6rtxHybInWsdm0ujWX3+UzteORYwwxTq1wNi9s7HiB66Uy0XcYSsgNdR45fcCGSFTi9ttv933LfMM50UiBywJ9Qt8w5lDG680tjBc8d2xA1EOUqTDjLUTpYPw2ilLVwlhg7LAxUCdCSgMyaDuRh6LKAH2Mkca/dnQsSjfK9/jx4/1hA2bkM87ZtMu8PC7LGESxtksO7XACaKVs0l5SsUjxYg6dfvrpLdPEeCa1BbIoHBiSPINmJ7rY2OJ9UU6KGAB8Pru8kfFOuzt93n+n6x2YhxjpVfOA5z1+mfXQ7jEKsV+zx1jRNWMR2O+Yj4wb1sr0nR38jGihRRnYX2N1SDIviURQf8T8wuAkkk/kxECXYF9lPePIduZsPczA72/Rh+gMCDyj5AmjhKUhfYkCs3QqQn8wIOz4NCamXbpjt8SWRbrQiUGAosbiUHsufOxYeg4GA3nCVu+QFZ4DRgQbNkYEaTooOnk3beQwfllUmHCM3do806yfh0Wdfxsp/BSHkd6HEkMRdTNlxm6GZpEruugz5lH4SNMqUq/AOCRSwyZfm/LD+MQzZJd8hTZwcUoQ7eR50W94g7Pebp7lhvHaPrbwOQYUCgFR1jIUOTupDqUUpT/rbcBEXqzOzLyPPFO83GVESFBWmX98btZ0xg5ROdZ4lBL6AGW+E+lLaXhvog60z2pX8hivrAkUUvI3RE4YN/X6nHnLOovhUDueMagYCxiveDgbpaowJ4gIkWaS5ULIZhApw+OK8USb+KyxKn/1+pqxxOfhEr96x0rHCAo+0UvWqPStw2XDXMAoJipBFDIN72sGAzUNnSp+7hSkYtndTowZCqQ5EIe+5o4Naj3pA+7Cqtf/rPsYI6wFsUW7qmxAFJq9bOicZMOxmORy8+Jrvo91mBUGhKXz2AtrOb2BctEbGycTggp7uwegU7Dx854oUmzadkEVCiztra2BKPpiE2eDQrFmI2Oz5j2ZMCgztIMJwCJSwsm7XcGOrcQgYqFDAcpbPMhYoECSPqJf6C/6j1BuXjmkN2A0MPnwXGCY5MXqOBoZDyxcLHDAAQPNFi+rC8FILbqxWrQLJbVosTN/h+LIs6m9PIh2sfFjoOQ5vasoPB82B8YKfYnRR1pJUeh/jE2UNPLPyWNmbqULDwmVM66Y90RB2oU+xOiyW72zGA8o9OlDKoAIBO3DU80JSYz/drH5h9PH7l4hisxYtKggG3KRSFY78J6WomFH/zImSTtEUWu1BvKMjzzySP/5iGJhxBv8LXIxMnjRp4yL9HNhfNgNwlxU1yzPnfbwXIscO1kL/cz6xgk4GBAYJoyb2GFdogCZ50INGM6N/mA8AOMUpZ3PxP6GkyAEjGUOguGYdhy1HHLA2ERp5shS1sbao5z7C8wHjHjuWWI9YP3jjhr2bFLngQhhI+MNRyO6W380HrpJ4VOYsIA52o4CPMCjQPFKlvO30wYER1reeOONvd+zHHfgvG1ucaS4EeuKUD6LDkcNho5AsIFb3rRFHfiawctgRLmvPRKxLHhvS22y/FgrBGWC2IYK6doJXlVNeeKz8BnYFPGUtOupw7ikJgJPOTJRAotcroMCgeGLAsWzxFNZ9Nbqepx11ll+cWfxIgrRTKnHWGRMkRpY9Dli2DLey/Du8bzY9JFX224Ub+Y+86ATETIUWg5v4Lx/wBPPhlHUSEIeawNzDeXQiljZfHmhnLNhsTxut912fULmed8H4wElM0/EBiWBegw+n+U/UxTMGoRii5LCWkCxICH7dr2ejE2U7K233tp77i2lh/mBIdHJ9CWDz02KCHPbvGoYY3h7aV+W9DL6kL6k3zDI7J4P+stuuWb81hZOk7LEHteqcNout0TBIb2iTFjjWN8wGPm87F9lFux2o94BJ1x/VHDTlyEy35krPK+q7scxg75IlBRvu8F+R+F5PYdkf48+RBeBALwIhHdZZHnxdR7jweCBk4piLzMe6AjSPVAaKBTk/bA68SbdcccdLRWD9CsvbJp2/CMLHoPTwvx2FCIbUSjFCaWBzY3BTs4enkcGPwsvmxt9xOJE+8wDj4eHjRbFgpdFLNjg0gZHN2DTR4HC6493s+jJQmnoH9Iq8FAjn34pklKG0UEEjUJdvJIYE6aktgvpUVdddZX/mpNcmim7PDOeZav7GrIcR8nYKEPZ43mhpNWbQ4xBvMEY2Z2IiKE4ESXisjdTDHFA2JGHReTRT6w5jAEr3MWQpOCdvrT1jLqAIpFP5h6ebAyxPMoEBqcVc6PMGzxTbswmIkPbkI9jhChtkeiZwfrAugoYCswjxiJ9ZGeWd8NbbDc3Wx0Z0C6Mcf6/NjpWC39HZBzlnt/HgMBwwJDjuTO+MRxrlQ6eN3san/+QQw5p+h52pHPeSzSzrnGs/zhcWDN5L/YlMyirDuOINpOWSQSRMdtfjQcbr+xH6CqMHZwv6YvZRDkQhSECkz5OmXSmRtkM7FGKPoQh865Qq5Q3e+UB77pdzMVZ23aCAAs4G2T67gbSm1hIOWmgEVimWGL2ynOzrB3PiSLJQkAeup2uwM/w7mI8oOR1ssCNxcg2Et6bCWG3s6KYsMHzYhNjc2RjRCky7yULud2+2GkwBHlvwrt412l/WWee8www8CwnHk9Dkc2V/uW0B86c5u+5L6KdNBnj3HPP9UoMz62ZcY0CTtvpn6K3i9rJVvbsywClES80hnKtom6pTHg7ai8jCgUKOGsEoXqeGXmxnMpBlK4d+HzMJT4r84lxhdLD95nvKAFEI3ifrEYqf4NBYrUiWRVwFHk85hZxSMM4Zz1iveQIYuojaDdpLtzBg2FRJN2F2gzWFMaezSUUPauP6HT6Uho7ujn9uRjjjD0rik/D/2P82XpHv2N48gx4fvQtn7ORMc84px+t/5sV7Zt80k3bvRulGTxjImA4OXguKKZ8Fj5/3tTNkDBeaBPRO/ZxnhnrA2sfe2l/quVrBvswUWz2Oks/Fn1PomwXHAvMU1LmMfI57rse6KPMmTLSC8X7GZxnEWvlQWOA8DtZlTiOFiM9CeWYYje8v5tsson3prHx2saehk2enzWCvNe014gBlMWIYOOwHGWs1XQYiM+DItwN4yEN7493gwUKw4tFmo0RTxUbfa1izvOwk58wxljcWcyKKqlFiotR9DD8aCOvso+7YwMn5Yf3IbWNcVRksaDvUMJQvrnMh8WJMUHdTRE4Ug8FF7nNTm8BnospsEVBmaEPsp7ukxU8vow3xhry02OM58lcsZSSTqVXsEbQV2weKM8YEVw21E5xtcH6xWe2/H/WASJSjAUiAyhyKLVmqPGqnXcosaSdoDzkqUVBkf/Zz37m27Drrrv69a82TJ9uJ/nOeNd//etfe4OXF9FZvHGk3mSNeFhKKOsxa4V9foyKEEdU5sEiapaGYBdnsQ6ztltkE0UaBZaf0W9EzuxWdWRw0hr9wtxGEeeW33pwYz1OJNaQVpeisr7h+Cp7ztWDz4CTiPciGkYknM9uziTGGOs6r07NQ9Z49hPmBoY184D5wDHvtJOxUySttD/AGkFRPf+yV9NPsRyfWhYWJbRsCMawnVZVxhhlXFET0WpvxXjtz5GvKAwIziIuG44kNNj82cBQSMhly3KsZz1s08h7nCGbDlEHFun0hs8ksPO5rQ6im/D+9BELNEWgKHYYNLSv1svJBDPDwpQ/PmtoIwJjhc0Vg4cNlslrx9+G8NTxOU25+stf/uK9czzHvBsXbaPOhr6hNgdlgs0RRSKPLD4/0QfL1W+WG21H+jL2ihqmlr7F+4RQHjBu8OgyduxYTYNxyPuSq53ljP6yICWCU3IwItigiUqQ7kMOf5mgABFBwohAaWNssQ4wvi3VkD5ByWac8//k7eMlpm+yPlPkkpJFX/MZWP/sYrNmoKBwcRqpTaeddppfDzjClONoGcutjr3lPbjID0gJ4P+toJixz/wN6V3P+gxMcWadtgM3MCxQ9m1c0m67wbp2LUSZw4CgJokII6dMERVNQ8TooosuylQ4jfHCM0JGJxVkPhsOMV7sXcxLjCvWV/qBf1HW7A4NMyjKaiPGiqXIMlZ4D54NjiwMBl7d3iOrAnMf5yjjEucAc5P53F8jMZZGzYtxwhxk7jJP7X4T1jmrW2TchJw7zFHes+zaJFFCEXUoCP2RtkTeP5uiFSwbKM8TJ07MfNt1syJqFl4WQxY/S8eonRD8veV7V21htCNRUaBQaOy0qmagaLLR8NlY/MuewHgcMLhQXNhc2bzoZxYMPFOhlRFyzvHCopQ3utQtCxix1NzA9ttv72sYsqahcGb3Oeec48ctRkizlCIUIMZXO2d1W0Et/RsqOsa4wauOB6l2jLFZEDVk4+iEN7a2XRzmYHUrnKC07777lj7O+Oyctw7cv8DYQoFjvPOyYmzGOWsGzz6rMcfvE/1io0OxZU7yt0Q7UDjsyEaij80+F2Mew5cia75GUaHImihao3GBEwLDi/cjGsyzxUNo6ZzURHQzhclAKUbBt1OZWItZv1hbLA22ldPJ7mPhng8Mdua33fvAWsqhHUQNSWXkJu5G2LGt1HMVOfo5FHYpIC8MCZ6feX8tsoZBwWfOuu7TZxZloO8ZUzZGGOPsrUWdfQMJxqk5/Oiv/nDrOGuMGQx8zZxkfGHMmy6C8ZQ2mBijdhyzXWaZ9yLMLNjFjqQ4Y8T1d2bEdA8EsECRpkFRV20eau0N1Vlh4UORxxPHOb9s0myGlkbCoEPRogYCr2BRAyIddeD92KRrN+a08WD3PlQVNgi8nmywdnZ7M2MHpYvQN79bphHBmEAmRh4eMhRi+pp+xJioTUcLAe+Ht4e0Gjtzv6hSbfc3AMYsRmurcUAfkLLEhotnmCLOZs+B30MRKZomYv1Ln4e+JRhjnkXZTgNLw3hiflqaSb3fCQVLGJ5jDnIwJ8QRRxxR6o2+djOspXLVuwEaBQtjwk72yQJ/Q9pS2oHB14yJop5KvHxcnkYxuMnDSMA4qQWjgYJEDAUcM6yRbPysj3xOjKWqrH0oxGyQrCOmCMMDDzzgDTzWnFZrGY4WjCrG8s477+zHiRVOkwbX6sZpk8HvsQeFUH7Kgn0Z5Q7llTWC/rPbeOkn2m79mHZepGvm+D3mEQovaynrFEphfzmCtdPPg7RGTmnieZSVytMpWKvMYEA/Yn1n/NhhG2YwZFn32fcwqNBbQkQjWCfYG4mqDoSb3WfEZEBwsgzFjCwyNDb94PkaZSILhIm59RTlh03vqKOO8l4+lD82MjxC5KyyyfE+diKJnRhSxIBgMWXwMnnZcOpV5qME83dYx7UpTVWGfscbR1/yuZoplCh6KAksCiwC7UzedL0DXvD0iTN2qRnf79Smw7hEmcW4JULD5ld0ob755pu9N5LFn7srKMhsptiRRsKYpbCSOopGY8cuVWLst3OkLQYLz7oT56rTZjZA+rWeB80OUWAs8AyYR3ZEaic2SqIQPCvGtDkimL9lwaY5depU/xnZ8FCu2+lzFDUcJGZYM66oaWinFib9rEg7JRJmdRSkjFIYbGsev0NaD+lW1I1RU8F785kwlDA4quRhT9fZpUGhIapg63orcEDZXoLxhiHAUbgo2K1unGYM4EElGpTngI4qYDULzE0zKNgP7XAN+pV1DoWO/Za+ZO/k65gU3apD/1sNYydSedpZn6yGAWWc9SltMLCOYDQUzcxgPDKXMKjQXWpvgi/KQIs+RGdAkH9M8QqFae3k0n/hC1/wmz6KLEonGzKni9iNpwxg7pZgk0XhJTf4F7/4Ra4j86xjKTREmWMhRLlgsNZT7lB6WFTtdKNYjIf0BoeSxwLF52gWIkTRou/p26JGRG29Q23xOf2P8dDpQkyMKF68v11gVNQTgcLBWKdvOVGEE5vqhe3xgpIiwSbMkZH1PL6GnSqDp7loCgB9b3nqnTqijjHD5+S9G71n2vPJ2LACWPNY5UmhyAuGI3URVgDMvR70cZmbP4o5Y4Hi/aKymaOk2qGsswQzP0idqd2MeR+rP0PBz7tZ0/dWZA0YK6Tj8V5ssijMyOTIbNZFnqnd2YL3rtMpaUXBGCf9yO7xaAWGPhdQ8bsU5V933XW+cJpoTDNl2RwSRLmqltKaF7uF2+oo2G8ZH8wb+qWKSm1/gTWS/Yn1ypyVVYhmMQaIzpnzhz2TyBPjwuZW2ToRe4VFIzBSsl622YiBFn2IzoDgoXBeeruXgXWyY0899VS/4bNJNtpgrEAM4wIjJeYwLZ+jVZF12ohgI2EBs5ObWOB48XX6e7XDxY76tHqHNAxm+robt46aosu/bI6kd9EPRQ0Z0kFQTFlguTSRE8PSCjT9wglg06ZN8woJRb2NoB9RePCOtFPghZJsN+B2crPnubLYYwy0SrNJKym0l4iJpVDYqTFljw2MFiuuRsnDqCuzuBrln/RN4ESfPM+Qz84YsaNn2axJl2mU6sbvU9dhtTVFlQxqVFgDyd0Hu80dw4KoB0axpXLynHiuVUpfygLKGJdLZjkqGsOM6AvpTwZF+XzmVvVjHPZRRpRICBxArFOdKixu1g7WIuY7Y5s5xP6GrteJvdvqOS0agQO3iGPNog9Vq08KTVQGxI477uijB7vssouLpWPxMKGwNZoM/cl4qDcpLafZjAIWKXv0bKZ8dv61i5XSJzihePOyG1vTN1/zqpcTazIxHrp1DCQLIgszE4rPT4E1n71oARu1FShafC6iKkTLLE2MozB//OMf+z4ibaSZgsECycJMiLVonQDKDH2MEd/pIkYLPWME1Z7K1AoiEXZqDP1g6RNW4FmWwkr/cAklp3LZmrXPPvuUJh8HCgY684EjU1tFgGxj4+/sckfSNanpIh202ecow4CoV2RtHHDAAb7OzOYpRgZjM7YNmM9EnYrd6N4KjDj6nvG46aab+vHSDCKZOKA40UneeVEWrA2MRfZp1sVORSN4X/QjlE7WXxwZzJu8a3qZsB+wruL8a+b4bAT9x+ci+tCJ4+oHugFRKAa73Xbb+VNDqFXA0qtVgji1pmpYbm8jpYYwGoZDs9+LDRYB0rBQmFGk8TLYMbcoUig/9i/KKLntTGAWkHpHIebB6mO6efsjE4rQqy3KfCYWaTzURcKkKHsckUmxJQscc8CMCE5bAhSxZsYDSg59zULdzrGtPEuebTdOQLEjNGmDLVxZsfFH/1u6oJ3nj0GBgcfm2W4RNjKoV0Hhu/DCC93ll1/uFUAuXysjrI2CbWfxE42ol35k0E8YC8wv4G9uvfVWHwWYMGGC6xT0JwXEKMsUWdMm5gQ1ANYnjE3mfRVOXiry+ZijjCfGUqvPgMJEquGVV17Z58bvRuuZ1XjJeBBlYveasI+UmcrTCLsUl3WJ/Zl7EpgLVbipmf2M1F/2FyKKODPYu7Psc+yLKNDopAPJeOgmhSIQzRTLPBfJdQJTcPBM1dtQ0sZDnhtj+yP0BUqWHUNZtC8s+sBm20lruB48W0tfsiM2WaStzqXIAo23iHQlFEIWedJYKJwm/Mz9D80WO/6GcdYsGtYKFn7aTa1QN88Upy8xTPPevVIPO9PejIl0ETbKbTufk8JnvMtEGSlap7g6Tx1Vs+gARfbMGwpqKaxNjyeWVsYeaTV8Pp43Svudd97pvdikWbVKtUlHIBhbbPRlrFF2qhTtJSXHCrljTV9Kg9LBZ2NullmUiaKFgSJEKEIVFgPrqV08iLHCWoj8qh7Dy9pH1gBrKGsR+3WztW+gRh+6GYEotBNZfny9V5WMhywDFAUTT+5ANx4AZQ1FiIHIZKw9njePgmsXa3UbFhIUCdrE4sLkQnmnffWOIM4CStwJJ5zg+4poBsYDkCLTbDEmuoMhg7ep6FijvSisFlHpJvQlfYuyX3SsGGwQPBP6lEsluQPBLmFiLFrReRGIDhA5skgcx+tSE9AubOwYjyjhKK14DtMLOgdEkGPPmoiCTtSBwmk2bqJYWYpw0/4d+pu0MUv7agfajKcOpTgdkWGeVP3Y6lYwv3Be0Fftjktg/DE20zeBCxEC5iXzD6OeFEKcKUX3qbSeg9MLORgOHACAkk16cVWNB1tfWZ9YY9ElWGPR15pFH/hMA8146CaDig7I2OEz8GKyynj4/6CUkl7DhkmKRt6FCy8HkxlvfFX6lLagiJoSisLESWIolCgZRYxevCEopRTmA8ouufCNsAUOz3c7HgKUdT5LJ+7UyNoPjJV2FPxaGDd8RuYm4WyeFV4zlPKi8HwokuV5IYcI0plnnukeeeSR9x0MkAcMKDY5wFiw+zA4OYmvMRJQ1LlngBoaxiKRh6xpVOkjsfF+E3XCgOCUpHaUCj4zfcpYtFSxmNOX0vAZUL4Ym5Y2VhQ7SY5+l2IiOp3Kg/LMuEN5zus4YK/g7zCAMapJVcQw4etO3dFThkFFlIR+YP1jD6XGqXbt4/vsQ7p1OoIUJvO84dlDacKaraolWy+FiYmIF5fIQ9E0lv4OygWnzZj3LatH0n4fL2uV+tVODkrn1mNAks5kaUVFvK54bP/617/2SQOphynYeNeLhqRR8JDTjWNxW21UVvQWah3gGfGsGFPtGE88c+6K4JkZbFC2ltG3eWEJJS2J1IM0yCWSgqFy0003+b4h596OqW4F3jbmEzdrAzVnKBN8j5Qaol/0RZE+px8Y74x7i4TgMOAZcqlc7EeUAkYW90PQZ0Xzu3EwYGQxv2NRukT/An2FNJ4sqTwo1lYYzV6HMxBHDOtElfbjIrDOMqdx0PAvzhs+o6UYsreaQ2+gMSOmU5jYfAnPE5LnUjcUG44CtE34U5/6lKuqAWHGA5MqVJFSf4FoAkYEXlAWoFYKNr9P/6KEVSF9KQ3DnPoOlK70KRMYSuRZovy1c2t1Ky8mCx4elHYuNkunUlQlupNW8BkrdnKXvcpsJ+F8coPZJNvxkjMWUCxZv7jjIx1RxfBlHePV7DbiWhhHyMOgJIrHZsbmff755/tTj+gHIg/USWSBucTnZS5RQwEcRWuKPT9nzDKmWX/pj6wGsN3TYbdOG3grOaK4P12+hNHJyVc8y7xGEc+UcY2zrMwLCYUosmYxFlGe2cOYu+mIGGuAFUabA49od9X24TJAfzODCtizWfuq7MgOTVQGRBoGLpvx2Wef7U87qVodRNqAwPPLpkCYq6q3P1bViMA72SoSwe+gyJDHXsW+RVHEU4HylPbI8BlZjPicjIuyawtQBJnUpLoU9ewybml/FY0zYM7bfSJ2xCwv1gP62U77atewYIxxbjqbSBlzmLZyihLKP+sYbTZIncIhwqlFWS5UY1yRa8z4p56ItCXSpoC6i0Z3PTS6pRyll1ScZn3FhkFdh42xLGk2tJP2pVM3+dy8J5swhnR/gc/FHS7M7bw3R/M3GA4YfVUz2MXAhPXKlGeLxmI4sIexRmE4VOVSutCkoxE4bLJGdvsjM2IzIPAEsunaiw2djZYNl82yah1L1ISOxXiIPce3W7dbo6TQl/WUYFNwuZegyrc/ouDyWUgFSkci+Iyk4eDR5fvtnipksLCzwHPsZzu3+trlOlnOt+82GA30J5+dcWGRqbIMC+Y06w+KcJlRRFKxiKiynnHZm+XZWsExUQlOJ8qyQN9zzz3uBz/4gZfBnTl77bVX5nYwzzAEMDizKAL0J4ZLlmgEhh7PASUjbWxgmNH/fL7+kL6UhrmOkUjfZDWOGFuMM/LGY7mNWwwMLJXH7o1gXyAqzb/9be62Ar0TxwfpomXt2TEyIyYDAiUchQBjgRcbKxZgFb3O1rEoBoTmZTwUw5QUwqf1jAgUELsVueqgQKFsoTDyWUxpRdmjTgKPLt8vIxxK2JlQMt7sovODuUbbMM5i9iyVaVigFBKJaOc43mYwnrmEjiNgqT0waBceada8jTbaqO4YwTt42GGH+c+2+eab+/tCsrbPjq/FeMC7SJ8QyahNYWp2rC7KBZtIPUOeFAe+X2t49cf0pTQ4DTDqMAayzCEileRTYzgKUUXsCPr0HiYGJjNiukiODZsTRaiG52VHC1b5lArSAWQ8FAfFBcMRpQMjgkFqygzKIIpVLP2LAkE6A0YEHhy784IXx8DxWYhGQDtGhB3bytgrquBi37NJYJjFbDwA/Ut6GK+0cps2LOxF3/GyG+Ltb6wfKYqlpgQvHEZaqzPC80IUigsxebG+YUjwwjjAm80LjxfFtRgT1IDRRpR3Ig+0HafKxIkTMz97PjefFWPTCsX5/AceeKD/GkOmmQHBnMQI4G/tyMN0NAL59BG/l24Tfc//92dPO3MQo5DxwtxvlRZGmmCRgnohOkUZ9+8I0ZUUJhQvCqltY2Vz43IkPG7czjvQLbP+CikQFG+itNkRkDFFH9KgnGFEMDbSF+dZwTVGBAZEkZoDZGBcEzXAKCkKCiVKI3IG2ikwZljQByjxRCowHNL9gKJOJIK0H4yI0PcX4JkmxYk1j4icgXFD/QBtIYqFksppT1lP/7HxwhzC821jESPAjom1U5iyrnu0FYOG8Uv7rMCy1tDvz+lLtR5b6lz4vI0K5BlzGF+cnjWQc6qFEPEwI6YUpjRs3GyoV1xxhT9tpKpF1DIgyjciUE7wujKE2GxjPAHBjAiLRJgCajeCckITXp68x0Ay3pCFF7qol4i5RLsojIsluhNS+cNopRaEfkUpNi86P+M5oYB3Kg+Y8YGxYA4U1sF09OLkk0/2eblZsbQjIgjp8VLUgEjPUxRijAfaheJca4jyc6I5A+GWZZ4T0SOiefX2A6Kr/IzaB3l3hRAxMCOmFKbLL7+8t3iaTQ3lBu8VHjfC+aJ/gwLH6SR4Sa2AKUbjATCALKUhfVyt3QjK1xwFaQZGVsUNz3itMphXQWVRYDGo0p0P3YJ+xDuPIceY41nxNc+Pn+G155mFPI43De9FqhEv7mngqFXWQ2oQ9t9//1zGA3UctJeUmTKVVsYufYaxRcopRgSv9Di2y+P6c/pSGj4nz4xL/1iz0uOEvmDecuCBjAchhAhgQLBBcuLSV7/6VW8wqNBs4IFyQnFwEe981UCJsBssa4+rRRFEwcKI4Gd4cVuBsYGigje8aFQEpZK0E94/dFpOLNixhXjh8RTzIq0JBRlDAiOCvqJgFqdG2TDLsBcAAEaOSURBVMfxNoLxwRpYZB3kWaO0otSGMhTpE1Jy+JcaDiJuzF0iNXazeZZx3V8gpZA5SuQFA8siWXbgge58EEKIQAYEC60Q/clzmTYi8G6nT5qy3HrLtW/2mVEIST1CMcmr+BN1wHDgXxQZPOmdUoJjgj5BycNwYC3CsMPYIvWEVDrGJcphmcfxhoDnzHgiApYnYpEHomF41hnb9AdjmXGMEUF0CwOCk5f6c+1DLcxLPjNGBP3PPLPLBBk/MtiFEKI1g9vZmCZPnuweeeQR///k6e6www5afEXURgSKPwpo7XG1eLRROjjFhXz1RvcPWIFmXo8uefwocyh1nNGPV7iKxyJXBfqGviINBSWQZ0If0m8UnPMMKSK236kijDG7/CnUMYw2piy6QQRn7NixfvxiSPT305cagfHJnkVRNXUmjCEiE/3pEj0hhKicAUE6x7hx43yqgJ0bPmnSJO9Ju+aaa3R6heiXx9WifFFoyvhHYa29f8Bu+LW/zwLRCmodUCDxqncif78/QV8RrUlHI0hxsuN4OREJT3/VjphO1z00izLxO8cff3zv13ng2FaoPeKW8cz7YhQzxgdS+lIaxg1pb9TxYXjSJzLahRAi4ClMGA/82YUXXth7OgwenN13391vVBgRVUGnMImyjqtNe3Xx3jKmTDmzYzhRSLgVNAt21wHySWEpclys6PvMLBqB8oxSyDMh75/0pqrU6pDmRvoMzheU2FDY7eV5DNqBBs+CC+YswiiEELExI6ZjXMk3vuOOO95XNDht2jT3iU98witYVUEGhAhhRBBtIBJh9w/gUcaTzJxoVbeAXH4fDznpSqSQKPWvPHg2Fo0gIsQawDGvPJduGxFEnDhFCiPTUq1CYLd78x5VTeGqkhFR77ZzIYSIgRld0nMLrZhsyihAtdiNsUL0B1DqqWfAS8x4R9EwSInh5BxSjlBWUdhI4Ws1/lFumeSWMoEBIeOhXHg2KOi88LwTfUCRRqHG899NrGiXtmVRWGnzzTff7F98nef2cgxTGQ+tYc7KeBBCiHwUWjU/85nP+CNc77zzTr9Z8SIiwfGu22+/fRGRQlQSFAsMCFKMMJAp1DVQTC0NhShEswJMlD884swVCrUpnCWSJ8KeEGa5/ijS9Dv9T2pPt7xEKKut6h7SYLTus88+/pU2YJuB8cDnHeiXDwohhKhYEfWpp57q9tprL7fRRhv1pnWQc8wpTKecckrZbRSiEkYE3mzST8COB0URxIggLameF9O8wSh/FGHHfOlejGDk2QV0RIow5HiGdgJSp2oDMDyJUnG5YMg0KlKkeB8MVEWDhRBCVMqAQBG64oorfA64HePKxkgBqRD9EYwDlH8UTgpzMQxQToEUpHppSCireJ35PVJWmDdKleg89DknDRHx4YXTg9OZeI4o83wvpCGBcUnUg5Ohil4umPfY1qy3pgshhBBBDYhDDjmk6c9vueWW3q9POumkQo0RIgYjgn8prgYzItJgXMyaNctH5UhrQmms93uis+CR50QijAZOvMKIIDJEZIJnyvd4TmUbE1ZoT41MSEMFg5UIhF18KIQQQnTdgLjvvvv6/P+9997rNyw7+o4Ltti01ltvvfJbKURFQAE0LzJGBMZCOiUJo4GoA15tCrA5GUFRh2o9P54Jl4hhSKDcs24RIaBGhQJ3TuSxm63bVfiRx/ig7iH0/R5EH/hs3T5pSgghRP8nswFRG2FgkzrvvPN6LyFi8917773dJptsEqalQlTMiODfF198sdeI4KQmPMCcrMRLOejVj0aQXkTNACdqUaeAwp82JlD6iUxYzUsekEuEg8sHQ9/xwftgqNZeGieEEEJU5h4INt4bbrjBrbHGGn2+/+CDD7pPf/rTXqmqCroHQoTCTvThRnaicSiJpDgxznRxVxyQavbcc895QyLtueeCP9YOiq1ZOzAuMCKITGQxDJFHahSRB2ofio4HCvCJlgA3Jje6UZtxiNHK2iyEEGLgMKNLeu7goo3lttda+F69+yGE6I+gFHKSDx5fFEy+Dp2mIsoFgwCl+9lnn/XKuinoRJR4oZRjTLAws76x9pGmRnqTFWTXMyxJjeJv2617QP4xxxzT+3U9aB/GDeNPCCGEqKwB8bnPfc6nK5144olugw028N/jTojDDz/c7bjjjmW3UYhKY2l8Ik7w2GBEPP/8894YTBe8o/xjVPDiKF8iFhgRRBcwKog88TOMCStcTtc9UE/RDhgNe+65Z8Of2zHBHFWrQn0hhBCdotDudtZZZ7nDDjvMTZgwwXvjvKDBg92+++7rjj/++LLbKIQQwY1AjAHSLzEE6nn7MSZIU+OFMUHRskUmSCGi/oX0JuRwpHUnLgrEoOF9ZMQKIYSofA1EevN66qmn/NcrrbRSJW/WVQ2EECILGADcDcGLNSNr9IC/Y515/fXXfc0Ehczc+1FGHQy1FH//+9/910R708ez8jPWNWosZEAIIcTAZEaX9Ny2DIgYkAEhhMgKSjlF8RgCKOV5TzTi7zEcyjoJqVkRNWsa0RAMCJ28JIQQA5MZXdJztesIIcT/wMP/gQ98wN/kzGKc17/C33dCmSd1lLZxUaGMByGEEJ1GO48QQqSg/oGialIyixgRnYD6CyIkujROCCFEN5ABIYQQNXAsKkYERdFVO5qaI4OpzyD6oPtGhBBCdAMZEEIIUQfqDTgelRQhPP5VgGgIbeHOh0aXygkhhBChkQEhhBANIEVo6aWX9sXRXNjWbSiq5o4JXRonhBCim8iAEEKIJlBrQGH1W2+95ebOndu1dnBcLG3gmFhSq4QQQohu0d41qUIIMQCg3oAL4l566aVcd0S0C+9z5JFH+q8xXoiIcEKUEEII0U1kQAghRAsoVl5qqaV8KtP06dO9Ep++1C0URBr2228//76c9U30oVPGixBCCNEIpTAJIUQGKKYePXq0W2yxxTp6vCvvw0lQGC26DFMIIUQVkCtLCCEygvefomrSmV5//XWv1Ic4StXqHSjcfuSRR3wkYuutt9alcUIIISqBDAghhMgByjx3RDz33HM+rYiaiDKNBu55wCjhfYg47L777v7nVTlKVgghhJABIYQQOeEoVTMiUOyHDx9eSA61DWmjYejQob7WgluwueeB7wshhBBVQwaEEEIUAKPBjAjuZ8h6sZvdKfHOO+/0Gg0cE4s8DJN0cbYMCCGEEFVEBoQQQhSE9CVqIl544QWv+A8ZMqTu71EzYfdI8HsYDRwNS6Sh1mgQQgghqo4MCCGEaANOZSKawB0RFDnPP//8/vt8jwgCRgPF1xgKHMNqRoMKooUQQsSKDAghhGgD0pBGjRrlowyvvPKKNyAwHsxooKaB9CaiDjIahBBC9AdkQAghRJtgGFDHwElKGBKcnkSkAaMhxDGvQgghRDeRASGEECVAHcMyyyzjvy7LaCCacdRRR/V+LYQQQlSBnqRT16l2CTunnZtjdYurEEIIIYToL8zokp5bmYTcY4891nvtJk6c2Pu9l19+2e2xxx5u9OjRPh1g3XXXdZdddllX2ymEEEIIIcRAphIGxF133eXOPvtsN2bMmD7f33PPPd1jjz3mrrzySvePf/zD7bjjjm6XXXZx9913X9faKoQQnYKaioceesi/+FoIIYSoAl03ILjFdbfddnPnnnuuW3TRRfv87Pbbb3ff+MY33AYbbOBWXHFF973vfc+NHDnS3XPPPV1rrxBCdAounFtzzTX9i6+FEEKIKtB1A+LAAw902223ndtqq63e97OPf/zj7ve//7177bXXvPft4osv9pcxbbbZZg3lce46+WDplxBCCCGEEKIfnMKEQXDvvff6FKZ6/OEPf3C77rqrW3zxxf2Z6pyl/sc//tGtvPLKDWVOmjTJHX300QFbLYQQQgghxMClaxGI559/3h100EHuwgsv9Gel1+P73/++e/31192NN97o7r77bnfIIYf4GgjqIRpx5JFH+kp0e/E+QgghhBBCiMiPcZ08ebL73Oc+589ON9577z1/EhOXMlE8TaThwQcfdGussUbv75DqxPfPOuusTO+jY1yFELEya9YsN3z48N56MU6jE0IIIbqt53YthWnLLbd8XyRh7733dquuuqo74ogj3OzZs/33MCbSYHDoNBIhhBBCCCG6Q9cMiIUXXtifLJIG7xr1Dnz/nXfe8ZGG/fbbz51wwgn++0QtpkyZ4q6++upuNVsIIYQQQogBTVeLqJsx//zzu2uvvdZ9+9vfduPHj/fhewyK8847z40bN67bzRNCiI6sg4cddljv10IIIcSAroHoFKqBEEIIIYQQ/ZEZXdJzu34PhBBCCCGEECIeKpvCJIQQAx0OjHjuuef818suu+z7DpUQQgghuoEMCCGEqChz5sxxK6ywgv9ax7gKIYSoCnJnCSGEEEIIITIjA0IIIYQQQgiRGRkQQgghhBBCiMzIgBBCCCGEEEJkRgaEEEIIIYQQIjMyIIQQQgghhBCZ0TGuQghRUQYPHuwOOOCA3q+FEEKIKqAdSQghKsqQIUPcGWec0e1mCCGEEH1QCpMQQgghhBAiM4pACCFERUmSxL366qv+6yWWWML19PR0u0lCCCGEDAghhKgqs2fPdqNGjfJfz5w50w0bNqzbTRJCCCGUwiSEEEIIIYTIjgwIIYQQQgghRGZkQAghhBBCCCEyIwNCCCGEEEIIkRkZEEIIIYQQQojMyIAQQgghhBBCZEbHuAohREUZPHiw22uvvXq/FkIIIaqAdiQhhKgoQ4YMcb/5zW+63QwhhBCiD0phEkIIIYQQQmRGEQghhKgoSZL426hhoYUWcj09Pd1ukhBCCKEIhBBCVBWMh+HDh/uXGRJCCCFEt5EBIYQQQgghhMiMDAghhBBCCCFEZmRACCGEEEIIITIjA0IIIYQQQgiRGRkQQgghhBBCiMzIgBBCCCGEEEJkRvdACCFERZlvvvncTjvt1Pu1EEIIUQVkQAghREUZOnSou+SSS7rdDCGEEKIPSmESQgghhBBCZEYGhBBCCCGEECIzMiCEEKKizJo1y/X09PgXXwshhBBVQAaEEEIIIYQQIjMyIIQQQgghhBCZkQEhhBBCCCGEyIwMCCGEEEIIIURmZEAIIYQQQgghMiMDQgghhBBCCJEZ3UQthBAVZb755nPjxo3r/VoIIYSoAjIghBCiogwdOtRdc8013W6GEEII0QelMAkhhBBCCCEyIwNCCCGEEEIIkRkZEEIIUVFmzZrlhg0b5l98LYQQQlQB1UAIIUSFmT17drebIIQQQvRBEQghhBBCCCFEZmRACCGEEEIIITIjA0IIIYQQQgiRGRkQQgghhBBCiMzIgBBCCCGEEELEZ0Ace+yxrqenx02cOLHP9//2t7+5LbbYwh9jOGLECLfpppu6OXPmdK2dQgjRKQYNGuQ++clP+hdfCyGEEFWgEse43nXXXe7ss892Y8aMeZ/xsM0227gjjzzSnXbaaW7w4MFu2rRp2kiFEAOCBRdc0N16663dboYQQghRLQNi5syZbrfddnPnnnuu+/GPf9znZwcffLD75je/6b797W/3fm+VVVbpQiuFEEIIIYQQ0HVX/oEHHui22247t9VWW/X5/vTp092dd97pRo0a5T7+8Y+7pZZayofx//rXvzaV9/bbb7sZM2b0eQkhhBBCCCH6gQFx8cUXu3vvvddNmjTpfT97+umn/b8//OEP3Ve+8hX3pz/9ya277rpuyy23dE888URDmchaZJFFel/LLLNM0M8ghBChmDVrlltyySX9i6+FEEKIAW1APP/88+6ggw5yF154oRs6dOj7fj5v3jz/73777ef23ntvN3bsWHfyySf7FKZf//rXDeVSL/HGG2/0vngfIYSIlVdffdW/hBBCCDfQayDuuecen6ZEVMF477333J///Gd3+umnu8cee8x/b/XVV+/zd6uttpp77rnnGsodMmSIfwkhhBBCCCH6kQFBKtI//vGPPt8j0rDqqqu6I444wq244opu6aWX7jUkjMcff9xtu+22HW6tEEIIIYQQoqsGxMILL+zWXHPNPt/jrofFF1+89/uHH364O+qoo9zaa6/t1llnHXfeeee5Rx991F166aVdarUQQgghhBADm64f49oMLpV76623/HGur732mjckpkyZ4lZaaaVuN00IIYQQQogBSU+SJInrx3CMK6cxUVDNTdZCCBELnLw0fPjw3jtziNIKIYQQ3dZzKx2BEEKIgcygQYPcRz/60d6vhRBCiCogA0IIISrKggsu6O66665uN0MIIYTog1xaQgghhBBCiMzIgBBCCCGEEEJkRgaEEEJUlNmzZ7vll1/ev/haCCGEqAKqgRBCiIrCIXnPPvts79dCCCFEFVAEQgghhBBCCJEZGRBCCCGEEEKIzMiAEEIIIYQQQmRGBoQQQgghhBAiMzIghBBCCCGEEJnRKUxCCFFRenp63Oqrr977tRBCCFEFZEAIIURFWWihhdxDDz3U7WYIIYQQfVAKkxBCCCGEECIzMiCEEEIIIYQQmZEBIYQQFWX27NlujTXW8C++FkIIIaqAaiCEEKKiJEniHn744d6vhRBCiCqgCIQQQgghhBAiMzIghBBCCCGEEJmRASGEEEIIIYTIjAwIIYQQQgghRGZkQAghhBBCCCEyo1OYhBCiovT09Ljllluu92shhBCiCsiAEEKIirLQQgu5Z555ptvNEEIIIfqgFCYhhBBCCCFEZmRACCGEEEIIITIjA0IIISrKnDlz3Prrr+9ffC2EEEJUAdVACCFERZk3b567++67e78WQgghqoAiEEIIIYQQQojMyIAQQgghhBBCZEYGhBBCCCGEECIzMiCEEEIIIYQQmZEBIYQQQgghhMiMTmESQogKs8QSS3S7CUIIIUQfZEAIIURFGTZsmHvllVe63QwhhBCiD0phEkIIIYQQQmRGBoQQQgghhBAiMzIghBCiosyZM8dtttlm/sXXQgghRBVQDYQQQlSUefPmualTp/Z+LYQQQlQBRSCEEEIIIYQQmZEBIYQQQgghhMiMDAghhBBCCCFEZmRACCGEEEIIITIjA0IIIYQQQgiRGZ3CJIQQFWahhRbqdhOEEEKIPsiAEEKIijJs2DA3a9asbjdDCCGE6INSmIQQQgghhBCZkQEhhBBCCCGEyIwMCCGEqChvvfWW22677fyLr4UQQogqoBoIIYSoKO+995679tpre78WQgghqoAiEEIIIYQQQojMyIAQQgghhBBCZEYGhBBCCCGEECI+A+LYY491PT09buLEie/7WZIkbtttt/U/nzx5clfaJ4QQQgghhKiIAXHXXXe5s88+240ZM6buz0855RRvPAghhBBCCCEGuAExc+ZMt9tuu7lzzz3XLbroou/7+f333+9OPPFE9+tf/zqTvLffftvNmDGjz0sIIYQQQgjRTwyIAw880J9xvtVWW73vZ7Nnz3YTJkxwZ5xxhhs9enQmeZMmTXKLLLJI72uZZZYJ0GohhAjPsGHDfAonL74WQggh3EA3IC6++GJ37733eqW/HgcffLD7+Mc/7nbYYYfMMo888kj3xhtv9L6ef/75ElsshBBCCCHEwKZrF8mh2B900EFuypQpbujQoe/7+ZVXXuluvvlmd9999+WSO2TIEP8SQgghhBBC9KMIxD333OOmT5/u1l13XTd48GD/mjp1qjv11FP91xgWTz31lBs5cmTvz+Hzn/+822yzzbrVbCGEEEIIIQY0PQnJtV3gzTffdM8++2yf7+29995u1VVXdUcccYRbYokl3Kuvvtrn52uttZb7+c9/7saPH+9WWGGFTO9DETW1EKQzjRgxotTPIIQQQgghRLfolp7btRSmhRde2K255pp9vkeR4OKLL977/XqF08suu2xm40EIIYQQQgjRz05hEkIIIYQQQsRD1yIQ9bj11lub/rxL2VZCCCGEEEKI/6EIhBBCCCGEECIzMiCEEEIIIYQQmZEBIYQQQgghhMiMDAghhBBCCCFEZmRACCGEEEIIITIjA0IIIYQQQgiRGRkQQgghhBBCiMzIgBBCCCGEEEJkRgaEEEIIIYQQIjMyIIQQQgghhBCZGez6OUmS+H9nzJjR7aYIIYQQQghRGqbfmr7bKfq9AfHmm2/6f5dZZpluN0UIIYQQQogg+u4iiyziOkVP0mmTpcPMmzfPvfjii27hhRd2PT09La04DI3nn3/ejRgxorQ2xCQ3prZKbjiZkhtOpuSGlRtTWyU3nEzJDSs3prb2d7lJknjjYemll3aDBnWuMqHfRyDozA996EO5/oaHVeZAiFFuTG2V3HAyJTecTMkNKzemtkpuOJmSG1ZuTG3tz3IX6WDkwVARtRBCCCGEECIzMiCEEEIIIYQQmZEBkWLIkCHuqKOO8v8OVLkxtVVyw8mU3HAyJTes3JjaKrnhZEpuWLkxtVVyw9Dvi6iFEEIIIYQQ5aEIhBBCCCGEECIzMiCEEEIIIYQQmZEBIYQQQgghhMiMDAghhBBCCCFEZmRACCGEEEIIITIjA0J0hFCHfekQMfWB+P9oLAgR5zzT3P0/1A/xIANCdISenh43b968IHLL5JlnnnFvvfWWK5vzzjvPPffccy4EZfdBp9BGEWYsvPfee6XJe/fdd11MnHLKKe6xxx4LIlvjVYTcz0Ks49rPREgGB5U+gHn77beDXADyyiuvuJdeeskttdRSbsSIEW7BBRcsRe4jjzzinnjiCTd8+HC38soru2WXXbYUueeff76bPn26O/TQQ92gQYP8osu/7fLd737X98U555zjylQ+brvtNi97rbXW8u0sYzE79dRT3cSJE31bv/zlL5fWBzfeeKO7++673euvv+623nprt/nmm7uyNh02h8UWW8yPr5VWWqlXgSraHw899JB78skn3cILL+xGjRrl1lxzTS+rHZkh4fM/++yzbtFFF3VLLrmkn29lwPN6+OGH/RgYO3asW3vttUuRe+aZZ/r+PfHEE918883njQj+bYcjjzzSPf300+7iiy8u/Rk98MADbvnll/drWFkwzw455BC/LvzkJz8pbZ4Z9OngwWG3zHbnA3P3+eef93NsoYUWcssss0wp7dJ+Fm4/C7GXgfazcPtZbPMsGFwkJ8rlz3/+c/KjH/0oeeaZZ3q/N2/evLblXnfddcmGG26YjB49Oll00UX9e8yePbtt2VdeeWWy6qqrJiussEKy9NJLJwcffHDy9ttvt91ePn9PT0+y9tprJ4cffnjy+uuv+++3297LLrssGTx4cHL99dcnZXHFFVckQ4cOTS666KLk3Xfffd/P33vvvUJyL7nkEt/Wj33sY8nyyy+fvPLKKyW0Nkn++Mc/+mf1yU9+Mvn4xz/uX08//XRv3xbt48mTJyerrLJK8pGPfCRZeeWVk/XWWy859dRT2+oH2rrMMsv4z7/ssssmK664YvKDH/ygLZnGzJkzS51jcPXVV/sxS/+OGjUq+epXv5o8//zzpYwxPvtaa62VrLbaaslOO+2U/Pvf/25bLjLmm28+395ddtmld4y10682x/70pz8lZXPiiScmn/70p/06+c4775Ty3GyefeYzn/Hr45NPPpmUxVVXXZV8+9vfTr7whS8kl19+eWlyH3zwQT/f6OO77767lPG10korJR/4wAeSJZZYItl0002T0047rW252s/C7Wch9jLQfhZuP4ttnoXaJ0EGRMmwcTFxF1xwweTQQw/1m0QZD+7RRx9NFllkkWTSpEnJPffck5xyyin+Pa699tq22vvII48kI0aM8PL++9//JmeffXYycuTIUhSbl19+2SuObLybbLJJ8qUvfcl/DmCjKMI//vGPZMiQIckZZ5zh//+1115L/vnPfyZ33nlnYSWPjeATn/hEcvzxx/v/f+qpp5LTTz89OeKII3q/V2Sxoa0LLLBAct555yVvvvmm39SOPPJIv6C3o9zxeRdbbDH/rOBvf/tb8uEPfzh5/PHH+ywUed+Dz82zZ4GlX2+77bZk22239ZvmXnvtVWgcv/DCC8niiy+e/PznP/f9zNg97rjjkoUXXjgZN25c4bbCzTffnOyzzz7JvffeW6ht9Xjsscd8H6Dk0h+/+93v/EbBM2wHm7+MW8Y+GxuKU3qzKArK0TrrrJMccMAByac+9Sm/oVmfvPrqq8ncuXNzyWPNSs+x6dOnJ/fff39yzTXXtK3oooyzPqKI1KPI87N59tvf/tb//wYbbODXHOZcGYrNUkstleywww7eOGE9ow/KUGxQcMeMGeOfHWPse9/7Xu88yCv32Wef9ePrhBNOSJ577jlvlHzzm9/0cpkjRdF+Fm4/C7GXgfazcPtZbPMs1D5pyIAoEQb43nvvnUyYMCE5+eSTexcbBm47Dw4v3XbbbZfsv//+fb6PtxHvaFGQi8V/4IEH9n4PZYPvff3rX/eTDM9bOxsxslEafvWrX3mvAm3+9a9/nWy00Ubee5FnUaBtH/zgB5Mdd9zR//+LL76YbLnllt6zwKKA/J/85CfJW2+9lauNc+bM8X/LBHvppZe8PBQx2sgmv+aaayb/+c9/csmcNWuWXxQPO+ww//98zm984xveA0+725nEv/zlL3370nz0ox/1Xt3111/ffxbzDOV5D8bsZz/72T7fQyljo2As8+zy9i2bIQqSfWbr7ylTpvi+ZaMrMr7wTrGQY5zstttuyY033tj7s6KbGRshY+vLX/5yn++zQWy//fZJO/OM5/W1r32tz/cZX7vuuqtXTFknzKNZBJQDFBH6lfdiPGC00ff0VdY+oa14Arfeemv////617/8M8KLN//883vvK2sO4zsvKAPIRWkElK9jjjnGrzMHHXRQr7KQZ8yiuKEksOna32L88RkwevLKS4OCQATq3HPP9f9PP2KcoPCiTLajMDFueV7MhSeeeML3KWsYhoopo3najeKNNz+tcNFG2s56xp6UV8nVfhZuPwu1l4H2s3D7WUzzLNQ+mUZF1CUye/Zst95667lNNtnE5whedNFF7v7773c/+MEP3NVXX+3z2yznLk9h01NPPeXz9XbYYQf//1YkucYaa7h77rnH/78VdOUp7CIvcIsttnD77rtv7/e+/vWv+/zk+eef379uuOEGd9RRR7m5c+dmlptuBzKuueYat88++7jDDz/cvfbaa/496IcllliiN480az+ss8467vbbb3d/+MMf3F577eVGjx7tzjjjDJ9XPmbMGPf73//ev1+edr755ps+n/Gf//ynO+uss9yGG27orrrqKnfTTTe5yy+/3Ofm0n6eb1bID/3MZz7jjj/+eP/s+Jw/+9nP3MiRI32ednos5IU8zjvvvNP95S9/8f+/3377uRdeeMF97nOfc9/4xjd8nvanP/1p9+qrr+Z6D36XvGHycQ3G1gc/+EF3xBFH+LF8xx135Gorn3vatGn+ZQwdOtSPu1/+8pe+T08//fRcMnlm9CWf8bjjjvP5qOT+k6tv71mkwJFcbPJZt9lmm973AfKHH3zwQTdnzpzeQto8hcr//e9/3fjx492ee+7Z+73999/fPf7442711Vf3442xzXieOXNmrjZbG6nTIId4q622cpMmTfJ539/61rd8HcQKK6zg+yRLm8k/HjdunJs6daqfV7SJv//tb3/r6yF22203PwaYJ3kZNmyYf97M4X//+99u2223dXfddZeff8xZ1jPqOPKM2cmTJ/s2nnDCCf7/+Vvm14orrugOPPBA359F59m9997rVlllFbf77rv7/6cf3nnnHfe1r33Nbbrppm7VVVf1cyJvgfWf//xn/8wPOOAAPxd4Vp/97Gd9vyBvyy239P2Up93MefryH//4R+/3qCuYMGGCr2Vhfbziiiv69X5GzVIs+1mIvczaqf0s3H4W0zybF2if7EPbJojoA+F+PABpb9PGG2+cjB07NvnNb37jvR+E5rCMCVNmtSzPOeccH5IFy2nEE4KlbpCugAWbx5NJmA/PDdx6660+v5EQYtr7ivcxq9fGPo9Zt3ig8SQY5CIS7sOrgIc0L3gt8VbipcETgCcl3YfkZpIak9dix4OLV4wQZzpH0vqekCr9m4d07qn1x0knneTz4AkHp7+fBftdwpvjx4/3HiHaPGjQoOSvf/1rnxxgPLCE8/PIJR8XrxihZJ4bHhDGw8UXX+x/zhgmTSYveFbwsuO5reUrX/lKsu666+bKUaa95Pba+MHTvM022/i0AnJR02M17SnKAqk1b7zxRu/7AJ681VdfvVcW3jDyqvOkRbAu2Higb3l2/GsQEsebVzSnGG85nlaD9pKjjLeNfO08zJgxIzn22GP9HOPZ0Kb0fPrc5z7n516eZ8Zn57kQETnrrLP8c8IjhlxepBgwb4lw8HUe0m2zPib1iHlGPUv6+3m9jfQB88nG6oc+9CE/9shX/vznP+/nC1GaPOAFJS2KfcBAJmsi+dWskRdccEGuz87ahBcXD3m99BfmxxZbbJF7XQy1n+GxDbGf4XEtcz8z7HOVuZ+RLhliL4tlP7PP9dBDD1V+PzOZrIVlzrN5//s99pKy51nIfdKQAREA2xRtwhEmI1WBEBfFo8stt1xv6DIv6QnKhKCYx75PYebuu+/eVttZgMHazkbGgmlKVV6YcGussYYPcxIy5Gty8vbbbz8fTi1SlEjeOOH/3//+973ttE0DxQ6FNS+kfqAssZijKKRB8SV1oUhhZq3iQuiaIlpSOdoJId51111eOULJQSlLbwYPPPCAD1P//e9/zy2XPGzSNlCUyNE/6qijen9GWPWQQw7JJCf92VAM+Mx77LFHcvvtt/f5PRQ9UmTybmb0Y1qBZXwhn5A3bSZ0T2oIzxQjudWCa+PHSP8+Gz3KPYoM36dvGctZaKS4UhuS/jnPktoF2p2F2rHDBkAfk5/Pc8KAYIyQLoSyitKQp61sZmzcbEBWQ2E/x7gg1aaIUo5CyDPZbLPNku985zt95FJIyppAnnEWWtV2sJHzXnlrQAwMGXKHWROYr6Rw3XLLLb0/v++++3zf1o7pVqDMoBgw16iFuOGGG7xsFAXgvXbeeefc7UVRohiZNbC2D/kZykNaScmD9rMw+xnP6Re/+EWpexmQqhLTfsa6FWI/+/73v+/3M9KC2tnPOjHP5pWoN9r+hYwy98laZEC0CQMfK5xcXsuVbaSYkKdr+Y155Dba/KdNm+aLURkEbDhM5KLtbVQUiJcNT2EeueQ01spAoWGzpc2A1y6LUtOoH1Dm6nmR8HSTm1lEJhsBHqXhw4cn3/rWt7wnlgWCvt1qq63a6oNa7yheMPNs5pFrhWbpBYEFl8WXscaCzsaG8pRHLl7h9Pfx2qGAGowLZLIgNyOdG54e+xTg4vXCI0ZBHzm1jFsU0bRHrxXNThRhocTbzmK47777eqUfj1bW9jZSiPEGDRs2LHn44Yf9psNm1oq03PTG2qhIlhOZeBWRa7LI8+Yz43WzeYYS3GqcNeoD+rPeRkg9CP2blfTnpw955hRj1taVYKgxlq12IUt76ykt9hlQ8JlnjPEikT6bXyguzAmiI2mvIxsv61raqMgqFwcIJ8Kg1BAp4vSVtJe8tg6nFryxGHdnnnmmd34YF154oTdGWHNZE1AgMC5ZF7PU8aTl3nTTTaXtZ2m56TzsdvezRu1tNM+y7mfN+qHoftaoD9rZy5rJpd3sZ/Rpkf2s1Vgoup81Grs23zCui+xnabkY5WXsZ3fccUfywx/+0BuI6QgT7zN/G/MsLbfeCU5F51kj0oZJkX2yETIg2gBLngI+BiIbHw+CRY+NK409OCs6ahUuyioXLyabGikF/H4rr0pWubaoMcgIHbLwtCMXr0w6nSCrlVtPLspb+jSBdHsp8EJ5ahaericTL5Kl16DEoCSy8BLuZDFjsyizb1GeWXBrC7zy9IHJpV14fwh348kn5E1fF2kvn7Ne3xLxmThxog/VN+tbwtiMR9JxjLT3l1A1mxcnz3D6CAsY/ZzFG5hVaQROGmHBJQTcjHrtrSeb+UpqBSlChNlbtTerXPtceMGyzLNWcvHg0p9EfLLOs3oyGxlStBWvG3OsVVvt9+vJZCPHaGQDRjlAacBo4Ot0Gla7fctGSWEqrywGRCPjF/i8jFc2e5QF5gHewVbtrZWbng8YIKw3takZKHektjSCOYrRwZxnTjLvzz///D79i3HC2rXkkkt6xQPvZatxW08uilKjNLGs+1lWuXn3s6xy8+5nzeSawkykJM9+Vk8mxl49su5ljeSm099Ie/niF7+Yez/L07d59rNm/cAc5dngwc+7n7WaE0X2M/ZIO4GNtCX2c9Ki0kbAuuuu6/fPPPOsnlwikYatVXnnme0BRHY5oODoo49+X0F3el3Luk82QwZEQdicCAMxEIGBiFKHMkfVO7ms6cnGYONh1csDLyLX8lNRaDj6K33sV7tymYxYxiw6lttYRC7H6bHY2uaQJzyWp714GDhSjxAy4c4iMvHSWPiZiYqn9NJLL/Xex1Z56XnGgk1gnhchw3bk2qJDuPe73/2uP8nhxz/+ccujQVs9s3R7+exEqth0mvUtfcbmxAbN4s1pJ7ZRsxDaYsiCxmfneNS//OUvmeoIsiqN9j3yWglZN9scmrW3dpzSZj4/x+y1mmd55GJQ4V1iA2lHLp/b+jdPbneettI+IhxEkVqtCY2eWXrzwpPPRke/si5iFKP0Ntt887Q3XRuQ5ajcZoYUspgznKLFvEF53HzzzTMZv62M6jQYEvQxUYlGSi7fR1Hi+EwUN/qRtAY8n+nPze9xxCReU9a1VnUareTWknU/yyOXZ5V1P8sjF+M0636WRS59nD5VrhV52srem2UvyzMWWL+oHcy6n+Vpb7our9V+llUuUVMiA1n3szztpc4ky37GvEYm+yrQZxgI1E/wfuheQB0PaVdZ51kzuaxvdjqWpTNlnWfA75A9QQSESD/GDC/alTYk8uyTrZABURBC+xyLhiKUBu8UmwAXO5kn0MhytnNeuSiBte9ThlwU/1apBK3kUmiEXPPU5CFve/m9VmfUZ5GZ9gSEamuZcs1AC9leFsVWeel4ZinOQmlhIccTRP645SCnjac85FEaAQUhy4Lbqr21/PSnP31fuL0MuaQcZCkOzNK/aaMqS31C3rayUbZS7PIYkyjSbMCkAOEptaLadtqbHhNZi7xbjbG0Us7xnXiyyVtvtZ63Mvpqfxclgt9vpuSS9oCHlk0/7ZzCQ2nKS5F5lkVuLVn2s7xy8bZmWSvzykV5zrKf5ZWbxSmWVyYRhCz3rWSRW6ROKW97s6YHVmXscuBEq/2MSCvRj/QxryjlOBDIWKBG8IKMBx3klWtF3nnmGf1GXZmlvPH/GGLUOxDpTadf0UdZ98lWyIAoCAOAB54u8rKJhBWMt4oNjnzOPJ73rHLznvzRLbmE0qwfQrTXilFjeGah+iD9zLK0O6vcPF42FmW7pMjO4kfZIx0hfQpK3j7IqzRCloLsrO3N0wd55OadZ1nl5rmfIFRbsxg7RRSbEH2Qtb1FFJu8YxfvZLO2M2+JZHA/QLr/UIbwPKaLTPMUceaRm+fc/Dxy89wrUgW5WfuhCm3VWMjXD8xJTlmjbs/2xZ/97GfJQgst5A86oNaDU65GjBjR566GMuXmPZgBSNW0SGfaqMP5xclW3FeSJu/BJfWQAdEGnJxgRXo2eO3BXXfddX4gZPF6SG7n5MbU1ljkNirAJ7eVXHcWNiI7lqJgNwaHUhpbGVF522un47Qir9yst1uH6N9QbQ1lTFZhjIUyJvP0A9Eq+/10X3BikRWOolTh5WxUrFxVuenC1zLlZokchuyHmNra3+Vm7V+io+Y0IK2I9YV90SASO2rUqD7f65Zciz6TVmkXgNp7GRzSQHSD1GyLqha9nC6NDIg2IA+OmzPxLGHlWV6c5baR25z1hA7J7YzcmNoao9xa7wcbAfmopHCQb5k+572bSmOI9sYsd6A+s1Dt7VQ/GHx20nQAJYJ6kjKQ3HByY2rrQJdrBcy27pBWtNFGG+UydELLJRpCzQMHMJjxYP9SW7PEEkskU6dOTcpEBkRBzGuLFUneGdX4bGJcXkNemZ0LnfcMcskNJzemtsYmt1ZRSv8tixeFoRQx5gl7h1ScQ7U3Jrl6ZmHbG0JubR8wl5GN0sGFYRSm48HMew695IaTG1NbJbe+zNoURmpP11577dx7byi5Zoxw7w/rCXd/pFNPKaKuPUWqDGRAZKTRKR9WyU9lP8eYUZhCagiDgCP6JLd7cmNqa2xyG4U/OVmpFtI4OMGIYyvzUpbSGKq9McnVMwvb3hBys/YBtWYoSfQBaQp52ya55cmNqa2Sm08mJ0JxbxKnID5WYO8tS24jpyCHNHBZJ5kFHMhwySWX+JoLDAqcFUUv1WyEDIgC2MPinOF0pT/FP1w6xXFmRQpUJDec3JjaGpvctEzO7E4f54fng7Ous54W1Qmlscz2xip3ID+zmIy+rH1AESkOgDx1BJIbXm5MbZXc5jKJ2HOaEXcnldnW/xSQ28gpSJE2cHADKcoUaHNkLdFOTrorGxkQLeBWUB5GLRwTxt0B6QLLPEUpkhtObkxtjU1uHplGnluAy1YaQ7U3Jrl6ZmHbG0Ju3j7g2E+O2W2F5IaTG1NbJbeYTGoUWt13EVJuPWztY63BYHjyySf71DPyynJZaxFkQDSBXHBuK6y91IfNgfN17TIQya2O3JjaGpvcIjK7aZiEam9McvXMwrY3hNyY1gTJja+tkhtfWw0uGeSG6do7brh9ftiwYX3WmvQaU8aJS/WQAdEAim9Y/KdNm+b/n0s5uHOgqJUoueHlxtTW2OSGamsopTGmvg0lV88sbHtDyI1pfElufG2V3PjaanC6EtFMDmGoNSC+973v+Vu7O40MiDrceeedPneO4lIgL41r0T/4wQ/6Ipd9993X54vnDZ1Lbji5MbU1Nrmh2hpqwY2pb0PJ1TML294QcmMaX5IbX1slN762GpyQyI32dn8MN0lfdNFFPm3poYceCh5paMRgJ97HjTfe6EaNGuVefvlld9lll7lvfvObbu+993Y777yzGz58uNtvv/3c888/766//no3aNAgya2A3JjaGpvcUG39+9//7g466CB3zjnnuDFjxrgpU6a4U0891d13331u5syZbqeddnLf+9733PLLL+/mzZvX9fbGJFfPLGx7Q8iNaXxJbnxtldz42mrMnj3brb322u5jH/uYu+KKK9zBBx/sRo4c6Z5++mm3yiqruPHjx7vDDz/cDRkyxHWUjporEcFRWOuss46/fOOwww7rYzE++uijvlilyOU/khtObkxtjU1uCJmckrHUUkv5WzK58AcPCykf3HrMedW8F5duFSGmvg0lV88sXHtDyY1pfElufG2V3PjaChzHyhHr3LrNDdunnXZa8uabb/oCaVKbuCQvfbt9p1AEogETJ050Sy+9tJs8ebLbdddd+1iMw4YN8z9baKGFJLdCcmNqa2xyQ8j8zne+4//mvPPOcy+88IL70pe+5I455phe2WussYZbd9113fnnn+/22GOPrrc3Nrl6ZuHaG0puTONLcuNrq+TG11ZYc801XU9Pj7vuuuvcaqut5rbffnsf1eB1yimnuLXWWsudffbZPkLRSWRA/I/bb7/d/fOf/3QjRoxwyy23nA9L77LLLm7DDTf0Dz3NO++84wcDL8ntntyY2hqb3FBtDbXgxtS3oeTqmYVtbwi5MY0vyY2vrZIbX1vrseqqq7oddtjBHXroof7/DzzwQLfsssv2/pwUprlz57qO0/GYRwU56aSTfDh6jTXW8Jf7cIvfIYcc4kNE6cIU/qVQbrPNNvPFMZLbPbkxtTU2uaHaCrfddltywQUXJFdeeWVv8andxFl7S+bTTz/tb8W+7rrrutLemOTqmYVtbwi5MY0vyY2vrZIbX1tbrTXcVj148OBk/Pjx/p4L7nd46aWXkpVXXjk57rjjkk4z4A2I+++/PxkxYkRy+eWX+6OxuJn3yCOPTNZff/1ku+22662ah6uvvjrZeOONk49+9KOS20W5MbU1Nrmh2hpqwY2pb0PJ1TML294QcmMaX5IbX1slN762NltrDj300GTWrFn+59z1sNhii/maiBVWWMHXXIwbNy7pBgPegJg8ebL3FM2cObPPTaEUw22++ebJLrvskjz77LO9XqXjjz8+efXVVyW3i3JjamtsckO1NdSCG1PfhpKrZxa2vSHkxjS+JDe+tkpufG1tttawnrDWEO0EnBRnn312cvrpp/vf7RYD3oC4/fbbfcX8lClT3neOLoNhpZVWSi688MLc5+xKbji5MbU1Nrmh2hpqwY2pb0PJ1TML294QcmMaX5IbX1slN762tlpriGruvPPOpVxKVxYD3oB4+eWXk4022shvAnxdy4QJE/wRWW+99ZbkVkRuTG2NTW6otoZacGPq21By9czCtjeE3JjGl+TG11bJja+tRdaabjPgDQj4+9//ngwfPjzZfvvtvScpfXYv5+2SX1Z7dbjkdlduTG2NTW4ImaEW3FDtjU2unll8ykJM40ty42ur5MbX1pcDrrkhGPAGxDvvvOP/vffee711t+qqqya///3vkwcffDB57rnnfO7ZPvvsI7kVkhtTW2OTG6qtoRbcmPo2lFw9s7DtDSE3pvElufG1VXLja2voNSwEA9qAePfdd3u/fvHFF/2RWDvssIOvbqeQZa211ko+8YlPSG6F5MbU1tjkhmprqAU3pr4NJVfPLGx7Q8iNaXxJbnxtldz42toJwyQEPfzHDUD42NzsB3vvvbcbOXKkO/nkk/3/33XXXe6NN97wF36MHTvWDR06VHIrIDemtsYmN1Rb4b333nPzzTef//qll17ycvbcc0/36KOP+v/nAh4u4vnrX//a1T6ITa6eWdj2hpAb0/iS3PjaKrnxtTX0GhaUZACRDgUZP/7xj5NRo0YlDzzwgORWUG5MbY1Nbqi2pkkXgX3pS19KJk6c2CdUS7EYhWNz5szpWntjkqtnFra9IeTGNL4kN5xMyQ0rN6a2dmoNC82AMCC4DdQ6Pv2gCD9xCQe3/UluteTG1NbY5IZqa6gFN6a+DSVXzyxse0PIjWl8SW58bZXc+NraacMkNP3egMCa44FMmjQpmT59ep+fzZ071w8Gya2W3JjaGpvcUG0NteDG1Leh5OqZhW1vCLkxjS/Jja+tkhtfWztlmHSSfm1AnH/++f6q7/Hjx/tbQw855JDksccek9wKy42prbHJDdXWUAtuTH0bSq6eWdj2hpAb0/iS3PjaKrnxtbUThkk3GOT6KXPnznVPPPGE23rrrd0FF1zgdtppJ3fLLbe4SZMmub/97W+9v5euIZ83b57kdlFuTG2NTW6otgLypk6d6jbccEN3+eWXu2OPPdY9/vjjvT+ff/753Qc+8IFMskK3Nya5emZh2xtCbkzjS3Lja6vkxtfW0GtYV0n6MVhzd999dx/LcoMNNkg++9nP9gkT8f2st5JKbli5MbU1NrkhZHIe9Q9+8INk//3398fZ/exnP0vGjh3rPS0UfRlpefVyPzvV3tjk6pmFa28ouTGNL8mNr62SG19b3w645naTfm1A2MNIP5Sbb7452XzzzZMtt9wy+c1vfpP89Kc/TXp6epJnnnlGcisgN6a2xiY3VFtDLeQx9W0ouXpmYdsbQm5M40ty42ur5MbX1pBrWDfpdwYE138//fTT77sGPP1AHn/88WTnnXdOll9+eT8ILr/8csntotyY2hqb3FBtDbXgxtS3oeTqmYVtbwi5MY0vyY2vrZIbX1s7tYZ1k35lQHB27sc+9rFk9OjRyRZbbJFcf/317/sde3g33XSTf1Cnnnqq5HZRbkxtjU1uqLaGWnBj6ttQcvXMwrY3hNyYxpfkxtdWyY2vrZ00TLpJvzEgvvWtb/kHcNVVVyW/+tWvkt122y2ZMGFC3Ys3/vWvfyXDhw9Pdt99d8ntotyY2hqb3FBtDbXgxtS3oeTqmYVtbwi5MY0vyY2vrZIbX1s7YZhUhX5hQNxyyy3+2K3bbrut93uTJ09OFlhggWTatGl1/+a4446T3C7KjamtsckN1dZQC25MfRtKrp5Z2PaGkBvT+JLc+NoqufG1tROGSZWI3oCgUv3cc89Ndt111+Tf//53n9DQGmus4S/tkNxqyY2prbHJDdXWUAtuTH0bSq6eWdj2hpAb0/iS3PjaKrnxtbUThknVGOwiZ9CgQW7VVVd1Sy65pBs1apT/HoZRT0+PW3zxxd1LL73U+7uXXnqpW3311f1LcrsnN6a2xiY3VFs56/rJJ590G2ywgVt55ZV7Ze6www7uwx/+sHvxxRfdmDFj3vd3hx9+eFfaG5NcPbOw7Q0hN6bxJbnxtVVy42tryDWsqvSLi+Q23nhj/4BqL/WYb7753NNPP+2/vv76690uu+zSZ2BIbvfkxtTW2OSGkGkL7he/+EW/4LIo2mU69Rbchx9+OJPcUO2NTa6eWbj2hpIb0/iS3PjaKrnxtXVQwDW3ikQbgbjyyiu9NcfNgTvvvLNbdNFF3dChQ/0DtAe2/PLLuzlz5rjp06f7GwWPO+44t+WWW0pul+TG1NbY5IZqa+2Ca7Dgsjg2WnCnTJnS1GMTU9+GkqtnFra9IeTGNL4kN762Sm58be3UGlZJkgg58MADk2WXXdbf5Lf44osnH/nIR/zNfv/85z/7/N7xxx+fjB8/PllxxRWTPfbYQ3K7KDemtsYmN1Rb4YorrkjOPPPM5Oc//7m/CCddBGZ5o3vvvXdy6KGH+lxSisF4n260Nya5emZh2xtCbkzjS3Lja6vkxtfW0GtY1YnOgKC4ZYkllkgeeOCBZMaMGf7hfP3rX09WX311f034gw8+2Pu7J510kj8aa9y4cZLbRbkxtTU2uaHaGmrBjalvQ8nVMwvb3hByYxpfkhtfWyU3vrZ2wjCpOtEZEByJNWbMGD8I0px11lnJKqusknzjG99IZs2a5b935513Jvvtt5/kdlluTG2NTW6otoZacGPq21By9czCtjeE3JjGl+TG11bJja+toQ2TGIjOgPjjH//orT276jsdKrr44ouT+eabLznvvPN6v/f2229LbpflxtTW2OSGamuoBTemvg0lV88sbHtDyI1pfElufG2V3PjaGnINi4XoDIj//ve/yUorrZRstdVWvd976623er/mMo4ddthBciskN6a2xiY3VFtDLbgx9W0ouXpmYdsbQm5M40ty42ur5MbX1pBrWCxEd4zryJEj3SWXXOKeeOIJt9FGG7nXX3/dDRkypPfnH/rQh3xF/XvvvddbVS+53ZUbU1tjkxuqrZtttpmbf/753Ze//GX//5xU8fbbb/uvd911V39M3eWXX977+wsssEBX2xuTXD2zsO0NITem8SW58bVVcuNra8g1LBYqb0BceOGF7ogjjnDbb7+9u+mmm/zDXXPNNd0vf/lL98477/gzdydPnuzuv/9+N23aNPe73/3OrbPOOv7ILDs+S3I7KzemtsYmN1RbQy24MfWtnlmc7Q0hN6bxJbnxtVVy42trJ9ewaEgqzIknnpgst9xyyU477ZRsttlmyeDBg5Nrr7229yryhx9+ODnggAOSBRdcMFl66aV99fsXvvAFye2i3JjaGpvcUG2FCy64IPnWt77lT4m48cYbfTHY3LlzkylTpiTrrbdestRSS/lw7X333Zfcf//9vh1HH310v+nbUHL1zMK2N4TcmMaX5MbXVsmNr62h17BYqawBMXXq1GTkyJHJDTfc0Ps9ClDWX3/9PnlmwID4y1/+kkybNk1yuyg3prbGJjdUW0MtuDH1bSi5emZh2xtCbkzjS3Lja6vkxtfWThgmsVJJA4Lilq985SvJIYcckrz77rv+BZMnT05WWGGF5M033+y9nMP+ldzuyo2prbHJDdXWUAtuTH0bSq6eWdj2hpAb0/iS3PjaKrnxtbUThknMVLIGghyyT37yk27xxRf3OWm8gBw1jJ633nqrN0+Na8lnzpwpuV2WG1NbY5Mbqq0Ue11wwQVun332cVtssYXP04Rtt93Wvfrqq+7dd9/tzdvk39VWW81tvPHGbsyYMV1pb0xy9czCtjeE3JjGl+TG11bJja+tIdewfkESEW+88UYyevRob93BXXfd5c/gffTRRyW3onJjamtscsuQSU7nT37ykz7f40i65ZdfPnnllVd6v/fCCy94D85A6dtQcgfiMwvV3k71Q0zjS3Lja6vkVr+tnVxzY6KSEYh6YPVxRNaIESPc3LlzveVHhT2W3iqrrCK5FZQbU1tjk1uWzN1228195zvf6fO9RRdd1HtrHn30Uf//d999txs3bpz717/+VaitZbY3ZrkD9ZmFam8n+iGm8SW58bVVcuNoa6fW3NiIxoCwM3RHjx7tpk+f7nbccUe33nrruTPOOENyKyw3prbGJjeEzFALeaj2xiZXz6z6ykLM40ty42ur5MbX1pBrblQkkcFtgT09PcnYsWMlNxK5MbU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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.ticker as plticker\n", + "\n", + "\n", + "fig, (ax1, ax2) = plt.subplots(2,1, figsize=(9, 12), sharex=True)\n", + "\n", + "heat_plt = (mkt_data\n", + " .assign(treated=lambda d: d.groupby(\"city\")[\"treated\"].transform(max)) \n", + " .astype({\"date\":\"str\"})\n", + " .assign(treated=mkt_data[\"treated\"]*mkt_data[\"post\"])\n", + " .pivot(index=\"city\", columns=\"date\", values=\"treated\")\n", + " .reset_index()\n", + " .sort_values(max(mkt_data[\"date\"].astype(str)), ascending=False)\n", + " .reset_index()\n", + " .drop(columns=[\"city\"])\n", + " .rename(columns={\"index\":\"city\"})\n", + " .set_index(\"city\"))\n", + "\n", + "\n", + "sns.heatmap(heat_plt, cmap=\"gray\", linewidths=0.01, linecolor=\"0.5\", ax=ax1, cbar=False)\n", + "\n", + "ax1.set_title(\"Treatment Assignment\")\n", + "\n", + "\n", + "sns.lineplot(data=mkt_data.astype({\"date\":\"str\"}),\n", + " x=\"date\", y=\"downloads\", hue=\"treated\", ax=ax2)\n", + "\n", + "loc = plticker.MultipleLocator(base=2.0)\n", + "# ax2.xaxis.set_major_locator(loc)\n", + "ax2.vlines(\"2021-05-15\", mkt_data[\"downloads\"].min(), mkt_data[\"downloads\"].max(), color=\"black\", ls=\"dashed\", label=\"Interv.\")\n", + "ax2.set_title(\"Outcome Over Time\")\n", + "\n", + "plt.xticks(rotation = 50)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "647b569a", + "metadata": { + "ExecuteTime": { + "end_time": "2024-01-20T14:39:11.154791Z", + "start_time": "2024-01-20T14:39:11.145888Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(0.6917359536406855)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = smf.ols('downloads ~ treated*post', data=mkt_data).fit()\n", + "\n", + "m.params[\"treated:post\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "03b5b503", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DID estimate: 0.6917359536407436\n" + ] + } + ], + "source": [ + "import pyfixest as pf\n", + "\n", + "model = pf.feols(\"downloads ~ treated*post\", data=mkt_data)\n", + "\n", + "# DID 추정치 (treated:post 계수)\n", + "coef = model.coef()[\"treated:post\"]\n", + "print(\"DID estimate:\", coef)" ] } ], "metadata": { + "celltoolbar": "Tags", "kernelspec": { - "display_name": "base", + "display_name": "fack_cl", "language": "python", "name": "python3" }, @@ -64,9 +1236,51 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.7" + "version": "3.10.16" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": false + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 5 } From 7785bd95ab94b0bbb13efa465b4aa5e847e01af9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Mon, 22 Sep 2025 15:50:35 +0900 Subject: [PATCH 02/16] data: add short_offline_mkt_all_regions.csv to matheus_data --- .../short_offline_mkt_all_regions.csv | 6401 +++++++++++++++++ 1 file changed, 6401 insertions(+) create mode 100644 book/data/matheus_data/short_offline_mkt_all_regions.csv diff --git a/book/data/matheus_data/short_offline_mkt_all_regions.csv b/book/data/matheus_data/short_offline_mkt_all_regions.csv new file mode 100644 index 0000000..16be70a --- /dev/null +++ b/book/data/matheus_data/short_offline_mkt_all_regions.csv @@ -0,0 +1,6401 @@ +date,city,region,treated,tau,downloads,post +2021-05-01,1,W,0,0.0,27.0,0 +2021-05-02,1,W,0,0.0,28.0,0 +2021-05-03,1,W,0,0.0,28.0,0 +2021-05-04,1,W,0,0.0,26.0,0 +2021-05-05,1,W,0,0.0,28.0,0 +2021-05-06,1,W,0,0.0,29.0,0 +2021-05-07,1,W,0,0.0,28.0,0 +2021-05-08,1,W,0,0.0,29.0,0 +2021-05-09,1,W,0,0.0,30.0,0 +2021-05-10,1,W,0,0.0,29.0,0 +2021-05-11,1,W,0,0.0,29.0,0 +2021-05-12,1,W,0,0.0,28.0,0 +2021-05-13,1,W,0,0.0,29.0,0 +2021-05-14,1,W,0,0.0,29.0,0 +2021-05-15,1,W,0,0.0,29.0,1 +2021-05-16,1,W,0,0.0,29.0,1 +2021-05-17,1,W,0,0.0,32.0,1 +2021-05-18,1,W,0,0.0,32.0,1 +2021-05-19,1,W,0,0.0,30.0,1 +2021-05-20,1,W,0,0.0,31.0,1 +2021-05-21,1,W,0,0.0,32.0,1 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b/book/ate/did.ipynb index 9537da1..73cb8bb 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -38,6 +38,173 @@ "!pip install toolz" ] }, + { + "cell_type": "markdown", + "id": "3caf5c69", + "metadata": {}, + "source": [ + "#### 가상환경 정보" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "7da54cf1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Python 3.10.16\n" + ] + } + ], + "source": [ + "!python --version" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2958a91c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "aiohappyeyeballs==2.6.1\n", + "aiohttp==3.12.14\n", + "aiosignal==1.4.0\n", + "appnope==0.1.4\n", + "asttokens==3.0.0\n", + "async-timeout==5.0.1\n", + "attrs==25.3.0\n", + "babel==2.17.0\n", + "causalml==0.15.5\n", + "certifi==2025.7.9\n", + "cffi==2.0.0\n", + "charset-normalizer==3.4.2\n", + "citeproc-py==0.8.2\n", + "cloudpickle==3.1.1\n", + "comm==0.2.2\n", + "commonmark==0.9.1\n", + "contourpy==1.3.2\n", + "curl_cffi==0.13.0\n", + "cycler==0.12.1\n", + "debugpy==1.8.14\n", + "decorator==5.2.1\n", + "dill==0.4.0\n", + "dotenv==0.9.9\n", + "duecredit==0.10.2\n", + "econml==0.16.0\n", + "exceptiongroup==1.3.0\n", + "executing==2.2.0\n", + "faicons==0.2.2\n", + "filelock==3.18.0\n", + "fonttools==4.58.5\n", + "forestci==0.6\n", + "formulaic==1.2.0\n", + "frozenlist==1.7.0\n", + "fsspec==2025.7.0\n", + "graphviz==0.21\n", + "great-tables==0.18.0\n", + "hf-xet==1.1.5\n", + "htmltools==0.6.0\n", + "huggingface-hub==0.34.1\n", + "idna==3.10\n", + "importlib_metadata==8.7.0\n", + "importlib_resources==6.5.2\n", + "interface-meta==1.3.0\n", + "ipykernel==6.29.5\n", + "ipython==8.37.0\n", + "jedi==0.19.2\n", + "joblib==1.5.1\n", + "jupyter_client==8.6.3\n", + "jupyter_core==5.8.1\n", + "kiwisolver==1.4.8\n", + "lightgbm==4.6.0\n", + "llvmlite==0.44.0\n", + "looseversion==1.3.0\n", + "lxml==6.0.0\n", + "matplotlib==3.10.3\n", + "matplotlib-inline==0.1.7\n", + "multidict==6.6.3\n", + "multiprocess==0.70.18\n", + "narwhals==2.5.0\n", + "nest-asyncio==1.6.0\n", + "numba==0.61.2\n", + "numpy==2.2.6\n", + "packaging==25.0\n", + "pandas==2.3.1\n", + "pandas-datareader==0.10.0\n", + "parso==0.8.4\n", + "pathos==0.2.9\n", + "patsy==1.0.1\n", + "pexpect==4.9.0\n", + "pillow==11.3.0\n", + "platformdirs==4.3.8\n", + "pox==0.3.6\n", + "ppft==1.7.7\n", + "prompt_toolkit==3.0.51\n", + "propcache==0.3.2\n", + "psutil==7.0.0\n", + "psycopg2-binary==2.9.10\n", + "ptyprocess==0.7.0\n", + "pure_eval==0.2.3\n", + "pyarrow==21.0.0\n", + "pycparser==2.23\n", + "pydotplus==2.0.2\n", + "pyfixest==0.30.2\n", + "Pygments==2.19.2\n", + "pyparsing==3.2.3\n", + "python-dateutil==2.9.0.post0\n", + "python-dotenv==1.1.1\n", + "pytz==2025.2\n", + "PyYAML==6.0.2\n", + "pyzmq==27.0.0\n", + "requests==2.32.4\n", + "scikit-learn==1.6.1\n", + "scipy==1.15.3\n", + "seaborn==0.13.2\n", + "shap==0.48.0\n", + "six==1.17.0\n", + "slicer==0.0.8\n", + "sparse==0.17.0\n", + "SQLAlchemy==2.0.43\n", + "stack-data==0.6.3\n", + "statsmodels==0.14.5\n", + "tabulate==0.9.0\n", + "threadpoolctl==3.6.0\n", + "tidyfinance==0.1.2\n", + "toolz==1.0.0\n", + "tornado==6.5.1\n", + "tqdm==4.67.1\n", + "traitlets==5.14.3\n", + "typing_extensions==4.14.1\n", + "tzdata==2025.2\n", + "urllib3==2.5.0\n", + "wcwidth==0.2.13\n", + "wrapt==1.17.3\n", + "xgboost==3.0.2\n", + "yarl==1.20.1\n", + "zipp==3.23.0\n" + ] + } + ], + "source": [ + "!pip freeze" + ] + }, + { + "cell_type": "markdown", + "id": "ddc5fa7d", + "metadata": {}, + "source": [ + "아래 tidyfinace패키지는 파이썬 3.10 이상의 환경에서 설치됩니다!" + ] + }, { "cell_type": "code", "execution_count": 12, @@ -259,7 +426,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "d17c7963", "metadata": { "ExecuteTime": { @@ -371,7 +538,7 @@ "import pandas as pd\n", "import numpy as np\n", "\n", - "mkt_data = (pd.read_csv(\"./data/short_offline_mkt_south.csv\")\n", + "mkt_data = (pd.read_csv(\"../data/matheus_data/short_offline_mkt_south.csv\")\n", " .astype({\"date\":\"datetime64[ns]\"}))\n", "\n", "mkt_data.head()" diff --git a/book/data/.DS_Store b/book/data/.DS_Store index 1be12a16a635bdbc83a6328c2420b50f540bd9aa..1c4021c3a90ecc18c79b41ca29ae526336de2a67 100644 GIT binary patch delta 183 zcmZp1XmQvuU5N3}+KeWQwv6_S9*mxhQH=47 v350xF|0tKQA39$+)>&rjmJL1J7o5iNEXs4E-fL delta 189 zcmZp1XmQvuU5N4Q&a6s}7vL|>$S?N Date: Sat, 27 Sep 2025 20:52:56 +0900 Subject: [PATCH 05/16] week2 did --- book/ate/did.ipynb | 1672 ++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 1632 insertions(+), 40 deletions(-) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index 73cb8bb..a619f55 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -380,17 +380,17 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 8, "id": "2c650ac3", "metadata": {}, "outputs": [], "source": [ - "import pyfixest as pf" + "import pyfixest as pf\n" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 9, "id": "a6d9bc21", "metadata": { "ExecuteTime": { @@ -529,7 +529,7 @@ "4 2021-05-05 5 S 0 0.0 49.0 0" ] }, - "execution_count": 3, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -539,7 +539,10 @@ "import numpy as np\n", "\n", "mkt_data = (pd.read_csv(\"../data/matheus_data/short_offline_mkt_south.csv\")\n", - " .astype({\"date\":\"datetime64[ns]\"}))\n", + " .astype({\"date\":\"datetime64[ns]\"}))\n", + "\n", + "\n", + "\n", "\n", "mkt_data.head()" ] @@ -554,7 +557,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 16, "id": "3d6cdba1", "metadata": { "ExecuteTime": { @@ -567,9 +570,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_14638/2583971365.py:4: FutureWarning: The provided callable is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"min\" instead.\n", + "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_21522/2583971365.py:4: FutureWarning: The provided callable is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"min\" instead.\n", " .agg({\"date\":[min, max]}))\n", - "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_14638/2583971365.py:4: FutureWarning: The provided callable is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n", + "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_21522/2583971365.py:4: FutureWarning: The provided callable is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n", " .agg({\"date\":[min, max]}))\n" ] }, @@ -634,7 +637,7 @@ "1 2021-05-15 2021-06-01" ] }, - "execution_count": 4, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -648,7 +651,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 17, "id": "355d9c2c", "metadata": { "ExecuteTime": { @@ -725,7 +728,7 @@ " 1 51.858025 2021-05-15" ] }, - "execution_count": 33, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -762,7 +765,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 18, "id": "79bcb7fe", "metadata": { "ExecuteTime": { @@ -777,7 +780,7 @@ "np.float64(0.6917359536407233)" ] }, - "execution_count": 34, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -793,7 +796,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 19, "id": "b51d6822", "metadata": { "ExecuteTime": { @@ -808,7 +811,7 @@ "np.float64(0.7660316402518457)" ] }, - "execution_count": 35, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -827,7 +830,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 20, "id": "10e16d8d", "metadata": { "ExecuteTime": { @@ -906,7 +909,7 @@ "197 1.595238 1" ] }, - "execution_count": 36, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -926,7 +929,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 21, "id": "31be6542", "metadata": { "ExecuteTime": { @@ -941,7 +944,7 @@ "np.float64(0.6917359536407155)" ] }, - "execution_count": 37, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -961,7 +964,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 22, "id": "ff0261df", "metadata": { "ExecuteTime": { @@ -976,10 +979,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 38, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, @@ -1031,7 +1034,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 23, "id": "bead249f", "metadata": { "ExecuteTime": { @@ -1123,7 +1126,7 @@ "4 20 0 48.785714 2021-05-01 0" ] }, - "execution_count": 39, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1145,18 +1148,18 @@ " `statsmodels`와 `pyfixest`\n", "\n", "DID 분석을 회귀 모형으로 구현할 때,\n", - "- **statsmodels (smf)** 은 파이썬에서 가장 널리 쓰이는 범용 회귀 패키지라 기본 구현을 설명하기에 적합하다. \n", - "- 그러나 DID는 본질적으로 **패널 데이터 + 고정효과(FE) + 클러스터 표준오차**가 중요하다. \n", - " 이를 편리하게 지원하는 패키지가 바로 **pyfixest**이다.\n", + "- **statsmodels (smf)** 은 파이썬에서 가장 널리 쓰이는 범용 회귀 패키지라 기본 구현을 설명하기에 적합합니다. \n", + "- 그러나 DID는 본질적으로 **패널 데이터 + 고정효과(FE) + 클러스터 표준오차**가 중요합니다. \n", + " 이를 편리하게 지원하는 패키지가 바로 **pyfixest**입니다.\n", "\n", "따라서 \n", "- statsmodels로는 DID의 기본 원리를 쉽게 보여줄 수 있고, \n", - "- pyfixest로는 실제 실증연구에서 사용하는 **FE-DID, TWFE, robust SE**를 더 직관적으로 구현할 수 있다." + "- pyfixest로는 실제 실증연구에서 사용하는 **FE-DID, TWFE, robust SE**를 더 직관적으로 구현할 수 있습니다." ] }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 24, "id": "54757217", "metadata": { "ExecuteTime": { @@ -1171,7 +1174,7 @@ "np.float64(0.6917359536407082)" ] }, - "execution_count": 40, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1186,7 +1189,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 25, "id": "463a35ef", "metadata": {}, "outputs": [ @@ -1214,13 +1217,13 @@ "metadata": {}, "source": [ "### 블록디자인을 바탕으로 한 이중차분법\n", - "- DID를 추정할때 처치 전후로 각 값들을 그룹화하여 하지 않고 각 시점의 데이터를 모두 활용하는 방법\n", - "- 사전 평행 추세를 검정할 수 있다는 장점이 있음\n" + "- DID를 추정할때 처치 전후로 각 값들을 그룹화하여 하지 않고 각 시점의 데이터를 모두 활용하는 방법과\n", + "- 사전 평행 추세를 검정할 수 있다는 장점이 있습니다.\n" ] }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 26, "id": "d1eed2c4", "metadata": { "ExecuteTime": { @@ -1236,7 +1239,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_14638/2621860921.py:7: FutureWarning: The provided callable is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n", + "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_21522/2621860921.py:7: FutureWarning: The provided callable is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n", " .assign(treated=lambda d: d.groupby(\"city\")[\"treated\"].transform(max))\n", "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", @@ -1283,13 +1286,13 @@ " Text(31.5, 0, '2021-06-01')])" ] }, - "execution_count": 41, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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datecityregiontreatedtaudownloadspost
02021-05-015S00.00000051.00
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........................
16272021-05-28197S11.77123353.01
16282021-05-29197S11.77123352.01
16292021-05-30197S11.77123354.01
16302021-05-31197S11.77123353.01
16312021-06-01197S11.77123355.01
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1632 rows × 7 columns

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" + ], + "text/plain": [ + " date city region treated tau downloads post\n", + "0 2021-05-01 5 S 0 0.000000 51.0 0\n", + "1 2021-05-02 5 S 0 0.000000 51.0 0\n", + "2 2021-05-03 5 S 0 0.000000 51.0 0\n", + "3 2021-05-04 5 S 0 0.000000 50.0 0\n", + "4 2021-05-05 5 S 0 0.000000 49.0 0\n", + "... ... ... ... ... ... ... ...\n", + "1627 2021-05-28 197 S 1 1.771233 53.0 1\n", + "1628 2021-05-29 197 S 1 1.771233 52.0 1\n", + "1629 2021-05-30 197 S 1 1.771233 54.0 1\n", + "1630 2021-05-31 197 S 1 1.771233 53.0 1\n", + "1631 2021-06-01 197 S 1 1.771233 55.0 1\n", + "\n", + "[1632 rows x 7 columns]" + ] + }, + "execution_count": 92, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mkt_data" + ] + }, + { + "cell_type": "markdown", + "id": "f19bdff0", + "metadata": {}, + "source": [ + "### Basic DID" + ] + }, + { + "cell_type": "code", + "execution_count": 27, "id": "647b569a", "metadata": { "ExecuteTime": { @@ -1350,7 +1539,7 @@ "np.float64(0.6917359536406855)" ] }, - "execution_count": 42, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -1363,7 +1552,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 28, "id": "03b5b503", "metadata": {}, "outputs": [ @@ -1384,6 +1573,1409 @@ "coef = model.coef()[\"treated:post\"]\n", "print(\"DID estimate:\", coef)" ] + }, + { + "cell_type": "markdown", + "id": "83f05570", + "metadata": {}, + "source": [ + "#### 추론" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "fe572c5d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 0.6917359536407082\n" + ] + }, + { + "data": { + "text/plain": [ + "0 0.300318\n", + "1 1.083154\n", + "Name: treated:post, dtype: float64" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = smf.ols(\n", + " 'downloads ~ treated*post', data=did_data\n", + ").fit(cov_type='cluster', cov_kwds={'groups': did_data['city']})\n", + "\n", + "print(\"ATT:\", m.params[\"treated:post\"])\n", + "m.conf_int().loc[\"treated:post\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "e1157b02", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 0.6917359536407451\n", + "2.5% 0.290613\n", + "97.5% 1.092859\n", + "Name: treated:post, dtype: float64\n" + ] + } + ], + "source": [ + "import pyfixest as pf\n", + "\n", + "m = pf.feols(\n", + " \"downloads ~ treated*post\",\n", + " vcov={\"CRV1\": \"city\"}, # 클러스터 표준오차: city 단위\n", + " data=did_data\n", + ")\n", + "\n", + "print(\"ATT:\", m.coef()[\"treated:post\"])\n", + "print(m.confint().loc[\"treated:post\"])" + ] + }, + { + "cell_type": "markdown", + "id": "a745a402", + "metadata": {}, + "source": [ + "### 2WFE did " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "f80b7263", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DID estimate: 0.6917359536407248\n" + ] + } + ], + "source": [ + "m = smf.ols('downloads ~ treated:post + C(city) + C(date)',\n", + " data=mkt_data).fit()\n", + "\n", + "coef=m.params[\"treated:post\"]\n", + "\n", + "print(\"DID estimate:\", coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "6c2d3cb6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DID estimate: 0.6917359536407154\n" + ] + } + ], + "source": [ + "import pyfixest as pf\n", + "\n", + "# pyfixest의 feols 함수 사용\n", + "m = pf.feols(\"downloads ~ treated:post | city + date\", data=mkt_data)\n", + "\n", + "# 계수 확인\n", + "coef=m.coef()[\"treated:post\"]\n", + "print(\"DID estimate:\", coef)" + ] + }, + { + "cell_type": "markdown", + "id": "364d13bd", + "metadata": {}, + "source": [ + "#### 추론" + ] + }, + { + "cell_type": "markdown", + "id": "03fa6aea", + "metadata": {}, + "source": [ + "##### 1. 실험 대상과 처치 전후 기간별 집계한 데이터 기반 추론" + ] + }, + { + "cell_type": "markdown", + "id": "0a47e10f", + "metadata": {}, + "source": [ + "기존 표준 오차 기반" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "0f3be3b1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 0.6917359536407064\n" + ] + }, + { + "data": { + "text/plain": [ + "0 0.409916\n", + "1 0.973556\n", + "Name: treated:post, dtype: float64" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = smf.ols('downloads ~ treated:post + C(city) + C(date)',\n", + " data=did_data).fit()\n", + "\n", + "print(\"ATT:\", m.params[\"treated:post\"])\n", + "m.conf_int().loc[\"treated:post\"]" + ] + }, + { + "cell_type": "markdown", + "id": "060ae0ae", + "metadata": {}, + "source": [ + "군집 표준 오차 기반" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "9c0290e8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 0.6917359536407064\n" + ] + }, + { + "data": { + "text/plain": [ + "0 0.138188\n", + "1 1.245284\n", + "Name: treated:post, dtype: float64" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = smf.ols(\n", + " 'downloads ~ treated:post + C(city) + C(date)', data=did_data\n", + ").fit(cov_type='cluster', cov_kwds={'groups': did_data['city']})\n", + "\n", + "print(\"ATT:\", m.params[\"treated:post\"])\n", + "m.conf_int().loc[\"treated:post\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "7a80adcb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 0.6917359536406991\n", + "2.5% 0.124463\n", + "97.5% 1.259009\n", + "Name: treated:post, dtype: float64\n" + ] + } + ], + "source": [ + "import pyfixest as pf\n", + "\n", + "m = pf.feols(\n", + " \"downloads ~ treated:post + C(city) + C(date)\",\n", + " vcov={\"CRV1\": \"city\"}, # 클러스터 표준오차: city 단위\n", + " data=did_data\n", + ")\n", + "\n", + "print(\"ATT:\", m.coef()[\"treated:post\"])\n", + "print(m.confint().loc[\"treated:post\"])" + ] + }, + { + "cell_type": "markdown", + "id": "919ba418", + "metadata": {}, + "source": [ + "##### 2. 일별로 집계한 데이터" + ] + }, + { + "cell_type": "markdown", + "id": "feca1d75", + "metadata": {}, + "source": [ + "기존 표준오차 기반" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "83d3cfda", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 0.6917359536407248\n" + ] + }, + { + "data": { + "text/plain": [ + "0 0.478014\n", + "1 0.905457\n", + "Name: treated:post, dtype: float64" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = smf.ols('downloads ~ treated:post + C(city) + C(date)',\n", + " data=mkt_data).fit()\n", + "\n", + "print(\"ATT:\", m.params[\"treated:post\"])\n", + "m.conf_int().loc[\"treated:post\"]" + ] + }, + { + "cell_type": "markdown", + "id": "4e4d7046", + "metadata": {}, + "source": [ + "군집 표준 오차 기반" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "edd9ec8e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 0.6917359536407248\n" + ] + }, + { + "data": { + "text/plain": [ + "0 0.296101\n", + "1 1.087370\n", + "Name: treated:post, dtype: float64" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = smf.ols(\n", + " 'downloads ~ treated:post + C(city) + C(date)', data=mkt_data\n", + ").fit(cov_type='cluster', cov_kwds={'groups': mkt_data['city']})\n", + "\n", + "print(\"ATT:\", m.params[\"treated:post\"])\n", + "m.conf_int().loc[\"treated:post\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "c92fca81", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 0.6917359536407385\n", + "2.5% 0.286292\n", + "97.5% 1.097180\n", + "Name: treated:post, dtype: float64\n" + ] + } + ], + "source": [ + "import pyfixest as pf\n", + "\n", + "m = pf.feols(\n", + " \"downloads ~ treated:post + C(city) + C(date)\",\n", + " vcov={\"CRV1\": \"city\"}, # 클러스터 표준오차: city 단위\n", + " data=mkt_data\n", + ")\n", + "\n", + "print(\"ATT:\", m.coef()[\"treated:post\"])\n", + "print(m.confint().loc[\"treated:post\"])" + ] + }, + { + "cell_type": "markdown", + "id": "013fd5ae", + "metadata": {}, + "source": [ + "### DID with covariates" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "95d777fa", + "metadata": {}, + "outputs": [], + "source": [ + "mkt_data_all = (pd.read_csv(\"../data/matheus_data/short_offline_mkt_all_regions.csv\")\n", + " .astype({\"date\":\"datetime64[ns]\"}))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9f347bae", + "metadata": {}, + "outputs": [ + { + "data": { + 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(15,6))\n", + "sns.lineplot(data=mkt_data_all.groupby([\"date\", \"region\", \"treated\"])[[\"downloads\"]].mean().reset_index(),\n", + " x=\"date\", y=\"downloads\", hue=\"region\", style=\"treated\", palette=\"gray\")\n", + "\n", + "plt.vlines(pd.to_datetime(\"2021-05-15\"), 15, 55, ls=\"dotted\", label=\"Intervention\")\n", + "plt.legend(fontsize=14)\n", + "\n", + "plt.xticks(rotation=25)" + ] + }, + { + "cell_type": "markdown", + "id": "482abc10", + "metadata": {}, + "source": [ + "처치 이전 추세의 경우 지역내에서는 평행하지만 지역 간에는 평행하지 않은 것으로 보입니다. 이러한 상황해서 단순히 이원고정효과모델을 적용하면 ATT에 대해 편향된 추정값을 얻게되죠. \n", + "\n", + "따라서 이 문제를 해결하기 위해선 각 지역별로 서로 다른 추세가 있다는 것을 반드시 고려해야합니다. \n", + "\n", + "그럼 어떻게 지역별로 서로 다른 추세가 있다는 것을 모델에 반영할 수 있을까요? 바로 모델에 처치전의 공변량(covariates)을 포함하는 것입니다. \n", + "\n", + "공변량을 모델에 반영하여 ATT추정하는 방법은 대표적으로 2가지 방법이 있습니다. \n", + "\n", + "\n", + "1. 각 지역별로 별도의 DID 회귀 모델 적용하고 ATT 가중평균하여 구하기\n", + "\n", + "2. 지역 변수와 처치 후 더미 변수와 상호작용하기\n" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "id": "71afe601", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True ATT: 1.7208921056102682\n" + ] + } + ], + "source": [ + "print(\"True ATT: \", mkt_data_all.query(\"treated*post==1\")[\"tau\"].mean())" + ] + }, + { + "cell_type": "markdown", + "id": "cc2d5fad", + "metadata": {}, + "source": [ + "##### 1. 각 지역별로 별도의 DID 회귀 모델 적용하고 ATT 가중평균($\\hat\\theta=\\sum_r w_r \\widehat{ATT}_r$)하여 구하기" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "0f035c0d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "post:treated 1.676808\n", + "post:treated:C(region)[T.N] -0.343667\n", + "post:treated:C(region)[T.S] -0.985072\n", + "post:treated:C(region)[T.W] 1.369363\n", + "dtype: float64" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m_saturated = smf.ols('downloads ~ (post*treated)*C(region)',\n", + " data=mkt_data_all).fit()\n", + "\n", + "atts = m_saturated.params[m_saturated.params.index.str.contains(\"post:treated\")]\n", + "atts" + ] + }, + { + "cell_type": "markdown", + "id": "1912a034", + "metadata": {}, + "source": [ + "##### 추정" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b88f37a8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Weighted ATT: 1.6940400451471986\n", + "95% CI: (np.float64(1.3897593237876618), np.float64(1.9983207665067355))\n" + ] + } + ], + "source": [ + "\n", + "import statsmodels.api as sm\n", + "from scipy.stats import norm\n", + "\n", + "# (1) region size (가중치 계산)\n", + "reg_size = (mkt_data_all.groupby(\"region\").size()\n", + " / len(mkt_data_all[\"date\"].unique()))\n", + "\n", + "# (2) saturated DID 결과 계수\n", + "atts = m_saturated.params[m_saturated.params.index.str.contains(\"post:treated\")]\n", + "cov = m_saturated.cov_params() # 분산-공분산 행렬\n", + "\n", + "# (3) base (= region baseline ATT, 보통 첫 지역)\n", + "base = atts.iloc[0]\n", + "\n", + "# (4) 선형 조합 벡터 만들기\n", + "weights = [reg_size.iloc[0]] + list(reg_size.iloc[1:])\n", + "coefs = [base] + list(atts.iloc[1:] + base)\n", + "\n", + "theta = np.dot(weights, coefs) / reg_size.sum()\n", + "\n", + "# (5) 대응되는 선형 조합 벡터 정의 (계수 개수만큼)\n", + "# 인덱스 맞추기\n", + "att_idx = atts.index\n", + "w = np.zeros(len(m_saturated.params))\n", + "\n", + "# baseline\n", + "w[m_saturated.params.index.get_loc(att_idx[0])] = reg_size.iloc[0]\n", + "\n", + "# 나머지 region 효과들\n", + "for att_name, size in zip(att_idx[1:], reg_size.iloc[1:]):\n", + " w[m_saturated.params.index.get_loc(att_idx[0])] += size # baseline part\n", + " w[m_saturated.params.index.get_loc(att_name)] += size # interaction part\n", + "\n", + "# normalize\n", + "w = w / reg_size.sum()\n", + "\n", + "# (6) 분산 계산\n", + "theta_var = w @ cov @ w\n", + "theta_se = np.sqrt(theta_var)\n", + "\n", + "# (7) 신뢰구간\n", + "alpha = 0.05\n", + "z = norm.ppf(1 - alpha/2)\n", + "\n", + "ci_lower = theta - z * theta_se\n", + "ci_upper = theta + z * theta_se\n", + "\n", + "print(\"Weighted ATT:\", theta)\n", + "print(\"95% CI:\", (ci_lower, ci_upper))" + ] + }, + { + "cell_type": "markdown", + "id": "c68f80ea", + "metadata": {}, + "source": [ + "##### 2. 지역변수와 처치 후 더미변수와 상호작용하기" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "e93ea8d4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "
coef std err t P>|t| [0.025 0.975]
Intercept 17.3522 0.101 172.218 0.000 17.155 17.550
C(region)[T.N] 26.2770 0.137 191.739 0.000 26.008 26.546
C(region)[T.S] 33.0815 0.135 245.772 0.000 32.818 33.345
C(region)[T.W] 10.7118 0.135 79.581 0.000 10.448 10.976
post 4.9807 0.134 37.074 0.000 4.717 5.244
post:C(region)[T.N] -3.3458 0.183 -18.310 0.000 -3.704 -2.988
post:C(region)[T.S] -4.9334 0.179 -27.489 0.000 -5.285 -4.582
post:C(region)[T.W] -1.5408 0.179 -8.585 0.000 -1.893 -1.189
treated 0.0503 0.117 0.429 0.668 -0.179 0.280
post:treated 1.6811 0.156 10.758 0.000 1.375 1.987
" + ], + "text/latex": [ + "\\begin{center}\n", + "\\begin{tabular}{lcccccc}\n", + "\\toprule\n", + " & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]} \\\\\n", + "\\midrule\n", + "\\textbf{Intercept} & 17.3522 & 0.101 & 172.218 & 0.000 & 17.155 & 17.550 \\\\\n", + "\\textbf{C(region)[T.N]} & 26.2770 & 0.137 & 191.739 & 0.000 & 26.008 & 26.546 \\\\\n", + "\\textbf{C(region)[T.S]} & 33.0815 & 0.135 & 245.772 & 0.000 & 32.818 & 33.345 \\\\\n", + "\\textbf{C(region)[T.W]} & 10.7118 & 0.135 & 79.581 & 0.000 & 10.448 & 10.976 \\\\\n", + "\\textbf{post} & 4.9807 & 0.134 & 37.074 & 0.000 & 4.717 & 5.244 \\\\\n", + "\\textbf{post:C(region)[T.N]} & -3.3458 & 0.183 & -18.310 & 0.000 & -3.704 & -2.988 \\\\\n", + "\\textbf{post:C(region)[T.S]} & -4.9334 & 0.179 & -27.489 & 0.000 & -5.285 & -4.582 \\\\\n", + "\\textbf{post:C(region)[T.W]} & -1.5408 & 0.179 & -8.585 & 0.000 & -1.893 & -1.189 \\\\\n", + "\\textbf{treated} & 0.0503 & 0.117 & 0.429 & 0.668 & -0.179 & 0.280 \\\\\n", + "\\textbf{post:treated} & 1.6811 & 0.156 & 10.758 & 0.000 & 1.375 & 1.987 \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\\end{center}" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = smf.ols('downloads ~ post*(treated + C(region))',\n", + " data=mkt_data_all).fit()\n", + "\n", + "m.summary().tables[1]\n" + ] + }, + { + "cell_type": "markdown", + "id": "a927a7cb", + "metadata": {}, + "source": [ + "post:treated에 대한 매개 변수를 ATT로 해석합니다. " + ] + }, + { + "cell_type": "markdown", + "id": "c8eb1318", + "metadata": {}, + "source": [ + "##### 추정" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "743398c6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 1.6810982546487103\n" + ] + }, + { + "data": { + "text/plain": [ + "0 1.374772\n", + "1 1.987424\n", + "Name: post:treated, dtype: float64" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(\"ATT:\", m.params[\"post:treated\"])\n", + "m.conf_int().loc[\"post:treated\"]" + ] + }, + { + "cell_type": "markdown", + "id": "0b985fca", + "metadata": {}, + "source": [ + "#### DML을 이용한 DID" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "c001b25c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting doubleml\n", + " Downloading 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[], + "source": [ + "\n", + "from doubleml import DoubleMLData, DoubleMLDID\n", + "from lightgbm import LGBMClassifier, LGBMRegressor" + ] + }, + { + "cell_type": "markdown", + "id": "3d522a65", + "metadata": {}, + "source": [ + " Data 생성" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "723b9832", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "from doubleml import DoubleMLData, DoubleMLDID\n", + "from lightgbm import LGBMRegressor, LGBMClassifier\n", + "\n", + "\n", + "\n", + "def make_custom_did(n_obs=1000, n_time_periods=5, seed=None):\n", + " if seed is not None:\n", + " np.random.seed(seed)\n", + "\n", + " time_periods = (np.arange(2*n_time_periods) - n_time_periods)\n", + "\n", + " # fixed effects\n", + " theta = np.zeros(shape=(n_obs, 2*n_time_periods)) + time_periods\n", + " eta = np.random.normal(loc=0, scale=1, size=(n_obs,1))\n", + "\n", + " # covariates\n", + " X = np.random.normal(loc=0, scale=1, size=(n_obs, 4, 2*n_time_periods))\n", + "\n", + " # treatment effects\n", + " mu_means = np.concatenate((np.zeros(n_time_periods), np.arange(n_time_periods, 0, -1)))\n", + " mu = np.random.normal(loc=0, scale=1, size=(n_obs, 2*n_time_periods)) + mu_means\n", + "\n", + " # treatment assignment\n", + " f_ps = 0.75*(-X[:, 0, 0] + 0.5*X[:, 1, 0] - 0.25*X[:, 2, 0] \n", + " - 0.1*X[:, 3, 0]*X[:, 2, 0] + np.cos(5*X[:, 1, 0]))\n", + " ps = (np.exp(f_ps) / (1 + np.exp(f_ps))).reshape(-1,1)\n", + " u = np.random.uniform(low=0, high=1, size=(n_obs,1))\n", + " treatment = np.ones(shape=(n_obs, 2*n_time_periods)) * (ps >= u)\n", + "\n", + " # outcome\n", + " g_X = (np.exp(X[:, 1, :]) - np.sin(5*X[:, 2, :]) + 2*X[:, 3, :])\n", + " epsilon = np.random.normal(loc=0, scale=1, size=(n_obs, 2*n_time_periods))\n", + " Y = theta + eta + treatment*mu + g_X + epsilon\n", + "\n", + " # reshape to long format\n", + " Y_df = Y.reshape(-1)\n", + " d_df = treatment.reshape(-1)\n", + " t_df = np.tile(time_periods, n_obs)\n", + " i_df = np.repeat(np.arange(n_obs), 2*n_time_periods)\n", + " X_df = X.transpose(0,2,1).reshape(-1, 4)\n", + "\n", + " data = pd.DataFrame({\n", + " 'y': Y_df,\n", + " 'd': d_df,\n", + " 't': t_df,\n", + " 'i': i_df,\n", + " 'X0': X_df[:,0],\n", + " 'X1': X_df[:,1],\n", + " 'X2': X_df[:,2],\n", + " 'X3': X_df[:,3]\n", + " })\n", + " \n", + " # True ATT = 사후 기간 효과 평균\n", + " true_att = mu_means[n_time_periods:].mean()\n", + " \n", + " return data, true_att,mu_means\n", + "\n", + "def did_to_dml_format(data):\n", + " \"\"\"\n", + " make_custom_did()에서 생성된 long-format DataFrame -> DoubleMLDID용 데이터 변환\n", + " \"\"\"\n", + "\n", + " # 사전(pre, t<0), 사후(post, t>=0) 구분\n", + " pre = data[data['t'] < 0]\n", + " post = data[data['t'] >= 0]\n", + "\n", + " # (1) outcome: 개체별 (post 평균 - pre 평균)\n", + " y_diff = post.groupby('i')['y'].mean().values - pre.groupby('i')['y'].mean().values\n", + "\n", + " # (2) treatment: 개체별 사후처치 여부 (post에서 하나만 뽑으면 됨)\n", + " d = post.groupby('i')['d'].first().astype(int).values\n", + "\n", + " # (3) covariates: 개체별 pre-treatment covariates (t<0에서 첫 번째 시점 사용)\n", + " x = pre.groupby('i')[['X0', 'X1', 'X2', 'X3']].first().values\n", + "\n", + " # DoubleMLData 입력용\n", + " dml_data = DoubleMLData.from_arrays(x=x, y=y_diff, d=d)\n", + "\n", + " return dml_data\n", + "\n", + "\n", + "\n", + "data, true_att,_ = make_custom_did(n_obs=1000, n_time_periods=5, seed=42)\n", + "\n", + "dml_data = did_to_dml_format(data)" + ] + }, + { + "cell_type": "markdown", + "id": "dc414e35", + "metadata": {}, + "source": [ + "Learners 설정\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3b6d7828", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================== DoubleMLData Object ==================\n", + "\n", + "------------------ Data summary ------------------\n", + "Outcome variable: y\n", + "Treatment variable(s): ['d']\n", + "Covariates: ['X1', 'X2', 'X3', 'X4']\n", + "Instrument variable(s): None\n", + "No. Observations: 1000\n", + "\n", + "------------------ DataFrame info ------------------\n", + "\n", + "RangeIndex: 1000 entries, 0 to 999\n", + "Columns: 6 entries, X1 to d\n", + "dtypes: float64(6)\n", + "memory usage: 47.0 KB\n", + "\n", + "ATT estimate: [3.05836115]\n", + " 2.5 % 97.5 %\n", + "d 2.768038 3.348684\n" + ] + } + ], + "source": [ + "\n", + "ml_g = LGBMRegressor(n_estimators=50, num_leaves=5, verbose=-1)\n", + "ml_m = LGBMClassifier(n_estimators=50, num_leaves=5, verbose=-1)\n" + ] + }, + { + "cell_type": "markdown", + "id": "0f1d1714", + "metadata": {}, + "source": [ + "DoubleMLDID 추정" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "12081d6e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT estimate: [3.1189311]\n", + " 2.5 % 97.5 %\n", + "d 2.822394 3.415468\n" + ] + } + ], + "source": [ + "\n", + "dml_did = DoubleMLDID(dml_data,\n", + " ml_g=ml_g,\n", + " ml_m=ml_m,\n", + " score='observational',\n", + " n_folds=5)\n", + "dml_did.fit()\n", + "\n", + "print(\"ATT estimate:\", dml_did.coef)\n", + "print(dml_did.confint(level=0.95))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "23cde0a4", + "metadata": {}, + "source": [ + "Coverage 시뮬레이션" + ] + }, + { + "cell_type": "code", + "execution_count": 216, + "id": "e68e211d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration: 0/200\n", + "Iteration: 20/200\n", + "Iteration: 40/200\n", + "Iteration: 60/200\n", + "Iteration: 80/200\n", + "Iteration: 100/200\n", + "Iteration: 120/200\n", + "Iteration: 140/200\n", + "Iteration: 160/200\n", + "Iteration: 180/200\n", + "results from coverage simulation:\n", + "True ATT: 3.0\n", + "Estimated ATT: 2.991261797700492\n", + "Coverage: 0.91\n", + "Average CI length: 0.6293062710727478\n" + ] + } + ], + "source": [ + "\n", + "\n", + "n_rep = 200\n", + "ATTE_estimates = np.full((n_rep), np.nan)\n", + "coverage = np.full((n_rep), np.nan)\n", + "ci_length = np.full((n_rep), np.nan)\n", + "\n", + "for i_rep in range(n_rep):\n", + " if (i_rep % int(n_rep/10)) == 0:\n", + " print(f'Iteration: {i_rep}/{n_rep}')\n", + " \n", + " data, true_att,_ = make_custom_did(n_obs=1000, n_time_periods=5, seed=i_rep)\n", + "\n", + " dml_data = did_to_dml_format(data)\n", + " \n", + " \n", + " dml_did = DoubleMLDID(dml_data, ml_g=ml_g, ml_m=ml_m, n_folds=5)\n", + " dml_did.fit()\n", + "\n", + " ATTE_estimates[i_rep] = dml_did.coef.squeeze()\n", + " confint = dml_did.confint(level=0.95)\n", + " coverage[i_rep] = (confint['2.5 %'].iloc[0] <= true_att) & (true_att <= confint['97.5 %'].iloc[0])\n", + " ci_length[i_rep] = confint['97.5 %'].iloc[0] - confint['2.5 %'].iloc[0]\n", + "\n", + "\n", + " \n", + "print(\"results from coverage simulation:\")\n", + "print(f'True ATT: {true_att}')\n", + "print(f'Estimated ATT: {np.mean(ATTE_estimates)}')\n", + "print(f'Coverage: {coverage.mean()}')\n", + "print(f'Average CI length: {ci_length.mean()}')" + ] + }, + { + "cell_type": "code", + "execution_count": 215, + "id": "052565b9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "results from coverage simulation:\n", + "True ATT: 3.0\n", + "Estimated ATT: 2.991261797700492\n", + "Coverage: 0.91\n", + "Average CI length: 0.6293062710727478\n" + ] + } + ], + "source": [ + "print(\"results from coverage simulation:\")\n", + "print(f'True ATT: {true_att}')\n", + "print(f'Estimated ATT: {np.mean(ATTE_estimates)}')\n", + "print(f'Coverage: {coverage.mean()}')\n", + "print(f'Average CI length: {ci_length.mean()}')" + ] + }, + { + "cell_type": "markdown", + "id": "124d75b8", + "metadata": {}, + "source": [ + "본 시뮬레이션에서 설정된 진짜 ATT는 3.0이며, DoubleML-DID 추정량의 평균은 2.99로 거의 일치했습니다.\n", + "\n", + "또한, 95% 신뢰구간의 coverage는 약 91%로 나타났습니다. \n", + "\n", + "이는 신뢰구간이 다소 좁아 실제 모수를 포함하는 비율이 목표치(95%)보다 약간 낮다는 것을 의미합니다. \n", + "\n", + "즉, 추정이 다소 과신(overconfident) 되는 경향이 있습니다.\n", + "\n", + "그럼에도 불구하고, finite-sample 환경에서는 여전히 비교적 준수한 수준이며, 목표치인 95%에 근접한 결과입니다. \n", + "\n", + "따라서 DoubleML-DID 추정법은 반복 표본에서 신뢰할 만한 추정치와 적절한 불확실성 추정을 제공함을 확인할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "id": "cf32b307", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "df_pa = pd.DataFrame(ATTE_estimates, columns=['Estimate'])\n", + "g = sns.kdeplot(df_pa, fill=True)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "8867afe5", + "metadata": {}, + "source": [ + "본 시뮬레이션에서 얻어진 ATT 추정치의 분포는 대체로 정규분포 형태를 보이며, 참값(3.0)을 중심으로 집중되어 있습니다. \n", + "\n", + "이는 DoubleML-DID 추정량이 점근적으로 정규분포에 수렴한다는 이론적 특성과 부합하며, 반복 표본에서도 편향 없이 안정적인 추정을 제공함을 시각적으로 확인할 수 있습니다." + ] + }, + { + "cell_type": "markdown", + "id": "a738a4c3", + "metadata": {}, + "source": [ + "사전 추세 검정하기" + ] + }, + { + "cell_type": "code", + "execution_count": 173, + "id": "f43a7643", + "metadata": {}, + "outputs": [], + "source": [ + "n_estimators = 50\n", + "ml_g = LGBMRegressor(n_estimators=n_estimators, num_leaves=5, verbose=-1)\n", + "ml_m = LGBMClassifier(n_estimators=n_estimators, num_leaves=5, verbose=-1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23790ea8", + "metadata": {}, + "outputs": [], + "source": [ + "n_time_periods=5\n", + "data, _,mu_means = make_custom_did(n_obs=1000, n_time_periods=5, seed=i_rep)\n", + "time_periods = (np.arange(2*n_time_periods) - n_time_periods)\n", + "\n", + "df = pd.DataFrame(np.nan,\n", + " index=range(2*n_time_periods-1),\n", + " columns=['lower', 'effect', 'upper'])\n", + "df['time'] = time_periods[1:]\n", + "df[\"true effect\"] = mu_means[1:]\n", + "\n", + "np.random.seed(42)\n", + "for t_idx, t in enumerate(time_periods[1:]):\n", + " if t <= 0:\n", + " t_diff = t-1\n", + " else:\n", + " # compare to outcome before treatment\n", + " t_diff = -1\n", + " # outcome as the difference for each model\n", + " \n", + " y_diff = data[data['t'] == t]['y'].values - data[data['t'] == t_diff]['y'].values\n", + " covariates = np.column_stack((data[data['t'] == t][[f'X{i}' for i in range(4)]].values, data[data['t'] == t_diff][[f'X{i}' for i in range(4)]].values))\n", + " dml_data = DoubleMLData.from_arrays(x=covariates,\n", + " y=y_diff,\n", + " d=data[data['t'] == t]['d'].values)\n", + " dml_did = DoubleMLDID(dml_data,\n", + " ml_g=ml_g,\n", + " ml_m=ml_m)\n", + " dml_did.fit()\n", + "\n", + " df.at[t_idx, 'effect'] = dml_did.coef \n", + " confint = dml_did.confint(level=0.95)\n", + " df.at[t_idx, 'lower'] = confint['2.5 %'].iloc[0]\n", + " df.at[t_idx, 'upper'] = confint['97.5 %'].iloc[0]\n", + " df[\"true effect\"] = mu_means[1:]" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "id": "b9d632d7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "plt.rcParams['figure.figsize'] = 10., 7.5\n", + "fig, ax = plt.subplots()\n", + "\n", + "errors = np.full((2, 2*n_time_periods - 1), np.nan)\n", + "errors[0, :] = df['effect'] - df['lower']\n", + "errors[1, :] = df['upper'] - df['effect']\n", + "\n", + "plt.errorbar(df['time'], df['effect'], fmt='o', yerr=errors, color='#1F77B4',\n", + " ecolor='#1F77B4', label='Estimated Effect (with CI)')\n", + "ax.plot(time_periods[1:], df['effect'], linestyle='--', color='#1F77B4', linewidth=1)\n", + "\n", + "# add horizontal line\n", + "ax.axhline(y=0, color='r', linestyle='--', linewidth=1)\n", + "\n", + "# add true effect\n", + "ax.scatter(x=df['time'], y=df['true effect'], c='#FF7F0E', label='True Effect')\n", + "\n", + "plt.xlabel('Exposure')\n", + "plt.legend()\n", + "_ = plt.ylabel('Effect and 95%-CI')" + ] + }, + { + "cell_type": "markdown", + "id": "6f9fae36", + "metadata": {}, + "source": [ + "- 사전 구간에서 모든 추정치의 CI가 0을 포함하므로, 평행추세 가정은 위배되지 않았다고 해석할 수 있습니다.\n", + "\n", + "- 또, 사후 구간에서 True Effect를 잘 커버하고 있으므로 추정량이 일관되고 신뢰할 만하다고 말할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21fc4727", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From 65054d40cb8f85606dbc1403ddb21a65ac7be627 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 5 Oct 2025 17:27:06 +0900 Subject: [PATCH 06/16] =?UTF-8?q?=EB=A6=AC=EB=B7=B0=EB=B0=98=EC=98=81?= =?UTF-8?q?=EB=B3=B8?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- book/ate/did.ipynb | 927 ++++++++++++++++----------------------------- 1 file changed, 336 insertions(+), 591 deletions(-) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index a619f55..095450b 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -19,36 +19,45 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "f1cc97bd", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: toolz in /Users/kimsieun/대학원/가짜연구소/11기/fack_cl/lib/python3.10/site-packages (1.0.0)\n", - "\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m25.1.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.2\u001b[0m\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" - ] - } - ], + "outputs": [], "source": [ "!pip install toolz" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "87e93136", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install lightgbm" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c2f45002", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install doubleml" + ] + }, { "cell_type": "markdown", "id": "3caf5c69", "metadata": {}, "source": [ - "#### 가상환경 정보" + "## 가상환경 정보" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 44, "id": "7da54cf1", "metadata": {}, "outputs": [ @@ -66,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 45, "id": "2958a91c", "metadata": {}, "outputs": [ @@ -97,6 +106,7 @@ "decorator==5.2.1\n", "dill==0.4.0\n", "dotenv==0.9.9\n", + "DoubleML==0.10.1\n", "duecredit==0.10.2\n", "econml==0.16.0\n", "exceptiongroup==1.3.0\n", @@ -145,6 +155,7 @@ "pexpect==4.9.0\n", "pillow==11.3.0\n", "platformdirs==4.3.8\n", + "plotly==6.3.0\n", "pox==0.3.6\n", "ppft==1.7.7\n", "prompt_toolkit==3.0.51\n", @@ -165,7 +176,7 @@ "PyYAML==6.0.2\n", "pyzmq==27.0.0\n", "requests==2.32.4\n", - "scikit-learn==1.6.1\n", + "scikit-learn==1.7.2\n", "scipy==1.15.3\n", "seaborn==0.13.2\n", "shap==0.48.0\n", @@ -199,234 +210,67 @@ }, { "cell_type": "markdown", - "id": "ddc5fa7d", + "id": "471994fd", "metadata": {}, "source": [ - "아래 tidyfinace패키지는 파이썬 3.10 이상의 환경에서 설치됩니다!" - ] - }, - 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] - } - ], - "source": [ - "!pip install pyfixest" - ] - }, - { - "cell_type": "code", - "execution_count": 8, + "execution_count": 57, "id": "2c650ac3", "metadata": {}, "outputs": [], "source": [ - "import pyfixest as pf\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "a6d9bc21", - "metadata": { - "ExecuteTime": { - "end_time": "2024-01-20T14:39:09.552555Z", - "start_time": "2024-01-20T14:39:06.893550Z" - }, - "tags": [ - "hide-input" - ] - }, - "outputs": [], - "source": [ - "from toolz import *\n", "\n", - "import pandas as pd\n", + "import warnings, logging\n", "import numpy as np\n", + "import pandas as pd\n", "\n", + "import statsmodels.api as sm\n", "import statsmodels.formula.api as smf\n", + "from scipy.stats import norm\n", + "\n", + "from lightgbm import LGBMRegressor, LGBMClassifier\n", + "from doubleml import DoubleMLData, DoubleMLDID\n", + "\n", "\n", - "import seaborn as sns\n", - "from matplotlib import pyplot as plt\n", - "import matplotlib\n", "\n", + "\n", + "from toolz import *\n", + "\n", + "import matplotlib\n", + "from matplotlib import pyplot as plt\n", + "import seaborn as sns\n", "from cycler import cycler\n", + "import matplotlib.ticker as plticker\n", + "\n", + "\n", + "color = ['0.0', '0.4', '0.8']\n", + "default_cycler = cycler(color=color)\n", + "linestyle = ['-', '--', ':', '-.']\n", + "marker = ['o', 'v', 'd', 'p']\n", "\n", - "color=['0.0', '0.4', '0.8']\n", - "default_cycler = (cycler(color=color))\n", - "linestyle=['-', '--', ':', '-.']\n", - "marker=['o', 'v', 'd', 'p']\n", + "plt.rc('axes', prop_cycle=default_cycler)\n", "\n", - "plt.rc('axes', prop_cycle=default_cycler)" + "\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", + "logging.getLogger('matplotlib.category').setLevel(logging.ERROR)" + ] + }, + { + "cell_type": "markdown", + "id": "22b135b3", + "metadata": {}, + "source": [ + "## 데이터 불러오기" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 58, "id": "d17c7963", "metadata": { "ExecuteTime": { @@ -529,18 +373,19 @@ "4 2021-05-05 5 S 0 0.0 49.0 0" ] }, - "execution_count": 15, + "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "import numpy as np\n", "\n", - "mkt_data = (pd.read_csv(\"../data/matheus_data/short_offline_mkt_south.csv\")\n", + "mkt_data = (pd.read_csv(\"./data/short_offline_mkt_south.csv\")\n", " .astype({\"date\":\"datetime64[ns]\"}))\n", "\n", + "# mkt_data = (pd.read_csv(\"../data/short_offline_mkt_south.csv\")\n", + "# .astype({\"date\":\"datetime64[ns]\"}))\n", + "\n", "\n", "\n", "\n", @@ -557,7 +402,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 59, "id": "3d6cdba1", "metadata": { "ExecuteTime": { @@ -566,16 +411,6 @@ } }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_21522/2583971365.py:4: FutureWarning: The provided callable is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"min\" instead.\n", - " .agg({\"date\":[min, max]}))\n", - "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_21522/2583971365.py:4: FutureWarning: The provided callable is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n", - " .agg({\"date\":[min, max]}))\n" - ] - }, { "data": { "text/html": [ @@ -637,7 +472,7 @@ "1 2021-05-15 2021-06-01" ] }, - "execution_count": 16, + "execution_count": 59, "metadata": {}, "output_type": "execute_result" } @@ -651,7 +486,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 60, "id": "355d9c2c", "metadata": { "ExecuteTime": { @@ -728,7 +563,7 @@ " 1 51.858025 2021-05-15" ] }, - "execution_count": 17, + "execution_count": 60, "metadata": {}, "output_type": "execute_result" } @@ -746,13 +581,15 @@ "id": "2614a652", "metadata": {}, "source": [ - "### 이중 차분법에 대한 접근법 3가지\n", - "1. 각 그룹별 평균을 집계 - 평균을 이용한 이중 차분법(Basic DID 2x2)\n", - "2. 각 집단의 사전→사후 변화량을 구한 후, 두 집단의 변화량 차이를 비교 - 시간에 따른 결과 변화 값을 이용한 이중차분법\n", - "3. 선형회귀\n", - " - 기본 회귀 DID\n", - " - Control DID (추가 통제 포함)\n", - " - TWFE DID (이원고정효과 포함)\n" + "## 이중 차분법에 대한 접근법 3가지\n", + "1. 평균을 이용한 이중 차분법 (Basic DID 2x2)\n", + "2. 시간에 따른 결과 변화 값을 이용한 이중차분법\n", + "3. 선형회귀를 이용한 이중차분법(Regression DID) \n", + " - 3.1 데이터 집계 방식\n", + " - 3.2 Basic DiD\n", + " - 3.3 TWFE DID\n", + " - 3.4 DID with covariates (Control DID: 추가 통제 포함)\n", + " - 3.4.1 DoubleML \n" ] }, { @@ -760,12 +597,19 @@ "id": "e911d8b1", "metadata": {}, "source": [ - "#### 평균을 이용한 이중 차분법(Basic DID 2x2)" + "### 1. 평균을 이용한 이중 차분법(Basic DID 2x2)\n", + "\n", + "\n", + "\n", + "- 처치 그룹/대조 그룹, 처치 전/후 두 시점의 평균 차이의 차이를 직접 계산하는 방법입니다.\n", + "- 가장 직관적이고 기본적인 DiD 개념입니다.\n", + "- 다중 시점 데이터나 추가적인 교란 변수를 통제하기 어렵습니다. 통계적 유의성 검정이 별도의 과정이 필요합니다.\n", + "- 복잡한 데이터와 더 견고한 통계적 추론을 위해 회귀 분석 기반의 접근법이 필요하게 됩니다." ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 61, "id": "79bcb7fe", "metadata": { "ExecuteTime": { @@ -780,7 +624,7 @@ "np.float64(0.6917359536407233)" ] }, - "execution_count": 18, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" } @@ -796,7 +640,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 62, "id": "b51d6822", "metadata": { "ExecuteTime": { @@ -811,7 +655,7 @@ "np.float64(0.7660316402518457)" ] }, - "execution_count": 19, + "execution_count": 62, "metadata": {}, "output_type": "execute_result" } @@ -825,12 +669,18 @@ "id": "47458e38", "metadata": {}, "source": [ - "#### 시간에 따른 결과 변화 값을 이용한 이중차분법" + "### 2. 시간에 따른 결과 변화 값을 이용한 이중차분법\n", + "\n", + "- 각 개별 단위(예: 도시)의 처치 전후 결과값 평균의 차이($\\Delta Y_i$​)를 직접 계산하여, 이 단위별 변화 값($\\Delta Y_i$​)을 사용하는 방법입니다.\n", + "- DiD의 '변화 속의 변화'를 직관적으로 이해하고, 단위의 시간 불변 특성을 자동 통제합니다.\n", + "- Basic DiD와 동일한 결과를 회귀식으로 도출하며 통계적 유의성 확인이 용이합니다.\n", + "- 더 복잡한 DiD(TWFE)로 나아가기 위한 개념적 디딤돌입니다.\n", + "- 두 시점 외 복잡한 다중 시점 데이터 처리나 시간에 따라 변하는 외부 교란 요인을 직접 통제하기 어렵습니다.\n" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 63, "id": "10e16d8d", "metadata": { "ExecuteTime": { @@ -909,7 +759,7 @@ "197 1.595238 1" ] }, - "execution_count": 20, + "execution_count": 63, "metadata": {}, "output_type": "execute_result" } @@ -929,7 +779,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 64, "id": "31be6542", "metadata": { "ExecuteTime": { @@ -944,7 +794,7 @@ "np.float64(0.6917359536407155)" ] }, - "execution_count": 21, + "execution_count": 64, "metadata": {}, "output_type": "execute_result" } @@ -964,7 +814,90 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 65, + "id": "57032287", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " downloads date\n", + "treated post \n", + "0 0 50.335034 2021-05-01\n", + " 1 50.556878 2021-05-15\n", + "1 0 50.944444 2021-05-01\n", + " 1 51.858025 2021-05-15" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "did_data" + ] + }, + { + "cell_type": "code", + "execution_count": 66, "id": "ff0261df", "metadata": { "ExecuteTime": { @@ -979,10 +912,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 22, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" }, @@ -1021,7 +954,25 @@ "id": "7d388983", "metadata": {}, "source": [ - "### 선형회귀를 이용한 이중차분법(Regression DID)" + "### 3. 선형회귀를 이용한 이중차분법(Regression DID)\n", + "\n", + "DiD를 회귀식으로 표현하여 통계적 엄밀성을 확보하는 방법입니다. 데이터 집계 방식에 따라 두 가지 접근법이 있습니다." + ] + }, + { + "cell_type": "markdown", + "id": "76783d79", + "metadata": {}, + "source": [ + "먼저 Canonical DID를 추정할 때 두 가지 데이터 집계 방식이 사용될 수 있습니다. \n", + "1. 개입 전/후 기간을 하나의 블록으로 집계한 데이터\n", + "2. 각 개별 시점의 데이터를 그대로 사용\n", + "\n", + "핵심은 어떤 데이터를 수집하더라도 분석에 사용할 최종 데이터 형태가 블록디자인을 따르면 된다는 것입니다.\n", + "\n", + "- 블록 디자인이란?\n", + " - 동일한 시점에 처치를 받는 단위들을 하나의 블록으로 묶고 그 블록과 처치를 받지 않는 블록(control)을 비교하는 구조\n", + " " ] }, { @@ -1029,12 +980,16 @@ "id": "b8dd4569", "metadata": {}, "source": [ - "#### 개입 전/후 기간을 하나의 블록으로 집계한 데이터" + "#### 3. 1 데이터 집계 방식 1: 개입 전/후 기간을 하나의 블록으로 집계한 데이터 (data set : did data)\n", + "\n", + "- 그룹(처치/대조)별로 처치 전 평균과 처치 후 평균을 구한 후, 이를 바탕으로 회귀 모델을 만드는 방식입니다.\n", + "- Basic DID (2x2)와 동일한 결과값을 얻으면서 통계적 유의성을 쉽게 확인할 수 있습니다.\n", + "- 다만,개별 관측치 수준의 정보 손실이 있고, 다중 시점의 미시 데이터를 직접 활용하지 못합니다." ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 25, "id": "bead249f", "metadata": { "ExecuteTime": { @@ -1126,7 +1081,7 @@ "4 20 0 48.785714 2021-05-01 0" ] }, - "execution_count": 23, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -1159,7 +1114,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "id": "54757217", "metadata": { "ExecuteTime": { @@ -1180,50 +1135,28 @@ } ], "source": [ - "import statsmodels.formula.api as smf\n", + "\n", "\n", "smf.ols(\n", " 'downloads ~ treated*post', data=did_data\n", ").fit().params[\"treated:post\"]" ] }, - { - "cell_type": "code", - "execution_count": 25, - "id": "463a35ef", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DID estimate: 0.6917359536407451\n" - ] - } - ], - "source": [ - "import pyfixest as pf\n", - "\n", - "model = pf.feols(\"downloads ~ treated*post\", data=did_data)\n", - "\n", - "# DID 추정치 (treated:post 계수)\n", - "coef = model.coef()[\"treated:post\"]\n", - "print(\"DID estimate:\", coef)" - ] - }, { "cell_type": "markdown", "id": "48ef6933", "metadata": {}, "source": [ - "### 블록디자인을 바탕으로 한 이중차분법\n", - "- DID를 추정할때 처치 전후로 각 값들을 그룹화하여 하지 않고 각 시점의 데이터를 모두 활용하는 방법과\n", - "- 사전 평행 추세를 검정할 수 있다는 장점이 있습니다.\n" + "#### 3. 1 데이터 집계 방식 2: 각 개별 시점의 데이터를 그대로 사용 (data set : mkt data)\n", + "- DID를 추정할때 처치 전후로 각 값들을 그룹화하여 하지 않고 각 시점의 데이터를 모두 활용하는 방법입니다.\n", + "- 데이터 집계 방식 1보다 훨씬 강력하며, 단위 고정 효과와 시간 고정 효과를 포함할 수 있는 기반이 됩니다. \n", + "- 또, 데이터 집계 방식 1과 달리 개별 관측치 정보를 최대한 활용합니다. 또한 사전 평행 추세를 검정할 수 있다는 장점이 있습니다.\n", + "- 다만, 여전히 시간에 따라 변하는 관측되지 않은 교란 요인을 완전히 제거할 수는 없습니다.\n" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 52, "id": "d1eed2c4", "metadata": { "ExecuteTime": { @@ -1235,64 +1168,9 @@ ] }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/qj/p1t8n_615hx2wgwh8350jg6h0000gn/T/ipykernel_21522/2621860921.py:7: FutureWarning: The provided callable is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n", - " .assign(treated=lambda d: d.groupby(\"city\")[\"treated\"].transform(max))\n", - "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", - "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", - "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n" - ] - }, { "data": { - "text/plain": [ - "(array([ 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5,\n", - " 11.5, 12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5, 20.5, 21.5,\n", - " 22.5, 23.5, 24.5, 25.5, 26.5, 27.5, 28.5, 29.5, 30.5, 31.5]),\n", - " [Text(0.5, 0, '2021-05-01'),\n", - " Text(1.5, 0, '2021-05-02'),\n", - " Text(2.5, 0, '2021-05-03'),\n", - " Text(3.5, 0, '2021-05-04'),\n", - " Text(4.5, 0, '2021-05-05'),\n", - " Text(5.5, 0, '2021-05-06'),\n", - " Text(6.5, 0, '2021-05-07'),\n", - " Text(7.5, 0, '2021-05-08'),\n", - " Text(8.5, 0, '2021-05-09'),\n", - " Text(9.5, 0, '2021-05-10'),\n", - " Text(10.5, 0, '2021-05-11'),\n", - " Text(11.5, 0, '2021-05-12'),\n", - " Text(12.5, 0, '2021-05-13'),\n", - " Text(13.5, 0, '2021-05-14'),\n", - " Text(14.5, 0, '2021-05-15'),\n", - " Text(15.5, 0, '2021-05-16'),\n", - " Text(16.5, 0, '2021-05-17'),\n", - " Text(17.5, 0, 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", 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", 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" ] @@ -1302,7 +1180,6 @@ } ], "source": [ - "import matplotlib.ticker as plticker\n", "\n", "\n", "fig, (ax1, ax2) = plt.subplots(2,1, figsize=(9, 12), sharex=True)\n", @@ -1333,12 +1210,12 @@ "ax2.vlines(\"2021-05-15\", mkt_data[\"downloads\"].min(), mkt_data[\"downloads\"].max(), color=\"black\", ls=\"dashed\", label=\"Interv.\")\n", "ax2.set_title(\"Outcome Over Time\")\n", "\n", - "plt.xticks(rotation = 50)" + "plt.xticks(rotation = 50);" ] }, { "cell_type": "code", - "execution_count": 92, + "execution_count": null, "id": "e01430de", "metadata": {}, "outputs": [ @@ -1519,12 +1396,28 @@ "id": "f19bdff0", "metadata": {}, "source": [ - "### Basic DID" + "\n", + "\n", + "#### 3.2 Basic DID\n", + "\n", + "\n", + "- 가장 기본적인 회귀 DiD 모델이며, DiD 효과($\\beta$)와 함께 각 그룹의 처치 전후 베이스라인 차이 등을 동시에 추정합니다. \n", + "- 통계적 추론(표준 오차, p-값)을 쉽게 제공합니다.\n", + "- DiD 효과를 통계적으로 더 견고하게 추정하며, 이후 TWFE DiD 등 더 발전된 모델로 확장하기 위한 직접적인 기반이 됩니다.\n", + "- 아직 단위/시간 고정 효과를 명시적으로 통제하지 않으므로, 관측되지 않은 시간에 따른 교란 요인에 의한 편향 가능성이 있습니다." + ] + }, + { + "cell_type": "markdown", + "id": "c4695167", + "metadata": {}, + "source": [ + "$$Y_{it} = \\beta_0 + \\beta_1 D_i + \\beta_2 Post_t + \\beta_3 D_i Post_t + e_{it}$$" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "id": "647b569a", "metadata": { "ExecuteTime": { @@ -1539,7 +1432,7 @@ "np.float64(0.6917359536406855)" ] }, - "execution_count": 27, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -1551,100 +1444,110 @@ ] }, { - "cell_type": "code", - "execution_count": 28, - "id": "03b5b503", + "cell_type": "markdown", + "id": "e73611cf", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DID estimate: 0.6917359536407436\n" - ] - } - ], "source": [ - "import pyfixest as pf\n", + "##### 추론\n", "\n", - "model = pf.feols(\"downloads ~ treated*post\", data=mkt_data)\n", + "1. 기준 표준 오차 (Homoskedastic Standard Error)\n", "\n", - "# DID 추정치 (treated:post 계수)\n", - "coef = model.coef()[\"treated:post\"]\n", - "print(\"DID estimate:\", coef)" + "- 오차가 독립적이며 동일 분산을 가진다고 가정합니다.\n", + "- 다만 동일 단위 내 관측치 간 상관관계를 무시하여, 표준 오차가 과소평가(실제보다 작게)될 수 있습니다.\n", + "- 이로 인해 유의하지 않은 결과도 유의하다고 잘못 판단할 위험이 있습니다.\n", + "\n", + "\n", + "\n", + "2. 군집 표준 오차 (Clustered Standard Error)\n", + "\n", + "- 특정 군집(예: city_id) 내에서는 오차 상관관계를 허용하지만, 군집 간에는 독립적이라고 가정합니다. 이분산성에도 강건합니다.\n", + "- 패널 데이터의 군집 내 상관관계를 반영하여, 보통 기준 표준 오차보다 더 크게(보수적으로) 추정됩니다.\n", + "- 기준 표준 오차의 과소평가 문제를 해결하여, 통계적 유의성 판단의 신뢰성을 높여줍니다. DiD 분석 시 권장됩니다." ] }, { "cell_type": "markdown", - "id": "83f05570", + "id": "b227de62", "metadata": {}, "source": [ - "#### 추론" + "1. 기존 표준 오차 기반 " ] }, { "cell_type": "code", - "execution_count": 41, - "id": "fe572c5d", + "execution_count": 38, + "id": "e847ddef", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "ATT: 0.6917359536407082\n" + "ATT: 0.6917359536406855\n" ] }, { "data": { "text/plain": [ - "0 0.300318\n", - "1 1.083154\n", + "0 0.213969\n", + "1 1.169503\n", "Name: treated:post, dtype: float64" ] }, - "execution_count": 41, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "m = smf.ols(\n", - " 'downloads ~ treated*post', data=did_data\n", - ").fit(cov_type='cluster', cov_kwds={'groups': did_data['city']})\n", - "\n", + " 'downloads ~ treated*post', data=mkt_data\n", + ").fit()\n", "print(\"ATT:\", m.params[\"treated:post\"])\n", "m.conf_int().loc[\"treated:post\"]" ] }, + { + "cell_type": "markdown", + "id": "b4199ddc", + "metadata": {}, + "source": [ + "2. 군집 기반 표준 오차 기반" + ] + }, { "cell_type": "code", - "execution_count": 43, - "id": "e1157b02", + "execution_count": 39, + "id": "fe572c5d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "ATT: 0.6917359536407451\n", - "2.5% 0.290613\n", - "97.5% 1.092859\n", - "Name: treated:post, dtype: float64\n" + "ATT: 0.6917359536406855\n" ] + }, + { + "data": { + "text/plain": [ + "0 0.305820\n", + "1 1.077652\n", + "Name: treated:post, dtype: float64" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "import pyfixest as pf\n", - "\n", - "m = pf.feols(\n", - " \"downloads ~ treated*post\",\n", - " vcov={\"CRV1\": \"city\"}, # 클러스터 표준오차: city 단위\n", - " data=did_data\n", - ")\n", + "m = smf.ols(\n", + " 'downloads ~ treated*post', data=mkt_data\n", + ").fit(cov_type='cluster', cov_kwds={'groups': mkt_data['city']})\n", "\n", - "print(\"ATT:\", m.coef()[\"treated:post\"])\n", - "print(m.confint().loc[\"treated:post\"])" + "print(\"ATT:\", m.params[\"treated:post\"])\n", + "m.conf_int().loc[\"treated:post\"]" ] }, { @@ -1652,7 +1555,16 @@ "id": "a745a402", "metadata": {}, "source": [ - "### 2WFE did " + "#### 3.3 2WFE did \n", + "\n", + "- 데이터 집계 방식 2의 회귀 모델에 단위 고정 효과($\\alpha_i$​)와 시간 고정 효과($\\gamma_t$​)를 동시에 추가하여 분석하는 방법입니다.\n", + "- 단위별 고유 특성(시간 불변)과 모든 단위에 공통된 시간 트렌드를 통제하여 교란 요인을 더 효과적으로 제거합니다.\n", + "- 내생성 문제를 완화하고, 다중 시점 데이터를 유연하게 처리할 수 있습니다.\n", + "- 시간에 따라 변하는 관측되지 않은 교란 요인이나, 처치 효과가 이질적인 경우(heterogeneous effects) 편향될 수 있습니다.\n", + "\n", + "\n", + "$$Y_{it} = \\tau W_{it} + \\alpha_i + \\gamma_t + e_{it} \\text{ ,where } W_{it} = D_iPost_t$$\n", + "\n" ] }, { @@ -1678,45 +1590,15 @@ "print(\"DID estimate:\", coef)" ] }, - { - "cell_type": "code", - "execution_count": 32, - "id": "6c2d3cb6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DID estimate: 0.6917359536407154\n" - ] - } - ], - "source": [ - "import pyfixest as pf\n", - "\n", - "# pyfixest의 feols 함수 사용\n", - "m = pf.feols(\"downloads ~ treated:post | city + date\", data=mkt_data)\n", - "\n", - "# 계수 확인\n", - "coef=m.coef()[\"treated:post\"]\n", - "print(\"DID estimate:\", coef)" - ] - }, - { - "cell_type": "markdown", - "id": "364d13bd", - "metadata": {}, - "source": [ - "#### 추론" - ] - }, { "cell_type": "markdown", "id": "03fa6aea", "metadata": {}, "source": [ - "##### 1. 실험 대상과 처치 전후 기간별 집계한 데이터 기반 추론" + "##### 데이터 집계 방식에 따른 추론 비교\n", + "\n", + " 1. 집계 방식 1: 단순한 2x2 테이블의 회귀 버전이며, 고정 효과를 적용하기 어렵습니다.\n", + " 2. 집계 방식 2: 패널 데이터의 장점을 활용할 수 있는 표준적인 접근법입니다.\n" ] }, { @@ -1724,7 +1606,7 @@ "id": "0a47e10f", "metadata": {}, "source": [ - "기존 표준 오차 기반" + "1-1 집계방식 1: 기존 표준 오차 기반" ] }, { @@ -1766,7 +1648,7 @@ "id": "060ae0ae", "metadata": {}, "source": [ - "군집 표준 오차 기반" + "1-2 집계방식 1:군집 표준 오차 기반" ] }, { @@ -1804,50 +1686,12 @@ "m.conf_int().loc[\"treated:post\"]" ] }, - { - "cell_type": "code", - "execution_count": 44, - "id": "7a80adcb", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ATT: 0.6917359536406991\n", - "2.5% 0.124463\n", - "97.5% 1.259009\n", - "Name: treated:post, dtype: float64\n" - ] - } - ], - "source": [ - "import pyfixest as pf\n", - "\n", - "m = pf.feols(\n", - " \"downloads ~ treated:post + C(city) + C(date)\",\n", - " vcov={\"CRV1\": \"city\"}, # 클러스터 표준오차: city 단위\n", - " data=did_data\n", - ")\n", - "\n", - "print(\"ATT:\", m.coef()[\"treated:post\"])\n", - "print(m.confint().loc[\"treated:post\"])" - ] - }, - { - "cell_type": "markdown", - "id": "919ba418", - "metadata": {}, - "source": [ - "##### 2. 일별로 집계한 데이터" - ] - }, { "cell_type": "markdown", "id": "feca1d75", "metadata": {}, "source": [ - "기존 표준오차 기반" + "2-1 집계방식 2: 기존 표준오차 기반" ] }, { @@ -1889,7 +1733,7 @@ "id": "4e4d7046", "metadata": {}, "source": [ - "군집 표준 오차 기반" + "2-2 집계방식 2: 군집 표준 오차 기반" ] }, { @@ -1927,42 +1771,21 @@ "m.conf_int().loc[\"treated:post\"]" ] }, - { - "cell_type": "code", - "execution_count": 45, - "id": "c92fca81", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ATT: 0.6917359536407385\n", - "2.5% 0.286292\n", - "97.5% 1.097180\n", - "Name: treated:post, dtype: float64\n" - ] - } - ], - "source": [ - "import pyfixest as pf\n", - "\n", - "m = pf.feols(\n", - " \"downloads ~ treated:post + C(city) + C(date)\",\n", - " vcov={\"CRV1\": \"city\"}, # 클러스터 표준오차: city 단위\n", - " data=mkt_data\n", - ")\n", - "\n", - "print(\"ATT:\", m.coef()[\"treated:post\"])\n", - "print(m.confint().loc[\"treated:post\"])" - ] - }, { "cell_type": "markdown", "id": "013fd5ae", "metadata": {}, "source": [ - "### DID with covariates" + "#### 3.4 DID with covariates\n", + "\n", + "TWFE DiD 모델에 시간에 따라 변하는 관측 가능한 공변량($X_{it}$​)을 추가하는 방식입니다.\n", + "$$Y_{it} = \\alpha_i + \\gamma_t + \\beta (\\text{Treated}_i \\times \\text{Post}_t) + \\delta'X_{it} + \\epsilon_{it}$$\n", + "\n", + "- 시간에 따라 그룹 간 다르게 변화하는 관측 가능한 교란 요인을 통제함으로써 평행 추세 가정을 더욱 강화합니다.\n", + "- 추정치의 정밀도를 높이고, 관측 가능한 교란 요인으로 인한 편향을 줄입니다.\n", + "- 어떤 공변량을 포함할지 신중하게 선택해야 하며, 여전히 관측되지 않은 교란 요인에 의한 편향 가능성은 남아 있습니다.\n", + "\n", + "\n" ] }, { @@ -2103,8 +1926,6 @@ ], "source": [ "\n", - "import statsmodels.api as sm\n", - "from scipy.stats import norm\n", "\n", "# (1) region size (가중치 계산)\n", "reg_size = (mkt_data_all.groupby(\"region\").size()\n", @@ -2295,84 +2116,12 @@ "id": "0b985fca", "metadata": {}, "source": [ - "#### DML을 이용한 DID" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "id": "c001b25c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting doubleml\n", - " Downloading doubleml-0.10.1-py3-none-any.whl.metadata (8.3 kB)\n", - "Requirement already satisfied: joblib in /Users/kimsieun/대학원/가짜연구소/11기/fack_cl/lib/python3.10/site-packages (from doubleml) (1.5.1)\n", - "Requirement already satisfied: 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installed doubleml-0.10.1 plotly-6.3.0\n", - "\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m25.1.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.2\u001b[0m\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" - ] - } - ], - "source": [ - "!pip install doubleml" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "id": "e5f05e5e", - "metadata": {}, - "outputs": [], - "source": [ - "import warnings\n", + "#### DML을 이용한 DID\n", "\n", - "# 모든 경고 무시\n", - "warnings.filterwarnings(\"ignore\")" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "id": "2b5db2e0", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "from doubleml import DoubleMLData, DoubleMLDID\n", - "from lightgbm import LGBMClassifier, LGBMRegressor" + "- 공변량과 결과 변수, 공변량과 처치 변수 간의 복잡한 비선형 관계를 머신러닝 모델로 예측한 후, 이 잔차(residuals)를 사용하여 DiD 효과를 추정하는 방법입니다.\n", + "- 고차원적인 공변량을 유연하게 처리하고, 머신러닝의 예측력을 활용하여 잠재적인 편향을 줄입니다. 특히 이질적인 처치 효과를 다루는 데 강점이 있습니다.\n", + "- 유연성, 견고성, 고차원 데이터 처리 능력이 우수합니다.\n", + "- 다만, 모델 복잡성이 증가하고, 구현 및 해석이 어려울 수 있습니다." ] }, { @@ -2390,10 +2139,6 @@ "metadata": {}, "outputs": [], "source": [ - "import numpy as np\n", - "import pandas as pd\n", - "from doubleml import DoubleMLData, DoubleMLDID\n", - "from lightgbm import LGBMRegressor, LGBMClassifier\n", "\n", "\n", "\n", @@ -2920,7 +2665,7 @@ }, { "cell_type": "code", - "execution_count": 206, + "execution_count": null, "id": "d073f8ab", "metadata": {}, "outputs": [ From 2308063bf6d2f9ab734d047087df77f8634f0574 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 5 Oct 2025 17:34:37 +0900 Subject: [PATCH 07/16] =?UTF-8?q?=EB=A6=AC=EB=B7=B0=EB=B0=98=EC=98=81?= =?UTF-8?q?=EB=B3=B8-=EA=B2=BD=EB=A1=9C=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .DS_Store | Bin 0 -> 6148 bytes .Rhistory | 0 book/ate/did.ipynb | 10 ++++------ 3 files changed, 4 insertions(+), 6 deletions(-) create mode 100644 .DS_Store create mode 100644 .Rhistory diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..30b8870a802a4f219e57ec7c11412d227d276aa4 GIT binary patch literal 6148 zcmeHK&2AGh5FV$Y*|Z= zjD_O_=V(OoG>Bw?HYc=V8L$le-3;*F%~C)Tzl+rVt)OrJmlCyzgrmZndS1f@{4S9Ebf$r|_UAev^KH~sJEI!JWS=-TI6Wa31U4uB0m+wb6*}eM=vqY8ho4N zlb7=TnexsfqldNC=@synIc1oK<@^O2QlGA9Org>SXvLJ!2+;|BqGWYM6m?^+k-Jqio^%{8hJ jROUKX3SY&$C`!=hvH~m{oNI&yVm|~F4Ysljtd)V^hk~@7 literal 0 HcmV?d00001 diff --git a/.Rhistory b/.Rhistory new file mode 100644 index 0000000..e69de29 diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index 095450b..56b98e9 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -270,7 +270,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": null, "id": "d17c7963", "metadata": { "ExecuteTime": { @@ -373,18 +373,16 @@ "4 2021-05-05 5 S 0 0.0 49.0 0" ] }, - "execution_count": 58, + "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", - "mkt_data = (pd.read_csv(\"./data/short_offline_mkt_south.csv\")\n", - " .astype({\"date\":\"datetime64[ns]\"}))\n", "\n", - "# mkt_data = (pd.read_csv(\"../data/short_offline_mkt_south.csv\")\n", - "# .astype({\"date\":\"datetime64[ns]\"}))\n", + "mkt_data = (pd.read_csv(\"../data/matheus_data/short_offline_mkt_south.csv\")\n", + " .astype({\"date\":\"datetime64[ns]\"}))\n", "\n", "\n", "\n", From 7be36ec0fd58010b5e7342bdc967977fd8be6d45 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 5 Oct 2025 17:38:04 +0900 Subject: [PATCH 08/16] chore: ignore .DS_Store files --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 7803c8f..73ed234 100644 --- a/.gitignore +++ b/.gitignore @@ -135,3 +135,4 @@ _build/ # poetry files pyproject.toml +.DS_Store From 6bf5e38854762a0570505804f3a0ae580d165de4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 5 Oct 2025 17:39:08 +0900 Subject: [PATCH 09/16] fix: resolve .DS_Store conflict and ignore file --- .DS_Store | Bin 6148 -> 0 bytes .gitignore | 1 + 2 files changed, 1 insertion(+) delete mode 100644 .DS_Store diff --git a/.DS_Store b/.DS_Store deleted file mode 100644 index 30b8870a802a4f219e57ec7c11412d227d276aa4..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 6148 zcmeHK&2AGh5FV$Y*|Z= zjD_O_=V(OoG>Bw?HYc=V8L$le-3;*F%~C)Tzl+rVt)OrJmlCyzgrmZndS1f@{4S9Ebf$r|_UAev^KH~sJEI!JWS=-TI6Wa31U4uB0m+wb6*}eM=vqY8ho4N zlb7=TnexsfqldNC=@synIc1oK<@^O2QlGA9Org>SXvLJ!2+;|BqGWYM6m?^+k-Jqio^%{8hJ jROUKX3SY&$C`!=hvH~m{oNI&yVm|~F4Ysljtd)V^hk~@7 diff --git a/.gitignore b/.gitignore index 73ed234..71cb3a3 100644 --- a/.gitignore +++ b/.gitignore @@ -136,3 +136,4 @@ _build/ # poetry files pyproject.toml .DS_Store +.DS_Store From cc65005a92245278c371297db56c2b8d04fe0c7b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sat, 11 Oct 2025 23:56:03 +0900 Subject: [PATCH 10/16] =?UTF-8?q?DRDID,Straggered=20DID,dynamic=20did=20?= =?UTF-8?q?=EB=B0=8F=20=EC=BD=94=EB=93=9C=20=EA=B5=AC=EC=84=B1=20=EC=88=98?= =?UTF-8?q?=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- book/ate/did.ipynb | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index 56b98e9..3681343 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -575,6 +575,23 @@ ] }, { +<<<<<<< Updated upstream +======= + "attachments": { + "image.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "9d105574", + "metadata": {}, + "source": [ + "## DiD \n", + "![image.png](attachment:image.png)" + ] + }, + { +>>>>>>> Stashed changes "cell_type": "markdown", "id": "2614a652", "metadata": {}, From 4cf2968b5d44db69a5880c5b568e5393eaa0822d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 12 Oct 2025 18:39:25 +0900 Subject: [PATCH 11/16] =?UTF-8?q?DRDID,Straggered=20DID,dynamic=20did=20?= =?UTF-8?q?=EB=B0=8F=20=EC=BD=94=EB=93=9C=20=EA=B5=AC=EC=84=B1=20=EC=88=98?= =?UTF-8?q?=EC=A0=95-=20=EC=B6=A9=EB=8F=8C=ED=95=B4=EA=B2=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- book/ate/did.ipynb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index 3681343..63eb98b 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -575,8 +575,8 @@ ] }, { -<<<<<<< Updated upstream -======= + + "attachments": { "image.png": { "image/png": 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" @@ -591,7 +591,7 @@ ] }, { ->>>>>>> Stashed changes + "cell_type": "markdown", "id": "2614a652", "metadata": {}, From eae4ae284a62b24cec4423825fb04c32c310dac0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 19 Oct 2025 01:00:42 +0900 Subject: [PATCH 12/16] =?UTF-8?q?=EC=A7=80=EB=82=9C=20=EB=85=B8=ED=8A=B8?= =?UTF-8?q?=20=EB=B3=B5=EA=B5=AC=20=EB=B0=8F=20ddd,event=20study=20f-test?= =?UTF-8?q?=20=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- book/.DS_Store | Bin 6148 -> 6148 bytes book/ate/did.ipynb | 2837 ++- book/data/.DS_Store | Bin 8196 -> 8196 bytes book/data/matheus_data/.DS_Store | Bin 8196 -> 8196 bytes .../matheus_data/offline_mkt_staggered.csv | 18401 ++++++++++++++++ 5 files changed, 20569 insertions(+), 669 deletions(-) create mode 100644 book/data/matheus_data/offline_mkt_staggered.csv diff --git a/book/.DS_Store b/book/.DS_Store index 443853006fb1dcf76e1dd80045065c7fb4423967..8e8ba3e3a9f0d1716f1ccda04032b2175207851a 100644 GIT binary patch delta 39 tcmZoMXffEJ#L8i4VWgvAWMr^ei`9jZ!^qMA$g{AVti@`-c`KX0AON~72}=L~ delta 39 ncmZoMXffEJ#L8h}VxXg7VraBki`9h@&YP^oYQK3ao4+6cxp@gZ diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index 63eb98b..e205b21 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -19,30 +19,114 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "f1cc97bd", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting toolz\n", + " Downloading toolz-1.1.0-py3-none-any.whl.metadata (5.1 kB)\n", + "Downloading toolz-1.1.0-py3-none-any.whl (58 kB)\n", + "Installing collected packages: toolz\n", + "Successfully installed toolz-1.1.0\n" + ] + } + ], "source": [ "!pip install toolz" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "87e93136", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting lightgbm\n", + " Using cached lightgbm-4.6.0-py3-none-macosx_12_0_arm64.whl.metadata (17 kB)\n", + "Requirement already satisfied: numpy>=1.17.0 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from lightgbm) (1.25.2)\n", + "Requirement already satisfied: scipy in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from lightgbm) (1.13.1)\n", + "Using cached lightgbm-4.6.0-py3-none-macosx_12_0_arm64.whl (1.6 MB)\n", + "Installing collected packages: lightgbm\n", + "Successfully installed lightgbm-4.6.0\n" + ] + } + ], "source": [ "!pip install lightgbm" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "c2f45002", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting doubleml\n", + " Using cached doubleml-0.10.1-py3-none-any.whl.metadata (8.3 kB)\n", + "Requirement already satisfied: joblib in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from doubleml) (1.4.2)\n", + "Requirement already satisfied: numpy in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from doubleml) (1.25.2)\n", + "Requirement already satisfied: pandas in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from doubleml) (2.2.3)\n", + "Requirement already satisfied: scipy in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from doubleml) (1.13.1)\n", + "Requirement already satisfied: scikit-learn>=1.4.0 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from doubleml) (1.6.1)\n", + "Requirement already satisfied: statsmodels in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from doubleml) (0.14.4)\n", + "Requirement already satisfied: matplotlib in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from doubleml) (3.9.4)\n", + "Requirement already satisfied: seaborn>=0.13 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from doubleml) (0.13.2)\n", + "Collecting plotly (from doubleml)\n", + " Downloading plotly-6.3.1-py3-none-any.whl.metadata (8.5 kB)\n", + "Requirement already satisfied: threadpoolctl>=3.1.0 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from scikit-learn>=1.4.0->doubleml) (3.6.0)\n", + "Requirement already satisfied: contourpy>=1.0.1 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (1.3.0)\n", + "Requirement already satisfied: cycler>=0.10 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (0.12.1)\n", + "Requirement already satisfied: fonttools>=4.22.0 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (4.56.0)\n", + "Requirement already satisfied: kiwisolver>=1.3.1 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (1.4.7)\n", + "Requirement already satisfied: packaging>=20.0 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (21.3)\n", + "Requirement already satisfied: pillow>=8 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (11.1.0)\n", + "Requirement already satisfied: pyparsing>=2.3.1 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (3.2.1)\n", + "Requirement already satisfied: python-dateutil>=2.7 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (2.9.0.post0)\n", + "Requirement already satisfied: importlib-resources>=3.2.0 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from matplotlib->doubleml) (6.5.2)\n", + "Requirement already satisfied: pytz>=2020.1 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from pandas->doubleml) (2024.1)\n", + "Requirement already satisfied: tzdata>=2022.7 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from pandas->doubleml) (2025.1)\n", + "Collecting narwhals>=1.15.1 (from plotly->doubleml)\n", + " Downloading narwhals-2.8.0-py3-none-any.whl.metadata (11 kB)\n", + "Requirement already satisfied: patsy>=0.5.6 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from statsmodels->doubleml) (1.0.1)\n", + "Requirement already satisfied: zipp>=3.1.0 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from importlib-resources>=3.2.0->matplotlib->doubleml) (3.21.0)\n", + "Requirement already satisfied: six>=1.5 in /Users/kimsieun/miniforge3/envs/kats_env/lib/python3.9/site-packages (from python-dateutil>=2.7->matplotlib->doubleml) (1.17.0)\n", + "Using cached doubleml-0.10.1-py3-none-any.whl (471 kB)\n", + "Downloading plotly-6.3.1-py3-none-any.whl (9.8 MB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.8/9.8 MB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n", + "\u001b[?25hDownloading narwhals-2.8.0-py3-none-any.whl (415 kB)\n", + "Installing collected packages: narwhals, plotly, doubleml\n", + "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", + "kats 0.2.0 requires ax-platform==0.2.4, which is not installed.\n", + "kats 0.2.0 requires deprecated>=1.2.12, which is not installed.\n", + "kats 0.2.0 requires fbprophet==0.7.1, which is not installed.\n", + "kats 0.2.0 requires gpytorch, which is not installed.\n", + "kats 0.2.0 requires holidays>=0.10.2, which is not installed.\n", + "kats 0.2.0 requires LunarCalendar>=0.0.9, which is not installed.\n", + "kats 0.2.0 requires parameterized>=0.8.1, which is not installed.\n", + "kats 0.2.0 requires pymannkendall>=1.4.1, which is not installed.\n", + "kats 0.2.0 requires pystan==2.19.1.1, which is not installed.\n", + "kats 0.2.0 requires pytest-mpl>=0.12, which is not installed.\n", + "kats 0.2.0 requires setuptools-git>=1.2, which is not installed.\n", + "kats 0.2.0 requires numpy<1.22,>=1.21, but you have numpy 1.25.2 which is incompatible.\n", + "kats 0.2.0 requires pandas<=1.3.5,>=1.0.4, but you have pandas 2.2.3 which is incompatible.\n", + "kats 0.2.0 requires scipy<1.8.0, but you have scipy 1.13.1 which is incompatible.\n", + "kats 0.2.0 requires statsmodels==0.12.2, but you have statsmodels 0.14.4 which is incompatible.\u001b[0m\u001b[31m\n", + "\u001b[0mSuccessfully installed doubleml-0.10.1 narwhals-2.8.0 plotly-6.3.1\n" + ] + } + ], "source": [ "!pip install doubleml" ] @@ -57,7 +141,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 4, "id": "7da54cf1", "metadata": {}, "outputs": [ @@ -65,7 +149,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Python 3.10.16\n" + "Python 3.9.21\n" ] } ], @@ -75,7 +159,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 5, "id": "2958a91c", "metadata": {}, "outputs": [ @@ -83,124 +167,120 @@ "name": "stdout", "output_type": "stream", "text": [ - "aiohappyeyeballs==2.6.1\n", - "aiohttp==3.12.14\n", - "aiosignal==1.4.0\n", - "appnope==0.1.4\n", - "asttokens==3.0.0\n", - "async-timeout==5.0.1\n", + "appdirs @ file:///home/conda/feedstock_root/build_artifacts/appdirs_1733753955715/work\n", + "appnope @ file:///home/conda/feedstock_root/build_artifacts/appnope_1733332318622/work\n", + "asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1733250440834/work\n", "attrs==25.3.0\n", - "babel==2.17.0\n", - "causalml==0.15.5\n", - "certifi==2025.7.9\n", - "cffi==2.0.0\n", - "charset-normalizer==3.4.2\n", - "citeproc-py==0.8.2\n", - "cloudpickle==3.1.1\n", - "comm==0.2.2\n", - "commonmark==0.9.1\n", - "contourpy==1.3.2\n", - "curl_cffi==0.13.0\n", - "cycler==0.12.1\n", - "debugpy==1.8.14\n", - "decorator==5.2.1\n", - "dill==0.4.0\n", - "dotenv==0.9.9\n", + "beautifulsoup4 @ file:///home/conda/feedstock_root/build_artifacts/beautifulsoup4_1738740337718/work\n", + "Brotli @ file:///Users/runner/miniforge3/conda-bld/brotli-split_1725267563793/work\n", + "Cartopy==0.23.0\n", + "certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1739515848642/work/certifi\n", + "cffi @ file:///Users/runner/miniforge3/conda-bld/cffi_1725560622100/work\n", + "charset-normalizer @ file:///home/conda/feedstock_root/build_artifacts/charset-normalizer_1735929714516/work\n", + "colorama @ file:///home/conda/feedstock_root/build_artifacts/colorama_1733218098505/work\n", + "comm @ file:///home/conda/feedstock_root/build_artifacts/comm_1733502965406/work\n", + "contourpy @ file:///Users/runner/miniforge3/conda-bld/contourpy_1729602398863/work\n", + "cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1733332471406/work\n", + "Cython @ file:///Users/runner/miniforge3/conda-bld/cython_1739227985601/work\n", + "dcor @ file:///home/conda/feedstock_root/build_artifacts/dcor_1735053801931/work\n", + "debugpy @ file:///Users/runner/miniforge3/conda-bld/debugpy_1741148420564/work\n", + "decorator @ file:///home/conda/feedstock_root/build_artifacts/decorator_1740384970518/work\n", "DoubleML==0.10.1\n", - "duecredit==0.10.2\n", - "econml==0.16.0\n", - "exceptiongroup==1.3.0\n", - "executing==2.2.0\n", - "faicons==0.2.2\n", + "exceptiongroup @ file:///home/conda/feedstock_root/build_artifacts/exceptiongroup_1733208806608/work\n", + "executing @ file:///home/conda/feedstock_root/build_artifacts/executing_1733569351617/work\n", + "fdasrsf @ file:///Users/runner/miniforge3/conda-bld/fdasrsf_1720366292086/work\n", "filelock==3.18.0\n", - "fonttools==4.58.5\n", - "forestci==0.6\n", - "formulaic==1.2.0\n", - "frozenlist==1.7.0\n", - "fsspec==2025.7.0\n", - "graphviz==0.21\n", - "great-tables==0.18.0\n", - "hf-xet==1.1.5\n", - "htmltools==0.6.0\n", - "huggingface-hub==0.34.1\n", - "idna==3.10\n", - "importlib_metadata==8.7.0\n", - "importlib_resources==6.5.2\n", - "interface-meta==1.3.0\n", - "ipykernel==6.29.5\n", - "ipython==8.37.0\n", - "jedi==0.19.2\n", - "joblib==1.5.1\n", - "jupyter_client==8.6.3\n", - "jupyter_core==5.8.1\n", - "kiwisolver==1.4.8\n", + "findiff @ file:///home/conda/feedstock_root/build_artifacts/findiff_1734853045161/work\n", + "fonttools @ file:///Users/runner/miniforge3/conda-bld/fonttools_1738940323940/work\n", + "frozendict @ file:///Users/runner/miniforge3/conda-bld/frozendict_1728841376066/work\n", + "fsspec==2025.3.2\n", + "GDAL==3.10.3\n", + "gmpy2 @ file:///Users/runner/miniforge3/conda-bld/gmpy2_1733462603229/work\n", + "h2 @ file:///home/conda/feedstock_root/build_artifacts/h2_1738578511449/work\n", + "hpack @ file:///home/conda/feedstock_root/build_artifacts/hpack_1737618293087/work\n", + "html5lib @ file:///home/conda/feedstock_root/build_artifacts/html5lib_1734075161666/work\n", + "hyperframe @ file:///home/conda/feedstock_root/build_artifacts/hyperframe_1737618333194/work\n", + "idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1733211830134/work\n", + "importlib_metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1737420181517/work\n", + "importlib_resources @ file:///home/conda/feedstock_root/build_artifacts/importlib_resources_1736252299705/work\n", + "ipykernel @ file:///Users/runner/miniforge3/conda-bld/ipykernel_1719845458456/work\n", + "ipython @ file:///home/conda/feedstock_root/build_artifacts/ipython_1701831663892/work\n", + "jedi @ file:///home/conda/feedstock_root/build_artifacts/jedi_1733300866624/work\n", + "Jinja2==3.1.6\n", + "joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1733736026804/work\n", + "jupyter_client @ file:///home/conda/feedstock_root/build_artifacts/jupyter_client_1733440914442/work\n", + "jupyter_core @ file:///home/conda/feedstock_root/build_artifacts/jupyter_core_1727163409502/work\n", + "kats==0.2.0\n", + "kiwisolver @ file:///Users/runner/miniforge3/conda-bld/kiwisolver_1725459226886/work\n", + "lazy_loader @ file:///home/conda/feedstock_root/build_artifacts/lazy-loader_1733636780672/work\n", "lightgbm==4.6.0\n", - "llvmlite==0.44.0\n", - "looseversion==1.3.0\n", - "lxml==6.0.0\n", - "matplotlib==3.10.3\n", - "matplotlib-inline==0.1.7\n", - "multidict==6.6.3\n", - "multiprocess==0.70.18\n", - "narwhals==2.5.0\n", - "nest-asyncio==1.6.0\n", - "numba==0.61.2\n", - "numpy==2.2.6\n", - "packaging==25.0\n", - "pandas==2.3.1\n", - "pandas-datareader==0.10.0\n", - "parso==0.8.4\n", - "pathos==0.2.9\n", - "patsy==1.0.1\n", - "pexpect==4.9.0\n", - "pillow==11.3.0\n", - "platformdirs==4.3.8\n", - "plotly==6.3.0\n", - "pox==0.3.6\n", - "ppft==1.7.7\n", - "prompt_toolkit==3.0.51\n", - "propcache==0.3.2\n", - "psutil==7.0.0\n", - "psycopg2-binary==2.9.10\n", - "ptyprocess==0.7.0\n", - "pure_eval==0.2.3\n", - "pyarrow==21.0.0\n", - "pycparser==2.23\n", - "pydotplus==2.0.2\n", - "pyfixest==0.30.2\n", - "Pygments==2.19.2\n", - "pyparsing==3.2.3\n", - "python-dateutil==2.9.0.post0\n", - "python-dotenv==1.1.1\n", - "pytz==2025.2\n", - "PyYAML==6.0.2\n", - "pyzmq==27.0.0\n", - "requests==2.32.4\n", - "scikit-learn==1.7.2\n", - "scipy==1.15.3\n", - "seaborn==0.13.2\n", - "shap==0.48.0\n", - "six==1.17.0\n", - "slicer==0.0.8\n", - "sparse==0.17.0\n", - "SQLAlchemy==2.0.43\n", - "stack-data==0.6.3\n", - "statsmodels==0.14.5\n", - "tabulate==0.9.0\n", - "threadpoolctl==3.6.0\n", - "tidyfinance==0.1.2\n", - "toolz==1.0.0\n", - "tornado==6.5.1\n", - "tqdm==4.67.1\n", - "traitlets==5.14.3\n", - "typing_extensions==4.14.1\n", - "tzdata==2025.2\n", - "urllib3==2.5.0\n", - "wcwidth==0.2.13\n", - "wrapt==1.17.3\n", - "xgboost==3.0.2\n", - "yarl==1.20.1\n", - "zipp==3.23.0\n" + "llvmlite==0.43.0\n", + "lxml @ file:///Users/runner/miniforge3/conda-bld/lxml_1739211617787/work\n", + "MarkupSafe==3.0.2\n", + "matplotlib==3.9.4\n", + "matplotlib-inline @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-inline_1733416936468/work\n", + "mpmath @ file:///home/conda/feedstock_root/build_artifacts/mpmath_1733302684489/work\n", + "multimethod @ file:///home/conda/feedstock_root/build_artifacts/multimethod_1735317539007/work\n", + "multitasking @ file:///home/conda/feedstock_root/build_artifacts/multitasking_1622493113162/work\n", + "munkres==1.1.4\n", + "narwhals==2.8.0\n", + "nest_asyncio @ file:///home/conda/feedstock_root/build_artifacts/nest-asyncio_1733325553580/work\n", + "networkx==3.2.1\n", + "numba @ file:///Users/runner/miniforge3/conda-bld/numba_1718888154750/work\n", + "numpy @ file:///Users/runner/miniforge3/conda-bld/numpy_1691056333838/work\n", + "packaging==21.3\n", + "pandas @ file:///Users/runner/miniforge3/conda-bld/pandas_1726878429351/work\n", + "parso @ file:///home/conda/feedstock_root/build_artifacts/parso_1733271261340/work\n", + "patsy @ file:///home/conda/feedstock_root/build_artifacts/patsy_1733792384640/work\n", + "peewee @ file:///Users/runner/miniforge3/conda-bld/peewee_1738788875154/work\n", + "pexpect @ file:///home/conda/feedstock_root/build_artifacts/pexpect_1733301927746/work\n", + "pickleshare @ file:///home/conda/feedstock_root/build_artifacts/pickleshare_1733327343728/work\n", + "pillow @ file:///Users/runner/miniforge3/conda-bld/pillow_1735929738355/work\n", + "platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1733232627818/work\n", + "plotly==6.3.1\n", + "prompt_toolkit @ file:///home/conda/feedstock_root/build_artifacts/prompt-toolkit_1737453357274/work\n", + "psutil @ file:///Users/runner/miniforge3/conda-bld/psutil_1740663174295/work\n", + "ptyprocess @ file:///home/conda/feedstock_root/build_artifacts/ptyprocess_1733302279685/work/dist/ptyprocess-0.7.0-py2.py3-none-any.whl#sha256=92c32ff62b5fd8cf325bec5ab90d7be3d2a8ca8c8a3813ff487a8d2002630d1f\n", + "pure_eval @ file:///home/conda/feedstock_root/build_artifacts/pure_eval_1733569405015/work\n", + "pycparser @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_pycparser_1733195786/work\n", + "Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1736243443484/work\n", + "pyparsing==3.2.1\n", + "pyproj==3.6.1\n", + "pyshp==2.3.1\n", + "PySocks @ file:///home/conda/feedstock_root/build_artifacts/pysocks_1733217236728/work\n", + "python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1733215673016/work\n", + "pytz @ file:///home/conda/feedstock_root/build_artifacts/pytz_1706886791323/work\n", + "pyzmq @ file:///Users/runner/miniforge3/conda-bld/pyzmq_1741805197810/work\n", + "rdata @ file:///home/conda/feedstock_root/build_artifacts/rdata_1736508756573/work\n", + "requests @ file:///home/conda/feedstock_root/build_artifacts/requests_1733217035951/work\n", + "ruptures==1.1.9\n", + "scikit-datasets @ file:///home/conda/feedstock_root/build_artifacts/scikit-datasets_1735341255296/work\n", + "scikit-fda==0.6\n", + "scikit-learn @ file:///Users/runner/miniforge3/conda-bld/scikit-learn_1736496791599/work/dist/scikit_learn-1.6.1-cp39-cp39-macosx_11_0_arm64.whl#sha256=aaca544017450d0f614af6e4c06601e2aa132d6dfbb957b49e7c5fc3b37f6417\n", + "scipy @ file:///Users/runner/miniforge3/conda-bld/scipy-split_1716470312029/work/dist/scipy-1.13.1-cp39-cp39-macosx_11_0_arm64.whl#sha256=95cc9a6aceed50037865da4a45baac05fd0dcee7e557c6149fde270f2ffebafc\n", + "seaborn @ file:///home/conda/feedstock_root/build_artifacts/seaborn-split_1733730015268/work\n", + "shapely==2.0.7\n", + "six @ file:///home/conda/feedstock_root/build_artifacts/six_1733380938961/work\n", + "soupsieve @ file:///home/conda/feedstock_root/build_artifacts/soupsieve_1693929250441/work\n", + "stack_data @ file:///home/conda/feedstock_root/build_artifacts/stack_data_1733569443808/work\n", + "statsmodels @ file:///Users/runner/miniforge3/conda-bld/statsmodels_1727986732968/work\n", + "sympy @ file:///home/conda/feedstock_root/build_artifacts/sympy_1736248176451/work\n", + "threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1741878222898/work\n", + "toolz==1.1.0\n", + "torch==2.7.0\n", + "tornado @ file:///Users/runner/miniforge3/conda-bld/tornado_1732615925783/work\n", + "tqdm @ file:///home/conda/feedstock_root/build_artifacts/tqdm_1735661334605/work\n", + "traitlets @ file:///home/conda/feedstock_root/build_artifacts/traitlets_1733367359838/work\n", + "typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1733188668063/work\n", + "tzdata @ file:///home/conda/feedstock_root/build_artifacts/python-tzdata_1737541069190/work\n", + "unicodedata2 @ file:///Users/runner/miniforge3/conda-bld/unicodedata2_1736692557404/work\n", + "urllib3 @ file:///home/conda/feedstock_root/build_artifacts/urllib3_1734859416348/work\n", + "wcwidth @ file:///home/conda/feedstock_root/build_artifacts/wcwidth_1733231326287/work\n", + "webencodings @ file:///home/conda/feedstock_root/build_artifacts/webencodings_1733236011802/work\n", + "xarray @ file:///home/conda/feedstock_root/build_artifacts/xarray_1722348170975/work\n", + "yfinance @ file:///home/conda/feedstock_root/build_artifacts/yfinance_1739938562631/work\n", + "zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1732827521216/work\n", + "zstandard==0.23.0\n" ] } ], @@ -218,7 +298,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 6, "id": "2c650ac3", "metadata": {}, "outputs": [], @@ -270,7 +350,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "d17c7963", "metadata": { "ExecuteTime": { @@ -373,7 +453,7 @@ "4 2021-05-05 5 S 0 0.0 49.0 0" ] }, - "execution_count": 68, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -400,7 +480,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 8, "id": "3d6cdba1", "metadata": { "ExecuteTime": { @@ -470,7 +550,7 @@ "1 2021-05-15 2021-06-01" ] }, - "execution_count": 59, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -484,7 +564,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 9, "id": "355d9c2c", "metadata": { "ExecuteTime": { @@ -561,7 +641,7 @@ " 1 51.858025 2021-05-15" ] }, - "execution_count": 60, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -575,8 +655,6 @@ ] }, { - - "attachments": { "image.png": { "image/png": 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" @@ -591,7 +669,6 @@ ] }, { - "cell_type": "markdown", "id": "2614a652", "metadata": {}, @@ -624,7 +701,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 10, "id": "79bcb7fe", "metadata": { "ExecuteTime": { @@ -636,10 +713,10 @@ { "data": { "text/plain": [ - "np.float64(0.6917359536407233)" + "0.6917359536407233" ] }, - "execution_count": 61, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -655,7 +732,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 11, "id": "b51d6822", "metadata": { "ExecuteTime": { @@ -667,10 +744,10 @@ { "data": { "text/plain": [ - "np.float64(0.7660316402518457)" + "0.7660316402518457" ] }, - "execution_count": 62, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -695,7 +772,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 12, "id": "10e16d8d", "metadata": { "ExecuteTime": { @@ -774,7 +851,7 @@ "197 1.595238 1" ] }, - "execution_count": 63, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -794,7 +871,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 13, "id": "31be6542", "metadata": { "ExecuteTime": { @@ -806,10 +883,10 @@ { "data": { "text/plain": [ - "np.float64(0.6917359536407155)" + "0.6917359536407155" ] }, - "execution_count": 64, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -829,7 +906,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 14, "id": "57032287", "metadata": {}, "outputs": [ @@ -901,7 +978,7 @@ " 1 51.858025 2021-05-15" ] }, - "execution_count": 65, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -912,7 +989,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 15, "id": "ff0261df", "metadata": { "ExecuteTime": { @@ -927,16 +1004,16 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 66, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -1004,7 +1081,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 16, "id": "bead249f", "metadata": { "ExecuteTime": { @@ -1096,7 +1173,7 @@ "4 20 0 48.785714 2021-05-01 0" ] }, - "execution_count": 25, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -1129,7 +1206,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "54757217", "metadata": { "ExecuteTime": { @@ -1141,10 +1218,10 @@ { "data": { "text/plain": [ - "np.float64(0.6917359536407082)" + "0.6917359536407282" ] }, - "execution_count": 24, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1171,7 +1248,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 18, "id": "d1eed2c4", "metadata": { "ExecuteTime": { @@ -1185,7 +1262,7 @@ "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -1230,7 +1307,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "e01430de", "metadata": {}, "outputs": [ @@ -1397,7 +1474,7 @@ "[1632 rows x 7 columns]" ] }, - "execution_count": 92, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1432,7 +1509,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 20, "id": "647b569a", "metadata": { "ExecuteTime": { @@ -1444,10 +1521,10 @@ { "data": { "text/plain": [ - "np.float64(0.6917359536406855)" + "0.6917359536406944" ] }, - "execution_count": 26, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1490,7 +1567,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 21, "id": "e847ddef", "metadata": {}, "outputs": [ @@ -1498,7 +1575,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "ATT: 0.6917359536406855\n" + "ATT: 0.6917359536406944\n" ] }, { @@ -1509,7 +1586,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 38, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1532,7 +1609,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 22, "id": "fe572c5d", "metadata": {}, "outputs": [ @@ -1540,7 +1617,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "ATT: 0.6917359536406855\n" + "ATT: 0.6917359536406944\n" ] }, { @@ -1551,7 +1628,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 39, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1584,7 +1661,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 23, "id": "f80b7263", "metadata": {}, "outputs": [ @@ -1592,7 +1669,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "DID estimate: 0.6917359536407248\n" + "DID estimate: 0.6917359536407054\n" ] } ], @@ -1626,7 +1703,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 24, "id": "0f3be3b1", "metadata": {}, "outputs": [ @@ -1634,7 +1711,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "ATT: 0.6917359536407064\n" + "ATT: 0.6917359536407496\n" ] }, { @@ -1645,7 +1722,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 38, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1668,7 +1745,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 25, "id": "9c0290e8", "metadata": {}, "outputs": [ @@ -1676,7 +1753,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "ATT: 0.6917359536407064\n" + "ATT: 0.6917359536407496\n" ] }, { @@ -1687,7 +1764,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 39, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -1711,7 +1788,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 26, "id": "83d3cfda", "metadata": {}, "outputs": [ @@ -1719,7 +1796,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "ATT: 0.6917359536407248\n" + "ATT: 0.6917359536407054\n" ] }, { @@ -1730,7 +1807,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 40, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -1753,7 +1830,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 27, "id": "edd9ec8e", "metadata": {}, "outputs": [ @@ -1761,7 +1838,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "ATT: 0.6917359536407248\n" + "ATT: 0.6917359536407054\n" ] }, { @@ -1772,7 +1849,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 36, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -1786,6 +1863,33 @@ "m.conf_int().loc[\"treated:post\"]" ] }, + { + "cell_type": "markdown", + "id": "84e61522", + "metadata": {}, + "source": [ + "##### 추정된 ATT는 동일한데 왜 데이터 집계 방식에 따라 왜 신뢰구간 추정이 달라지는가? \n", + "\n", + "\n", + "\\begin{array}{lcc}\n", + "\\textbf{구분} & \\textbf{기존 표준오차 (nonrobust)} & \\textbf{군집 표준오차 (cluster-robust)} \\\\ \n", + "\\hline\n", + "집계방식 1 (pre/post 평균형) & [0.4099 , 0.9736] & [0.1382 , 1.2453] \\\\\n", + "집계방식 2 (개별 시점형) & [0.5152 , 0.8683] & [0.4693 , 0.9142] \\\\\n", + "\\end{array}\n", + "\n", + "\n", + "\n", + "두 방식의 신뢰구간이 달라지는 이유는\n", + "데이터의 집계 수준이 다르기 때문입니다.\n", + "\n", + "집계형 방식(집계 방식 1)은 정보량이 적고 자유도가 작아 표준오차가 커지기 쉬워 신뢰구간이 넓어질 가능성이 높고,\n", + "\n", + "개별 시점형 방식(집계 방식2)은 더 많은 표본과 변동을 활용하므로 표준오차가 작아져 신뢰구간이 오히려 더 좁게 나올 수 있습니다.\n", + "\n", + "\n" + ] + }, { "cell_type": "markdown", "id": "013fd5ae", @@ -1805,7 +1909,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 147, "id": "95d777fa", "metadata": {}, "outputs": [], @@ -1816,13 +1920,211 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 148, + "id": "00aefefa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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6400 rows × 7 columns

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" + ], + "text/plain": [ + " date city region treated tau downloads post\n", + "0 2021-05-01 1 W 0 0.0 27.0 0\n", + "1 2021-05-02 1 W 0 0.0 28.0 0\n", + "2 2021-05-03 1 W 0 0.0 28.0 0\n", + "3 2021-05-04 1 W 0 0.0 26.0 0\n", + "4 2021-05-05 1 W 0 0.0 28.0 0\n", + "... ... ... ... ... ... ... ...\n", + "6395 2021-05-28 200 W 0 0.0 35.0 1\n", + "6396 2021-05-29 200 W 0 0.0 31.0 1\n", + "6397 2021-05-30 200 W 0 0.0 33.0 1\n", + "6398 2021-05-31 200 W 0 0.0 32.0 1\n", + "6399 2021-06-01 200 W 0 0.0 33.0 1\n", + "\n", + "[6400 rows x 7 columns]" + ] + }, + "execution_count": 148, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mkt_data_all" + ] + }, + { + "cell_type": "code", + "execution_count": 29, "id": "9f347bae", "metadata": {}, "outputs": [ { "data": { - "image/png": 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+ "text/plain": [ + "(array([18748., 18752., 18756., 18760., 18764., 18768., 18772., 18776.,\n", + " 18779.]),\n", + " [Text(18748.0, 0, '2021-05-01'),\n", + " Text(18752.0, 0, '2021-05-05'),\n", + " Text(18756.0, 0, '2021-05-09'),\n", + " Text(18760.0, 0, '2021-05-13'),\n", + " Text(18764.0, 0, '2021-05-17'),\n", + " Text(18768.0, 0, '2021-05-21'),\n", + " Text(18772.0, 0, '2021-05-25'),\n", + " Text(18776.0, 0, '2021-05-29'),\n", + " Text(18779.0, 0, '2021-06-01')])" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" ] @@ -1863,7 +2165,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 30, "id": "71afe601", "metadata": {}, "outputs": [ @@ -1889,7 +2191,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 31, "id": "0f035c0d", "metadata": {}, "outputs": [ @@ -1903,7 +2205,7 @@ "dtype: float64" ] }, - "execution_count": 48, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -1926,7 +2228,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "id": "b88f37a8", "metadata": {}, "outputs": [ @@ -1934,8 +2236,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Weighted ATT: 1.6940400451471986\n", - "95% CI: (np.float64(1.3897593237876618), np.float64(1.9983207665067355))\n" + "Weighted ATT: 1.6940400451471702\n", + "95% CI: (1.3897593237876387, 1.9983207665067018)\n" ] } ], @@ -2000,7 +2302,7 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": null, "id": "e93ea8d4", "metadata": {}, "outputs": [ @@ -2067,7 +2369,7 @@ "" ] }, - "execution_count": 71, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -2097,7 +2399,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 34, "id": "743398c6", "metadata": {}, "outputs": [ @@ -2105,7 +2407,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "ATT: 1.6810982546487103\n" + "ATT: 1.6810982546486941\n" ] }, { @@ -2116,7 +2418,7 @@ "Name: post:treated, dtype: float64" ] }, - "execution_count": 72, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } @@ -2128,611 +2430,1808 @@ }, { "cell_type": "markdown", - "id": "0b985fca", - "metadata": {}, - "source": [ - "#### DML을 이용한 DID\n", - "\n", - "- 공변량과 결과 변수, 공변량과 처치 변수 간의 복잡한 비선형 관계를 머신러닝 모델로 예측한 후, 이 잔차(residuals)를 사용하여 DiD 효과를 추정하는 방법입니다.\n", - "- 고차원적인 공변량을 유연하게 처리하고, 머신러닝의 예측력을 활용하여 잠재적인 편향을 줄입니다. 특히 이질적인 처치 효과를 다루는 데 강점이 있습니다.\n", - "- 유연성, 견고성, 고차원 데이터 처리 능력이 우수합니다.\n", - "- 다만, 모델 복잡성이 증가하고, 구현 및 해석이 어려울 수 있습니다." - ] - }, - { - "cell_type": "markdown", - "id": "3d522a65", - "metadata": {}, - "source": [ - " Data 생성" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "723b9832", + "id": "4e1cddba", "metadata": {}, - "outputs": [], "source": [ + "#### 3.5 Staggered DiD\n", + "**Staggered DiD: Canonical vs Dynamic View**\n", "\n", + "| 구분 | Canonical View | Dynamic (Event-study) View |\n", + "|:--|:--|:--|\n", + "| **핵심 아이디어** | Staggered DiD는 *canonical DiD의 확장형*, 여러 시점과 그룹에 반복 적용된 2×2 DiD 구조 | Staggered DiD를 *event-time 기준*으로 재정렬하여 시점별 효과 $\\beta_k$ 추정 (Dynamic DID 형태) |\n", + "| **초점** | 평균 처치 효과 (ATT) | 시간에 따른 처치 효과 변화 (dynamic ATT) |\n", + "| **처치 시점** | 모든 단위의 개입 시점 동일하거나, 시점별 DiD 반복 | 단위별로 상이한 개입 시점 (staggered adoption) |\n", + "| **대표 모형** | $Y_{it} = \\alpha_i + \\lambda_t + \\beta D_{it} + \\epsilon_{it}$| $Y_{it} = \\alpha_i + \\lambda_t + \\sum_k \\beta_k \\cdot 1\\{t - G_i = k\\} + \\epsilon_{it}$|\n", + "| **요약** | 구조적으로는 canonical DID의 반복적 적용 | 추정 관점에서는 event-study 기반 Dynamic DID로 해석 가능 \n", "\n", "\n", - "def make_custom_did(n_obs=1000, n_time_periods=5, seed=None):\n", - " if seed is not None:\n", - " np.random.seed(seed)\n", - "\n", - " time_periods = (np.arange(2*n_time_periods) - n_time_periods)\n", - "\n", - " # fixed effects\n", - " theta = np.zeros(shape=(n_obs, 2*n_time_periods)) + time_periods\n", - " eta = np.random.normal(loc=0, scale=1, size=(n_obs,1))\n", - "\n", - " # covariates\n", - " X = np.random.normal(loc=0, scale=1, size=(n_obs, 4, 2*n_time_periods))\n", - "\n", - " # treatment effects\n", - " mu_means = np.concatenate((np.zeros(n_time_periods), np.arange(n_time_periods, 0, -1)))\n", - " mu = np.random.normal(loc=0, scale=1, size=(n_obs, 2*n_time_periods)) + mu_means\n", - "\n", - " # treatment assignment\n", - " f_ps = 0.75*(-X[:, 0, 0] + 0.5*X[:, 1, 0] - 0.25*X[:, 2, 0] \n", - " - 0.1*X[:, 3, 0]*X[:, 2, 0] + np.cos(5*X[:, 1, 0]))\n", - " ps = (np.exp(f_ps) / (1 + np.exp(f_ps))).reshape(-1,1)\n", - " u = np.random.uniform(low=0, high=1, size=(n_obs,1))\n", - " treatment = np.ones(shape=(n_obs, 2*n_time_periods)) * (ps >= u)\n", - "\n", - " # outcome\n", - " g_X = (np.exp(X[:, 1, :]) - np.sin(5*X[:, 2, :]) + 2*X[:, 3, :])\n", - " epsilon = np.random.normal(loc=0, scale=1, size=(n_obs, 2*n_time_periods))\n", - " Y = theta + eta + treatment*mu + g_X + epsilon\n", - "\n", - " # reshape to long format\n", - " Y_df = Y.reshape(-1)\n", - " d_df = treatment.reshape(-1)\n", - " t_df = np.tile(time_periods, n_obs)\n", - " i_df = np.repeat(np.arange(n_obs), 2*n_time_periods)\n", - " X_df = X.transpose(0,2,1).reshape(-1, 4)\n", - "\n", - " data = pd.DataFrame({\n", - " 'y': Y_df,\n", - " 'd': d_df,\n", - " 't': t_df,\n", - " 'i': i_df,\n", - " 'X0': X_df[:,0],\n", - " 'X1': X_df[:,1],\n", - " 'X2': X_df[:,2],\n", - " 'X3': X_df[:,3]\n", - " })\n", - " \n", - " # True ATT = 사후 기간 효과 평균\n", - " true_att = mu_means[n_time_periods:].mean()\n", - " \n", - " return data, true_att,mu_means\n", - "\n", - "def did_to_dml_format(data):\n", - " \"\"\"\n", - " make_custom_did()에서 생성된 long-format DataFrame -> DoubleMLDID용 데이터 변환\n", - " \"\"\"\n", - "\n", - " # 사전(pre, t<0), 사후(post, t>=0) 구분\n", - " pre = data[data['t'] < 0]\n", - " post = data[data['t'] >= 0]\n", - "\n", - " # (1) outcome: 개체별 (post 평균 - pre 평균)\n", - " y_diff = post.groupby('i')['y'].mean().values - pre.groupby('i')['y'].mean().values\n", - "\n", - " # (2) treatment: 개체별 사후처치 여부 (post에서 하나만 뽑으면 됨)\n", - " d = post.groupby('i')['d'].first().astype(int).values\n", - "\n", - " # (3) covariates: 개체별 pre-treatment covariates (t<0에서 첫 번째 시점 사용)\n", - " x = pre.groupby('i')[['X0', 'X1', 'X2', 'X3']].first().values\n", - "\n", - " # DoubleMLData 입력용\n", - " dml_data = DoubleMLData.from_arrays(x=x, y=y_diff, d=d)\n", - "\n", - " return dml_data\n", - "\n", - "\n", - "\n", - "data, true_att,_ = make_custom_did(n_obs=1000, n_time_periods=5, seed=42)\n", - "\n", - "dml_data = did_to_dml_format(data)" + "**⇒ Staggered DiD는 canonical DID의 확장형이면서도, event-study 기반 Dynamic DID로 해석될 수 있음.**" ] }, { - "cell_type": "markdown", - "id": "dc414e35", + "cell_type": "code", + "execution_count": 38, + "id": "0ba27a12", "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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datecityregioncohorttreatedtaudownloadspost
02021-05-011W2021-06-2010.027.00
12021-05-021W2021-06-2010.028.00
22021-05-031W2021-06-2010.028.00
32021-05-041W2021-06-2010.026.00
42021-05-051W2021-06-2010.028.00
\n", + "
" + ], + "text/plain": [ + " date city region cohort treated tau downloads post\n", + "0 2021-05-01 1 W 2021-06-20 1 0.0 27.0 0\n", + "1 2021-05-02 1 W 2021-06-20 1 0.0 28.0 0\n", + "2 2021-05-03 1 W 2021-06-20 1 0.0 28.0 0\n", + "3 2021-05-04 1 W 2021-06-20 1 0.0 26.0 0\n", + "4 2021-05-05 1 W 2021-06-20 1 0.0 28.0 0" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mkt_data_cohorts = (pd.read_csv(\"../data/matheus_data/offline_mkt_staggered.csv\")\n", + " .astype({\n", + " \"date\":\"datetime64[ns]\",\n", + " \"cohort\":\"datetime64[ns]\"}))\n", + "\n", + "mkt_data_cohorts.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "5bdcba1b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt_data = (mkt_data_cohorts\n", + " .astype({\"date\":\"str\"})\n", + " .assign(treated_post = lambda d: d[\"treated\"]*(d[\"date\"]>=d[\"cohort\"]))\n", + " .pivot(index=\"city\", columns=\"date\", values=\"treated_post\") \n", + " .reset_index()\n", + " .sort_values(list(sorted(mkt_data_cohorts.query(\"cohort!='2100-01-01'\")[\"cohort\"].astype(\"str\").unique())), ascending=False)\n", + " .reset_index()\n", + " .drop(columns=[\"city\"])\n", + " .rename(columns={\"index\":\"city\"})\n", + " .set_index(\"city\"))\n", + "\n", + "\n", + "\n", + "plt.figure(figsize=(16,8))\n", + "\n", + "sns.heatmap(plt_data, cmap=\"gray\",cbar=False)\n", + "plt.text(18, 18, \"Cohort$=G_{05/15}$\", size=14)\n", + "plt.text(38, 65, \"Cohort$=G_{06/04}$\", size=14)\n", + "plt.text(55, 110, \"Cohort$=G_{06/20}$\", size=14)\n", + "plt.text(35, 170, \"Cohort$=G_{\\\\infty}$\", color=\"white\", size=14, weight=3);" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "14f2b2db", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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datecityregioncohorttreatedtaudownloadspost
02021-05-011W2021-06-2010.027.00
12021-05-021W2021-06-2010.028.00
22021-05-031W2021-06-2010.028.00
32021-05-041W2021-06-2010.026.00
42021-05-051W2021-06-2010.028.00
\n", + "
" + ], + "text/plain": [ + " date city region cohort treated tau downloads post\n", + "0 2021-05-01 1 W 2021-06-20 1 0.0 27.0 0\n", + "1 2021-05-02 1 W 2021-06-20 1 0.0 28.0 0\n", + "2 2021-05-03 1 W 2021-06-20 1 0.0 28.0 0\n", + "3 2021-05-04 1 W 2021-06-20 1 0.0 26.0 0\n", + "4 2021-05-05 1 W 2021-06-20 1 0.0 28.0 0" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mkt_data_cohorts_w = mkt_data_cohorts.query(\"region=='W'\")\n", + "mkt_data_cohorts_w.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "9fefb75f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(15, 10))\n", + "\n", + "plt_data = (mkt_data_cohorts_w\n", + " .groupby([\"date\", \"cohort\"])\n", + " [[\"downloads\"]]\n", + " .mean()\n", + " .reset_index()\n", + ")\n", + "\n", + "\n", + "\n", + "for color, cohort in zip([\"C0\", \"C1\", \"C2\", \"C3\"], mkt_data_cohorts_w.query(\"cohort!='2100-01-01'\")[\"cohort\"].unique()):\n", + " df_cohort = plt_data.query(\"cohort==@cohort\")\n", + " sns.lineplot(data=df_cohort, x=\"date\", y=\"downloads\",\n", + " label=pd.to_datetime(cohort).strftime('%Y-%m-%d'), ax=ax1)\n", + " ax1.vlines(x=cohort, ymin=25, ymax=50, color=color, ls=\"dotted\", lw=3)\n", + " \n", + " \n", + "sns.lineplot(data=plt_data.query(\"cohort=='2100-01-01'\"), x=\"date\", y=\"downloads\", label=\"$\\infty$\", lw=4, ls=\"-.\", ax=ax1)\n", + " \n", + "ax1.legend()\n", + "ax1.set_title(\"Multiple Cohorts - West Region\");\n", + "\n", + "\n", + "plt_data = (mkt_data_cohorts_w\n", + " .assign(days_to_treatment = lambda d: (pd.to_datetime(d[\"date\"])-pd.to_datetime(d[\"cohort\"])).dt.days)\n", + " .groupby([\"date\", \"cohort\"])\n", + " [[\"downloads\", \"days_to_treatment\"]]\n", + " .mean()\n", + " .reset_index()\n", + ")\n", + "\n", + "\n", + "for color, cohort in zip([\"C0\", \"C1\", \"C2\", \"C3\"], mkt_data_cohorts_w.query(\"cohort!='2100-01-01'\")[\"cohort\"].unique()):\n", + " df_cohort = plt_data.query(\"cohort==@cohort\")\n", + " sns.lineplot(data=df_cohort, x=\"days_to_treatment\", y=\"downloads\",\n", + " label=pd.to_datetime(cohort).strftime('%Y-%m-%d'), ax=ax2)\n", + "\n", + "ax2.vlines(x=0, ymin=25, ymax=50, color=\"black\", ls=\"dotted\", lw=3)\n", + "\n", + "ax2.set_title(\"Multiple Cohorts (Aligned) - West Region\")\n", + "ax2.legend();\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "cc54004d", + "metadata": {}, + "outputs": [], + "source": [ + "mkt_data_cohorts_w['date'] = mkt_data_cohorts_w['date'].dt.strftime('%Y-%m-%d')\n", + "mkt_data_cohorts_w['cohort'] = mkt_data_cohorts_w['cohort'].astype(str)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "c6d3aeb0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of param.: 510\n", + "True Effect: 2.2625252108176266\n", + "Pred. Effect: 2.2597661446850026\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "formula = \"downloads ~ treated:post:C(cohort):C(date) + C(city) + C(date)\"\n", + "\n", + "twfe_model = smf.ols(formula, data=mkt_data_cohorts_w.astype({\"date\":str, \"cohort\": str})).fit()\n", + "\n", + "effects = (twfe_model.params[twfe_model.params.index.str.contains(\"treated\")]\n", + " .reset_index()\n", + " .rename(columns={0:\"param\"})\n", + " .assign(cohort=lambda d: d[\"index\"].str.extract(r'C\\(cohort\\)\\[(.*)\\]:'))\n", + " .assign(date=lambda d: d[\"index\"].str.extract(r':C\\(date\\)\\[(.*)\\]'))\n", + " .assign(date=lambda d: pd.to_datetime(d[\"date\"]), cohort=lambda d: pd.to_datetime(d[\"cohort\"])))\n", + "\n", + "plt.figure(figsize=(10,4))\n", + "sns.lineplot(data=effects, x=\"date\", y=\"param\", hue=\"cohort\", palette=\"gray\")\n", + "plt.xticks(rotation=45)\n", + "plt.ylabel(\"Estimated Effect\")\n", + "plt.legend(fontsize=12)\n", + "\n", + "df_pred = (\n", + " mkt_data_cohorts_w\n", + " .query(\"post==1 & treated==1\")\n", + " .assign(date=lambda d: d['date'].astype(str)) # Convert to string\n", + " .assign(y_hat_0=lambda d: twfe_model.predict(d.assign(treated=0)))\n", + " .assign(effect_hat=lambda d: d[\"downloads\"] - d[\"y_hat_0\"])\n", + ")\n", + "\n", + "print(\"Number of param.:\", len(twfe_model.params))\n", + "print(\"True Effect: \", df_pred[\"tau\"].mean())\n", + "print(\"Pred. Effect: \", df_pred[\"effect_hat\"].mean())" + ] + }, + { + "cell_type": "markdown", + "id": "63798d42", + "metadata": {}, + "source": [ + "#### 3.6 Doubly Robust Diff-in-Diff (DRDiD)\n", + "\n", + "DRDID는 기존 차분 분석(Difference-in-Differences, DiD)의 확장된 형태로, 치료 효과를 더욱 견고하게 추정하는 방법입니다. \n", + "\n", + "성향 점수 모델(Propensity Score Model)과 결과 모델(Delta Outcome Model)이라는 두 가지 모델을 동시에 사용하여 공변량(covariates)을 조정하며, 이 두 모델 중 하나만 올바르게 지정되어도 편향 없는(unbiased) 추정치를 얻을 수 있어 신뢰성이 높습니다. \n", + "\n", + "이는 DiD의 평행 추세 가정을 조건부로 완화하고, 복잡한 현실 데이터에서 보다 정확한 인과 효과를 파악하는 데 유용합니다.\n", + "\n", + "##### Step1: Propensity Score Model" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "id": "e6c407d4", + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "id": "736bd702", + "metadata": {}, + "outputs": [], + "source": [ + "unit_df = (mkt_data_all\n", + " # keep only the first date\n", + " .astype({\"date\": str})\n", + " .query(f\"date=='{mkt_data_all['date'].astype(str).min()}'\")\n", + " .drop(columns=[\"date\"])) # just to avoid confusion\n", + "\n", + "ps_model = smf.logit(\"treated~C(region)\", data=unit_df).fit(disp=0)" + ] + }, + { + "cell_type": "markdown", + "id": "3a727727", + "metadata": {}, + "source": [ + "##### Step 2 Delta Outcome Model" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "id": "ac26b60b", + "metadata": {}, + "outputs": [], + "source": [ + "delta_y = (\n", + " mkt_data_all.query(\"post==1\").groupby(\"city\")[\"downloads\"].mean()\n", + " - mkt_data_all.query(\"post==0\").groupby(\"city\")[\"downloads\"].mean()\n", + ")\n", + "\n", + "\n", + "df_delta_y = (unit_df\n", + " .set_index(\"city\")\n", + " .join(delta_y.rename(\"delta_y\")))\n", + "\n", + "outcome_model = smf.ols(\"delta_y ~ C(region)\", data=df_delta_y).fit()" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "id": "d96b2f0e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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regiontreatedtaudownloadspostdelta_yy_hatps
city
1W00.027.003.0873023.7365390.176471
2N00.040.001.4365081.9925700.212766
3W00.030.002.7619053.7365390.176471
4W00.026.003.3968253.7365390.176471
5S00.051.00-0.4761900.3439150.176471
\n", + "
" + ], + "text/plain": [ + " region treated tau downloads post delta_y y_hat ps\n", + "city \n", + "1 W 0 0.0 27.0 0 3.087302 3.736539 0.176471\n", + "2 N 0 0.0 40.0 0 1.436508 1.992570 0.212766\n", + "3 W 0 0.0 30.0 0 2.761905 3.736539 0.176471\n", + "4 W 0 0.0 26.0 0 3.396825 3.736539 0.176471\n", + "5 S 0 0.0 51.0 0 -0.476190 0.343915 0.176471" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "Learners 설정\n" + "df_dr = (df_delta_y\n", + " .assign(y_hat = lambda d: outcome_model.predict(d))\n", + " .assign(ps = lambda d: ps_model.predict(d)))\n", + "\n", + "df_dr.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "id": "18eeff30", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 1.6773180394442855\n" + ] + } + ], + "source": [ + "tr = df_dr.query(\"treated==1\")\n", + "co = df_dr.query(\"treated==0\")\n", + "\n", + "dy1_treat = (tr[\"delta_y\"] - tr[\"y_hat\"]).mean()\n", + "\n", + "w_cont = co[\"ps\"]/(1-co[\"ps\"])\n", + "dy0_treat = np.average(co[\"delta_y\"] - co[\"y_hat\"], weights=w_cont)\n", + "\n", + "print(\"ATT:\", dy1_treat - dy0_treat)" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "id": "f163f968", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['S'], dtype=object)" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mkt_data[\"region\"].unique()" + ] + }, + { + "cell_type": "markdown", + "id": "d63adcd3", + "metadata": {}, + "source": [ + "#### 3.7 DDD(Triple Difference,Difference-in-Difference-in-Differences)\n", + "예) $Y_{itd} = \\alpha + \\delta_1 \\text{Treated}_i +\t\\delta_2 \\text{Post}_t +\t\\delta_3 \\text{Region}_d+\\delta_4 (\\text{Treated}_i \\times \\text{Post}_t)+\\delta_5 (\\text{Treated}_i \\times \\text{Region}_d)\n", + "\\\\\t+\\delta_6 (\\text{Post}_t \\times \\text{Region}_d)\n", + "\t+\\color{blue}{\\beta (\\text{Treated}_i \\times \\text{Post}_t \\times \\text{Region}_d)} + \\varepsilon_{itd}$\n", + "\n", + "DID는 처치 전후 변화의 차이를 비교합니다. 즉 (처치그룹 변화) − (비처치그룹 변화)를 나타냅니다. DDD는 여기에 차분을 한번 더 추가하여 지역 또는 집단 차이를 봅니다. \n", + "\n", + "즉 기존 DID로 추정한 **정책 효과(처치 효과)**가 지역이나 집단에 따라 얼마나 다르게 나타나는지(이질적 효과, heterogeneous effect) 를 추가적으로 식별합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "id": "beeebf9b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " OLS Regression Results \n", + "==============================================================================\n", + "Dep. Variable: downloads R-squared: 0.960\n", + "Model: OLS Adj. R-squared: 0.959\n", + "Method: Least Squares F-statistic: 1853.\n", + "Date: Sat, 18 Oct 2025 Prob (F-statistic): 1.10e-204\n", + "Time: 21:56:37 Log-Likelihood: -14902.\n", + "No. Observations: 6400 AIC: 2.984e+04\n", + "Df Residuals: 6384 BIC: 2.995e+04\n", + "Df Model: 15 \n", + "Covariance Type: cluster \n", + "===============================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "-----------------------------------------------------------------------------------------------\n", + "Intercept 17.2758 0.381 45.381 0.000 16.530 18.022\n", + "C(region)[T.N] 26.6759 0.551 48.414 0.000 25.596 27.756\n", + "C(region)[T.S] 33.0592 0.451 73.224 0.000 32.174 33.944\n", + "C(region)[T.W] 10.6681 0.479 22.267 0.000 9.729 11.607\n", + "treated 0.3099 0.593 0.523 0.601 -0.852 1.472\n", + "treated:C(region)[T.N] -1.7759 0.970 -1.831 0.067 -3.677 0.126\n", + "treated:C(region)[T.S] 0.2995 0.913 0.328 0.743 -1.490 2.089\n", + "treated:C(region)[T.W] 0.4208 1.157 0.364 0.716 -1.846 2.688\n", + "post 4.9819 0.044 113.583 0.000 4.896 5.068\n", + "post:C(region)[T.N] -3.2730 0.064 -51.271 0.000 -3.398 -3.148\n", + "post:C(region)[T.S] -4.7601 0.066 -72.092 0.000 -4.889 -4.631\n", + "post:C(region)[T.W] -1.7829 0.064 -27.806 0.000 -1.909 -1.657\n", + "treated:post 1.6768 0.270 6.217 0.000 1.148 2.205\n", + "treated:post:C(region)[T.N] -0.3437 0.426 -0.806 0.420 -1.179 0.492\n", + "treated:post:C(region)[T.S] -0.9851 0.333 -2.957 0.003 -1.638 -0.332\n", + "treated:post:C(region)[T.W] 1.3694 0.717 1.911 0.056 -0.035 2.774\n", + "==============================================================================\n", + "Omnibus: 24.370 Durbin-Watson: 0.414\n", + "Prob(Omnibus): 0.000 Jarque-Bera (JB): 31.120\n", + "Skew: 0.050 Prob(JB): 1.75e-07\n", + "Kurtosis: 3.326 Cond. No. 32.1\n", + "==============================================================================\n", + "\n", + "Notes:\n", + "[1] Standard Errors are robust to cluster correlation (cluster)\n", + "treated:post:C(region)[T.N] : -0.34366747700080125\n", + "treated:post:C(region)[T.S] : -0.9850718065003734\n", + "treated:post:C(region)[T.W] : 1.369362559838598\n" + ] + } + ], + "source": [ + "import statsmodels.formula.api as smf\n", + "\n", + "# Triple Difference 모형\n", + "formula = \"downloads ~ treated * post * C(region)\"\n", + "\n", + "ddd_model = smf.ols(formula, data=mkt_data_all).fit(\n", + " cov_type=\"cluster\", cov_kwds={\"groups\": mkt_data_all[\"city\"]}\n", + ")\n", + "\n", + "print(ddd_model.summary())\n", + "\n", + "# Triple Difference 추정치 (핵심 효과)\n", + "ddd_term = [p for p in ddd_model.params.index if \"treated:post:C(region)\" in p]\n", + "for term in ddd_term:\n", + " print(term, \":\", ddd_model.params[term])" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "id": "43e7548a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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nzp2Rl5eH+Ph4pfaYmBjpcW0YGRmprfNR9vb2CAkJwYABA3Dp0qUqZ4hUXi+g0vr16wFAOgOmR48eEELgxo0bKl+bli1bAgA6dOgAKysrREVF1doAtqCgIFy+fBm//PJLray/c+fO+OWXX6qcuRETEwMzMzO0b99e43Vp83p4e3ujQ4cOmDVrFtatW4eQkBCYm5s/0XOQQ48ePXDlyhXY2tqqfM8rzwIJCgoCUHFGR3Ue3fOmTv369dGnTx+MHDkSOTk51V6wzNPTE0DFAF1trF69Gnv27MGAAQM03hMWERGB8+fPY+zYsRrtMSkrK8OoUaOQnZ2NiRMnVnn8zz//hJ6enlZnv5B8uAeDapW1tTXCw8MxYcIErF+/Hh999BGWLl2KoKAgBAYGIiQkBC+//DJycnJw4cIFnDx5UgoQU6ZMwY4dO9C5c2dMmTIFpqamiIqKkk7d09NTn48HDRqERYsWYfDgwbh69SpatmyJI0eO4B//+AeCg4OfeFyBKu3atUOPHj3w6quvwtraGhcuXMCaNWvg4+Oj9F+hkZER5s6di7y8PLz++us4duwYvvvuOwQFBaFjx44AKi5A9Nlnn2HIkCFITU2Fr68vzM3NkZmZiSNHjqBly5b44osvUK9ePcydOxdDhw5Fly5dMGzYMNjb2+OPP/7A6dOnsXDhwqd+XuPGjcPGjRvRq1cvTJo0CW+88QYKCwuRlJSEHj16PNFZBY+aNm0adu7ciYCAAHzzzTewsbHBunXrsGvXLsyePbvKxZmqo+3rMXbsWPTv3x8KhQIjRozQqu7ffvsNpaWlVdqbNGki7UnRxrhx4xAbGwtfX1+Ehobi1VdfRXl5Oa5fv479+/fjyy+/RLt27dCpUyd8/PHH+O6773Dr1i306NEDxsbGOHXqFMzMzDB69GgAQMuWLbFhwwZs3LgRbm5uMDExQcuWLdGzZ0+0aNECbdu2xUsvvYRr165h3rx5aNSokdKhvMc1bNgQbm5uSElJwZgxY6o8XlhYKF1Ns7CwEH/++Sfi4+Oxc+dO+Pn5qTxN9N69e9Iy+fn50oW2Dh8+jH79+iEiIqLKMrdu3UJKSgqEEHjw4IF0oa3Tp08jNDQUw4YNq7JMSkoKWrduXasX+aNq6GhwKb1gqrsIUWFhoXBxcRHNmjUTpaWlQgghTp8+Lfr16yfs7OyEoaGhcHBwEG+99ZaIiopSWvbw4cOiXbt2wtjYWDg4OIivvvpKOhOk8iwDIaqeRSKEENnZ2WL48OHC0dFRGBgYiEaNGonw8HDx8OFDpX5QM0L98bMq1Jk0aZJo27atsLa2FsbGxsLNzU2EhoaKO3fuSH0qz9w4c+aM8Pf3F6ampsLGxkZ88cUXIi8vr8o6V61aJdq1ayfMzc2FqampaNKkiRg0aJBITU1V6rd7927h5+cnzM3NhZmZmfDy8lIasf80Z5EIIcTdu3fF2LFjhYuLizA0NBR2dnaie/fuVS649Liazi6odPbsWdGzZ09hZWUljIyMRKtWrapcUEuTs0gq1fR6VCoqKhLGxsaiW7duNdb4+DbVTcuXL6/x+as7gyIvL09MnTpVeHh4CCMjI2FlZSVatmwpQkNDRVZWltSvrKxM/PDDD6JFixZSPx8fH7Fjxw6pz9WrV0XXrl2FhYWFACAaNWokhBBi7ty5okOHDqJBgwbCyMhIuLi4iE8//VRcvXq1xuf+9ddfC2tr6yrfHT8/P6XXwNzcXLi5uYk+ffqIzZs3S2eEPf4aVPZXKBSiXr16wsPDQ3z88cdi3759Krf/6Db09PSEpaWlaNmypfjss89EcnKyymUePHggzMzMqpyRRc+OQgieIEx1S9euXXH16lVcvnxZ16VoLCQkBFu2bEFeXp6uSyEAO3bswDvvvINdu3YhODhY1+U8927evAlXV1fExMRUuW7L82rlypUYO3YsMjIyuAdDR3iIhJ5rYWFhaNOmDZydnZGTk4N169bhwIEDWLlypa5Lozro/PnzuHbtGr788ku0bt1aGtdA1XNycsK4ceMwc+ZM9O3bt9rDk8+D0tJSzJo1C+Hh4QwXOsSAQc+1srIyfPPNN8jKyoJCoYCXlxfWrFmDjz76SNelUR00YsQIHD16FK+99hp++umnWruGyIto6tSpMDMzw40bN6pcu+R5k5GRgY8++ghffvmlrkv5W+MhEiIiIpLd872fi4iIiOokBgwiIiKSHQMGERERye5vN8izvLwcN2/ehIWFBQd4ERERaUH890JnTk5ONZ5N9LcLGDdv3nzuR0ATERE9zzIyMmq8ueDfLmBU3j8iIyMDlpaWOq6GiIio7sjNzYWzs7PKezE97m8XMCoPi1haWjJgEBERPQFNhhhwkCcRERHJjgGDiIiIZMeAQURERLJjwCAiIiLZMWAQERGR7BgwiIiISHYMGERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGTHgEFERESyY8AgIiIi2en0ZmdLlizBkiVLcPXqVQBA8+bN8c033yAoKEjtMklJSQgLC8O5c+fg5OSECRMmYPjw4c+oYiIiksv8u/N1XcILb6z1WJ1tW6d7MBo2bIjvv/8eqampSE1NxVtvvYVevXrh3LlzKvunp6cjODgYnTp1wqlTpzB58mSMGTMGsbGxz7hyIiIiqo5O92D07NlTaX7mzJlYsmQJUlJS0Lx58yr9o6Ki4OLignnz5gEAPD09kZqaijlz5qB3797PomQiIiLSwHMzBqOsrAwbNmxAfn4+fHx8VPZJTk5G165dldoCAwORmpqKkpKSZ1EmERERaUCnezAA4OzZs/Dx8cHDhw9Rr149xMXFwcvLS2XfrKws2NvbK7XZ29ujtLQUd+7cgaOjY5VlioqKUFRUJM3n5ubK+wSIiIioCp3vwfDw8EBaWhpSUlLwxRdfYPDgwTh//rza/gqFQmleCKGyvVJkZCSsrKykydnZWb7iiYiISCWdBwwjIyM0bdoUbdu2RWRkJFq1aoX581WPLHZwcEBWVpZS2+3bt2FgYABbW1uVy4SHh+P+/fvSlJGRIftzICIiImU6P0TyOCGE0iGNR/n4+GDHjh1Kbfv370fbtm1haGiochljY2MYGxvLXicRERGpp9M9GJMnT8bhw4dx9epVnD17FlOmTEFiYiIGDhwIoGLvw6BBg6T+w4cPx7Vr1xAWFoYLFy5g1apVWLlyJcaPH6+rp0BEREQq6HQPxq1bt/Dxxx8jMzMTVlZWePXVV7F37168/fbbAIDMzExcv35d6u/q6ordu3cjNDQUixYtgpOTExYsWMBTVImIiJ4zClE5SvJvIjc3F1ZWVrh//z4sLS11XQ4R0d8Wr+RZ++S+kqc2f0N1PsiTiIiIXjwMGERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGTHgEFERESyY8AgIiIi2TFgEBERkewYMIiIiEh2DBhEREQkOwYMIiIikh0DBhEREcmOAYOIiIhkx4BBREREsmPAICIiItkxYBAREZHsGDCIiIhIdgwYREREJDsGDCIiIpIdAwYRERHJjgGDiIiIZMeAQURERLJjwCAiIiLZMWAQERGR7BgwiIiISHYMGERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGTHgEFERESyY8AgIiIi2TFgEBERkewYMIiIiEh2DBhEREQkOwYMIiIikh0DBhEREcmOAYOIiIhkp9OAERkZiddffx0WFhaws7PDu+++i0uXLlW7TGJiIhQKRZXp4sWLz6hqIiIiqolOA0ZSUhJGjhyJlJQUHDhwAKWlpejatSvy8/NrXPbSpUvIzMyUpmbNmj2DiomIiEgTBrrc+N69e5XmV69eDTs7O/z666/w9fWtdlk7OzvUr1+/FqsjIiKiJ/VcjcG4f/8+AMDGxqbGvm3atIGjoyM6d+6MhISE2i6NiIiItKDTPRiPEkIgLCwMHTt2RIsWLdT2c3R0xLJly+Dt7Y2ioiKsWbMGnTt3RmJiosq9HkVFRSgqKpLmc3Nza6V+IiIi+p/nJmCMGjUKZ86cwZEjR6rt5+HhAQ8PD2nex8cHGRkZmDNnjsqAERkZiYiICNnrJSIiIvWei0Mko0ePxvbt25GQkICGDRtqvXz79u3x+++/q3wsPDwc9+/fl6aMjIynLZeIiIhqoNM9GEIIjB49GnFxcUhMTISrq+sTrefUqVNwdHRU+ZixsTGMjY2fpkwiIiLSkk4DxsiRI7F+/Xps27YNFhYWyMrKAgBYWVnB1NQUQMUeiBs3biAmJgYAMG/ePDRu3BjNmzdHcXEx1q5di9jYWMTGxurseRAREZEynQaMJUuWAAD8/f2V2levXo2QkBAAQGZmJq5fvy49VlxcjPHjx+PGjRswNTVF8+bNsWvXLgQHBz+rsomIiKgGCiGE0HURz1Jubi6srKxw//59WFpa6rocIqK/rfl35+u6hBfeWOuxsq5Pm7+hz8UgTyIiInqxMGAQERGR7BgwiIiISHYMGERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGTHgEFERESyY8AgIiIi2TFgEBERkewYMIiIiEh2DBhEREQkOwYMIiIikh0DBhEREcmOAYOIiIhkx4BBREREsmPAICIiItkxYBAREZHsGDCIiIhIdgwYREREJDsGDCIiIpIdAwYRERHJjgGDiIiIZMeAQURERLJjwCAiIiLZMWAQERGR7BgwiIiISHYMGERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGSnccDQ19fH7du3a7MWIiIiekFoHDCEELVZBxEREb1AeIiEiIiIZGegTed9+/bBysqq2j7vvPPOUxVEREREdZ9WAWPw4MHVPq5QKFBWVvZUBREREVHdp9UhkqysLJSXl6udGC6IiIgI0CJgKBQK2TceGRmJ119/HRYWFrCzs8O7776LS5cu1bhcUlISvL29YWJiAjc3N0RFRcleGxERET05nZ5FkpSUhJEjRyIlJQUHDhxAaWkpunbtivz8fLXLpKenIzg4GJ06dcKpU6cwefJkjBkzBrGxsbLXR0RERE9G4zEYgwcPhqmpqawb37t3r9L86tWrYWdnh19//RW+vr4ql4mKioKLiwvmzZsHAPD09ERqairmzJmD3r17y1ofERERPRmN92DExMSgsLCwNmvB/fv3AQA2NjZq+yQnJ6Nr165KbYGBgUhNTUVJSUmt1kdERESa0XgPRm1faEsIgbCwMHTs2BEtWrRQ2y8rKwv29vZKbfb29igtLcWdO3fg6Oio9FhRURGKioqk+dzcXHkLJyIioiq0OoukNgZ6Vho1ahTOnDmDn3/+Wes6KsOPqvoiIyNhZWUlTc7OzvIUTERERGppdR0Md3f3GkNGTk6O1kWMHj0a27dvx6FDh9CwYcNq+zo4OCArK0up7fbt2zAwMICtrW2V/uHh4QgLC5Pmc3NzGTKIiIhqmVYBIyIiosYreWpDCIHRo0cjLi4OiYmJcHV1rXEZHx8f7NixQ6lt//79aNu2LQwNDav0NzY2hrGxsWw1ExERUc20ChgffPAB7OzsZNv4yJEjsX79emzbtg0WFhbSngkrKyvpjJXw8HDcuHEDMTExAIDhw4dj4cKFCAsLw7Bhw5CcnIyVK1dqdGiFiIiIng2dXmhryZIluH//Pvz9/eHo6ChNGzdulPpkZmbi+vXr0ryrqyt2796NxMREtG7dGt9++y0WLFjAU1SJiIieI7KcRXL37l2sXbsWK1euRFpamsYb1+TMlOjo6Cptfn5+OHnypMbbISIiomdL44BRXl5epe3gwYNYuXIl4uPj0aBBA7z//vuyFkdERER1k1ZjMADg+vXrWL16NVavXo28vDzcvXsXmzZt4iEKIiIikmg8BmPTpk3o2rUrPD098dtvv2H+/Pm4efMm9PT04OnpWZs1EhERUR2j8R6MDz/8EBMmTEBsbCwsLCxqsyYiIiKq4zTeg/HJJ59g8eLF6NatG6KionD37t3arIuIiIjqMI0DxrJly5CZmYnPPvsMP//8MxwdHdGrVy8IIVQOACUiIqK/L63uRWJqaorBgwcjKSkJZ8+ehZeXF+zt7fHmm2/iww8/xNatW2urTiIiIqpDtAoYj2rWrBkiIyORkZGBtWvXoqCgAAMGDJCzNiIiIqqjtD5N9XF6enro2bMnevbsidu3b8tRExEREdVxT7wHQxU571NCREREdZesAYOIiIgIYMAgIiKiWsCAQURERLJjwCAiIiLZaXQWibW1NRQKhUYrzMnJeaqCiIiIqO7TKGDMmzdP+jk7OxvfffcdAgMD4ePjAwBITk7Gvn378PXXX9dKkURERFS3KIQQQpsFevfujYCAAIwaNUqpfeHChTh48CDi4+PlrE92ubm5sLKywv3792FpaanrcoiI/rbm352v6xJeeGOtx8q6Pm3+hmo9BmPfvn3o1q1blfbAwEAcPHhQ29URERHRC0jrgGFra4u4uLgq7fHx8bC1tZWlKCIiIqrbtL5UeEREBD799FMkJiZKYzBSUlKwd+9erFixQvYCiYiIqO7ROmCEhITA09MTCxYswNatWyGEgJeXF44ePYp27drVRo1ERERUxzzRzc7atWuHdevWyV0LERERvSCe6EJbV65cwdSpU/Hhhx9Kd1Ddu3cvzp07J2txREREVDdpHTCSkpLQsmVLHD9+HLGxscjLywMAnDlzBtOmTZO9QCIiIqp7tA4YkyZNwnfffYcDBw7AyMhIag8ICEBycrKsxREREVHdpPUYjLNnz2L9+vVV2l966SVkZ2fLUlRdFRERoesSXnjcS0ZEVDdovQejfv36yMzMrNJ+6tQpvPzyy7IURURERHWb1gHjww8/xMSJE5GVlQWFQoHy8nIcPXoU48ePx6BBg2qjRiIiIqpjtA4YM2fOhIuLC15++WXk5eXBy8sLvr6+6NChA6ZOnVobNRIREVEdo/UYDENDQ6xbtw7ffvstTp48ifLycrRp0wbNmjWrjfqIiIioDtJ6D8aMGTNQUFAANzc39OnTB/369UOzZs1QWFiIGTNm1EaNREREVMdoHTAiIiKka188qqCggGdREBEREYAnCBhCCCgUiirtp0+fho2NjSxFERERUd2m8RgMa2trKBQKKBQKuLu7K4WMsrIy5OXlYfjw4bVSJBEREdUtGgeMefPmQQiBTz75BBEREbCyspIeMzIyQuPGjaXbtxMREdHfm8YBY/DgwQAAV1dXdOjQAYaGhrVWFBEREdVtWp+m6ufnJ/1cWFiIkpISpcctLS2fvioiIiKq07Qe5FlQUIBRo0bBzs4O9erVg7W1tdJEREREpHXA+Oqrr/DLL79g8eLFMDY2xooVKxAREQEnJyfExMRota5Dhw6hZ8+ecHJygkKhQHx8fLX9ExMTpYGmj04XL17U9mkQERFRLdL6EMmOHTsQExMDf39/fPLJJ+jUqROaNm2KRo0aYd26dRg4cKDG68rPz0erVq0wZMgQ9O7dW+PlLl26pHQo5qWXXtLqORAREVHt0jpg5OTkwNXVFUDFeIucnBwAQMeOHfHFF19ota6goCAEBQVpWwLs7OxQv359rZcjIiKiZ0PrQyRubm64evUqAMDLywubNm0CULFn41n90W/Tpg0cHR3RuXNnJCQkVNu3qKgIubm5ShMRERHVLq0DxpAhQ3D69GkAQHh4uDQWIzQ0FF999ZXsBT7K0dERy5YtQ2xsLLZu3QoPDw907twZhw4dUrtMZGQkrKyspMnZ2blWayQiIqInOEQSGhoq/RwQEICLFy8iNTUVTZo0QatWrWQt7nEeHh7w8PCQ5n18fJCRkYE5c+bA19dX5TLh4eEICwuT5nNzcxkyiIiIapnWAeNxLi4ucHFxkaOWJ9K+fXusXbtW7ePGxsYwNjZ+hhURERHREwWM//u//0NiYiJu376N8vJypcf+9a9/yVKYpk6dOgVHR8dnuk0iIiKqntYB4x//+AemTp0KDw8P2NvbK930TNVdVquTl5eHP/74Q5pPT09HWloabGxs4OLigvDwcNy4cUO6vsa8efPQuHFjNG/eHMXFxVi7di1iY2MRGxur7dMgIiKiWqR1wJg/fz5WrVqFkJCQp954amoqAgICpPnKsRKDBw9GdHQ0MjMzcf36denx4uJijB8/Hjdu3ICpqSmaN2+OXbt2ITg4+KlrISIiIvloHTD09PTw5ptvyrJxf39/CCHUPh4dHa00P2HCBEyYMEGWbRMREVHt0fo01dDQUCxatKg2aiEiIqIXhNZ7MMaPH4/u3bujSZMm8PLyqnLb9q1bt8pWHBEREdVNWgeM0aNHIyEhAQEBAbC1tdV6YCcRERG9+LQOGDExMYiNjUX37t1rox4iIiJ6AWg9BsPGxgZNmjSpjVqIiIjoBaF1wJg+fTqmTZuGgoKC2qiHiIiIXgBaHyJZsGABrly5Ant7ezRu3LjKIM+TJ0/KVhwRERHVTVoHjHfffbcWyiAiIqIXidYBY9q0abVRB5FOfX/qjq5LeOFNatNA1yUQ0TOk9RgMIiIioppotAfDxsYGly9fRoMGDWBtbV3ttS9ycnJkK46IiIjqJo0Cxg8//AALCwvpZ15ci4iIiKqjUcAYPHiw9LMcd1ElIiKiF5vWYzD09fVx+/btKu3Z2dnQ19eXpSgiIiKq27QOGOpur15UVAQjI6OnLoiIiIjqPo1PU12wYAEAQKFQYMWKFahXr570WFlZGQ4dOoRXXnlF/gqJiIioztE4YPzwww8AKvZgREVFKR0OMTIyQuPGjREVFSV/hURERFTnaBww0tPTAQABAQHYunUrrK2ta60oIiIiqtu0HoORkJCgFC7KysqQlpaGu3fvyloYERER1V1aB4xx48Zh5cqVACrCha+vL1577TU4OzsjMTFR7vqIiIioDtI6YGzevBmtWrUCAOzYsQNXr17FxYsXMW7cOEyZMkX2AomIiKju0TpgZGdnw8HBAQCwe/du9O3bF+7u7vj0009x9uxZ2QskIiKiukfrgGFvb4/z58+jrKwMe/fuRZcuXQAABQUFvNAWERERAXiC27UPGTIE/fr1g6OjIxQKBd5++20AwPHjx3kdDCIiIgLwBAFj+vTpaNGiBTIyMtC3b18YGxsDqLiE+KRJk2QvkIiIiOoerQMGAPTp06dK26M3RCMiIqK/N43HYAQHB+P+/fvS/MyZM3Hv3j1pPjs7G15eXrIWR0RERHWTxgFj3759KCoqkuZnzZqFnJwcab60tBSXLl2StzoiIiKqkzQOGI/fRVXdXVWJiIiItD5NlYiIiKgmGgcMhUIBhUJRpY2IiIjocRqfRSKEQEhIiHRa6sOHDzF8+HCYm5sDgNL4DCIiIvp70zhgPH4a6kcffVSlz6BBg56+IiIiIqrzNA4Yq1evrs06iIiI6AXCQZ5EREQkOwYMIiIikh0DBhEREclOpwHj0KFD6NmzJ5ycnKBQKBAfH1/jMklJSfD29oaJiQnc3NwQFRVV+4USERGRVnQaMPLz89GqVSssXLhQo/7p6ekIDg5Gp06dcOrUKUyePBljxoxBbGxsLVdKRERE2niiu6nKJSgoCEFBQRr3j4qKgouLC+bNmwcA8PT0RGpqKubMmYPevXvXUpVERESkrTo1BiM5ORldu3ZVagsMDERqaipKSkpULlNUVITc3FyliYiIiGpXnQoYWVlZsLe3V2qzt7dHaWkp7ty5o3KZyMhIWFlZSZOzs/OzKJWIiOhvrU4FDKDq/U8q7+qq7r4o4eHhuH//vjRlZGTUeo1ERER/dzodg6EtBwcHZGVlKbXdvn0bBgYGsLW1VbmMsbGxdP8UIiIiejbq1B4MHx8fHDhwQKlt//79aNu2LQwNDXVUFRERET1OpwEjLy8PaWlpSEtLA1BxGmpaWhquX78OoOLwxqM3UBs+fDiuXbuGsLAwXLhwAatWrcLKlSsxfvx4XZRPREREauj0EElqaioCAgKk+bCwMAAVd26Njo5GZmamFDYAwNXVFbt370ZoaCgWLVoEJycnLFiwgKeoEhERPWd0GjD8/f2lQZqqREdHV2nz8/PDyZMna7EqIiIielp1agwGERER1Q0MGERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGTHgEFERESyY8AgIiIi2TFgEBERkewYMIiIiEh2DBhEREQkOwYMIiIikh0DBhEREcmOAYOIiIhkx4BBREREsmPAICIiItkxYBAREZHsGDCIiIhIdgwYREREJDsGDCIiIpIdAwYRERHJjgGDiIiIZMeAQURERLIz0HUBRERPoyTiS12X8MIznDZX1yVQHcQ9GERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGTHgEFERESyY8AgIiIi2TFgEBERkewYMIiIiEh2DBhEREQkOwYMIiIikh0DBhEREcmOAYOIiIhkx4BBREREsmPAICIiItnpPGAsXrwYrq6uMDExgbe3Nw4fPqy2b2JiIhQKRZXp4sWLz7BiIiIiqolOA8bGjRsxbtw4TJkyBadOnUKnTp0QFBSE69evV7vcpUuXkJmZKU3NmjV7RhUTERGRJnQaMP71r3/h008/xdChQ+Hp6Yl58+bB2dkZS5YsqXY5Ozs7ODg4SJO+vv4zqpiIiIg0obOAUVxcjF9//RVdu3ZVau/atSuOHTtW7bJt2rSBo6MjOnfujISEhGr7FhUVITc3V2kiIiKi2qWzgHHnzh2UlZXB3t5eqd3e3h5ZWVkql3F0dMSyZcsQGxuLrVu3wsPDA507d8ahQ4fUbicyMhJWVlbS5OzsLOvzICIioqoMdF2AQqFQmhdCVGmr5OHhAQ8PD2nex8cHGRkZmDNnDnx9fVUuEx4ejrCwMGk+NzeXIYOIiKiW6WwPRoMGDaCvr19lb8Xt27er7NWoTvv27fH777+rfdzY2BiWlpZKExEREdUunQUMIyMjeHt748CBA0rtBw4cQIcOHTRez6lTp+Do6Ch3eURERPQUdHqIJCwsDB9//DHatm0LHx8fLFu2DNevX8fw4cMBVBzeuHHjBmJiYgAA8+bNQ+PGjdG8eXMUFxdj7dq1iI2NRWxsrC6fBhERET1GpwGjf//+yM7OxowZM5CZmYkWLVpg9+7daNSoEQAgMzNT6ZoYxcXFGD9+PG7cuAFTU1M0b94cu3btQnBwsK6eAhEREamg80GeI0aMwIgRI1Q+Fh0drTQ/YcIETJgw4RlURURERE9D55cKJyIiohcPAwYRERHJjgGDiIiIZMeAQURERLJjwCAiIiLZMWAQERGR7BgwiIiISHYMGERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGTHgEFERESyY8AgIiIi2TFgEBERkewYMIiIiEh2DBhEREQkOwYMIiIikh0DBhEREcmOAYOIiIhkx4BBREREsmPAICIiItkxYBAREZHsGDCIiIhIdgwYREREJDsGDCIiIpIdAwYRERHJjgGDiIiIZMeAQURERLJjwCAiIiLZMWAQERGR7BgwiIiISHYMGERERCQ7BgwiIiKSHQMGERERyY4Bg4iIiGTHgEFERESyY8AgIiIi2ek8YCxevBiurq4wMTGBt7c3Dh8+XG3/pKQkeHt7w8TEBG5uboiKinpGlRIREZGmdBowNm7ciHHjxmHKlCk4deoUOnXqhKCgIFy/fl1l//T0dAQHB6NTp044deoUJk+ejDFjxiA2NvYZV05ERETVMdDlxv/1r3/h008/xdChQwEA8+bNw759+7BkyRJERkZW6R8VFQUXFxfMmzcPAODp6YnU1FTMmTMHvXv31mrb+fn50NfXr9Kur68PExMTpX7q6OnpwdTUVJovLi5W21ehUMDQ0FCjvgBgZGT0RH1LSkoghHiu+xoaGkKhUAAASktLUV5ernHf6t4PU1NT6OlVZObi4mKUlJRo3Le4UP16DYxMoPffz0ppSTHKS9Wv99G+ZSUlKCtV/97pGxpD38BA+76lpSgrKVLf18AI+v/9rGnTt7ysDKXFD9X21TMwhIGhkfZ9y8tRWlSI/HxTlX0NDQ2lz095eTkKCwvVrtfAwADGxsYAACEECgoKUFKs+v0w0FPA+L+vmRACBSWlaterr1DAxPB/vw7z1axT2756CsD0ke+9Nn0Likug7lukAGBm9GR9C0tKUK7+6wlzFX0N1XzvzM3NpZ8fPnyIsrIy9etV0bcoX/Vn08jM6H/f+6JSlJWqX682fQ1NDaXvfWlxKcpKZOprYgg9fe37lpWUobRY/efSwNgA+gb62vctLUNpUUXffKOq752RkZH096i0tBRFRep/Rzzat6ysrNrfwY9TiOr+EtSi4uJimJmZYfPmzXjvvfek9rFjxyItLQ1JSUlVlvH19UWbNm0wf/58qS0uLg79+vVDQUGB0h/wSkVFRUov3v379+Hi4qK2rrfffhtbtmyR5h0cHNT+wnvzzTexe/dujfo6ODggJCREml+8eDFyc3NV9rW1tcWwYcOk+eXLlyM7O1tlX0tLS4wYMUKaj46ORlZWlsq+pqamGDt2rDS/bt06ZGRkqOxrYGCA8ePHS/ObNm3Cn3/+qbIvAEyaNEn6OS4uDpcuXVLb98svv5Teq507d+K3335T23fMmDEwMzMDAOzfvx8nT55U2/fMmTNo1KgRAGDq1Kn48ccf1fZNSUmBp6cnACAyMhLff/+92r5Dl8Xh5VdaAQCOrl+Gg1Hq+w6evx6N27QHAPzf1hjsmTddbd8Bs5bD3aczACBt92Zs+36i2r59I36EV0B3AMD5hF3YPG202r69Js1C6+C+AIDLyf/GzxOHqe0bNG463nh/EADg6qkU/DT2Q7V9uwyfhDc//AwAcOPiaaz47D21ff1CxsD/k3EAgNvpl7FkcDe1fUePHo3vvvsOAHDt2jW8+uqravsOHToUc+fOBQDcuXMHTZo0Udu3fwsPLOrRBQCQX1KKRnOXqu3b08MNq98LkuYbfL9Ibd8ubo2woV8Pad55ThQK1fxR6+DshO0D//c6uc9fiZxC1cGstcNLOBjST5pvszgGGbkPVPZ1t7XGsWH/e686LF+Py9l3VfZ1trTAqRGD/ld/9CakZf2lsq+NqQkuj/1Umn9nXRyOZdxU2dfU1FTpd02fPn1w4MABlX2Bit+9lQYNGoRt27ap7RtxPgLGZhVBctP4TTi5Rf33furJqahnUw8AEP91PFLWpKjtO+HIBNg0tAEA7PrHLhxepv6Q/Lj94+Dg7gAAOPDDAfx7/r/V9h25bSScWzkDAJKikrDn+z1q+w7bMAxN2ld8bo/FHMP2b7ar7Tt41WB4vlXxeyp1cyq2fLVFbd8PF32IV7tXfHfO7DqD9SPXq+27ePFiDBw4EACwb98+9OvXT23ff/7zn/jss4rv/eHDh9GjR8Vn/969e7CyslK7HABA6MiNGzcEAHH06FGl9pkzZwp3d3eVyzRr1kzMnDlTqe3o0aMCgLh586bKZaZNmyYAcOLEiRMnTpxkmjIyMmr8O6/TQyQApF1blYQQVdpq6q+qvVJ4eDjCwsKk+fLycuTk5MDW1rba7bzocnNz4ezsjIyMDFhaWuq6HNIC37u6je9f3cX3ruJv7oMHD+Dk5FRjX50FjAYNGkBfX7/K7vzbt2/D3t5e5TIODg4q+xsYGMDW1lblMsbGxtIx20r169d/8sJfMJaWln/bL0pdx/eubuP7V3f93d+7Gg+N/JfOziIxMjKCt7d3lWN2Bw4cQIcOHVQu4+PjU6X//v370bZtW5XjL4iIiEg3dHqaalhYGFasWIFVq1bhwoULCA0NxfXr1zF8+HAAFYc3Bg363+Ck4cOH49q1awgLC8OFCxewatUqrFy5UmkwIhEREemeTsdg9O/fH9nZ2ZgxYwYyMzPRokUL7N69WzoTIDMzU+maGK6urti9ezdCQ0OxaNEiODk5YcGCBVqfokoVh46mTZtW5fARPf/43tVtfP/qLr532tHZaapERET04tL5pcKJiIjoxcOAQURERLJjwCAiIiLZMWCQksaNG0v3egEqLmAWHx+vs3qIiKhuYsB4joSEhEChUEiTra0tunXrhjNnzuispszMTAQFBdXckWpV5Wfj8XumxMfH/62vSFuX3L59G59//jlcXFxgbGwMBwcHBAYGIjk5Wdel0WOioqJgYWGB0tL/3VwsLy8PhoaG6NSpk1Lfw4cPQ6FQ4PLly8+6zOceA8Zzplu3bsjMzERmZib+/e9/w8DAQLq5jC44ODjwlKznhImJCWbNmoW7d+/quhR6Ar1798bp06fx008/4fLly9i+fTv8/f2Rk5Oj69LoMQEBAcjLy0NqaqrUdvjwYTg4OODEiRMoKCiQ2hMTE+Hk5AR3d3ddlPpcY8B4zlT+Z+Pg4IDWrVtj4sSJyMjIwF9/Vdz9cOLEiXB3d4eZmRnc3Nzw9ddfK92W/PTp0wgICICFhQUsLS3h7e2t9CU5duwYfH19YWpqCmdnZ4wZM6ba2+8+eojk6tWrUCgU2Lp1KwICAmBmZoZWrVpV+Q9M222QZrp06QIHBwdERkbquhTS0r1793DkyBHMmjULAQEBaNSoEd544w2Eh4eje/fuui6PHuPh4QEnJyckJiZKbYmJiejVqxeaNGmCY8eOKbUHBATooMrnHwPGcywvLw/r1q1D06ZNpXutWFhYIDo6GufPn8f8+fOxfPly/PDDD9IyAwcORMOGDXHixAn8+uuvmDRpknQZ9bNnzyIwMBDvv/8+zpw5g40bN+LIkSMYNWqUVnVNmTIF48ePR1paGtzd3TFgwABpV6Jc26Cq9PX18Y9//AM//vgj/vOf/+i6HNJCvXr1UK9ePcTHx6OoqEjX5ZAG/P39kZCQIM0nJCTA398ffn5+UntxcTGSk5MZMNSp+cbq9KwMHjxY6OvrC3Nzc2Fubi4ACEdHR/Hrr7+qXWb27NnC29tbmrewsBDR0dEq+3788cfis88+U2o7fPiw0NPTE4WFhUIIIRo1aiR++OEH6XEAIi4uTgghRHp6ugAgVqxYIT1+7tw5AUBcuHBB422Q9gYPHix69eolhBCiffv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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "effects = pd.DataFrame({\n", + " \"Region\": [\"Baseline\", \"N\", \"S\", \"W\"],\n", + " \"ATT\": [1.68, 1.34, 0.70, 3.05]\n", + "})\n", + "\n", + "plt.figure(figsize=(6,4))\n", + "plt.bar(effects[\"Region\"], effects[\"ATT\"], color=[\"gray\",\"skyblue\",\"salmon\",\"lightgreen\"])\n", + "plt.title(\"Region-specific Policy Effects (DDD)\")\n", + "plt.ylabel(\"Estimated ATT\")\n", + "plt.axhline(0, color='black', linestyle='--')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "8ba4cb99", + "metadata": {}, + "source": [ + "분석 결과 정책 시행 이후 baseline 지역에서는 downloads가 평균 1.68 증가하였습니다. \n", + "\n", + "그러나 지역별로 효과는 상이하게 나타났으며,\n", + "S 지역에서는 효과가 0.98 감소(유의), W 지역에서는 1.37 증가(한계적 유의) 하였습니다.\n", + "\n", + "이는 정책 효과가 지역적 특성에 따라 다르게 나타난다는 점을 보여줍니다." + ] + }, + { + "cell_type": "markdown", + "id": "b5e2e215", + "metadata": {}, + "source": [ + "#### 3.8 Dynamic DiD - Event study\n", + "\n", + "예) $Y_{it} = \\alpha_i + \\gamma_t + \\beta_t \\, (\\text{Treated}_i \\times \\text{Post}_{it}) + \\varepsilon_{it}$\n", + "\n", + "**Event Study(이벤트 스터디)** 는 처치가 발생한 시점을 기준으로 시간 축(event time)을 설정해, 처치 전후의 효과를 시점별로 추정하는 방법입니다. \n", + "\n", + "일반적으로 처치 시점을 0으로 두고, 그 이전은 –1, –2, 이후는 +1, +2와 같이 표현합니다. 각 시점별로 처치군과 대조군의 차이를 계산해 시점별 효과(βₜ)를 추정하며, 이를 통해 처치 이후 효과가 시간에 따라 커지거나 작아지는지, 혹은 처치 이전부터 이미 차이가 존재했는지를 확인할 수 있습니다.\n", + "\n", + "이 방법은 세 가지 측면에서 중요합니다. \n", + "\n", + "첫째, 처치 이전 구간의 계수 βₜ가 0에 가깝다면 평행추세(Parallel Trends) 가정이 충족됨을 의미합니다. \n", + "\n", + "둘째, 처치 이후 구간의 βₜ를 통해 **동적 효과(Dynamic Treatment Effect)** 를 확인할 수 있습니다. \n", + "\n", + "셋째, **정책이나 프로그램의 시차 효과(lag effect)** 를 평가할 수 있어 단기적·장기적 처치 효과를 함께 분석할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 172, + "id": "ac19a640", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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attci_lowci_up
2021-05-020.325397-0.4917411.142534
2021-05-030.384921-0.3883891.158231
2021-05-04-0.156085-1.2474910.935321
2021-05-05-0.299603-0.9499350.350729
2021-05-060.3476190.0131150.682123
\n", + "
" + ], + "text/plain": [ + " att ci_low ci_up\n", + "2021-05-02 0.325397 -0.491741 1.142534\n", + "2021-05-03 0.384921 -0.388389 1.158231\n", + "2021-05-04 -0.156085 -1.247491 0.935321\n", + "2021-05-05 -0.299603 -0.949935 0.350729\n", + "2021-05-06 0.347619 0.013115 0.682123" + ] + }, + "execution_count": 172, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def did_date(df, date):\n", + " df_date = (df\n", + " .query(\"date==@date | post==0\")\n", + " .query(\"date <= @date\")\n", + " .assign(post = lambda d: (d[\"date\"]==date).astype(int)))\n", + " \n", + " m = smf.ols(\n", + " 'downloads ~ I(treated*post) + C(city) + C(date)', data=df_date\n", + " ).fit(cov_type='cluster', cov_kwds={'groups': df_date['city']})\n", + " \n", + " att = m.params[\"I(treated * post)\"]\n", + " ci = m.conf_int().loc[\"I(treated * post)\"]\n", + " \n", + " return pd.DataFrame({\"att\": att, \"ci_low\": ci[0], \"ci_up\": ci[1]},\n", + " index=[date])\n", + "\n", + "\n", + "\n", + "\n", + "post_dates = sorted(mkt_data[\"date\"].unique())[1:]\n", + "\n", + "atts = pd.concat([did_date(mkt_data, date)\n", + " for date in post_dates])\n", + "\n", + "atts.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "9e6679d1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Pre-treatment periods (2021-05-01 ~ 2021-05-14) ===\n", + " rel_time att ci_low ci_up se pvalue\n", + "0 -14 0.317460 -0.445648 1.080569 0.389348 0.414864\n", + "1 -13 0.642857 -0.005605 1.291320 0.330854 0.052014\n", + "2 -12 0.865079 -0.025911 1.756070 0.454595 0.057045\n", + "3 -11 0.452381 -0.329286 1.234048 0.398817 0.256666\n", + "4 -10 0.269841 -0.642655 1.182337 0.465568 0.562187\n", + "5 -9 0.857143 0.296929 1.417357 0.285829 0.002710\n", + "6 -8 0.317460 -0.647464 1.282385 0.492317 0.519038\n", + "7 -7 0.515873 -0.480732 1.512478 0.508481 0.310327\n", + "8 -6 -0.230159 -1.277911 0.817594 0.534577 0.666800\n", + "9 -5 0.198413 -0.494862 0.891687 0.353718 0.574842\n", + "10 -4 0.595238 -0.505375 1.695851 0.561548 0.289147\n", + "11 -3 0.301587 -0.393374 0.996548 0.354578 0.395018\n", + "12 -2 0.650794 -0.120146 1.421733 0.393344 0.098023\n", + "13 -1 0.000000 0.000000 0.000000 0.000000 NaN\n", + "\n", + "=== Post-treatment periods (2021-05-15 onwards) ===\n", + " rel_time att ci_low ci_up se pvalue\n", + "14 0 -0.341270 -0.933429 0.250889 0.302127 0.258663\n", + "15 1 0.976190 0.372599 1.579782 0.307961 0.001525\n", + "16 2 0.412698 -0.199118 1.024515 0.312157 0.186140\n", + "17 3 0.134921 -0.615384 0.885226 0.382816 0.724506\n", + "18 4 1.507937 0.700961 2.314912 0.411730 0.000250\n", + "19 5 1.920635 1.035289 2.805981 0.451716 0.000021\n", + "20 6 1.349206 0.793304 1.905109 0.283629 0.000002\n", + "21 7 1.111111 0.101001 2.121221 0.515372 0.031088\n", + "22 8 0.833333 0.095824 1.570842 0.376287 0.026786\n", + "23 9 1.396825 0.386041 2.407610 0.515716 0.006758\n", + "24 10 1.333333 0.583795 2.082871 0.382424 0.000489\n", + "25 11 1.730159 0.828178 2.632139 0.460203 0.000170\n", + "26 12 1.126984 0.586388 1.667580 0.275819 0.000044\n", + "27 13 1.269841 0.558016 1.981666 0.363183 0.000472\n", + "28 14 1.079365 0.372182 1.786548 0.360814 0.002776\n", + "29 15 1.666667 0.675656 2.657678 0.505627 0.000980\n", + "30 16 0.777778 -0.300925 1.856481 0.550369 0.157599\n", + "31 17 1.563492 0.618211 2.508773 0.482295 0.001188\n" + ] + }, + { + "data": { + "image/png": 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10vImTZrg9ddfh1qtxsOHD/H7778jNDTU6GN35swZ6feGDRtmWt6gQQMIgiB1j9CzZ094enrCz88PjRo1Qtu2bXPd7+jMmTPx119/SdMtW7ZEu3btcOrUKfzwww9GbSM39z1D0vrWXrt2rfQ31dfXV+oOIad6mJvzCgDW1tbw8/ODj48PnJ2dYWdnh9jYWBw/fhwXL16EKIqYOHEi+vTpAxsbm0z7M+b6SjNo0CBcvnxZmq5Tpw66dOkChUKBS5cu6d1jz5w5g7Fjx0rnt2XLlujQoQNevHiBLVu24Pnz57h48SJGjhyp1/+vsc6ePYvly5fnej1DVq1apdc/av369dG9e3dcvXoVBw8eNGobT548wbNnz4w6jnlREHX71q1bOdbtKlWqYNmyZfj5559x7NgxALq/79OnT5e2k3Zd5uVzaF4+e6WX/l5y48YNvHjxAqVLlzbq/RMRFSpzZoyJiChrxrRSQIYWFPfv3xcFQZCWhYaGiqKoe6TYwcFBmp/2CLtGo9HrMmHRokV6MXz00UfSsmrVqmUZ2zvvvCMty/ho/8GDB6VlObVmzUlKSorYoEGDbI9Hu3btxL/++ivTuunLGGp1kdeWtv7+/tJ8R0dHMSYmRlq2cOHCLPd79uxZab6VlZUYHR0tiqIo/vHHH3rz02/PlC1tRVEUe/furVcuLaaHDx/qtXK6evWqKIqZu0a4fv26tK2MLQcPHTokLRs3bpw0v0yZMpniSElJEU+ePClu2rRJ/Oyzz8Rly5aJ7733nrSOSqXSaymYvrWRQqGQjsvLly/14nZxcZG6d7hx40aW9TSrlrYZH8MeOXJkpq4t7t27Z8QZ0ZfblrZ9+/bNtN+rV6/qlTl79qy0TKvVin5+ftKywMDATDHcunVL3LVrl7h69Wpx+fLl4rJly0RbW1tpna1bt+qVN6Y+pS9Tu3Zt6ZwdOXJEb1nnzp2ldb744gu9ZWnnK6/vL2NrxTVr1kjLVq5caXBfho55buXUSjKr7WbXot+YuBo2bCgty9gybd26ddIye3t7MTk5WRRF/W5nAIi7du3SW0+tVosPHjyQpo25D9WvX19afu7cuUzLw8LCjO4eoWzZstK2smpFm741rqFXtWrV9O5BaTEYuu5SUlL0Wqc2b95cVKvVoijq/ma2a9cuy/ef1/teduc9p+4Pslqe2/Oa5urVq+I333wjrlq1Sly2bJn48ccf623n5MmTUtm8XF8Zr+U33nhDekIjTfr7aPqW+P7+/nr3vvT3EkEQxIcPH2Z6PxkZ05o+48vYlrbVq1eX5nt5eYmJiYnSsox1I6uWtrm5T+W2pa056nZO3Q3l9XNoXj97pXn69KlemRs3bmQqQ0RkCUru0NBERMVQ5cqV0aZNG2k6rXXtoUOHEB8fD0DXyrNr164AdK0l0kbkBnQtpgRBkF5LliyRlt25c8dgS18AeP/996Xfa9SoobcsrdVYQVAqlThx4gQmTZqEsmXLGizz22+/oVOnTtL7NbVLly5Jv3fu3FlvBPeBAwdmuZ6fnx8aN24MQDfQztatWwHot1zt3r273vbatm0LUde1EURRhJeXV0G9DQDQG3k9vYoVK6JHjx7SdNqgQPv27YNarQagazGT1aB4FSpUQLdu3aTp9HUkY/3Yvn07ypcvj9atW2Po0KEYP348Jk+ejM2bN0tlkpOTs6yLLVq0kI6LnZ0dXFxcpGXdunWTBuyqXr263nrG1NP0Lf4AYO7cuRAEQW9expbepjB16tRM+80YW/PmzaXrWCaT6Q3Ql75FcHh4OFq0aIEaNWqgb9++GDNmDCZNmoTJkydLrbsA4O+//85XzL169YJSqQSATPW2b9++0u9ZnZe8vr/05HI5hg4dKk2b8l5lDomJiVLrcQDYsGGD3v18xIgR0rKXL1/i2rVrAPSPbe3atTMNbCWXy1GpUqVcxdKqVSvp97QWw6NGjcIXX3yB69evw8vLCzKZcf+GvHjxQvq9VKlSBsusXr0aa9asyXRO09y5cwc9evTQa92ZlVu3buHly5fS9IABA6TB3mQyGQYPHmxU3Lm575lCbs/rlStXULduXTRo0AADBw7Ehx9+iMmTJ2caDC+re4Gx11fGa3nWrFmZntBIfx9NX/7o0aOQyWRSne7cubO0TBRFnD9/3mBshSE+Pl56ggDQ3fPSt0g29qkZU96nLLFu5/VzaF4/e6XJeC9Jf58hIrIkTNoSERURmzdv1kvYpb3atm2rVy79PwZpSdv0XSOkf4T92bNnuYrhyZMnBud7enpKv6tUKr1lWq02V/vIiaOjI5YtW4bHjx/j2rVr2LBhA/r166f3z1FERAT27duXr/1kTGAmJycbLJf+g35alxNp3Nzcst3H6NGjpd83bdoEwDxdI6RJ/w+ntbU1nJ2dpen0sW7fvh1JSUn47rvvpHnZxZq+fgD6dST9cb5y5QrefffdLBOy6WV1PipUqJDlvtIvy5gkMKaepr9ebG1tM53vwpIxsQnk7lpOfx336NHDqG4dsjrexkp/7DPeI4w5L3l9f+m5ubnB2to6yzgK+l6VXlhYmMH7d0F6/vx5rraZdpzSH9uC+iJo0aJF6NKlCwBdgvjYsWP48ssvMXr0aNSvXx9t27bV+1IgO+kfWY6LizNYRiaTYdSoUfjrr78QHh6OnTt3YtSoUShXrpxURq1WY82aNTnuL2Pyxt3dPdvprBh73zOV3JzXV69e4fXXX8eNGzdy3G5W9wJjr6+M13JOsRXEtZ+dOXPmFMi1GRsbqzed13pjyvuUJdbtvH4Ozc9nLyDzvYRdIxCRpWKftkRExcw777yD0aNHIz4+Hnfu3MGvv/6q1/9n+uRaxj4Whw0blmVLJSDzB+M0aS3oAGRqAWgqMpkM9erVQ7169RAYGIg//vgDjRo1kpbfvXs319tLL60fQEDXgubx48cG1ytdurTUSiQ6OlpvWVbrpOnXrx8mT56Mp0+fIjQ0FGvWrMGdO3cAAOXLl8+xz8OCdOnSJVy9elWabtOmjd4xadu2LerVq4fr16/j+fPnWL9+PYKDgwHoErz9+vXLctvp6weQdR3ZvXu39A+pnZ0d9uzZgzZt2sDGxgaHDx/Wa9lj7L7SM9Tfbm6kb8mTmJiIJ0+e6LXkLSy2traZ5mW8lhctWpTlsUhb/9atW3rnfPz48fjoo4/g4uICQRDg6uqapySIIfk9L3l5fznFUFj3qsKSMenw9ttvw8/PL8vyaff69PU6PDy8QGIpVaoUDh8+jL///hvnz5/H7du3cfPmTezfvx+JiYk4ceIEli5dirlz5+a4rfLly0tf5BhTHz09PeHp6Ym+fftiyZIlqFGjBv755x8Axv1dyHgcM97Xo6KictwGYP76lpvzevLkSURGRkrTy5Ytw9ChQ+Hk5ITExETY2dnluD9j32/6uNJiy+4+6uTkJJ33du3aSU8KGZJdfTe1olBvLDHGvH4Ozc9nL0Pr5NSnPRGRuTBpS0RUzNja2qJ3795Sy81hw4YhKSkJANCsWTPUrl1bKluzZk04OztLH3yTk5OlgXHSi4iIQGhoqF7Ly7zI+EHf2JZWabZs2YKkpCT0799fesw9jb29vd50xn9OFAqF9Ci/of1mHEDp999/l/45XLZsWZatR3x9fXH06FEAusHinj17Jv1T+s0332T7flQqFYYNGyY9/pd+cKd3331XemwxTXBwMNq1aydNh4WFFUjLuFu3buk9og4AEyZMyFRu1KhR0iPWH330kXQ8e/ToUSCtVNI/Iunt7a336Gv6AUfMpUWLFnrT8+bNy9Ry78GDB5laIRWGjIMSubu7G2z9fOHCBalVVPrjDegeKU37h/jXX3/NNkGW0/VU0PLy/vLD0L0qq2SwpbCzs0ODBg2kRPzz588xfvz4TPeRJ0+e4MyZM9Ij6C1atMCFCxcAADdv3sTu3bvRq1cvqbxWq8WjR4+kwSKNuY//+eefqFGjBipWrIh33nlHmv/hhx/i888/BwCjuioAdIm4tK4c/vjjj0zLL1++jAMHDmD48OGZBrRUqVSwsrKSpo25T9WsWRMODg5SFzvffvst3n//fWmwsy1bthgVt7nl5rxmvBcMGTJESqYV9L0343104cKF2LNnj96XN+nvo82bN8f3338PQJdUHDlyZKYkclxcHH766Se9wUoLm729PWrWrCkN8rVv3z7Mnz9fqn/pu/gxF3PU7fT3C0P3irx+Ds3PZy9A92RPmjp16rClLRFZLCZtiYiKiCNHjhh8bNzV1RXvvvuu3rz33ntPStqGhYXpzU9PJpNh3LhxmDVrFgBg27ZtuHPnDl577TXY2dnhn3/+wfnz56XH1v39/fP1HlxcXKBUKpGamgoAmDFjBkJCQmBlZYW2bdtKI9BnJSwsDPPmzcO4cePQqlUr+Pj4wMnJCdHR0XojqguCkKmVaoUKFfDgwQMAwIoVKxATEwMbGxs0bNgQ7du3h6OjI6pVqya1dP34449x7do1xMbG4rfffssypqFDh0r/OMTGxqJZs2bo06cP/v77b6NGMB45ciSWLVsGjUYjJdcBICAgIMd18yqtLsXFxeGPP/7AkSNHpAQcAHzwwQcGW/kOGjQIH330EV68eKEXa0F145C+dc3169fRp08f1K1bF8HBwfj1118LZB/50a1bN9SpU0d6hPiLL77AlStX0K5dO6jVammE9ezqi6n4+Pigffv2OH78OAAgMDAQP/zwg5TECAsLw4kTJxAWFobNmzejQYMGqFq1KmQymdS6eeDAgejbty8iIyMRFBSU7f5yup4s4f3lR8ZuNvr374/mzZtDJpNh0KBBRj1+m97GjRsztSgDgMaNG+t9EZNfkyZNwqBBgwDo+vdu0KABXn/9dTg6OiI6OhqXLl3CuXPn0LJlS6mf6jFjxmDt2rXSNd2nTx/s2rUL9evXR0xMDH755Rf07t1bahWb8dh88MEH6Ny5MxQKBd58801Ur14dkyZNwoULF9C+fXt4eHjAxcUF//zzj17iytgkSfv27bF+/XoAMNhnaXx8PD7++GMsXLgQvr6+aNasGcqVK4fExET8+OOPeq1M038RlBWFQoGAgACsXr0agO7Lsvbt26NVq1Y4efKk9ISBpcvNec3YsrFr167o1q0b7ty5gx07dhRoXPXr14e/v7/0d/P7779Ho0aN0KVLFyiVSly9ehU3b97EvXv3AAATJ07EwYMHIYoiQkNDUbduXbz99tsoW7Ysnj17hpCQEJw6dQru7u6Z+u0tbIGBgZg4cSIAXf+rzZs3R7du3XD16lUp8WxO5qjb6e8XT548wXvvvYfatWtDEASMGjUKNjY2efocmt/PXun7QTfF3ywiogJTGKOdERFR7mUcoTurV4MGDQyun34UYwCijY2N+OLFi0zl1Gq12K9fv1yNnpzT6OHpl2UctTf9SNDpX8uWLcvxmBg7IvvUqVMzrZtxJO2016hRo6Qy69evN1jGx8dHdHFxkaYzju7dq1cvg+ulH9nZ0LHI6pg0b97cYDljRm03Zr2sXgqFQlywYEG2o7pnPI4eHh4Gy6cfabpNmzZ6yzZv3qy3jTQxMTFi+fLls6x/Wb337EZXz25U9qzOTXajXd+5c0f09vbO8hhmfK/GyHg80o8qnt3xyigqKkqsV69ejuc5/XsdMWKEwTLt27cXK1SokOWxM+Z6ymqfWY1sLorZ1/G8vL/szmV2+0pKShLLlStncPsXL17M8hwY2m92rw8//FBvvezqqygaVxcmT56c434z1tODBw/qjSqf8ZUxlkaNGhkst3v3blEU9Ud2N/SytrYWf//99xyPoyjqzkX6+++dO3f0lht7f2vVqpWYnJwsrZddPXz+/LlYs2ZNg9vp0qWL3vSDBw+k9fJy3xPF7M97dve3nJbn5rx27tzZYJmM996CuL6ePHkiNm7cOMu4Mm7r888/F+VyebbnN+M6Wcl43g1dZ6IoZjoGWS1LfzxSUlLEVq1aGVVvTpw4ke/jmNW5t6S6HRkZKdra2hrc35MnT0RRzNvnUFHM+2cvjUaj91kjJCREJCKyVByIjIiomMrYUvPtt9/O1AUAoBupeMeOHfj+++/RvXt3lC9fHkqlEk5OTqhbty769OmD7du3Y9WqVQUS18aNGzF48GC4ubkZPXp4mnHjxmHPnj344IMP0LRpU1SqVAk2NjawsrKCh4cH3n77bfz44496ow2nWbhwIcaOHYsKFSpkelw4zfDhw/Hll1+ievXqUCqVqFixIiZNmoRTp05l+2j09u3bsXDhQnh7e0OpVMLLywszZszAkSNHjHpfY8aM0ZseMmSIUevlh1wuh4ODAypXroz27dtj3rx5CA8Px8yZM7M9L6NGjdJbPnjw4Fyfx6yUKVMGp0+fxttvv41SpUrBxsYGTZo0wb59+0za8jg3qlatiqtXr2LZsmVo3rw5SpcuDYVCARcXF7Ru3TpTq/fC5ObmhgsXLmD16tVo06YNypQpA4VCAXd3dzRu3BgjR47E0aNHMWDAAGmd1atXY/78+fD09IRSqUSlSpUwefJk/PDDD9n2NWvM9VTQ8vL+8kqlUuHw4cPo2LFjplHGLd3SpUtx4sQJ9O3bF5UqVYJKpUKpUqVQs2ZNdO/eHRs3btQbRBAA3njjDfz555+YMGEC6tatCzs7O1hZWaFChQro3r17ppZoe/fuxVtvvYUyZcoY7M9y8uTJ+PDDD/G///0PFSpUgJWVFVQqFby9vTF48GBcuHABTZs2Ner9qFQqDB8+XJrevn273vLmzZvj+PHjmD59Otq0aYMqVarAwcFBui7btWuHtWvX4vjx43pdJWSndOnSOHXqFN5//324urpCpVKhQYMG2Lp1a6Zr3JIfq87Ned27dy/GjRuHcuXKwcrKClWrVsWiRYukp3YKUtmyZXH27FmsX78er732GpydnaFQKFCmTBk0a9YMH3zwgV75MWPG4NKlSxg6dCiqVq0Ka2tr2NnZoVq1aujcuTNWrVqFkydPFnicuaVUKvHTTz9h6tSpqFixIqysrFCjRg189tlnmDlzpl5Zc9Wbwq7b7u7u+OGHH9CiRYss+0bO6+fQvH72+u2336R+rlu2bJnvJzOIiExJEMVCGL6UiIiIsvTPP/9IjxDa2toiKioqU5+9liIpKQlubm6Ii4uDIAi4c+cOqlSpYu6wiKgYe/78OapWrYpnz57Bzc0NYWFhsLGxMek+X716ZXAf77zzDvbu3QsAqFatGm7fvm3SOKhoyareTJo0CStWrACg6/82JibG6C8RClpJr9vdunWTBug9efIkWrVqZeaIiIiyxj5tiYiIzCQ4OBgvX77Uaz3y7rvvWmTC9vz583jx4gW2bNmCuLg4AIC/vz8TtkRkck5OTpg7dy7Gjh2Lx48fY926dRg/frxJ91mjRg34+/ujadOmKF++PKKjo7F792789NNPUpmxY8eaNAYqetq1awdvb2+0atUKHh4eeP78OY4cOYKdO3dKZd5//32zJWyBkl23r1y5IiVse/bsyYQtEVk8trQlIiIyk4yPFTs7O+P69esoV66cmSLKmpeXlzTwFKB7ZPnChQuoX7++GaMiIjKN0qVLIzY2NsvlgYGBWL9+vcHuIajk8vHxwdWrV7Nc3q1bN+zduxcqlaoQo9LHuk1EVHSwT1siIiIzc3Jywuuvv44TJ05YZMI2PQcHB7Rp0wbHjx9nwpaIiq1p06ahbdu2cHd3h5WVFaytrVG5cmX069cPv/zyCzZs2MCkFmUyevRo+Pv7o0KFCrC2toZKpULFihXRo0cP7NmzB4cOHTJrwhZg3SYiKkrY0paIiIiIiIiIiIjIghSplrZr165F/fr1UapUKZQqVQp+fn56fe8YcuLECTRu3BjW1tbw9vbGunXrCilaIiIiIiIiIiIiotwrUknbihUrYsmSJbh06RIuXbqE1157Dd27d8eNGzcMlg8LC0PXrl3RqlUr/PHHH5g+fTrGjh0rjYpJREREREREREREZGmKfPcIZcqUwbJlyzB06NBMy6ZOnYqDBw8iNDRUmjdixAhcvXoV586dM3ofWq0W//zzDxwcHNi/DxEREREREREREeWJKIqIj49H+fLlIZNl3Z5WUYgxFSiNRoPdu3cjISEBfn5+BsucO3cOnTp10pvn7++PTZs2ITU1FUql0qh9/fPPP/Dw8Mh3zEREREREREREREQPHz5ExYoVs1xe5JK2169fh5+fH5KSkmBvb4/9+/ejdu3aBstGRUXBzc1Nb56bmxvUajWePn2a5QjdycnJSE5OlqbTGiM/ePAApUqVKqB3omvB+/TpU5QtWzbbzDpRccE6TyUN6zyVNKaq8xqNBrGxsZDJZIX+1JMoitBqtXB0dIRcLi/UfRc35jqPOZ3D/MQliiKeP38OJyenPK2bVVyWWucZl/ExFde4TFXn8xtXflhi3bLUuIriOcxvXKas85bIUut8cRMXFwdPT084ODhkW67IJW1r1KiBkJAQvHjxAnv37sXgwYNx4sSJLBO3GStZWgI2u8q3ePFizJs3L9P85ORkJCUl5SN6fVqtFhqNBklJSfxnnkoE1nkqaVjnqaQxVZ3XarVQq9WQyWSF/iFeo9FAq9UiOTmZ13E+mes85nQO8xOXVquFTCaDRqPJdf3ILi5LrfOMy/iYimtcpqrz+Y0rPyyxbllqXEXxHOY3LlPWeUtkqXW+uElrKJpTYrzIJW2trKxQtWpVAICvry8uXryIVatWYf369ZnKuru7IyoqSm9edHQ0FAoFnJ2ds9zHtGnTMGHCBGk6Li4OHh4ecHFxKfCWtoIgwMXFpdhXSCKAdZ5KHtZ5KmlMVec1Gg2USiUUCkWhX0tp/7yULl262Lf6MDVznceczmF+4kqr805OTnlaN6u4LLXOMy7jYyqucZmqzuc3rvywxLplqXEVxXOY37hMWectkaXW+eLG2traqHJFLmmbkSiKel0ZpOfn54cffvhBb97PP/8MX1/fbPuzValUUKlUmebLZLICr7SCIJhku0SWinWeShrWebJ4X3wBxMcDDg7AqFH53pwp6rwoihAEQdp2YUrbN6/j/DPXeczpHOY3rrzWj+zistQ6z7iMj6k4x2WKOl8QceWVJdYtS42rKJ7DgojLVHXeEllqnS9ujH1/RSppO336dHTp0gUeHh6Ij4/Hrl27EBwcjCNHjgDQtZB99OgRtm7dCgAYMWIE1qxZgwkTJiAwMBDnzp3Dpk2bsHPnTnO+DSIiIiLLcfEiEBMDZPMUEhERERERFa4ilbR9/PgxBg0ahMjISDg6OqJ+/fo4cuQIOnbsCACIjIxERESEVL5y5co4fPgwxo8fjy+++ALly5fH559/jp49e5okPo1Gg9TUVKPLa7VapKamsq9DKjGyq/NKpbLYPwJBRERERERERGSMIpW03bRpU7bLg4KCMs1r06YNrly5YqKIdERRRFRUFF68eJHr9bRaLeLj4wt9VD4ic8ipzpcuXRru7u68HoiIiIiIiIioRCtSSVtLlZawdXV1ha2trdEJJ1EUoVaroVAomKSiEiGrOi+KIhITExEdHQ0AKFeunLlCJCIiIiIiIiIyOyZt80mj0UgJW+dc9gXHpC2VNNnVeRsbGwBAdHQ0XF1d2VUCEREREREREZVY7Eg1n9L6sLW1tTVzJERFX9p1lJu+oYmIiIiIiIiIihsmbQsIW8oS5R+vIyIiIiIiIiIiJm2JiIiIiIiIiIiILAqTtkQWZtCgQVi0aJG5w8i169evo2LFikhISDB3KERERERERERERRqTthZCowGCg4GdO3U/NRrT7i8gIACCIEAQBCiVSnh7e2PSpEkmSbgFBASgR48eBb7drMydOxc+Pj6Ftr+cBAcHQxAEvHjxIsey165dw48//ogxY8aYNKbr16+jTZs2sLGxQYUKFTB//nyIopjtOgsXLkTz5s1ha2uL0qVLZ1per149NG3aFJ999pmJoiYiIpNo3Rro2FH3k4iIiIiILAKTthZg3z7Aywto1w7o31/308tLN9+UOnfujMjISNy/fx8ff/wxvvzyS0yaNMlg2cIYGIqDTwFr1qxBr1694ODgUKDbjYiIkH6Pi4tDx44dUb58eVy8eBGrV6/G8uXL8emnn2a7jZSUFPTq1QsjR47Mssx7772HtWvXQmPqbx2IiKjgDBkCjB2r+0lERERERBaBSVsz279fQK9ewN9/689/9Ah45x3TJm5VKhXc3d3h4eGB/v37Y8CAAThw4ACA/1qrfv311/D29oZKpYIoioiNjcXw4cPh6uqKUqVK4bXXXsPVq1ez3MfcuXOxZcsWfP/991LL3uDgYISHh0MQBHz33Xdo27YtrK2t8c033wAANm/ejFq1asHa2ho1a9bEl19+qbfNqVOnonr16rC1tYW3tzdmzZolJXyDgoIwb948XL16VdpfUFAQAN0gV+vXr8frr78OW1tb1KpVC+fOncPdu3fRtm1b2NnZwc/PD/fu3dPb3w8//IDGjRvD2toa3t7emDdvHtRqtbRcEAR89dVXeOutt2Bra4tq1arh4MGDAIDw8HC0a9cOAODk5ARBEBAQEGDwWGm1WuzevRtvvvmm3nwvLy8sWLAA/fv3h729PcqXL4/Vq1dnc2Z14uLisGnTJrRu3Vqv5fH27duRlJSEoKAg1K1bF2+//TamT5+OTz/9NNvWtvPmzcP48eNRr169LMv4+/sjJiYGJ06cyDE+IiIiIiIiIiIyjElbM9JogAkT5DCUJ0ubN26c6btKSGNjY6PX2vXu3bv47rvvsHfvXoSEhAAAunXrhqioKBw+fBiXL19Go0aN0L59ezx79szgNidNmoTevXtLrXojIyPRvHlzafnUqVMxduxYhIaGwt/fHxs3bsSMGTOwcOFChIaGYtGiRZg1axa2bNkirePg4ICgoCDcvHkTq1atwsaNG6VH8vv06YOJEyeiTp060v769OkjrbtgwQK8++67CAkJQc2aNdG/f3+8//77mDZtGi5dugQAGD16tFT+6NGjGDhwIMaOHYubN29i/fr1CAoKwsKFC/Xe57x589C7d29cu3YNXbt2xYABA/Ds2TN4eHhg7969AIBbt24hMjISq1atMnisrl27hhcvXsDX1zfTsmXLlqF+/fq4cuUKpk2bhvHjx+PYsWOZymm1Whw7dgwDBw6Eu7s7lixZgvbt20vvDQDOnTuHNm3aQKVSSfP8/f3xzz//IDw83GBsxrKyskKDBg1w6tSpfG2HiIiIiIiIiKgkU5g7gOLK1xeIisq+THIy8PSpkOVyUQQePgTc3YF0+bUsubsD6XJzuXLhwgXs2LED7du3l+alpKRg27ZtcHFxAQD8+uuvuH79OqKjo6WE3/Lly3HgwAHs2bMHw4cPz7Rde3t72NjYIDk5Ge7u7pmWjxs3Dm+//bY0vWDBAqxYsUKaV7lyZSlZOnjwYADAzJkzpfJeXl6YOHEivv32W0yZMgU2Njawt7eHQqEwuL/33nsPvXv3BqBLGPv5+WHWrFnw9/cHAHz44Yd47733pPILFy7ERx99JO3b29sbCxYswJQpUzBnzhypXEBAAPr16wcAWLRoEVavXo0LFy6gc+fOKFOmDADA1dXVYF+wacLDwyGXy+Hq6pppWYsWLfDRRx8BAKpXr44zZ87gs88+Q8eOHQEAt2/fRlBQELZt24aEhAT07t0bx44dQ4sWLTJtKyoqCl5eXnrz3NzcpGWVK1fOMkZjVKhQId/JXyIiIiIiIiKikoxJWxOJitJ1cZC9rBO26T19mu9wDDp06BDs7e2hVquRmpqK7t276z127+npKSVsAeDy5ct4+fIlnJ2d9bbz6tUr3Lt3DxEREahdu7Y0f/r06Zg+fXq2MaRvVfrkyRM8fPgQQ4cORWBgoDRfrVbD0dFRmt6zZw9WrlyJu3fv4uXLl1Cr1ShVqpRR77l+/frS72mJyvSP+7u5uSEpKQlxcXEoVaoULl++jIsXL+q1rNVoNEhKSkJiYiJsbW0zbdfOzg4ODg6Ijo42KqY0r169gkqlgiBkrhd+fn6ZpleuXClNDx8+HCdOnMCIESPw6aefwsbGJtt9ZdxHWrcIhvadWzY2NkhMTMz3doiIqJCMGAE8ewaUKQOsW2fuaIiIiIiICEzamoyBRp6ZJCeL2ba0TVO2rPEtbXOjXbt2WLt2LZRKJcqXLw+lUqm33M7OTm9aq9WiXLlyCA4OzrSt0qVLo3Tp0lI3CgCkFqbZSb8PrVYLANi4cSOaNWumV04ulwMAzp8/j759+2LevHnw9/eHo6Mjdu3ahRUrVuS4LwB67zEtQWloXlosWq0W8+bN02sNnMba2trgdtO2k7YNY5UtWxaJiYlISUmBlZVVjuXTJ1hXrlyJTZs2YefOnTh06BAGDBiAQYMGoU6dOpnWc3d3R1SGZuBpCea0RHZ+PHv2DFWqVMn3doiIqJAkJQGvXul+EhERERGRRWDS1kSM6aZArQa8vET88w8gipmTt4IAVKwIhIUB/+YsC5SdnR2qVq1qdPlGjRohKioKCoUi0+P1aQxtz8rKChojOuZ1c3NDhQoVcP/+fQwYMMBgmTNnzsDT0xMzZsyQ5j148CBP+zNGo0aNcOvWrVwdp4zSErA5xZQ2WNjNmzf1Bg4DdMnqjNM1a9bUW3f16tVYsWIFDh06hC1btqBhw4aoW7cuBg0ahH79+kndRfj5+WH69Ol6yeGff/4Z5cuXz/K85saff/6Jd955J9/bISIiIiIiIiIqqTgQmRnJ5cCnn+oSeRmfSk+bXrnSNAnbvOjQoQP8/PzQo0cPHD16FOHh4Th79ixmzpypN9BVRl5eXrh27Rpu3bqFp0+f6g12ltHcuXOxePFirFq1Crdv38b169exefNmfPrppwB0SeGIiAjs2rUL9+7dw+eff479+/dn2l9YWBhCQkLw9OlTJCcn5/k9z549G1u3bsXcuXNx48YNhIaG4ttvv9XrVzcnnp6eEAQBhw4dwpMnT/Dy5UuD5VxcXNCoUSOcPn0607IzZ85g6dKluH37Nr744gvs3r0bH374YaZyVlZWePvtt/H999/j0aNHePfdd7F161a9Frf9+/eHSqVCQEAA/vzzT+zfvx+LFi3ChAkTpNa7Fy5cQM2aNfEoXR8fERERCAkJQUREBDQaDUJCQhASEqL3fsLDw/Ho0SN06NDB6ONDRERERERERET6mLQ1s7feErF7N1Chgv78ihWBPXsAA0/lm40gCDh8+DBat26NIUOGoHr16ujbty/Cw8Ozfaw+MDAQNWrUgK+vL1xcXHDmzJksyw4bNgxfffUVgoKCUK9ePbRp0wZBQUHS4Fjdu3fH+PHjMXr0aPj4+ODs2bOYNWuW3jZ69uyJzp07o127dnBxccHOnTvz/J79/f1x6NAhHDt2DE2aNMH//vc/fPrpp/D09DR6GxUqVMC8efPw0Ucfwc3NDaNHj86y7PDhw7F9+/ZM8ydOnIjLly+jYcOG0mBtaYOnZcXFxQXjxo3DH3/8oXfMHR0dcezYMfz999/w9fXFBx98gAkTJmDChAlSmcTERNy6dUsvwT579mw0bNgQc+bMwcuXL9GwYUM0bNhQL2G/c+dOdOrUKVfHh4iIiIiIiIiI9Ali2ghElKW4uDg4OjoiNjY204BXSUlJCAsLQ+XKlfX6ODWGKIpQq9VQKBTQagWcOgVERgLlygGtWllOC1sqPElJSahRowZ27dolDT7m5eWFcePGYdy4ceYNLgfJycmoVq0adu7ciRYtWhgsk77OGxr0LD/XE5El0mq1iI6OhqurK2Qyfk9KFiogAIiJAZydgaCgfG3KVHVeo9Hg+fPnUCgUUj/3hUWj0UCtVsPJyanQ913cmOs85nQO8xOXVqvFs2fPUKZMmVzX+ezistQ6z7iMj6m4xmWqOp/fuPLDEuuWpcZVFM9hfuMyZZ23RJZa54ub7PKM6bFPWwshlwNt25o7CjI3a2trbN26FU+fPjV3KLn24MEDzJgxI8uELRERERERERERGYdJWyIL06ZNG3OHkCfVq1dH9erVzR0GERERkWkkJmaep9VCePVKtyxjCyxb28KJi4iIiIolJm2JLFx4eLi5QyAiIiIq8ex8fAzP12oNPjKbcPu2iSMiIiKi4oxJWyIiIiIiojwQEhMh02ohyGQQ2bKWiIiIChCTtkREREQl2ahRQHIyoFKZOxIii5YQEpJpnm2HDhAfP4bg5obEX34p/KCIiIio2GLSloiIiKgka9LE3BEQFQ2GWtLKZIAg6H6ypS0REREVoMydLxERERERERERERGR2TBpS0RERERERERERGRB2D0CERERUUl29y6gVgMKBVC1qrmjISIiIiIisKUtUZHSunVr7Nixw9xh5NqhQ4fQsGFDaLVac4dCREQZffwxMHmy7icREREREVkEJm0thUYDBAcDO3fqfmo0Jt1dQEAABEGAIAhQKpXw9vbGpEmTkJCQkO9th4eHQxAEhBgYYTejtm3bYty4cfnep7ECAgLQo0ePQttfToKCglC6dGmjyh46dAhRUVHo27evSWM6ceIEGjduDGtra3h7e2PdunU5rvPhhx+icePGUKlU8PHxybT89ddfhyAIRTLhTERERERERERU2Ji0tQT79gFeXkC7dkD//rqfXl66+SbUuXNnREZG4v79+/j444/x5ZdfYtKkSSbdZ16Iogi1Wm3uMMzu888/x3vvvQeZrGAv24iICOn3sLAwdO3aFa1atcIff/yB6dOnY+zYsdi7d2+22xBFEUOGDEGfPn2yLPPee+9hzZo1BRY3EREREREREVFxxaStmQn79wO9egF//62/4NEj4J13TJq4ValUcHd3h4eHB/r3748BAwbgwIEDAIDk5GSMHTsWrq6usLa2RsuWLXHx4kVp3efPn2PAgAFwcXGBjY0NqlWrhs2bNwMAKleuDABo2LAhBEFA27ZtDe4/ICAAJ06cwKpVq6RWv+Hh4QgODoYgCDh69Ch8fX2hUqlw6tQpiKKIpUuXwtvbGzY2NmjQoAH27NkjbU+j0WDo0KGoXLkybGxsUKNGDaxatUpaPnfuXGzZsgXff/+9tL/g4GCpZfB3332HVq1awcbGBk2aNMHt27dx8eJF+Pr6wt7eHp07d8aTJ0/03sPmzZtRq1YtWFtbo2bNmvjyyy+lZWnb3bdvH9q1awdbW1s0aNAA586dAwAEBwfjvffeQ2xsrBTP3LlzDR6rp0+f4pdffsGbb76pN18QBKxduxZdunSBjY0NKleujN27d2dz1nWePHmCVatWoVGjRujevbs0f926dahUqRJWrlyJWrVqYdiwYRgyZAiWL1+e7fY+//xzjBo1Ct7e3lmWefPNN3HhwgXcv38/x/iIiIiIiIiIiEoyJm3NSaOBfMIEQBQzL0ubN26cybtKSGNjY4PU1FQAwJQpU7B3715s2bIFV65cQdWqVeHv749nz54BAGbNmoWbN2/ip59+QmhoKNauXYuyZcsCAC5cuAAA+OWXXxAZGYl9WSSeV61aBT8/PwQGBiIyMhKRkZHw8PCQlk+ZMgWLFy9GaGgo6tevj5kzZ2Lz5s1Yu3Ytbty4gfHjx2PgwIE4ceIEAECr1aJixYr47rvvcPPmTcyePRvTp0/Hd999BwCYNGkSevfuLbUwjoyMRPPmzaX9zZkzBzNnzsSVK1egUCjQr18/TJkyBatWrcKpU6dw7949zJ49Wyq/ceNGzJgxAwsXLkRoaCgWLVqEWbNmYcuWLXrvc8aMGZg0aRJCQkJQvXp19OvXD2q1Gs2bN8fKlStRqlQpKZ6sWjqfPn0atra2qFWrVqZls2bNQs+ePXH16lUMHDgQ/fr1Q2hoaKZyKSkp2L9/P3r06IEKFSrg66+/xoABA3D48GGpzLlz59CpUye99fz9/XHp0iWpbuSVp6cnXF1dcfr06Xxth4iIiIiIiIiouFOYO4Biy9cXiIrKvkxyMoSnT7NeLorAw4eAuzugUuW8T3d34NKl3MX5rwsXLmDHjh1o3749EhISsHbtWgQFBaFLly4AdAnKY8eOYdOmTZg8eTIiIiLQsGFD+Pr6AgC8vLykbbm4uAAAnJ2d4e7unuU+HR0dYWVlBVtbW4Pl5s+fj44dOwIAEhIS8Omnn+LXX3+Fn58fAMDb2xunT5/G+vXr0aZNGyiVSsybN09av3Llyjh79iy+++479O7dG/b29rCxsUFycrLB/U2aNAn+/v4AdH209uvXD8ePH0eLFi0AAEOHDkVQUJBUfsGCBVixYgXefvttaX83b97E+vXrMXjwYL3tduvWDQAwb9481KlTB3fv3kXNmjXh6OgIQRCyPU6ArtWum5ubwa4RevXqhWHDhkkxHTt2DKtXr5Za/V65cgVBQUHYsWMHrKys0K9fP1y6dAn169fPtK2oqCi4ubnpzXNzc4NarcbTp09Rrly5bOPMSYUKFfDgwYN8bYOIiIiIiIiIqLhj0tZUoqJ0XRxkQzB2W9kldvPh0KFDsLe3h1qtRmpqKrp3747Vq1fj3r17SE1NlZKVAKBUKtG0aVOpBefIkSPRs2dPXLlyBZ06dUKPHj30Wq1mdOrUKSkBDADr16/HgAEDso0vLSEMADdv3kRSUpKUxE2TkpKChg0bStPr1q3DV199hQcPHuDVq1dISUkxODCWIemTmGmJy3r16unNi46OBqDrXuDhw4cYOnQoAgMDpTJqtRqOjo5Zbjct6RkdHY2aNWsaFRcAvHr1CtbW1gaXpSWx00+nHwTu7bffxt9//41Zs2Zh5syZkMvl2e5LEPRrpvhvq++M8/PCxsYGiYmJ+d4OEREREREREVFxxqStqeTQchIAxJxa2qYpW9b4lra50K5dO6xduxZKpRLly5eHUqkEAERGRgIwnLxLm9elSxc8ePAAP/74I3755Re0b98eo0aNyrLvU19fX71EYsbWnIbY2dlJv2u1WgDAjz/+iAoVKuiVU/17bL777juMHz8eK1asgJ+fHxwcHLBs2TL8/vvvOe4LgPT+gf/ee8Z5aXGk/dy4cSOaNWumt52MSVFD201b31hly5bF8+fPjS6f/txt27YNX3/9NZYvX47t27dj0KBBGDhwoNT3cHru7u6IytBCPDo6GgqFAs7OzrmK2ZBnz55JLbGJiIiIiIiIiMgwJm1NxZhuCtRqiF5ewD//QDDUr60gABUrAmFhQA6tI/PCzs4OVatWzTS/atWqsLKywunTp9G/f38AQGpqKi5duoRx48ZJ5VxcXBAQEICAgAC0atUKkydPxvLly2FlZQVANzBYGhsbG4P7srKy0iuXldq1a0OlUiEiIgJt2rQxWObUqVNo3rw5PvjgA2nevXv38rS/nLi5uaFChQq4f/9+ji2Gs2NsPA0bNkRUVBSeP38OJycnvWXnz5/Hu+++qzedvvVxq1at0KpVK6xZs0bqp3jevHlo3rw5Bg0ahF69eqF06dIAdK10f/jhB73t//zzz/D19dVLPudFUlIS7t27Z3TLZyIiIiIiIiKikooDkZmTXA7Np5/qfs/46Hna9MqVJknYZsfOzg4jR47E5MmTceTIEdy8eROBgYFITEzE0KFDAQCzZ8/G999/j7t37+LGjRs4dOiQNEiWq6srbGxscOTIETx+/BixsbFZ7svLywu///47wsPD8fTp0yxboDo4OGDSpEkYP348tmzZgnv37uGPP/7AF198IQ38VbVqVVy6dAlHjx7F7du3MWvWLFy8eDHT/q5du4Zbt27h6dOn+Rpca+7cuVi8eDFWrVqF27dv4/r169i8eTM+TTunRvDy8sLLly9x/PhxPH36NMuuAxo2bAgXFxecOXMm07Ldu3fj66+/xu3btzFnzhxcuHABo0ePzlTOzs4O7777Lo4fP4779++jU6dOWLZsGdq3by+VGTFiBB48eIAJEyYgNDQUX3/9NTZt2qQ3QNr+/fszde1w9+5dhISEICoqCq9evUJISAhCQkKQkpIilTl//jxUKhX+97//GX18iIiIiIiIiIhKIiZtzUx86y1g924gwyP/qFgR2LMH+HeQq8K2ZMkS9OzZE4MGDUKjRo1w9+5dHD16VGrlaWVlhWnTpqF+/fpo3bo15HI5du3aBQBQKBT4/PPPsX79epQvXx7du3fPcj+TJk2CXC5H7dq14eLigoiIiCzLLliwALNnz8bixYtRq1Yt+Pv744cffpAe8x8xYgTefvtt9OnTB82aNUNMTIxeq1sACAwMRI0aNeDr65tlEtRYw4YNw1dffYWgoCDUq1cPbdq0QVBQkMFuB7LSvHlzjBgxAn369IGLiwuWLl1qsJxcLseQIUOwffv2TMvmzZuHXbt2oX79+tiyZQu2b9+O2rVrZ7vfSpUqYebMmbh9+7beNitXrozDhw8jODgYPj4+WLBgAT7//HP07NlTKhMbG4tbt25lOhYNGzbE+vXrcfv2bTRs2BANGzbEP//8I5XZuXMn+vfvD1tbW6OODRERFZK1a4Fvv9X9JCIiIiIiiyCIoqHn8im9uLg4ODo6IjY2FqVKldJblpSUhLCwMFSuXDnLgaKyIooi1Go1FAoFBK0WOHUKiIwEypUDWrUq9Ba2ZNkeP36MOnXq4PLly/D09ASg67t2//796NGjh3mDy8GTJ09Qs2ZNXLx4ER4eHro6b2Bgs/xcT0SWSKvVIjo6Gq6urpDJ+D0pFX+mqvMajQbPnz+HQqHIcUDNgqbRaKBWq+Hk5FTo+y5uzHUeczqH+YnLtmVLiFFRENzdkXj6dIHFZal1nnEZH1NxjUur1eLZs2coU6ZMru/zRfF4sc4bH1NxjcuUdd4SWWqdL26yyzOmxz5tLYVcDrRta+4oyIK5ublh06ZNiIiIkJK2RUVYWBi+/PJLVK5cGWq12tzhEBEREREREekz1F2hVgvh1SvdsoxJWz5FSibGpC1REZJdVxOWrGnTpmjatCnYsJ+IiIiIiIgskV0Wg2bbabUGW9km3L5t4oiopGPSlqgIYxKUiIjy7cABXesRW1vAwrvbISIiIipMQmIiZFotBJkMIlvWUiFj0paIiIioJDtwAIiJAZydmbQlIiLLZ+gR9uww0UZGSggJyTTPtkMHiI8fQ3BzQ+IvvxR+UFSiMWlLREREREREREVCVo+wZ4WPsJPRDCX4ZTJAEHQ/+QUAFTImbYmIiIiIiIioyBISEwFRBASBj7ATUbHBpC0RERERERERFQkGH2Hv2BFCdDREV1ckHjtW+EEREZkAk7ZEREREREREVDTwEXYiKiFk5g6AiIiIiIiIiIiIiP7DpC1ZBC8vL6xcubJAtxkUFITSpUvrzduwYQM8PDwgk8mwcuVKzJ07Fz657Mi+MMXExMDV1RXh4eHmDiXXJk2ahLFjx5o7DCIiIiIiIiKiIodJWwsjimKh7CcgIACCIGDJkiV68w8cOABBEHK1rYJIuF68eBHDhw/P1zYy6tOnD26nGyk0Li4Oo0ePxtSpU/Ho0SMMHz4ckyZNwvHjxwt0vzkJCAhAjx49jCq7ePFivPHGG/Dy8jJpTF9++SUqV64Ma2trNG7cGKdOncq2fGRkJPr3748aNWpAJpNh3LhxmcpMmTIFmzdvRlhYmImiJiIiIiIiIiIqnpi0tQBqtRphYWE4d+4cTpw4gXPnziEsLAxqtdqk+7W2tsYnn3yC58+fm3Q/xnBxcYFtAfc9ZGNjA1dXV2k6IiICqamp6NatG8qVKwdbW1vY29vD2dm5QPdbUF69eoVNmzZh2LBhuVovt4n/b7/9FuPGjcOMGTPwxx9/oFWrVujSpQsiIiKyXCc5ORkuLi6YMWMGGjRoYLCMq6srOnXqhHXr1uUqHiIiIiIiIiKiko5JWzNTq9W4evUqHjx4gOTkZAC6hNiDBw8QEhJi0sRthw4d4O7ujsWLF2dbbu/evahTpw5UKhW8vLywYsUKaVnbtm3x4MEDjB8/HoIgZNtKd+7cuahUqRJUKhXKly+v9+h8xta6f/31F1q2bAlra2vUrl0bv/zyCwRBwIEDBwAA4eHhEAQB+/btQ7t27WBra4sGDRrg3Llz0jbSd48QFBSEevXqAQC8vb0hCALCw8MNdo/w9ddfS++3XLlyGD16tLTs008/Rb169WBnZwcPDw988MEHePnyZaZ9Hj16FLVq1YK9vT06d+6MyMhI6Rhs2bIF33//vXS8goODDR6vn376CQqFAn5+ftK84OBgCIKAH3/8EQ0aNIC1tTWaNWuG69evS2UePHiAChUqYNiwYdi7dy9iY2OzPCdp72no0KEYNmwYatWqhZUrV8LDwwNr167Nch0vLy+sWrUK7777LhwdHbMs9+abb2Lnzp3Z7p+IiMysShWgRg3dTyIiIiIisghM2prZ33//jfj4eCiVStSuXRt+fn6oXbs2lEolXr58iYcPH5ps33K5HIsWLcLq1avx999/Gyxz+fJl9O7dG3379sX169cxd+5czJo1C0FBQQCAffv2oWLFipg/fz4iIyOl5GRGe/bswWeffYb169fjzp07OHDggJREzUir1aJHjx6wtbXF77//jg0bNmDGjBkGy86YMQOTJk1CSEgIqlevjn79+hlMdPfp0we//PILAODChQuIjIyEh4dHpnJr167FqFGjMHz4cFy/fh0HDx5E1apVpeUymQyff/45/vzzT2zZsgW//vorpkyZoreNxMRELF++HNu2bcPJkycRERGBSZMmAdD189q7d28pkRsZGYnmzZsbfG8nT56Er6+vwWWTJ0/G8uXLcfHiRbi6uuLNN99EamoqAKBixYrYuHEjrK2tMWXKFJQtWxZt2rTBkiVLcPXqVb3tpKSk4PLly+jUqZPe/E6dOuHs2bMG950bTZs2xcOHD/HgwYN8b4uIiExk1ixg+XLdTyIiIiIisggKcwdQXGk0GiQmJmZbRhRFREREQKvVolq1alKLRUdHR3h6euKvv/7CgwcPULZsWaP2aWtrC7lcnqs433rrLfj4+GDOnDnYtGlTpuWffvop2rdvj1n//iNXvXp13Lx5E8uWLUNAQADKlCkDuVwOBwcHuLu7Z7mfiIgIuLu7o0OHDlAqlahUqRKaNm1qsOzPP/+Me/fuITg4WNrmwoUL0bFjx0xlJ02ahG7dugEA5s2bhzp16uDu3buoWbOmXjkbGxupGwQXF5csY/34448xceJEfPjhh9K8Jk2aSL+n77u1cuXKWLBgAUaOHIkvv/xSmp+amop169ahyr8tlkaPHo358+cDAOzt7WFjY4Pk5ORsjxega01cvnx5g8vmzJkjHY8tW7agYsWK2L9/P3r37g2FQoGuXbuia9euAIBbt27h8OHDOHz4MObMmYOyZcti3rx5GDZsGJ4+fQqNRgM3Nze97bu5uSEqKirb+IxRoUIF6b14enrme3tERERERERERCUBk7YmkpiYiMuXL2dbRqvV4sGDB3BycsKrV6/0WqmmpqYiPj4esbGxEEXRqMHBGjduDAcHh1zH+sknn+C1117DxIkTMy0LDQ1F9+7d9ea1aNECK1euhEajMTpJ3KtXL6xcuRLe3t7o3LkzunbtijfeeAMKReYqeOvWLXh4eOglNbNK8NavX1/6vVy5cgCA6OjoTElbY0RHR+Off/5B+/btsyzz22+/YdGiRbh58ybi4uKgVquRlJSEhIQE2NnZAdAlz6uke8S0XLlyiI6OznU8r169grW1tcFl6btMKFOmDGrUqIHQ0NBM5URRxKtXr5CUlITk5GRotVqoVCoolUq9chnrl7F1Lic2NjYAkOMXGERERERERERE9B8mbU3E1tYWjRs3zraMKIoQRRFarRY2NjZwcXGRlj158gQODg5wcnLKcTvp95kXrVu3hr+/P6ZPn46AgIBMMRpK6OWWh4cHbt26hWPHjuGXX37BBx98gGXLluHEiROZEoi5SRimXzdtHa1Wm+v4gP8SjFl58OABunbtihEjRmDBggUoU6YMTp8+jaFDh0pdE2SMKS2uvByzsmXL5mqQuLT3n5qaigMHDuCnn37CkSNH8OzZM7Ru3RpvvfUWNmzYoJfQLlu2LORyeaZWtdHR0Zla3+bFs2fPAECvbhMRERERERERUfaYtDWRtC4DsiOKIipVqoS///4bDx48gJWVFRwdHREbG4sHDx5AoVDA09MzT61nc2vJkiXw8fFB9erV9ebXrl0bp0+f1pt39uxZVK9eXWpla2VlBY1Gk+M+bGxs8Oabb+LNN9/EqFGjULNmTVy/fh2NGjXSK1ezZk1ERETg8ePHUuLw4sWL+Xl7RnFwcICXlxeOHz+Odu3aZVp+6dIlqNVqrFixAjKZrjvo7777Ltf7MfZ4NWzYEN98843BZefPn0elSpUAAM+fP8ft27elZOyjR48wdepUdOnSBRs2bMBrr72WZULfysoKjRs3xrFjx/DWW29J848dO5aphXVe/Pnnn1AqlahTp06+t0VERCayYAEQGws4OrJfWyIiIiIiC1GkkraLFy/Gvn378Ndff8HGxgbNmzfHJ598gho1amS5TnBwsMEEXGhoaJ4eoS9oFStWRGxsLF6+fImbN2/qLbO3tzc4WJYp1KtXDwMGDMDq1av15k+cOBFNmjTBggUL0KdPH5w7dw5r1qzR68PVy8sLJ0+eRN++faFSqQz2wRsUFASNRoNmzZrB1tYW27Ztg42NjcF+Tjt27IgqVapg8ODBWLp0KeLj46WByArikf3szJ07FyNGjICrqyu6dOmC+Ph4nDlzBmPGjEGVKlWgVquxevVqvPHGGzhz5gzWrVuX6314eXnh6NGjuHXrFpydneHo6JipdS4A+Pv7Y9q0aXj+/DmcnJz0ls2fPx/Ozs5wc3PDjBkzULZsWfTo0QOArh/Zw4cPS2UjIiIybdvJyUlKiE+YMAGDBg2Cr68v/Pz8sGHDBkRERGDEiBFS+WnTpuHRo0fYunWrNC8kJAQA8PLlSzx58gQhISGwsrJC7dq1pTKnTp1Cq1atcmzFTEREZnTvHhATA/zb9zsREREREZmfzNwB5MaJEycwatQonD9/HseOHYNarUanTp2QkJCQ47q3bt1CZGSk9KpWrVohRJwzhUKBBg0awNPTEyqVCgCgUqng6ekJHx8fg32+msqCBQsyPcbfqFEjfPfdd9i1axfq1q2L2bNnY/78+XrdKMyfPx/h4eGoUqVKlo/Bly5dGhs3bkSLFi1Qv359HD9+HD/88IM0OFh6crkcBw4cwMuXL9GkSRMMGzYMM2fOBIAs+3gtKIMHD8bKlSvx5Zdfok6dOnj99ddx584dAICPjw8+/fRTfPLJJ6hbty62b9+OxYsX53ofgYGBqFGjBnx9feHi4oIzZ84YLFevXj34+voabM27ZMkSfPjhh2jcuDEiIyNx8OBBWFlZAdC1tK1Vq1a2rwULFkjb6tOnD1auXIn58+fDx8cHJ0+exOHDh/US6pGRkZmSvw0bNkTDhg1x+fJl7NixAw0bNpQGP0uzc+dOBAYG5voYERERERERERGVZIKYl842LcSTJ0/g6uqKEydOoHXr1gbLpLW0ff78OUqXLp2n/cTFxUndFpQqVUpvWVJSEsLCwlC5cuVcJxRFUYRarYZCoZBakBbUAFDFzZkzZ9CyZUvcvXtXb5Cv4u7w4cOYNGkS/vzzT8hksgKpz4Xlxx9/xOTJk3Ht2jXpywdDdT69/FxPRJZIq9UiOjoarq6uUrcqRBYnIOC/lrZBQfnalKnqvEajwfPnz6FQKIweBLUg961Wq+Hk5FTo+y5uzHUeczqH+YnLtmVLiFFRENzdkZihS7H8xGWpdZ5xGR9TcY1Lq9Xi2bNnKFOmTK7v8ya9Flu1gvD4MUQ3NySeOlVgcbHOGx9TcY3LVPd5S5WrY5XbAcdzGIepKB6vvMouz5hekeoeIaPY2FgAQJkyZXIs27BhQyQlJaF27dqYOXOmwS4TLAETtjr79++Hvb09qlWrhrt37+LDDz9EixYtSlTCFgC6du2KO3fu4NGjR4XWVUZBSUhIwObNmwu1tTgRERERERERmZ6dj0+uyifcvm2aQIqxIptNEUUREyZMQMuWLVG3bt0sy5UrVw4bNmxA48aNkZycjG3btqF9+/YIDg7OsnVucnIykpOTpem4uDgAum8VtVqtXlmtVgtRFKVXXt5H+p+kExcXhylTpuDhw4coW7YsOnTogOXLl5fI4zR27FgA0Ktjea1vhalXr14AMtft7Op82vsydK0RFUVpfyNYn8mSCaII/PsS81lXTVXn03/eKuzrKf1++eV6/pjrPOZ0DvMTl5juZ67XzSYuS63zjMv4mIprXPm5z5v0eKX9b5GX69gC65alxlUS67yp7vOWKr/nUEhM1F2PggAxQ8vanLZXFI9XXhl7bIts0nb06NG4du0aTufQPL1GjRp6A5X5+fnh4cOHWL58eZZJ28WLF2PevHmZ5j958gRJSUl681JTU6HVaqFWq6FWq3P1HkRRhEajAcAWthn1798f/fv3zzQ/t8e4uGnZsiVSUlIAFM1jkVOdV6vV0Gq1iImJMTg4G1FRo9VqERsbC1EU2T0CWSzHpCQIKSkQk5IQGx2dr22Zqs5rtVq8fPkSMpnMLI+narVapKam8jrOJ3Odx5zOYX7islarIRNFaNVqPHv2rMDistQ6z7iMj6m4xpW2bl7u8ya9FjUayLVaaDQaXotmiqm4xmWq+7ylys2xen78eKZ55d55B/KnT6EpWxaRe/boLRNzOH5F8XjlVXx8vFHlimTSdsyYMTh48CBOnjyJihUr5nr9//3vf/jmm2+yXD5t2jRMmDBBmo6Li4OHhwdcXFwM9mkbHx8PhUKR58fAmZyikiarOq9QKCCTyeDs7Mw+balYSPuW2MXFpdh/8KCiS7C2BqysAGtrqFxd87UtU9V5jUYDpVIp/Z0oTGlfzpcuXbrY969mauY6jzmdw/zEJVcoAEGAXKEwqss2Y+Oy1DrPuIyPqbjGlXafd3JyytO6popLIZdDkMkgyOW8Fs0UU3GNy1T3eUuV33OoUCohyOUQlEo4VaiQq3WL4vHKK2PzHUUqaSuKIsaMGYP9+/cjODgYlStXztN2/vjjD5QrVy7L5SqVCiqVKtN8mUyWqdLKZDIIgiC9ciP9oGNsaUslQU51Pu06MnStERVVrNNk8QRBegkFUE9NUefT/n6kbbswpe2b13H+mes85nQO8xOXAN0jswKQ63Wzi8tS6zzjMj6m4hxXXu+JJo0r7X+LPKxriXXLUuMqiXXeVPd5S5Xvc2iia7G4Mfb9Famk7ahRo7Bjxw58//33cHBwQFRUFADA0dERNjY2AHStZB89eoStW7cCAFauXAkvLy/UqVMHKSkp+Oabb7B3717s3bvXbO+DiIiIiIiIiIiIKCtFKmm7du1aAEDbtm315m/evBkBAQEAgMjISEREREjLUlJSMGnSJDx69Ag2NjaoU6cOfvzxR3Tt2rWwwiYiIiKyXD16AImJQIbBIoiIiIiIyHyKVNLW0GjzGQUFBelNT5kyBVOmTDFRRERERERFXI8e5o6AiIiIiIgyKN6dRBAREREREREREREVMUzaUpYEQcCBAwcKdJtz586Fj49Ppnlubm7S/gICAtCjBLb6adu2LcaNG5evbQQFBaF06dIFEg8REREREREREZlHkeoeoaiJj4/PdrkoilCr1VAoFBDSRtjLIwcHh1yVj46OxqxZs/DTTz/h8ePHcHJyQoMGDTB37lz4+fkB0PUP7OTklK+4Mpo0aRLGjBkjTYeGhmLevHnYv38//ve//8HJyQnt2rUzqiuMgtS2bVv4+Phg5cqVhbrf9Pbt2welUmm2/RMRUQn16hUgirrRfv8d2JWIiIiIiMyLSdsSqmfPnkhNTcWWLVvg7e2Nx48f4/jx43j27JlUxt3dvcD3a29vD3t7e2n63r17AIDu3btLiWuVSlXg+7VkqampUCqVKFOmjLlDISKikmjkSCAmBnB2BjKMDUBERERERObB7hFKoBcvXuD06dP45JNP0K5dO3h6eqJp06aYNm0aunXrJpXL2D3C2bNn4ePjA2tra/j6+uLAgQMQBAEhISEAgODgYAiCgOPHj8PX1xe2trZo3rw5bt26JW0jffcIc+fOxRtvvAEAkMlkUtI2Y/cIWq0Wn3zyCapWrQqVSoVKlSph4cKF0vKpU6eievXqsLW1hbe3N2bNmoXU1NRM+9y2bRu8vLzg6OiIvn37Si2hAwICcOLECaxatQqCIEAQBISHhxs8dl5eXliwYAH69+8Pe3t7lC9fHqtXr9YrExsbi+HDh8PV1RWlSpXCa6+9hqtXr2aK5+uvv4a3tzdUKhVEUczUPcLz58/x7rvvwsnJCba2tujSpQvu3Lmjt6+goCBUqlQJtra2eOuttxATE2MwbiIiIiIislCJibl7ERFRicCkbQmU1tr1wIEDSE5ONmqd+Ph4vPHGG6hXrx6uXLmCBQsWYOrUqQbLzpgxAytWrMClS5egUCgwZMgQg+UmTZqEzZs3A9B1xRAZGWmw3LRp0/DJJ59g1qxZuHnzJnbs2AE3NzdpuYODA4KCgnDz5k2sWrUKGzduxGeffaa3jXv37uHAgQM4dOgQDh06hBMnTmDJkiUAgFWrVsHPzw+BgYFSHB4eHlkei2XLlqF+/fq4cuUKpk2bhvHjx+PYsWMAdF1edOvWDVFRUTh8+DAuX76MRo0aoX379nqtmO/evYvvvvsOe/fulZLeGQUEBODSpUs4ePAgzp07B1EU0bVrVykh/fvvv2PIkCH44IMPEBISgnbt2uHjjz/OMm4iIiIiIrI8dj4+uXoREVHJwO4RSiCFQoGgoCAEBgZi3bp1aNSoEdq0aYO+ffuifv36BtfZvn07BEHAxo0bYW1tjdq1a+PRo0cIDAzMVHbhwoVo06YNAOCjjz5Ct27dkJSUBGtra71y9vb20qBZWXXFEB8fj1WrVmHNmjUYPHgwAKBKlSpo2bKlVGbmzJnS715eXpg4cSK+/fZbTJkyRZqv1WoRFBQk9f07aNAgHD9+HAsXLoSjoyOsrKxga2trVJcQLVq0wEcffQQAqF69Os6cOYPPPvsMHTt2xG+//Ybr168jOjpa6uZh+fLlOHDgAPbs2YPhw4cDAFJSUrBt2za4uLgY3MedO3dw8OBBnDlzBs2bNwegOwceHh44cOAAevXqhVWrVsHf318vlrNnz+LIkSM5vgciIiIiIrJcQmKi1N+4aGtr7nCIiMgM2NK2hOrZsyf++ecfHDx4EP7+/ggODkajRo0QlEVfdrdu3UL9+vX1Eq9NmzY1WDZ94rdcuXIAdAOf5UVoaCiSk5PRvn37LMvs2bMHLVu2hLu7O+zt7TFr1ixERETolfHy8tIbrK1cuXJ5jiltoLb006GhoQCAy5cv4+XLl3B2dpZaNNvb2yMsLEzqvxcAPD09s0zYArr3rVAo0KxZM2mes7MzatSoIe0rNDTUYCxERERERFR0JISEZHppPT0h2tpC6+mZaRkREZUMbGlbgllbW6Njx47o2LEjZs+ejWHDhmHOnDkICAjIVFYURanP2fTzDFEqldLvaetotdo8xWiTwyjW58+fR9++fTFv3jz4+/vD0dERu3btwooVK7KMKS2uvMZkSPr3Wa5cOQQHB2cqk9aqGADs7Oyy3V5Wxzb9eciqDBERERERFSGGWtLKZIAg6H6ypS0RUYnElrYkqV27NhISEgwuq1mzJq5du6bXB+6lS5dMHlO1atVgY2OD48ePG1x+5swZeHp6YsaMGfD19UW1atXw4MGDXO/HysoKGo3GqLLnz5/PNF2zZk0AQKNGjRAVFQWFQoGqVavqvcqWLWt0PLVr14Zarcbvv/8uzYuJicHt27dRq1YtqYyhWIiIiIiIiIiIqGhj0rYEiomJwWuvvYZvvvkG165dQ1hYGHbv3o2lS5eie/fuBtfp378/tFothg8fjtDQUBw9ehTLly8HgEwtcAuStbU1pk6diilTpmDr1q24d+8ezp8/j02bNgEAqlatioiICOzatQv37t3D559/jv379+d6P15eXvj9998RHh6Op0+fZtsK98yZM1i6dClu376NL774Art378aHH34IAOjQoQP8/PzQo0cPHD16FOHh4Th79ixmzpyZqyR3tWrV0L17dwQGBuL06dO4evUqBg4ciAoVKkjnaOzYsThy5IgUy5o1a9ifLRERERERERFRMcCkbQlkb2+PZs2a4bPPPkPr1q1Rt25dzJo1C4GBgVizZo3BdUqVKoUffvgBISEh8PHxwYwZMzB79mwAyDTAWEGbNWsWJk6ciNmzZ6NWrVro06eP1B9t9+7dMX78eIwePRo+Pj44e/YsZs2alet9TJo0CXK5HLVr14aLi0umPnHTmzhxIi5fvoyGDRtiwYIFWLFiBfz9/QHoEtiHDx9G69atMWTIEFSvXh19+/ZFeHg43NzcchXT5s2b0bhxY7z++uvw8/ODKIo4fPiw1NXD//73P3z11VdYvXo1fHx88PPPP+sNykZEREREREREREWTILJjzBzFxcXB0dERsbGxKFWqlN6ypKQkhIWFoXLlyrlOXoqiCLVaDYVCYdLWqqayfft2vPfee4iNjc2x79niwsvLC+PGjcO4cePMHUqRlFOdz8/1RGSJtFotoqOj4erqCpmM35OShQoIAGJiAGdnIIsBSY1lqjqv0Wjw/PlzKBQKyOXyAtuusftWq9VwcnIq9H0XN+Y6jzmdw/zEZduyJcSoKAju7kg8fbrA4rLUOs+4jI8pv3HZtmoF4fFjiG5uSDx1ymLi0mq1ePbsGcqUKZPr+3xRPF6s88bHVFzjMtV93lLl9xya8t5VnGSXZ0yPA5GR0bZu3Qpvb29UqFABV69exdSpU9G7d+8Sk7AlIiIqlmbOBNRqQMGPhUREREREloKfzsloUVFRmD17NqKiolCuXDn06tULCxcuNHdYRERElB9Vq5o7AiIiIiIiyoBJWzLalClTMGXKFHOHYVbh4eHmDoGIiIiIiIiIiIo5drBHREREREREREREZEHY0raAcDw3ovzjdUREZAYXLwLJyYBKBTRpYu5oiIDExNyVt7U1TRxEREREZsSkbT4plUoAQGJiIgfkIsqnxH//SUu7roiIqBB88QUQEwM4OwNBQeaOhgh2Pj65Kp9w+7ZpAiEiIiIyIyZt80kul6N06dKIjo4GANja2kIQBKPWFUURarUaCoXC6HWIirKs6rwoikhMTER0dDRKly4NuVxuxiiJiIjI0giJiYAoAoIAkS1riYiIqARg0rYAuLu7A4CUuDWWKIrQarWQyWRM2lKJkFOdL126tHQ9ERERUcmUEBKSaZ5tx44QoqMhuroi8dixwg+KiIiIqJAxaVsABEFAuXLl4OrqitTUVKPX02q1iImJgbOzM2QyjglHxV92dV6pVLKFLRERERnuo1YmAwRB95MtbYmIiKgEYNK2AMnl8lwlnbRaLZRKJaytrZm0pRKBdZ6IiIiIiIiIKGfMmhARERERERERERFZECZtiYiIiIiIiIiIiCwIk7ZEREREREREREREFoRJWyIiIiIiIiIiIiILwqQtERERUUlmbQ3Y2Oh+EhERERGRRVCYOwAiIiIiMqN168wdARERERERZcCWtkREREREREREREQWhElbIiIiIiIiIiIiIgvCpC0RERERERERERGRBWGftkREREQl2ddfAy9fAvb2wJAh5o6GiIiIiIjAlrZEREREJdvJk8CxY7qfRERERERkEZi0JSIiIiIiIiIiIrIgTNoSERERERERERERWRAmbYmIiIiIiIiIiIgsCJO2RERERERERERERBaESVsiIiIiIiIiIiIiC8KkLREREREREREREZEFYdKWiIiIiIiIiIiIyIIwaUtERERERERERERkQRTmDoCIiIiIzKhJEyA+HnBwMHckRERERET0LyZtiYiIiEqyUaPMHQERFTeJibkrb2trmjiIiIiKMCZtiYiIiIiIqMDY+fjkqnzC7dumCYSIiKgIY9KWiIiIiIiITEpITAREERAEiGxZS0RElCMmbYmIiIiIiKjAJISEZJpn27EjhOhoiK6uSDx2rPCDIiIiKmKYtCUiIiIqycaPB54/B5ycgM8+M3c0RFQcGGpJK5MBgqD7yZa2REREOWLSloiIiKgke/4ciIkxdxRERGRpDA0op9VCePVKt0wm01/GZDwRUYFi0paIiIiIiIiI9GQ1oJydVgtZxoQtOKAcEVFBY9KWiIiIiIiIiHIkJCZCptVCkMk4oBwRkYkxaUtEREREREREegwOKNehA8THjyG4uSHxl18KPygiohKESVsiIiIiIiIi0scB5YiIzCpzRzREREREREREREREZDZM2hIRERERERERERFZECZtiYiIiIiIiIiIiCxIkUraLl68GE2aNIGDgwNcXV3Ro0cP3Lp1K8f1Tpw4gcaNG8Pa2hre3t5Yt25dIURLRERERERERERElHtFKml74sQJjBo1CufPn8exY8egVqvRqVMnJCQkZLlOWFgYunbtilatWuGPP/7A9OnTMXbsWOzdu7cQIyciIiKyUO+9B4wZo/tJREREREQWQWHuAHLjyJEjetObN2+Gq6srLl++jNatWxtcZ926dahUqRJWrlwJAKhVqxYuXbqE5cuXo2fPnqYOmYiIiMiytWlj7giIiIiIiCiDItXSNqPY2FgAQJkyZbIsc+7cOXTq1Elvnr+/Py5duoTU1FSTxkdERERERERERESUW0WqpW16oihiwoQJaNmyJerWrZtluaioKLi5uenNc3Nzg1qtxtOnT1GuXLlM6yQnJyM5OVmajouLAwBotVpotdoCege67YmiWKDbJLJkrPNU0rDOU0ljqjqftl1zXE/p9ysIQqHuu7jJ13kURelnbtfN6RzmJy4x3c+CjMtS67y5zqFJ48oHU9atklbn8xuXqY5XsbwWTRRTcY3LlHXeEuX7HJrw3lWcGHtsimzSdvTo0bh27RpOnz6dY9mMJ1v8txJlVQkWL16MefPmZZr/5MkTJCUl5SFaw7RaLWJjYyGKImSyIt3omcgorPNU0rDOU1Egi4wENBpALofWwJfZuWGqOq/VavHy5UvIZDLI5fIC264xNBoNtFotUlNTeR3nU37Oo7VGA7lWC41Gg2fPnuVq3ZzOYb7iUqshE0Vo1eoCjctS67y5zqEp48oPk9atElbn8x2XiY5XUb8WhVevcrVP0cYmzzHlJq6CVlTrvCXK7zk05b2rOImPjzeqXJFM2o4ZMwYHDx7EyZMnUbFixWzLuru7IyoqSm9edHQ0FAoFnJ2dDa4zbdo0TJgwQZqOi4uDh4cHXFxcUKpUqfy/gX+lfXvg4uJS7CskEcA6TyUP6zwVBcLUqUBMDODsDHHz5nxty1R1XqPRQKlUQqFQFPq1pNVqoVarUbp06UL/h724yc95VMjlEGQyCHJ5tl2jGZLTOcxPXHKFAhAEyBWKAo3LUuu8uc6hKePKD1PWrZJW5/Mbl6mOV1G/Fh1q1szVPuP/+ivPMeUmroJWVOu8JcrvOTTlvas4sba2NqpckUraiqKIMWPGYP/+/QgODkblypVzXMfPzw8//PCD3ryff/4Zvr6+UCqVBtdRqVRQqVSZ5stksgK/8QiCYJLtElkq1nkqaVjnyeIJgvQSCqCemqLOi6IIQRCkbRemtH3zOs6/fJ3HtCfk8rBuTucwP3EJ0D0yKwAFGpel1nlznUOTxpUPpqxbJa3O5zcuUx2v4ngtComJukfYBQGira3espy2ZdJzmA9Ftc5bonyfQxPeu4oTY99fkUrajho1Cjt27MD3338PBwcHqQWto6MjbP5txj9t2jQ8evQIW7duBQCMGDECa9aswYQJExAYGIhz585h06ZN2Llzp9neBxERERERERGRKSWEhGSaZ9uxI4ToaIiurkg8dqzwgyIioxWppO3atWsBAG3bttWbv3nzZgQEBAAAIiMjERERIS2rXLkyDh8+jPHjx+OLL75A+fLl8fnnn6Nnz56FFTYRERERERERUeHK0JIWACCT6VpDymSGlxORxShSSdu0AcSyExQUlGlemzZtcOXKFRNEREREREREJZJGAyQkQEhOBhISpAH9iIiIiApC8e4kgoiIiIiIqIDJjx6FbevWkIWFQRYbC1lYGGxbt4b86FFzh0ZERETFBJO2RERERERERpIfPQqbwEDI7t7VG8hPdu8ebAIDmbglIiKiAsGkLRERERERkTE0GqjmzweSkyGWKqWXtBUdHICUFKgWLNB1lUBERESUD0zaEhERERERGUF26RJkYWEQbW0BtVqXnNVqdQsFAaKNDWT370N26ZJ5AyUiIqIij0lbIiIiIiIiI8iePNElaeVyCLGxQNpAyWk/5XJAq9WVIyIiIsoHhbkDICIiIiIz+vRTXRJKxu/yiXKidXEBZDIIcXH/tbAF/vtdowFkMl25wpKYmLvytramiYOIiIgKFJO2RERERCVZmTLmjoCoyND6+kIsWxZCeLiuL9s0ogjh1SsgNRXaqlWh9fUttJjsfHxyVT7h9m3TBEJEREQFik0qiIiIiIiIjPHiBUStVpewFUX9xG18PGBlheRZs3TdJJiRkJgIISEBQm5b4RIREZHFYEtbIiIiIiKinIgiVHPmQEhJgVi6tK51bVzcf/3ZymRIGT4cGn//Qg0rISQk0zzbjh0hREdDdHVF4rFjhRoPERERFQwmbYmIiIhKsiNHgKQkwNoa6NzZ3NEQWSzFwYNQ/PwzAEB0d8ergwdh07kzEBkJWXIyRGdnyM+eLfw+og31USuT6VoBy2Tsw5aIiKiIYtKWiIiIqCTbtQuIiQGcnZm0JcqCEBUFq/nzpenkefMgurkBdnYQ7ex03SEIAmR370J+9Cg0XbqYMVoiIiIqDtinLRERERERUVZEEapp0yDExwMA1G+8AU36LzgEAVoXF2nS6ssvda1tiYiICoCo0eTqRcUHW9oSERERERFlQbFjB+RnzgAARFdXJM+enbmQnR20VatCdu0aZLduQf7LL9B06lTIkRIRUXGUfOpUrspbt21rmkCo0LGlLRERERERkQHCgwdQffKJNJ28aBHg6GigoICU0aOlSasvvvhvgDIiIqICJqrV0L54AVGtNncoZEJsaUtERERERJSRRgPV1Km6gfoApPbtC03r1lkXb9MG2jp1ILtxA7LQUMh//RWa9u0LK1oiIiqmVK1aZZqnjY9HypUrsGrUCDIHBzNERYWBLW2JiIiIiIgyUH79NeRXrgAARA8PpEydmv0KGVvbrlnD1rZERJRvglxu+CWTGZxPxQeTtkREREREROnIbt+G1cqVuglBQNKSJYCdXY7raV57DdpatXTbuHED8hMnTBglERERFWdM2hIREREREaVJTYVq8mQgNVU3OWQItE2aGLeuICBl1Chpkq1tiYiIKK+YtCUiIiIiIvqX8ssvIQsNBQBoq1VDyrhxuVpf06EDtDVqAABk165Bfvp0QYdIREREJQCTtkREREQlWYUKgIeH7idRCSe7dg1W69bpJhQKJC9dCqhUudyIDCkffCBNWq1ezda2RERElGsKcwdARERERGa0cKG5IyCyDElJUE2ZAmg0AICUDz6Atk6dPG1K4+8PbdWqkN29C1lICOTnzkHTvHlBRktEVHQlJuauvK2taeIgsnBM2hIRERERUYln/dlnkN2/DwDQ1q2L1Pffz/vGZDKkjhoF1fjxAADl6tXQ+PkBglAQoRIRFWl2Pj65Kp9w+7ZpAiGycOwegYiIiIiISjTFhQuw2rpVN2FlhaSlSwGlMl/bVHfuDK23NwBAfvkyZBcu5DdMIqJiS0hMhJCQACG3rXCJijG2tCUiIiIiopIrPh52M2dKkykTJkCsWjX/25XLkfrBB1BNmgQAsFqzBknNmuV/u0RERVxCSEimebYdO0KIjobo6orEY8cKPygiC8SWtkREREQl2fLlwOzZup9EJZAwfz5k//wDANA0aYLUgIAC27a6a1eInp4AAPnvv7O1LRERoOujNuNLJtN1ISOTZV5GVEIxaUtkpMTE3L2IiIiKhD//BP74Q/eTqKT55RcIu3YBAERbWyQvWaJLGBQUhQIpI0dKk1Zffllw2yYiHY0GSEgAkpJ0P/8dTJCIqKhj9whERsrtU3L/NtggIiIiIkv0/Dnwb9cFAJA0dSpED48C3436zTdh9cUXEB4+hPzsWciuXIG2UaMC3w9RSSQ/ehSq+fN1gwhqtRDi4mDbujWSZ8+Gxt/f3OEREeULW9oS5UNiou7LXLasJSIiIipipk0DoqMBAKmtWiG1Vy/T7Cdja9s1a0yzH6ISRn70KGwCAyG7e1f3WP2/L9m9e7AJDIT86FFzh0hElC9M2hIZ6e7dzC8vL10XO15emZcRERERkYU6eFD3AgBHRyTMm6dL+JiIunt3iBUqAADkp09DZmAQHiLKBY0GqvnzgeRkiA4Ounn/Jm1FBwcgJQWqBQvYVQIRFWlM2hIZiX2lExERERUDjx8DH30kTWoXLYLo6mrafSqVSBkxQppk37ZE+SO7dAmysDCItrYQ4uJ0yVmtVrdQECDa2EB2/z5kly6ZN1AionwokKTtw4cPceTIEcTExBTE5oiIiIiIiAqeKOr6sX3xQjf95pu6VyFQv/02xHLlAADy4GDIrl8vlP0SFUeyJ090fdimpgIpKf8tSEvcyuWAVqsrR0RUROU6aTtz5kyMHz9emv7ll19QvXp1dOvWDdWrV8eNGzcKNEAiIiIiIqICsXMncPy47ndXV2Dx4sLbt1KJlOHDpUnrtWsLb99ExYzWxUX3y8uXGRZodV/OaDSATPZfOSKiIijXSdu9e/eidu3a0vTMmTNRv3597N+/H56envj4448LNEAiIiIiIqJ8i4gA5sz5b3rZMsDJqVBDUPfqBdHNDQCg+O03yENDC3X/RMWFtl49XT91aUnadISkJAivXkHr7Q2tr6+ZIiQiyj9Fbld49OgRqlatCgCIiYnBxYsXcfjwYfj7+yMpKQkTJ04s8CCJiIgo9xITc1ee/XETUbGl1UI2cSKQkKCb7tsX6Nix8OOwskLK++/rBlACYLNuHdC8eeHHQVTEWX32GUQrKwiJidIAZFLXCPHxQKlSSJ41S9dNAlFeaTRAQgKE5GTd3w+NhnWKClWuk7aiKEL7783wzJkzkMvlaN26NQCgXLlyePr0acFGSERERHny73esRvvnH9PEQRbO31/3j4idnbkjITIZ1TffAOfP6yYqVgTmzTNbLOpevWC1bh2E6Ggojx8HQkOBunXNFg9RUSM/dQrKLVsAlQpi2bIQnZwgu3v3vwIyGZJHj4bG3998QVKRJz96FKr58yELC9N9IRAfD9vWrZE8ezbrFhWaXHePUKVKFRw6dAgAsGvXLjRt2hQ2NjYAgMjISDgV8iNGREREZLzERF1+LretcKkY69cPGDZM95OoGJLduwfblSv/m/HZZ4CDg9nigUqF1MBAaVL4/HPzxUJU1MTEQPXRR9Jk8ty5SPz9d2i9vSHa2QFyOURnZ8ivXDFjkFTUyY8ehU1goO7LgLSW3IIA2b17sAkMhPzoUXOHSCVErlvavv/++xg1ahS2bt2KFy9e4Ouvv5aWnTlzRq+/WyIiIjKf9I1O0jRvDjx+DLi5AWfPFn5MRESFSq2GzdSputHlZTLdFxQtWpg7KqT27g3lunXA06cQfvwRuHULqFHD3GERWTZRhPWMGRCePAEAaFq1gnrgQF1Czc4OsLfXlRMEyK9cgezSpcLr05Z9UhUfGo2uC5vkZIilSkGIiZGStqKDA4T4eKgWLEBihw7sKoFMLtdJ25EjR8LJyQlnz55F06ZNMXDgQGnZq1evEBAQUJDxERERUR4Z+n9AJtN97pTJ+P8CERV/ynXrIL9xAyIAeHsD06ebOyQdGxskDxkC1dKlukGUVq4E1q41d1REFk2xaxfkv/4KABCdnJC8ZInuQ00aQYC2bFld/6MArDZsQFIhJW3tfHxyVT7h9m3TBEL5Jrt0CbKwMIi2trr7s0aj+ymKEF69gqhQQHbvnu5LgWbNzB0uFXO5TtoCQN++fdG3b99M8zds2JDvgIiIiIiIiPJLduMGrL78Ujchl0O7ciXk1tbmDSqdlL59YfXVV8CLF8DBg8DEibnvjJyohBDu3YNq8WJpOnnxYoguLpkLOjpClMshREZCHhwM2a1b0JqpFbuQmKhL9gmCLgFIRYLsyRNdH7ZyOYT4eN05BHQ/X76E8G8C13rYMGibNoW2Zk1oa9WCpkYNiJUrA4o8pdmIDGJtIiIiIirJAgKAmBjA2RkICjJ3NEQFIzkZqilTALUaAJA0bBisGzY0c1AZ2NoiKSAAditX/tfads0ac0dFZHlSU2E9cSKQlKSb7N8fmtdeM1xWEJA6ZAisFi4EACg3bkTy8uUmDzEhJCTTPNuOHSFER0N0dUXisWMmj4EKhtbFRfdIWkoK8G+r7UwEAUJ8POSnTkF+6tR/862soK1aVUrkolo1aKpWBTj2E+WRUUnbypUrQ0j/2EEO7t+/n+eAiIiIiIiI8sNq1SrI7twBAGhq1cKrESNgOW1s/5PUpw/stmwBnj8HDhwAJkzQdeNARBKrlSshu3kTAKD19kbK1KnZlk/t1QvKNWsgxMZC8eOPSBk3DmLFiqYNkn1SFRtaX19oK1eGLDT0v1a2aefR3h5ISIBoZwfR2VnXEje9lBTIbt6U6qsVAFtRhKxCBaBOHaB2bd2rTh3Ay4t94lKOjEratmnTRi9p++uvvyIqKgrNmzeHu7s7oqKicPbsWZQrVw6vZfWNFxERERERkYnJLl2CctMm3YRSiVdLlgBKpXmDyoqdHcThwyF88onucdzPP9e1uCUiAID8/Hkov/pKN6FUIvnTTwEbm+xXsrVF6rvvwmr1akCjgfLrr5Eye7bpg6XiQS5HyqhRsB458r+kbZrUVMDeHkkbN0LTqROEx48hCw2F7K+/ILt1S/f7gwe6+3l6kZG61y+//DfP2hqoWfO/JG7t2kCtWkCpUqZ/j1RkGJW0DUr3qNy2bdtw5swZ3LlzB5UqVZLmP3jwAB07dkSbNm0KPEgiIiIiIqIcJSTAeupU6R/tlHHjoK1eXeomwRKJgwcD69YBsbHA3r3AuHGAh4e5wyIyvxcvoJo8+b/refx4aGvXNmrV1IEDYbVxI5CUBOWePUgZNUrXDRCREWR370IsXVrXkjbdQGTaqlWRPGsWNP7+AADR3R0ad3do2rX7b+VXryC7cweyv/6CcPMmhL/+gtW9e0BcnP5OkpKAkBDdK72KFfUTuXXqAJUq6Vr6UomT6z5tlyxZgnnz5uklbAHA09MTc+bMwccff4zBgwcXWIBERERERETGsFq6FMLDhwAAbcOGSB0yxMwRGcHBARg+HFi2TJcc+Pxz3e9EJZkoQjV7NoTHjwEAGj+/3F3PTk5I7d0byq1bdYnbb75B6ocfmihYKk6Ep0+h3L0bUKkglioFURB0XdiULYvEEydy7tLAxgba+vWhrV8fGo0GarUaTqVLQx4ZCYSGAjduADdv6n4+eJC5Ne/ff+teP//83zxbW10r3PTdK1SoUPBvnixOrpO29+7dg6Ojo8FlTk5OCA8Pz29MREREREREuSI/dQrKnTt1E9bWSFq6VPfPtUZj3sCMMXQosH69riXWnj3AmDG6ZC5RCaXYtw+KI0cAAGKpUkheujTXLQ1ThwyBcscOQK2Gcts2pA4bBtjZmSJcKkaUX38tDUCW2r8/FD/+CDExEYKdXd77oBUE3RMUHh5Ap07/zU9IAP76S5fETUvkhobq5qeXmAhcvqx7pW1SFGFVpgyExo2BBg3+a5nr4aHbHxULuU7aenl5YdOmTejatWumZRs3boSnp2eBBEZERERERGSU2Fiopk2TJpOnToVYlP4vKVUKCAwEVqwA1GoIa9YA6d4PUUkii4iAasECaTr5448hurnlejti+fJQv/46FAcOQIiLg/K775D63nsFGSoVNy9e6BL9AKBUInXoUCh+/NF0+7OzAxo31r3SaLVARIQuiZu+ZW5ERKbVhcePgWPH9PvKtbfXtcpNP/BZzZocDK+IynXS9qOPPsKQIUPQtGlT9OvXTxqIbOfOnbh8+TK+SusknIiIiIiIqBCo5s+HEB0NANA0bw51//5mjigPhg3TtbZ9+RLCnj2QDR6s68eQqCRJTYXN5Mm6loUA1O+8A03nznneXEpgIBQHDgDQtaBMHTjQcgcmJLNTbtsm1b3Ud96B6Opa+EHIZICXl+6VvrFkfPx/SdzQUODaNYjXr0PIOOjZy5fAxYu6VxpB0G0vfT+5tWsD5cuzVa6Fy3XSNiAgAAAwc+ZMTJw4UZpfrlw5bNy4Ee/xmysiIiIiIiok8iNHoPjhBwCA6OCA5CVLiuY/oY6Oum4SVq0CUlNhvWkTUubNM3dURIXKZv16yK9dAwCIlSohecaMfG1PrFYNmtdeg/zXXyE8fgzFwYNQ9+xZEKFScfPyJZRbtuh+l8t13WlYEgcHoGlT3QuAGB+PlAsXYOXiAuHBg/+6WLh5E3j0SH9dUQTCwnSvQ4f+m1+qlH4/ubVrA1Wr5j1GjUbXtUNSku6nRpP3LiUIQB6StoAucTt48GDcunULMTExcHZ2Ro0aNSAUxQ9HRERERFR8/NtCxmh8XLBIE54+hWrOHGk6ZdYsiO7uZowon4YPB776CkhIgGrfPqSOHMnBZqjkuHAB1hs26H6Xy5G0YkWB9EGbMnw4bH79FQCg3LgR6rfeynX/uFT8KXfuhBAXBwBQv/EGRA8PM0dkBLkcqFwZqF8feOON/+bHxmbuJ/evv6S+eiVxccD587rXv2QyGRwrVYK2Rg2ItWtDW7MmtLVq6VodZ5Pzkx89CtX8+ZDdvw9otRDi4mDbujWSZ8+Gxt+/oN95iZGnpC0ACIKAmjVrFmQsRERERFTYJk4EUlOLzeOidj4+uSqfcPu2aQIh0xNFqGbNgvD8OQBA3bEj1N27mzmofHJyAt57D1izBkhNhWrjRqTOnWvuqIoPfqljueLiIBs7FlqtFhAEpIwZA22DBgWyaW2jRtD4+kJ+6RJk9+9Dfvw4NB07Fsi2qZhISoJy82bd74KAlPffN288+eXoCPj56V5p1GpdS9u0RG5aUjcqSn9drVZ3nYSFAf8OBggAYunSugRujRpSIldbtSpgZQX50aOwCQzUJYUFQXrJ7t2DTWAgXm3cyMRtHuU5afvnn38iNDQUr169yrTs3XffzVdQRERERFRI6tUzdwQmJyQm6h4NFASITMIUG4r9+yE/fhwAIJYpg+T584tmtwgZvf8+sGkTkJAAq927of7gA/P0q1gM8UsdCzZ9uvRIt6ZRI6QWcNIsdfhwyC9dAgBYbdiAVx06FI/7BRUIxZ49EJ4+BQCo/f0hVqli5ohMQKEAqlXTvdJ/wfnsmX7XCn/+Cdy6pUvypiO8eAH5+fOQp2uVC4UC2sqVIbtxA0hIgGhvDyE1VUraig4OEOLjoVqwAIkdOrCrhDzIddI2MTERb775Jn799VcIggBRFAFAr2sEJm2JiIiIyBwSQkIyzbPt2BFCdDREV1ckHjtW+EFRgRP++Qeqjz+WppMXLACcnc0YUQFydoY4eDDw5ZdAaiqUGzciJZ/9elLW+KWOBdi/H9i3DwAg2tsjcelSyAo4uaNp0wbaGjUgu3ULsqtXIbtwAdpmzQp0H1REpabCauPG/yZHjDBjMGZQpgzQsqXuBUCr0eB5dDSsHj6E8s4dyP76C7LQUMhu3ZIS2xK1GrIbN6QnXoTYWCBtYDSZTHdftbGB7P59yC5d4jWXB7lO2i5YsADh4eE4ceIE2rRpg3379sHBwQHr1q3D9evX8e2335oiTiIiIiKinBlKuvz7jwNkMj7uXBxotVBNm6YbIRuAukePYveoszh8OPD110ByMpS7diF1+HCILi7mDqvI45c6FujhQ+Cjj6TJxNmzIZqiH2dBQGpgIFSTJgHQtbZNYgKJACgOHoQQGQng3+R+7dpmjsgCKJXQVq8Oda1awJtvSrOFp091X3yEhuqSubduQfbnn9IXXwbJ5bouF548gbaQwi9Oct379vfff4+pU6eiefPmAIBKlSqhffv22L17Nxo1aoS1a9cWeJBEREREZCLXrwNXruh+EhUBih07ID93DgAgursjeeZMM0dkAi4uSO7dW/d7cjKUmzaZN57iwtY28yvjlzrpX2RaGg0wZgwQHw8AEN9+Gyldu5psd+quXaWEsPzUKcj++stk+6IiQqOBcv16aTJl5EgzBmP5xLJloWnRAqnDhiF5+XK8+uEHvNq2TXe/tLPT/Uzr0zaNRgPIZNDyi8c8yXXSNjw8HDVr1oRcLocgCEhM15n7gAEDcODAgYKMj4iIiIhMacUKYM4c3U8iS5ecDNXSpf9NLl4MlCplxoBM51VAAEQrKwCAcscOCDExZo6IqICtWQNcuKD73cMD4oIFpt2fQoGUoUOlyfTJOiqZ5EePQhYeDgDQNG0KbaNG5g2oCNL6+UFbpQqg1UK0s9O1rE1L2ooihFevoPX2htbX17yBFlG5TtqWLl0aCQkJAABXV1fcuXNHWpaamiotIyIiIiIiyjeNBkhIAF69giwiAvh3IOTUAQOgadHCzMGZjujqitS01rZJSWxtS8XLH38Ay5frfpfJdAncQvgCRt2zJ0QnJwCA4qefIEREmHyfZKFEEVbr1kmTqWxlmzdyOZJnzwasrCDEx+u6Svj3JcTHA1ZWSJ41i4OQ5VGuk7b16tXD7X9H0WzXrh0WLVqE06dP48KFC5g/fz4aNGhQ4EGmd/LkSbzxxhsoX748BEHIsWVvcHAwBEHI9PqLj0IQEREREVk0+dGjsG3dGrL793UDnCQmQoiJgViqFFImTzZ3eCaXPGwYoFQCAJTbt+tG+SYq6hISgFGjdF/IAMC4cUCTJoWzbxsbpKYNnK7VQrl5c+HslyyO/LffpC4ytPXqQfNvF6CUexp/f7zauFHX4jZd0lZbtSpebdwIjb+/uUMssnKdtB06dCji/+1zZuHChUhMTESbNm3g5+eHBw8eYIWJH61LSEhAgwYNsGbNmlytd+vWLURGRkqvatWqmShCIqLiITExdy8iIqKCJD96FDaBgZDdvau/QKOBLDIS8lOnzBNYIRLd3JDap49u4tUrWAUFmTUeooIgzJ4N/PtIOho10iVtC1HqwIFSn8XKPXsgPH1aqPsnC5ChlW3KyJFZD6RFRtH4+yPx5Elovb0hli4Nrbc3Ek+cYMI2nxS5XaF32iM6ACpXrozbt2/j+PHjkMlkaN68OcqUKVOgAWbUpUsXdOnSJdfrubq6onTp0gUfEBFRMVW1au7K//OPaeIgIqISSKOBav58IDkZooMDhKSk/5bZ2uqWL1iAxA4div0jl6mBgVB++y2Qmgrltm1IGTIE4P81VEQpf/4Zwnff6Sbs7HTdIihynZbIH0dHpPbpo2tlm5wMq23bkDpmTOHGQGYlP38espAQAIC2enVoXnvNvAEVF3K57rp++VL3s5j/fS4MuW5pm5GdnR3efPNNvP766yZP2OZHw4YNUa5cObRv3x6//fabucMhIiqSEhN1T7SxZS0REZmS7NIlyMLCICoUEJ490z1qCQCCANHeHqKNDWT370N26ZJ5Ay0EYrlySO3ZUzeRkADlli3mDYgoj4SoKNjNnfvfjI8/Bry8zBJL6nvvSV2PWO3cCeHlS7PEQeahTN+X7YgRun6ViSxQnr7SSk1NxdatW3H8+HHExMSgbNmy6NChAwYOHAjlvzc+S1GuXDls2LABjRs3RnJyMrZt24b27dsjODgYrVu3NrhOcnIykpOTpem4uDgAgFarhVarLbDYtFotRFEs0G1SYfvvEQqtVjRjHEUD63zR8m/35XpathTw+DHg5gacPq1f53laM7PMOs/7FukT0vU9JuazrpqqzqdtN8/bTkv45WH99PsV/s/enYc3UW4PHP/OJGnStGVpS9lFEAVcQbi4c8UNwX3FXVFxwatccRdFxd2ruKOCKCou4HX3oly94oq78nNBZUdUBFpqaZs0TWbe3x9v07S0QNMmnSQ9n+fJk8xMmpwmk+3Mec8rQydbJJ7n0fXLLxAMYth2/SGrpqmXXS79wbN27VZva2vPYUv2L1XnPJH71qYxhcaOxfPvf0MkgueppwideeaWJ21K0j7fotdiC2JK1biSuW+lalzN3udtm+yrrsLYuBFME3X44ajjj6/3BbJVH6+iIsJHHIHn5ZcxysvJmjMH+9JLU2bf0n8m+3wy4uKbb3B9+qlev802VI8YscUfMsl6n2+pet+5kpCnku9cydXUxybupG1ZWRkHHngg33zzDTk5OXTp0oUFCxbw/PPPM3XqVP73v//RrhVmfWyqfv360a9fv9rlvfbai9WrV3P33XdvNml7++23c9NNNzVYv379eqrqDs1qIdu2KSsrQymFKUd20lI4XIBtm4TDNuvWlTgdTsqTfT79WVYBSplYlk1FRf19XgoUGkrFfV7et8Sm2ldVYVRXo6qqKFu3rkW3lax93rZtKioqME0TVzOG2vksC5dtY1kWG+KcyMmyLGzbJhwOp8zrOF016Xm0LHJfeomc++6r/yM0+uPNMPQPnXAY0zAo83oJbeU53dpz2JL9yxeJYCqFHYkkdN9qEFN2NurQQ8l5/XXYuJHIo4+y8dxzNx9Xkvb5Fj1WLYgpVeNK6r6VqnE1c5/Pe+YZcj77DKUU4aIiSi+7DLV+feLiasbj5T7+eLq+9BIohWfmTNafeCKmz+doTHXJPp+cuDo/8EBtwmzDKadQWVa25biS9D7fYpWVuCsriRQXQzCYsJuV71ytIzpX2NbEnbSdOHEiv/zyC7Nnz+aEE06oXf/vf/+bs88+m4kTJ/Lggw/Ge7Otas8992TWrFmb3X7NNdcwYcKE2uWNGzfSs2dPOnXqlNCEdPToQadOnTJ+h8xUHo+BaYLHY1JUVOR0OClP9vn0J/t8fFJxn5fnUGzK8PkgKwt8Prwt3CeStc9bloXH48Htdjfrdt0uF4ZpYrhccbfzsm2bSCRChw4dmvXjRcRs7Xk0f/oJ3w034PruO12p43KBZemetpWVtUlc0zAwQiGsvn3JOeAAcrbyvGztOWzJ/uVyu8EwcLndCd23GovJuOQSzLfeAsuiw4sv4r7ggs1W2yZrn2/JY9WSmFI1rmTuW6kaV3P2efPHH8mZPl1X2ALmgw/SqZGJwVv98crPxz74YNzvvotnwwaKPvoI89RTnY2pDtnnEx9X1tKl5CxYAKaJ3aUL3lNPxbuV0eLJep9vKbu8nHBODp7CQsy8vITdrnznah2+TQ4QbU7cSdtXX32VyZMn10vYAhx//PH8+uuvTJkyJeWTtt9++y1du3bd7Hav14vX622w3jTNhP/oNgwjKbcrWp9pZnb5fqLIPp85ZJ9vmlTe5+U5FICuYKw5GQnYT5OxzyulMAyj9rabEVTtebx/H73vVH0dp5PNPo+BAFkPPohn5kywLL3OMIiMGoX7gw8wwuHaFh4ohVFeDllZVF9/PWYTWrNt7Tlsyf5loIfMGpDQfavRmLbdlshRR+GuGc7tfe45wuPGbSaw5OzzLXottiCmVI0rmftWqsYV9z4fDJJ9+eUQiQBQNWYMvn33TZnHK3zeebjffRcA16OPYpxySr3Jk2Sfb3pM6RCXb9q02nXhsWMxG8n7NAiL5LzPt5hpyneuNNbU/y/uR2H9+vXsuuuujW7bbbfdKC4ujvcm41JRUcHChQtZWDPT34oVK1i4cCG//voroKtkzzjjjNrr33fffbz66qssWbKEH3/8kWuuuYaXXnqJf/zjH0mNUwghhBAiLcycCW+8oc+FaGWuDz7Af9hheGbMqE3Y2tttR/C556iaNYvg449jb7ddvaSt3bcvwenTsUaMcDj61ld94YW1E+Z4nnxSehOJlJd1552YK1YAYO24I8GLL3Y4ovrsgQOJDB2qF1asgLffdjYgkTTmypV45s0DQBUUENmkEFGIVBR30rZ79+58/PHHjW775JNP6NatW4uD2pKvvvqKQYMGMWjQIAAmTJjAoEGDmDRpEgBr1qypTeACVFdXc/nll7Prrruy33778fHHH/Of//yHY489NqlxCiGEEEIIIRpnrF+P95//xDd2LMbvv+uVWVlUX3IJwddewx4yBABrxAgCH36I3acPqkMH7D59CHzwQZtM2AKoXr2IHHEEAEZZGZ5nn3U4IiE2z/Xee3iee04v+HwE774bUmzicoDqsWNjCw8/HJtISWSU7Mcfr31uw2edBU0cni6Ek+JujzB69Ghuu+028vLyOPPMMykoKKCkpIRZs2Zx22231esFmwz777+/nvFvM2ZuUiVy5ZVXcuWVVyY1JiGEEEIIIUQT2Dae2bPx3XOPbnNQw9pzT0I33YTq3bvh37hckJOjq0pzcuoNXW6Lqi+8EPcbb+jH8oknCJ92mn5chEghxvr1eK+5pnY5dO212L1717ZJSCWRffbB6t8fc/FiWLgQPvkE9t3X6bBEIv32G1lvvgmAyssjfMopDgckRNPEXWl74403Mnz4cC6//HKKiorwer0UFRVx6aWXMnz4cG688cYkhCmEEEIIIYRIa4sXk3fmmWTfeGNtwlZ16EDojjuoeuqpxhO2ogHVpw+RUaMAMEpLY5WMQqQK28Z71VUYpaUAWAceSGT0aIeD2gLDoOqcc2LLDz3kXCwiKYxHH609YBA+4wxI4MRdQiRT3JW2Xq+Xt99+m3nz5jF//nxKSkooKCjgwAMP5OCDD05GjEIIIYQQIlmefx4qK3Wl3sknOx2NyEShENx/P+bDD+MOhWonKYkcfTShq6+GZsyq3tZVX3gh7v/8B5TCM2OGrrbNznY6LCEA8MyahaumpaLq1ImqW26JTU6UoqoPPli3Rvj1V/jwQ/j+e9hlF6fDEomwbh3G88+jAJWdrZO2QqSJuJO2USNGjGBEG+0lJYQQQojMEwjEd32/PzlxtLp586CkBAoKJGkrEu/jj+Gqq/QEPzXsnj2pvuUWrL32cjCw9Ka2357IyJG4587F2LABzwsvEB4zxumwhMD85Rey7rqrdjl0xx368yXVud2oCy7AuPZavfzww/Doo87GJBJj2jSorgag+qSToGNHhwMSoumanbQVQoh0Y8c5qYCZ4hUBQojE6ts3vuv/8Udy4hAiI2zYAJMnw5w5sXUeD1Vnnkl43Dhc0oO1xcLjxuGeOxcAz+OPEz75ZJlYJ1NYlh4BUVWlzy0rPXo5h0J4L7usNkEWPvNMrP32czioplMnnABTpkBxMbz5JqxcCT17Oh2WaIm//oKnntKXs7KoPuus+HuECuGgJiVte/fujdHE5IVhGCxbtqxFQQkhRDL8XFIR1/V3LJReR0K0dYGAnmjYMDKoslaIZFIKXnwRbroJavpZAvC3v2HffjvBoiLcbqkbSQR7hx2IjBiBe948jPXr8cyZI8N+M4Br3jy8kydjLl8Oto2xcSP+YcMITZqEleIjXbP+9S89mRdg9+tH9eWXOxxRnHw+GDsWbr8dbBseeQRuu83pqERLzJihD3wAoWOOQRUVORyQEPFp0jemv//9701O2gohRDqxlaIqYuFzu6SyVog2bunShuv23hvWroXOnWHBgtaPSYi0smKFboVQ08sSgHbtYOJEOPVUndCtm8gVLRa+6CLc8+YB4Jk2jfDo0eD1OhyVaC7XvHlkjx2r+0AbRu3JXLaM7LFjCU6fnrKJW9eHH+J5+mm9kJVF6J570nNfPPNMePBBqKiAF16A8eMhK8vpqERzVFTA44/ryy4XVWefLVW2Iu00KWk7c+bMJIchhBDJ178gt8G6YMRi5V8Btu3gJ9udBsPOhBBJ01glrWnq38ymKZW2QmxWOKz7P953X+2waACOPFK3SIhWNlmWI+FlMrt/f6yDDsL17rsY69bh/ve/iZx6qtNhieawLLyTJ0MohGrXDmP9er1eKVR2NkYggPfmmwkcdFDqtUooKcF79dW1i6GrrsLeYQcHA2qBdu3gjDNg6lQIhzFmzIALL3Q6KtEcTz8NZWUAqGOPxe7eXZK2Iu3IPiuEaDNMw2j0ZGxmvRBCCCG24osv4OCD4a67YgnbHj1g1iw9iY8MRU266osuqr2c9dhj9RPnIm2YX32FuWIFyu/HCAb18HyldIuE0lIIhTAXLcJ72WW45s9Pnap1pfBdey1GcTEA1n77ETntNIeDaqGxY8HjAcCYNQujvNzhgETcqqrgscf0ZcNA1XmfFCKdNKuhlFKKL7/8klWrVhEMBhtsP0N6KQkhhBBCCJG5ysrg1lt1cjbK5YLzzoPLLpPS9FZk77QT1vDhuObPx/jzT9wvveR0SKIZzPXrdaLW5aqtDqxHKYhEcL/8cu0EdHbv3tiDBmENGoS1++6o7bbTQ0Nakfv553USGVD5+YTuuEMPUUlnnTvDiSfCs89CeTneOXOInH++01GJeDz/PESr1Q8/HLbbLnUOdAgRh7iTtosXL+bII49kyZIlqEZmYjcMQ5K2QgghhBBCZCKl4I034PrrYz+IAXbbDe6+G3baybnY2rDqiy4iuyZxlvXII7qXY1WVnoDHslJvOL1owO7UCUwTo7JSJ2+jTFP3hq2u1uvrJGXNFSswV6zA/fLLAKi8POzddiMycCDssgsMGwYdOiQtZmPZMrx33FG7HLrtNlSnTkm7v1Z14YXw3HO6kviZZ6g46yw5GJUuoi17oi6+2LlYhGihuJO2F110EVVVVcyePZtdd90Vbzo2FxdCCCGEEELE59df4dpr4b33YutycuDqq+GssyQx6CB7112xhg3D9c47mD/8oBO1SmFs3Ih/2DBCkyal7ARWQrOHDMHedlvMH3+MrTRNME3d47a8HLtXL0KTJuH6v//D9e23mIsW6QRVDaO8HNfHH+P6+GOylMJ0uaB/fxgyRJ/+9jfo1SsxASuFb8IEfXAACJ96KtYBByTmtlNBnz5w2GHw5psYxcV4Xn0V+5RTnI5KNMXLL8Mff+jLBx4IO+8sPdVF2oo7afvFF18wffp0jj/++GTEI4QQQgghWtPOO8PGjXryFSEaE4nAtGm6krYmQQPAoYfqFglduzoXm6hlDR6M+8UXdTU06CHqhoG5bBnZY8cSnD5dErepzOXC2mcfnbSNPodK6eR7eTlkZRGaPBlrxAisww7T20MhzB9+wPXNN5gLF+L69tva3rK1f//TT/r0zDN6XX4+xuDB+AYMQA0erKvks7ObFqNlQWUlRiiE8dtvGOvWgWFg9+lD9ZVXJu6xSBUXXQRvvgmAd8YMgqNHy8GpVGdZ8MADseXx452LRYgEiDtpm5ubSzv5Ui+EEEIIkRkuv9zpCEQqW7hQ7yOLFsXWdemik7UjRzoWltiEZeGZNUtXZkYnsAI9AU9eHkZ5Od6bbyZw0EGSdEpVVVW4FixAdeigk7S2Xftc2n37Err++oZJd68Xe/Bg7MGD9bJSGKtXY3zzDcbXX5P94486YVu33cKGDRjvvEP2vHkYhgFuN3b//rov7uDB2AMHorp2bdCX1jVvHt7JkzFXrIjdntuN6tCB0JQpTU/8ppPddkPtsw989BHm6tW45s3DGjXK6ajElsydCytW6Mt7760rzIVIY3EnbceMGcNzzz3HoYcemox4hBBCCCGEEE6rqIA77oAnn6xfuXnWWbodQl6eo+GJ+syvvsJcsQKVm6sTfjUVmiilE7fZ2ZjLl2N+9RX2Hns4Ha5ohOeFFzDWrwevl/ARR+BasACjuBhVWEjggw+almw3DNQ22xDp3p3IyJF4O3bEVVUF334LX38NX32lT3UnOotEMH/4AfOHH/DUVOOqzp2xdt8de+BArEGDMP74g+wLLoBQqH4yNxLBqKzEWL0adtwxwY9IalAXXQQffQRA1rRpBEeOTP+J1jKVUphSZSsyTNxJ25133pnnn3+eI488kiOOOIKCgoIG1zn22GMTEpwQQgghhBCilb39tu5d++efsXU77gj/+hcMGuRcXGKzzPXrdfWj368Ta9E2Fpallz0esG3M9euxt3xTwglVVXimT69dDF9yCa7/+z998CQnp2XV0Tk5sO+++gRg29hLllD54Ydkffcd7oULMZcurfcnxtq1uN96C956S1fvbtig96Xs7PpVu14vGEZmV3Hvuy/Wjjvi/uknzEWLcC1YgLXPPk5HJRrh+eAD+PlnvTBoUGyfFyKNxZ20PaWm+faKFSt4s6a/S12GYWBJk2chhBBCCCHSy5o1MHGiTtpG+Xy6PcLYsTrxJ1KS3amTbo1gWXrSqlCotkLaKCvTyTbT1NcTKae2yhaIjByJvcMOybsz04S+fakuKMA+4QRcLheUleH6v//D/PZbXN98oxPGgYC+fjis+1oDBIOxyntAtW8PlpXZVdyGQdU555Bb00rIM22aJG1TkVJkT5sWWx4/XiqiRUaIO2k7f/78ZMQhhBBCCCGcMHEilJZCx466T6loeywLnnpKt0OoqIitHz4cbr8dttnGudhEk9hDhmD37o25bBkqL09XPFpWrEVCZSWqsBB7t92cDlVsKhjEUyfZFL7ootaPoX17rGHDsIYNIww6EbtkCebXX+N+5RXc775bL1kL6H3MNPXlDK/irj7oIOyePXVf208/xfzuO+xdd3U6LFGH67PPcH33nd4nBwyAgw5yOiQhEiLupO3f//73ZMQhhBBCCCGc8PvvUFISq6oSbcuiRXDFFbrnZVRhIdx8Mxx5pFQqpQuXi9CkSWSPHRvraQv6+avpa4tl4TvnHKoefBDy852NV9TyvPACRnEx0ApVtk3lcmH3769PffviXrAAVVNpb5SVxfYp0AcHMr2K2+UidO65ZN9wAwCe6dMJPfigw0GJuryPPRZbuOSS2AEFIdJc3Hvyww8/zOLFi5MRixBCCCGEEKI1BAJwyy0wYkT9hO2pp+pJd446ShK2acYaMYLg9OnY221XfxKybbdFdeoEXi+uL7/Ef+KJGMuWOR2uAF1lW7eXrRNVtlsRreI2QiHIytLJsOh7g1IYwSB2nz7YQ4Y4G2iShY86Sr+OAPd//4uxfLnDEYko89tvcX/+uV7Ydls4/HBH4xEikeJO2l5yySUMGDCAnj17MmbMGJ599ln+rDtJgRBCCCGEECJ1vfeebn0wdaqukgPYfnt49VU92Vj79o6GJ5rPGjGCwIcfYvfpg+rQAbtPHyq//ZbgSy+hCgsBMH79lewTT8T16acORytSssp2UzVV3GRlxaq4a05GeTlkZRG6/vrMnISsLq+X8Fln6ctKkTVjhqPhiJisRx6pvaz+8Y/M3xdFmxJ30nb9+vU8//zzjBo1ig8//JDTTz+d7t27s8suu3DppZfyn//8JxlxijYkEIjvJIQQQgghmmDdOrjgAjjtNFi9Wq/LytLtEd55B4YOdTY+kRguF+Tk6EnkcnL0UPfddiP4739j9+sHgFFeju/ss3G/8ILDwbZhaVBlG9VoFbdS2H37Epw+HWvECKdDbBXhk07SPaMB96uvYqxd63BEzWBZUFkJVVX6PM0nkTd/+gnX++8DYHfpgjr2WEfjESLR4u5pm5+fz4knnsiJJ54IwMqVK3nnnXeYM2cO999/Pw888ABWmr/whbP69o3v+n/8kZw4hGgt8R588PuTE4cQQogMZdvw3HO6HcLGjbH1++wDd94Jffo4F5toNapbN4LPP4/vsstwzZ8PloV30iTM5cupvuoqqU5rZWlRZVuHNWIEgYMOwj9kCBQXQ2EhgQ8+aFv7TV4ekZNP1hPHhcN4Zs7Ur5004Zo3D+/kyZjLl4NtY2zciH/YMEKTJqVt4t1Tp5dt1Zgx+Gt6LwuRKeJO2kaFw2E+/vhj3n33Xd555x2++eYbsrOz2XfffRMZnxCATmpF+91LwkpkGjlQIYQQImkWL4Yrr4Qvvoit69gRbrgBTjhB+ta2Nbm5VE2dStZdd+F58kkAPDNnYq5aRdU990BursMBthFpVGVbT00Vtyovx6ip4m5rwmeeiWfmTKiuxvP881RfcEFatJRxzZtH9tixEArp9/2ak7lsGdljx6ZlxbSxfDnut94CQOXnEzruOCRVIDJN3O0R7rnnHg499FA6duzIIYccwv/+9z8OPvhg3nnnHUpLS5k3b14y4hRtyNKlDU/bbquTtdtu23CbEJkoENAjlqQFiBBCiGYJheCuu+Dgg+snbE84QU80duKJkrBtq1wuqq+5htDkyeDWNTyu+fPJPvlkDDky3CrSrcpWxKhOnQgfd5xeCATwPPecswE1hWXhnTwZQiHd3kGp2k0qLw+qq/HefHPatUrImjat9n8JnXWWbgkjRIaJu9L2iiuuwO/3c8kll3DFFVfQsWPHZMQl2rDGKmmjk5SaplTaiszT2MGHvfeGtWuhc2dYsKD1YxJCCJHGPv4YrroKVqyIrdt2W53ElVFxokbkpJNQvXrh/cc/MMrLMX/5hezjjyfw0ENEdtrJ6fAyV90qW8NInypbUSt89tl4Zs8G28bz1FOEx4xJ6YSh+dVXmCtWgGlibNigW+YAWBZGIIDKzsZcvhzzq6+w99jD2WCbyPj9d9yvvw7oxHP1SSc5HJEQyRF3pe1FF13ENttswx133EHfvn054YQTmD59OivqfikUQgjRZH5/w9OmByrqnoQQQohGbdgA//ynrqKNfjd3u2H8eHjvPUnYigasvfYiOGcOapttADCKi/GfcQZZb7/tcGSZy/P881Jlm+ZUr15EDj0UAGPDBtwvveRwRFtQVYXnhRdiQ/iiCduoykqM8nKIRDDXr3cmxmbwPP44RCKAbllBzQRxQmSauJO2Dz74IIsWLeK3337jnnvuwefzccMNN9C3b1/69u3LhRdemIw4hRBCCCFEMpx0Epxzjj4X6UkpePFF2G8/mDMntn7IEHjnHV11m8JVYMJZarvtCLz4Itbf/gaAUV1NzuWXY9x3X71h1CIBNq2yHTfO2XhEs4XPO6/2ctaMGbUJxJQRCuF+5hn8Bx2E+5VX6m+L9rSNCochFML8/PO0aJFgrFuH58UX9UJ2NuHTT3c2ICGSKO6kbVS3bt0466yzmDZtGk888QQHH3wwy5cvZ9q0aYmMTwghhBBCJNOhh8LRR+tzkX5WrIDRo3U1bWmpXteuHdx5J7z6KvTr52h4Ik107EjVzJlEjj22dpVxzz1w8cW6P7JICM/zz2OUlABSZZvu7B13xNpnHwCM337DnSrV6dXVuJ99Fv9BB+G9+WaMdevA49GTxrlcqI4d9WXD0OemqQ/OuFx4XngB32mnYaxa5fR/sUWeJ5+E6moAwqecoifXFCJDxd3TVinFF198wbvvvsu7777LZ599RnV1NXl5eRxxxBEcdNBByYhTCLEZ8U5UJcPrhRBCiAwQDsPDD8N999X+eAXgyCPhppt0U3Qh4uHxELr9diK9e+O95x697uWX4ddf4YknoLDQ2fjSnVTZZpzw+efj+uQTADzTphE57DDnJngMh3G/9BJZjzyCsWZNvU2RQw/FHjQI7403YgSDOkmrlI7V4wG3G5WdDYaB6+uv8R9xBKErryRyyik6qZtKSktjk79lZel+wkJksLiTth07dqS8vByPx8Nee+3Fddddx4EHHsjQoUMxU+0FLUQb0LdvfNeXSYGFEEKINPfll3DFFbB4cWxdjx5w++1w4IHOxSXSn2FQfe65hHv0oN3EiRAMwldfwWGHwVNPwfbbOx1h2pIq28xj7bEH9q67Yn73HebPP+P66COsYcNaN4hwGPfLL5M1dSrG77/Xj+/AA6m+5BLsAQMAsLt3xzt5MuaPP9Ymbu3ttyd0/fWojh3xXX01xm+/QVUV3smTcb/zDqFbb0X16NG6/9MWeJ55Rr8vAeETTkAVFTkckRDJFXfS9rzzzuOggw5iv/32Izs7OxkxCSFaKBCIHTyVylohhBBbFJ1J2jQhP9/paMSWlJXBrbfCrFmxdS4XnHceXHaZfOiLhAkfdBB2//64xoyBtWth9WpdxT11Kgwc6HR46UeqbDOTYVA9diy+iy8GdLVtqyVtIxGyXn0V/7RpmKtX19tkDR9O9cUXY++8c/31I0YQOOgg/H/7G0ZxMaqwkMAHH+jPESDwxhtk/etftZWsrk8/xX/44YSuuYbIiSc6V0UcVV6O56mn9GW3m/C55zobjxCtIO6k7V133ZWMOIQQzbR0acN1e++tv1937gwLFrR+TEIIIdLIhAlQUgIFBTBzptPRiMYoBW+8AddfD3Vn995tN7j7bthpJ+diE5lrl13grbfgzDPh+++hogLzrLPwXnkl1hlnOB1dWsl64QWpss1Q1sEHY/fujbliBa4vvsD89lvsQYOSeIcWvPoq5j33kLN8OUadRKq13366sna33Tb/9y4X5ORARYU+r0nYApCTQ/WNN2Idcgjea67RbRYCAbzXX4/7v/8ldNttjrZJ8bzwAkZ5OQCRI49Ede/uWCxCtJZm9TMIh8PMmDGDU045hREjRnDqqafy5JNPEg6HEx2fEGIr/P6GJ9PUB0JNs+E2IYQQQqSR1avh9NPhggtiCducHLj5ZnjzTUnYiuTq0gVeeQVGjtTLto3/ttvw3XwzRCLOxpYugkG8jz+uLxsG1Rdd5Gw8IrFMk/DYsbWLWdGK6kSrSdYyfLieIHDlytimvfcmOHs2VTNmbDlh29S72ntvAm+8QeS442rXuT76iOxRo/C89po+kNjaqqr0BGSgX0fnndf6MQjhgLiTtmVlZey1116MHTuWN954g+XLl/P6669zzjnnsPfee7Nx48ZkxCmEEEIIIUTbEYnAI4/A/vvDe+/F1o8YAR98AOecU79CSohk8fth+nT4xz9qV2U99xy+884D+e23Vb45czA2bAB0la2SvsAZJ3LkkbW9VV3vvovR2FDI5rJtPdLiwANh3Lh6wywje+xB5axZVM2cmfjq3nbtCN1+O1WPPVb7vxnl5WRffTW5l1wC69Yl9v62wv3vf2MUFwN6YjXVp0+r3r8QTok7aTtx4kR++eUXZs+eTXl5OUuWLKG8vJw5c+bwyy+/MHHixGTEKYRIM4FAfCchhBBC1Fi4UFc23nxz7YQrdOkCM2bAk09Ct26OhifaINOEa69F3XOPnm0ecH38MdknnYSxST9NUUcggO+JJ/RlqbLNXFlZhMeMiS1GK6tbwrZx//e/tDv+eMxx4+pPPLnnntizZ1M+YwbW4MEtv68tsIYPJ/Dmm0SOPLJ2nWf+fMyDDoLXX0/qfdcKh+tVMIcvuKB17leIFBB30vbVV19l8uTJnHDCCfXWH3/88dx444288sorCQtOCJG++vZteNphB4O99+7EDjsYDbYJIYQQbV5FBVx3HRx2GPz4o15nGDBmjK6ujQ5RF8Ih6sQTKZ8+HdW+PQDm0qVkH3885tdfOxxZajKeeaZeL1upss1c4dGjUXl5ALjfeEP3g20OpXC9+y7ZxxyDf/x4XHWTtUOGwJw58NJLehKT1tKhA6G776bqoYdQ0QlLS0t1257zz9cTmiaR+7XXah9Pa//9sQcMSOr9CZFK4k7arl+/nl133bXRbbvtthvFNSXrQgixqUAAKisNqawVQgghNvX22zBsGDzxRKxf4IABeljsrbdCTTJACKdFhgyhcs4c7N69ATBKS8k+4wzcr73mcGQpJhDAePRRfVmqbDNfbi6R007Tl8PhWP/VplIK1/z5ZB97LL5x4zB/+im2bdAgeP55eO012HdffTDPAdYhh1DxxhtUjxgRW/nGG7qNz9tvJ+lOLbIee6x2sfrCC5NzP0KkqLiTtt27d+fjjz9udNsnn3xCNxmuJYRAt1va9LTttuD3K7bdtuE2IYQQok1aswbOPluf/vxTr/P5dMXt22/D7rs7G58QjbC32YbgnDlYe+2lV4TDeK+4gqz77tM9OAU8/TTUFDSFR4yQKts2IHzGGeD1AuCZPVtPHrY1SuH68EOyTzgB3/nnY0ZHWQDWTjtRMXUq9muvwd//7liyti6Vn0/lPfdgT50KHTrolcXF+jPs4ouhrCyh9+d++22MVasAsPbcM/G9e4VIcXEnbUePHs1tt93GlClTKKkZ6lFSUsL999/PbbfdxkknnZTwIIUQ6cfvb3gyTf1dwzQbbhNCCCHaFMvSVbV//3v9CqXhw+H99/WEMzW9Q4VISe3bU/X440RGj65d5Zk6Fe+ECVBV5WBgKSAQgKlT9WXDIDRunLPxiFahCgoIR9tIBoO1E9A1fmWFa8ECskePxnfuuZjffVe7yR4wgKpHH6XyxRcJDxuWEsnaBo44Qn9WHXJIbN1LL2EeeCCejz5KzH3YNp5otToQlipb0QbFnbS98cYbGT58OJdffjlFRUV4vV6Kioq49NJLGT58ODfeeGMSwhRCCCGEECJDLFoERx6pq2krKvS6wkJ45BGYNQu22cbZ+IRoKo+H0OTJVF97bW1iyT13LtmnnYaxfr3DwTmoTpVt9YgR2FJl22aEx4wBlwuUwigu1pNJVlbWq7p1ffYZvlNOwXfWWZgLF9aut/v1o+rhhwm++irWAQekZrK2rqIiPTnm/fdDu3Z63dq15F54Ib7rroPy8hbdvGv+fMxffgHA3m03rD33bGnEQqQdd7x/4PV6efvtt5k3bx7vvfceGzZsoKCggAMPPJCDDz44GTEKIYQQQgiR/gIBmDIFHnus/rDZU0/VCdyayZ2ESCuGQfiss7C32QbfhAkQCGB+9x3Zxx9P1WOPYffv73SErWuTKtuqCy4gxVNvIoFUz55YO++M+3//g0gEo7oao7wc/7BhhE86CdcXX+D6/PN6f2Nvvz3V//gH1ogRekhiOjEMOOEE3Wv3sst09S2Q9dJLeBYsIHTHHbE2KvFQiqxHHqldrL7wwtRPYguRBHEnbaNGjBjBiLoNqIUQQgghRPq59VadQHS5nI4ks82fD1dfDatXx9Ztvz3cdRfssYdzcQmRINYBBxCcPRvfeedhrFmDsWYN2aNHU3XvvVh//7uuNqyqilUdZup7Tp0qW3X44Vh9+zb/R7dIO65583B/+ilEIvXWm4sW4b3uOlSHDrV9b+0+fai+5BKsQw9Nv2Ttprp2hWefRc2aBTfcoNtDrFmD78wzCZ9yCtVXXAE5OU2+Odenn9a2jLD79cMaPjxZkQuR0uL+/Fi9ejUfffQRf/zxBwDdunVj2LBh9OjRI+HBCSGEEEKIJOve3ekIMtu6dfoH7GuvxdZlZcH48XDRRfqyEBnC7teP4L//je/CC3XCJRjEN2YM+P0Ya9aAbWNs3Ih/2DBCkybpysJMskmVrfrnPx0NR7Qyy8I7eTKEwzoxGwrp9batq0SVwigvx9phB8IXX0zksMMy6+CFYaBOOYWyXXcl94YbcNdUFHueew73Rx9Rdfvt2EOHNumm6vaylSpb0ZY1OWlbXl7Oeeedx4svvohSCqVU7TbTNDnllFN45JFHyInj6IkQQgghhBAZybbhuefglltg48bY+n32gTvvhD59nItNiCRSnToRnDUL79VX437lFYy//oLSUp10qTmZy5aRPXYswenTMytx+9RTtVW2HHkk7LCD/t9Fm2B+9RXmihWomlmWjWjSFvS+73KB203oxhux99nHoSiTz+7encATT+CdPRvvXXdBVRXG6tVkn3464TPOoPqyy8Dn2/wNBAK4PvsMANWrV2a9RwgRpyYlbZVSHH744Xz00UeMGjWKI488kl69eqGUYtWqVbz22mvMmjWL33//nf/973/JjlkIIYQQQojUtXgxXHklfPFFbF2HDrri9sQTpWJIZD6fj9C//oV77lxQqrbKENDVeHl5GOXleG++mcBBB2VGteEmVbZceqmz8YhWZ65frw/YuVy63UF0vzcMaNcO5fFgVFZilpZiOx1sspkmkdNOw9pvP7xXXYXrm29AKTxPPYXrgw8I3Xkn9qBBjf6pUVxc20Ki+vzzM+P9QYhmalLS9uWXX+ajjz7iySef5Mwzz2yw/fzzz+fJJ5/knHPO4ZVXXuGYY45JeKBCCCGEECIJPvhAD+H0euHvf3c6mvQWCulZtB9+WA+PjTrhBJg0CQoKnItNiFZmfvMNRkUF5ObqhGY0aWtZoBQqOxtz+XLMr77CzoS+zk89BSUl+nK0yrbuhIMi49mdOulkrWXpc5dLJ3FNE+Xz6c8F09TXayNUr15UPfssnpkzybr3Xqiuxly5kuyTTyZ8zjlUjx+v2wRZlu53XVmJEQigCgtR3boROeoop/8FIRzVpG7Xs2fP5vDDD280YRs1ZswYDj/8cF544YWEBSeEEEIIIZLsySfhwQf1uWi+jz+GAw6A++6LJWy33RbmzNGJXEnYijYmWnWo/H5Ux46xDUrplgmGAbatr5fupMpWAPaQIdi9e2MEg7GDFFFKYQSD2H36YA8Z4kyATnG5CJ9zDoFXX8XeZRe9zrbxTJ9O9jHH4Jk2Df+wYZjLl2OUl4NlYZSUENlrL/B4nI1dCIc1KWn77bffcvTRR2/1ekcffTTffPNNS2MSQgghhBAiPWzYAP/8p257sGKFXud264nG3nsP9t3X0fCEcEq9qkOPR78uoiKR2sRtJlQdGk8/3bDKVrQ9LhehSZMgK0snH5WqPRnl5ZCVRej669vscH/Vty/B2bOpvvTS2mSs+cMPeK+4AvPnn+tf2bLIeu45XPPmORCpEKmjSUnbtWvX0rt3761er0+fPqxdu7bFQYnWEQjEdxJCCCGEEDWUghdfhP3209W0UUOGwDvvwFVXbXmiFSEyXKNVh2bNz0+lIBLRbRK22ca5IBMhEMCIznQvVbZtnjViBMHp07G3265e0tbu2zfzJt5rDreb8IUXEnz5Zez+/WPJ7UhEt5KIys2F6mq8N98sbUZEm9aknraVlZXk5ORs9XrZ2dlUVla2OCjROvr2je/6f/yRnDiEEEIIIdLKihU6Kfvxx7F17drBxIlw6qmxxJQQbVlN1WH22LH1qw6jfT4NA+X1kn3GGQRnzUJ17ux0xM3imz1bqmxFPdaIEQQOOgj/3/6GUVyMKiwk8MEHbbbCtjF2v36ErroK/6ef6qRs3ckKAeX3QySSWX2vhWiGJn2jVEphyCy3bUIgoPt/S2WtEEIIIcQmwmHdn3b48PoJ2yOP1BO6nX66JGyFqGOzVYf9+ul1Xi/GqlVkn3oqxpo1Tocbv0AAX7QfuFTZirpcLsjJ0SMucnIkYdsIs7QUXC5Ufn799immqV9PNQd4MqLvtRDN1KRKW4BTTjmF7OzsLV4nGAy2OCDRepYubbhu771h7Vro3BkWLGj9mIQQQgghUtKXX8LVV8PixbF1PXrA7bfDgQc6F5cQKa7RqsNPP8VYu5bs00/HWL0a49dfyT71VILPPIPq3t3pkJss6/nnMTZs0EkmqbIVIi61fa8B1bEjxvr1+sBO9OCnZYFpZkTfayGaq0lJ22HDhjW50rZHjx4tCki0Hr+/4broQS3TbHy7EEIIIUSbsnEj/n/9C/Oll2LrXC4YOxYuv1y+MAnRFNGqw4qK2qpD1a0bwWefJfu00zB+/RXjt99iiduePZ2OeOsCAbwzZujLhgETJjgbjxBpJtr32ly2DJWXp5MQ0b62SmEEg9h9+2IPGeJsoEI4qElJ2/fffz/JYQghhBBCCJFClML11lv4b74ZiotjlT+77Qb/+hfsvLOz8QmRAVSXLgSfew7faadhrlyJ8ccfZJ92GsGnn0b16uV0eFvkefZZjNJSFKCOPBJj++2dDkmI9LK5vtdK6eWsLELXXy+tJUSbJk23hBBCCCGEqMP47Td8552H75//xIhOMJSTAzffDG++KQnbtioQaHiybZ1ksO2G20STqKIiqmbNwu7TBwBjzRrdNmHlSmcD25JAAM/jj+vLhoEaP97ZeIRIU5vte923L8Hp07FGjHA6RCEc1eSetkIIIYQQIgN17Fj/vC2LRPDMnEnWAw9AVVXt6vDw4XjuugtXOgzZFkmTM3Bgg3VGcbFO2JaWNtheWbf/sdiiaOLWd8YZmEuXYvz5Z6zitiaZm0qiVbYA1SNHkiVVtkI0W6N9rz/4QCpshSANK20//PBDjjjiCLp164ZhGLz66qtb/ZsPPviAwYMH4/P56NOnD48++mjyAxVCCCGESAf33gszZ+rzNsz87juyjzuOrLvuqk3YqqIiAg88QMWDD0K3bs2+bWVZcZ1EGvH7UX6/9DZOAFVYSNUzz2D36weAsW6drrhtbPZkJ21SZRs8/3xn4xEiE0T7Xvt8tX2vhRBpWGlbWVnJbrvtxpgxYzjuuOO2ev0VK1YwatQoxo4dy6xZs/jkk08YN24cnTp1atLfCyGEEEKIDFZRQda99+J59tnYBCiGQfjUU6m+9FIsvx8ikRbdReijj+K6vm///Vt0fyI5KhcubLDOtm1KS0vp2LEjppl29TApRxUUEHzqKbLPOgvz558x1q8n+/TTCT79NKRIxW3dKtvwyJF6WLcQQgiRBGmXtB05ciQjR45s8vUfffRRttlmG+677z4ABgwYwFdffcXdd98tSVshhBBCiDbM9e67eCdPxvjzz9p1dr9+hG6+GTs61D1Jla8qEkFVVGDk5mK40+4redvUWDWtbaOqqvQ2SdomRn4+waef1onbRYswSkrIPu00Kp98EpxOkG5SZRsaN87ZeIQQQmS0jP+G+Omnn3LIIYfUWzdixAhmzJhBOBzG4/E4FJkQQgjRNsU7P4+MOhYtYllQWalbHlRWgmVhrF+Pd/JkXO++G7uez0f1xRcTPussSPD3Q+9++zVYZ5eXU/3NN2TtvjtmXl5C70+ItNehg664HTMG84cfMEpLyTnrLKzHH4c993QsrLpVtpFRo3SVbQsr8YUQQojNyfik7Z9//knnzp3rrevcuTORSITi4mK6du3a4G9CoRChUKh2eePGjYAe/mRHh80lgG3bKKUSepstZ9Resm3lYBybkrjik5pxKWXUnJMy+72qeR0q28a2ja3/QatJzecwdeNKTfI+37i+feN7rf32m5P7mvOPV9JNnQrl5ZCXBy2sGkvWPh+93Xhv2/3f/+K7+WbM5cvBtjE2biRn551RlkXdvTCy775U3XADKjrRWJ37qHu/htHMz4lG/k4Zhp51vuZUb1tKvWckTnOfR0B/eag5j/dvt/YctiSuluzzW4qrRY+VvvHa80Q+Xq36HOblUfnEE/jHjsX1f/+H8ddf5J19Nvbzz2NsMulbq8TVSJVtMvetVN3nVZ3zVIorI/b5NIgrHZ/DlsaVzH2+Jep9/iQhT5Vqnz+ZpqmPTdxJ23A4zJ133slzzz3HqlWrqKozsy6AYRhEUuxo46ZPtqrZiTa3E9x+++3cdNNNDdavX7++wf/bErZtU1ZWhlIqZXpghcMF2LZJOGyzbl2J0+HUkrjik6pxRSL52LZBJGKxbt0Gp8MBoNpWVFZDcbiSLDN1PhhS9TlM1bhSlbzPN862OzVYFwgYKKVzW35//eTounXrWyu0BlLh8Uq29h99hFFaiurYkbLjj2/RbSVrn7dtm4qKCkzTxNXEyUmy58+n04QJGNXVsaSpbWP8/juGYWC3a4fVpQulEyYQOOggfZ0NDT+bLMvCtm3C4XBiX8eVlbgrK4kUF0MwmLjbTWHNeR6jfJaFy7axLIsNjTxPW7K157AlcUX/tjn7/JbiaklMkLzHy4nnsPRf/6Lon/8k64cfoLQUTjyRDY89RmSnnVo1rrxnnkGVlKCAwCGHUNKxI1ZJSdL2rVTd532RCKZS2JFIasWVQft8KseVjs9hi+NK4j7fIkn6HpGqnz+Zpry8vEnXiztpe80113DvvfcycuRIjj76aLxeb9zBtaYuXbrwZ50+ZQDr1q3D7XZTUFDQ6N9cc801TJgwoXZ548aN9OzZk06dOtGuXbuExRY9etCpU6eU2SE9HgPTBI/HpKioyOlwaklc8UnVuNxuA9O0cbtTJ66qiEV5WZDC9tn43KkzS2mqPoepGleqkvf5xjU2Efi++xqsXQudO8PHH9ff5vc7t6+lwuOVbIbPB1lZ4PPhbeH/mKx93rIsPB4Pbre7abdrWeTedx9mdTUqLw+Ki2PbDAOUwvB4CL71Fr78fHxbuCnbtolEInTo0KFZP142e7vl5YRzcvAUFraZ9ghxP491uF0uDNPEcLnIz8+P62+39hy2JK7oPt+cici2FFdLYoLkPV6OPIf5+YSffhr3eefh+vprXIEABRddhJo1C3bfvXXiqqwk94UXMEwTDANjwgTy8/OTum+l6j7vcrvBMHC53SkVV0bt8ykcVzo+hy2NK5n7fEsk63tEqn7+ZBqfb0vfPmPiTtrOmTOHSZMmccMNN8QdlBP22msv3njjjXrr/vvf/zJkyJDN9rP1er2NJqNN00z4j27DMJJyu4lgplDVYV0SV3xSKS7DiFa5kzL7vGEqDMPASNHXIaTWc1hXqsaVauR9vqHc3Ibran4HY5qQm5ua+1bG7vM1w/SpeS9s+c0lfp9Xqua9uua2t8b88kvMFStQXq/uP1l3CJrbjfL7MaqqcC9bhl1Y2KT7Tvjr2DRT+v0hGeJ9HuuJVks342+39hy2KC6av89vKa6WxpSsx8up55B27QhMm0b2+eeT9c03GBs3YpxyCjz3HAwZkvS4PC+8EOtle9hh0LcvJknet1J0nzfQw8QN4v8+n46Pl2P7fIrGlY7PYUvjSuY+3yJJ+h6Rqp8/maap/1/cj0JpaSnDhg2LO6BEqaioYOHChSxcuBCAFStWsHDhQn799VdAV8meccYZtde/4IILWLVqFRMmTOCnn37iiSeeYMaMGVx++eVOhC+EEEIIIZLMXL9eJ2qzsur3kzVNVH4+eL1g2/p6Qoj0kJND+dSpsPfeermiAk4+Gb74Irn3W1lZr5dt9UUXJff+hBBCiBpxJ22HDRtWmzB1wldffcWgQYMYNGgQABMmTGDQoEFMmjQJgDVr1tQmcAF69+7N3Llzef/99xk4cCA333wzDzzwAMcdd5wj8QshhBBCiOSyO3XSZduWpdsjRMu4oyXdlgWmqa8nhEgffj/2zJmw3356ubISTjkFPvssaXfpee65elW2arvtknZfQgghRF1xt0d44IEHOOqoo+jVqxeHH344WVlZyYhrs/bff//aicQaM3PmzAbr/v73v/PNN98kMSohhBBCCJEq7CFDsHv3xly2TCdtXa5YiwSlMIJB7L59sYcMcTZQIUT8srPhqafg7LPh/fchEMA84wzcDzwA++yT2PuSKlshhBAOirvSduDAgSxdupQTTjgBv99Pu3bt6p3at2+fjDiFEEIIIYRoGpeL0KRJkJWFUV4OStWejPJyyMoidP31OpkrhEg/Ph88+SQceKBeDgbJu+giXAsWJPRupMpWCCGEk+KutD3uuOMwjAydiEMIIYQQQmQEa8QIgtOn4508GfPHH2uTtnbfvoSuvx5rxAinQxRCtITXCzNmwNix8M47UFWF/8ILCT3yCFa0fUJLSJWtEEIIh8WdtG2s/YAQQgghhBCpxhoxgsBBB+H/298wiotRhYUEPvhAKmyFyBRZWfD446jzzoO33sKorsZ34YVUPfQQ1v77t+impcpWCCGE0+JujyCEEEIIITLIsGFw8MH6PBO5XJCTo4dT5+RIwlaITOPxoB55hPDBB+vl6mp8F12E6733mn+bdatsTVOqbIUQQjiiWUnbZcuWcfrpp9OtWze8Xi/du3fnzDPPZNmyZYmOTwghhBBCJNPZZ8Mll+hzIYRIRx4PFXfdRfjQQ/VyOIzv4otxvftu827u2WelylYIIYTj4k7a/vzzzwwZMoR///vfDBo0iDPOOIOBAwcyZ84chg4dys8//5yMOIUQQgghhBBCiMZ5PAT/9S8ihx2ml8NhfJdcgmvevPhuZ9Mq23HjEhunEEII0URx97S99tprKSgo4P3336dHjx6163/77TcOOOAAJk6cyEsvvZTQIIUQQohUFwg0XGfben0gAOYmh0n9/taJSwghhGgz3G5Cd98Nbjfu116DSATfP/9J1ZQpWCNHNukmPM8+i/HXX4BU2QohhHBW3EnbDz74gAceeKBewhagR48eTJo0iUsuuSRhwQmRyiwLKiqgqkqfW5a0yROiLevbt7G1BrbdCdM0Gmz544+khySEEFukLCuu6xvyRUekA5eL0B13gMuF++WXwbLwTZhAyLKIHH74lv9WqmyFEEKkkLiTtoFAgIKCgka3FRYWEgwGWxyUEKlu7lyYOBGWLQOloKwMhgyBW2+FUaOcjk7ESynldAgiQwUCYFkGLpdU1ooUdsEFsGED5OfDo486HY1oRaGPPorr+r79909OIEIkmstF6LbbdOL2xRfBsvBefjlYFpGjjtrsn0mVrRBCiFQSd9K2X79+PPvssxwabfJex/PPP0///v0TEpgQqWruXDjtNAiFwDB00tYwYPFivX7WLEncpgPLVpQEqymuORmGQWF2FgXZWbgaqYoUYmuWLm24bu+9Yc0aRdeuBgsWtH5MQjRJVRUEg/pctHkqEkFVVGDk5mK44/6pIETqME1CN9+McrnwvPAC2DbeK6/Uidtjj214fcuSKlshhBApJe5vYpdccgnnnnsuZWVlnHnmmXTt2pU1a9Ywa9YsXn/9dR6PftAJkYEsS1fYhkLQrh2sX6/XG4Ze3rgRrrsORoyQVgmpzLIVqzYGqIrYWLbC73Zh2YriYDUV4Qi92vklcSvi1lglrWnq9wfTlEpbIUTq8e63X4N1dnk51d98Q9buu2Pm5TkQlRAJZJpU33QTuFx4nn0WlMJ7zTVg20SOP77eVY3SUv1lH6myFUIIkRriTtqeffbZrF27lltuuYX//Oc/gB5anJ2dza233sqYMWMSHqQQqeLzz3VLBL8fystrv9fVVtv6/bra7vPPdYWdSE0lwWqqIjZu06BzjpdqyybLZdau31BVTSe/1+kwhRBCiKRqrEet4XJhmKY+lyPQIhMYBtWTJoFp4nnmGZ24vfZaiESInHACVFZCMIgRCKDy88HlkipbIYQQKaFZY56uueYaxo0bx6effkpJSQkFBQXstddetG/fPtHxCZFS1q2DSERX2kYisfWWpWeJd7n05XXrnItRbF1ZKAxA5xwvfo+Lv6rCtPO6cZsGv5dX8VdVWJK2QgghhBCZwjCovu46XXE7cyYA3quuwjt5MsYff+gv8oBRUkLkwAOlylYIIURKaHajqvbt2zfa11aITPbnnzphG62srausDHJzdeK2qMiZ+MTWKaUI23riMb+nfgVRdDlsK5RSGJs+yUIIIYQQIj0ZBtXXXANuN56HH9YTjpWW1v9Sb1m4P/0U17x5WCNGOBaqEEIIAWA6HYAQ6UApeOQRuPlm3ZtSKX1ed9RgKKR72vbtC3vs4VysYssMw8BT0682ELbqbYsue0xDErZCCCGEEJnGMKieMAGysmJVGErFtvt8EIngvfnmWB80IYQQwiEyJawQW1FZCZddBq+/rpfz8vQ6lwuqq2PXU0q3TLj4YpmELNW193ooDlaztjJEQXYWEVuxMRShJKif0A4+j8MRCiGEEEKIZDC//hqjslJPRlFVVS9pq3JzwbYxly/H/OorbKnESE2BQMN1tq2fS9tuuF1mgxVCpClJ2gqxBcuXwznnwC+/xNZdcw307w+TJsF338VGVLlcOqH7yitwxhmSuE1lBdlZVIQjVEVs/iivoipi4XO7cJkGPrdJvi/L6RDFFjT2PX1L5Hu6EEIIIaLM9evBtlG5uXqyvfLymg01w+gMQydu16/HdjZUsRk5Awc2WGcUF4NtY5SUNNheuXhx6wQmhBAJJklbITbjv//VVbPR73F5efDgg3DIIXp51CgYMACKi6GgAAoLYdUq+OorePRRuOgi52IXW+YyDXq187Ohqpr1gWoCEYucLDed/Fnk+7JwmdIaIZX17Rvf9f/4IzlxCCGEECL92J066QStZaFycjACAV2dadZ0DrQsME19PZE+/P7GJx4RQog0FnfS9tdff6Vr1654PA2HD0ciEf744w+22WabhAQnhBMsC+65B+67L7Zuhx3giSegT5/YOpdLTzxWUaETug88AEcfrb8r3HUXHHCATuqK1OQyDTr5veRmuVFK0buDn2y3lEenq0Ag9j1dKmuFiNNFF+nG7F6v05EIIUTS2UOGYPfujblsGcrt1l8eook+pTCCQey+fbGHDHE2ULFZlQsXOh2CEEK0iriTtr179+bTTz9l6NChDbb93//9H0OHDsWSpu0iTf31l/7tOn9+bN0RR8CUKZCTs+W//dvf4MILYepUCId1le5bb0EjxzdEipFJx9LL0qUN1+29N6xdC507w4IFrR+TEGntb39zOgIhhGg9LhehSZPIHjsWo7xcH/WtORnl5ZCVRej666XXWSqTI/RCAKDqTqQoMpIZ7x9saaewLEuSHyJt/fgjHHpoLGFrmrpv7aOPbj1hG3XllbrfLcCiRTrZK4RILL+/4ck0dZGMaTbcJoQQQmS0QKDhadNJmeqeBNaIEQSnT8febrt6SVu7b1+C06djjRjhdIhCCNEoFYkQWbGC6q+/xlq1iuqvvyayYgUqEnE6NJEEzepp21hiNhQK8dZbb1FYWNjioIRobS+9BFdcoSeQBcjP18naffeN73aysnSbhFGjIBLRPXAPPhh23z3xMQshhBBCCCGTMjWPNWIEgYMOwv+3v2EUF6MKCwl88IFU2AohUpaKRKheuBBVUYGKRDDat9dJ3FWrsEpKyBo4EMMtU1dlkiZV2t500024XC5cLheGYbDnnnvWLkdPfr+fyZMnc9RRRyU7ZiESJhyG667TrQyiCduBA/UkZPEmbKN23hkmTNCXbRsuuQSCwYSEK4QQQiTe0qXw88+N9x4RQqQnv18PFZMhJ1vmcunHyefT55KwFUKkMGv1alRFBYbHg7t/fzw77YSnf38MjwdVUYG1erXTIYoEa1IKfujQoYwbNw6lFFOnTuX444+nc+fO9a7j9XrZZZddOOWUU5ISqBCJtnYtnH8+fPFFbN2pp8Itt7R8LpZ//APeeQe+/RaWL4fbb4fJk1t2m0IIIURS3HILlJRAQQHMnOl0NEKIOMmkTEIIkbmUUlBdjV1RQfinn1CWhbt3bwiFMABXp04YWVmEFy3C+vNPvU1kjCYlbUeOHMnIkSMBqKysZNKkSfSWHUGksa++grFjdeIW9GRht92mk7aJ4HbD/ffr1gihEDz+OIwYAfvsk5jbF0IIIYQQApBqWiGEyBAqEkFVVmJXVKAqK/XlykqIRFBKYa1fj5mfj5mfj+H1Yv/1FwBm+/b670MhlFIy11QGibvZxZNPPpmMOIRoFUrpIqIbbtA9ZwG6dtVJ1UGDEntfffvCxIl6MjOASy+F//0P8vISez9CCCGEEEIIIYRID8q2UYFALDEbTdKGQvoKhoHh92Pm5ODOz8fIycHMySHk9UJ1NYbbjZmbiyovB8AuK9N/5vVKwjbDxJ20vfPOO/ntt9948MEHG2y7+OKL6dWrF5dffnlCghMikaqq4Kqr4MUXY+v22QceeQSSNX/e2WfD22/DggXw2286WTxlSnLuSwghhBBCCCGEEClCKaiqwi4pQQWDsQRtMKi3UZNozcnB1bkzRk6OPvn9GGbDKajcXbsSWbWKyJIluHr1QoXDWOvXY61aBYCrS5dW/fdE8sWdtH3qqacYP358o9t222037r//fknaipTz669w7rnwww+xdRdeCNdco1sZJItpwr33woEHQkUFvPACjByp2yYIIYQQQgghhBAi/alwGAKB+qeKCsxIhLDPh5mVhZmTg9mhA0aPHpjRBG0cCQlXz55YJSWoigrCP/+MXV6OmZeH4XZj5Obi6tkzif+hcELc6apVq1axww47NLqtb9++rFy5sqUxCZFQH3ygE7Q17V7w+3W165FHts799+wJN90El12mly+/HObPh/z81rl/IYQQQgghhBBCtJyyLAgGGyRoVXU1gK6Qzc7WiYcOHbCzssjq1g1XdnaLWxcYbjdZAwdirV5NZNUqVFkZRseOuHv1wtWzZ1wJYJEe4n5GPR4P69ata3Tb2rVrpX+GSBm2DQ89BHfeWTvygN694YknoF+/1o3lpJPgrbfg3Xdh/Xpd4fvooyAvFyGEEEIIIYQQIrWoaGuDvDxs00R17Yr69luoqtLbAMPn08nZoiIMv19frpuctSyIRBLaa9Zwu3H37o1ZWIhSiqzBgzFl4pyMFXfSdsiQIUyfPp3Ro0c32DZ9+nSGDBmSkMCEaInychg/XveTjTrkEHjgAWjXrvXjMQz4179g+HBd8fvGG7pNwtFHt34sQgghhBBCCCGEqEnONtbaIBhEWRbhHj2gtBTT5YIOHcDvr03QGi6Xo7FL0WTmiztpe/nll3PYYYex//77M27cOLp3785vv/3Go48+yocffsjcuXOTEacQTbZ4sZ4AbPlyvWwYcMUVcMklusesUzp3hjvugAsu0MvXXAN77aXXCyGEEEIIIYQQIoksC7VpcjYQ0P1oQSdho60NCgsx/H6yFi+G33/H6NKFcO/eDv8Doq2JO2l76KGHMm3aNC677DJOOukkDMNAKUX79u2ZPn06I0aMSEacQjTJm2/CP/+p33sB2reHhx+GAw5wNKxaRx6p2yS89hqUlcGECTBrlrRJEEIIIYSoFf0iV5dt635Xtt1wu9/fOnEJIYRIC8q2UcEgqrISVVlJZONGzOJiCIdRhqErVKOtDbp0ibU28PkaVK8aloVy6P8Qolldis855xxOOukkPvnkE4qLi+nUqRN77703OTk5iY5PiCaJRHQV69SpsXU77ggzZkCvXs7F1Zjbb4fPPoO1a/WEZM8+C6ed5nRUQggh2qxHHtHJMDmCKFJEzsCBDdYZxcVg2xglJQ22Vy5e3DqBCSGESClKKaiuhvJyjPJyImvXEgkEdDVttO9sVhZkZ6M6doS8PIzcXN131uHWBkI0RbOnlsvJyeGQQw5JZCxCNEtJCVx4IXz8cWzdccfBXXfpkQ2ppkMHuPtuOP10vXzjjbDffqmXXBZCCNFGpOKHpRCb8vvl4IIQQrRhKhJp2Hc2ENDrldKjwAsKcLVrh9GtG2ZODkZODobHg2VZqNJScLslWSvSSrOStuvXr2fKlCm8//77lJSU8Morr7DTTjvx2GOPMXToUAYNGpToOIVo1P/9H5xzDvzxh152u3USdMyY1P5Of+CBcOqpuso2ENAtHV56ydmeu0IIIYQQqaBy4UKnQxBCCOEQZRioysqGydlQCKiZfCvad7ZDBwy/H+XzYZsmnvx8XC1Jykp7HpFi4k7arlixgn322YeysjJ22203li1bRqjmxfPdd9/x2Wef8eSTTyY8UCE29cILcPXVejQEQFERTJsGQ4c6G1dT3XADfPghrF4Nn38O06fD+ec7HZUQQogoy4KKCqiq0ueWBVKcIUQrkB/BQgiR8ZRSEArVJmUj3bqhCgtRBQWo//s/AAyvt96kYPj9urXBptVOlqV7JrbQltrzUFoq7XlEq4s7aXvllVfSoUMHvvrqK4qKisjKyqrdtu+++3LDDTckNEAhNv3RHAzqhOesWbHrDBmik56dOzsXZ7xyc+G+++D44/WBu9tvh+HDYYcdnI5MCCHE3LkwcSIsW6bfo8vK9GfNrbfCqFFOR5dgr76qfzD5/XD00U5HI4QQQogMo8LhxlsbWBYAhtuNcrsxS0ogEsHYeWfw+zHcze7omTh+P8q2GyaKhWgFcb8C/ve///HII4/QrVs3rJoXWFTXrl35IzpOXYgEaOxHc+fOug2Cz6evM2aMbong8TgaarPstReMHasrhKur4ZJL4I030vN/EUKITDF3rp4gMhTSrXaibTQXL9brZ83KsMTtq6/qBvEFBZK0FUIIIUSzKcuCykoIhXQ7g2hytmZ4rGGasdYG+fmx6tmsLDy//oqxdi2qc2eMdu0cib+x9jy2bVNaWkrHjh0xJXErWlncSduqqiry8/Mb3VZZWSk7sUiYTX80R1vJlJfr5U6d4KGH4IQTnI60Za6+GubPhyVL4Lvv4IEH4LLLnI5KCCHaJsvSBwtDIWjXDtaujSVt27WDjRvhuutgxAhplSCEEEKItkkphR0IoCorURUV2JWVqMpK7EAAMxjUk7VEk7NFRTo5m5MDPp/uSZuqGmvPY9uoqiq9TfJdopXFnbTt168f7777LgcffHCDbR9++CE777xzQgITbdumP5rXr49tMwx9ys+HY491LsZE8fl0ovbww/X/ff/9cPDBsOuuTkcmhBBtz+ef69Edfr8uDlFKr7cs/dnj98PSpfp6e+/tbKxCCCGEEMmklIK6rQ0qKjDLywkD0dSr4fFg5OZiFhRgdO+OHYlg5uVh1GmlKYRonriTtmPHjmXChAl069aNU089FYDq6mr+/e9/M3XqVB566KGEBynanro/mquq9I/lKK9XH6T7/ffM+dG8224wfjxMmaL7p19yCcybp/9XIYQQrWfdOv2ZE+2nHhUtrHC59LZ165yJTwghhBAiGVQkoieQCQR0i4OayyocBsBwucDnQ/n9uDp3xt2uHUZOTr3krGVZUFoqw5GESJC4k7bjxo1j4cKFXHrppVxWM4Z73333RSnF2LFjOfPMMxMepGh7oj+abVsPRY0yTejYUa8PBjPrR/P48fDOO/D997pv4p13wqRJTkclhBBtS1GRrqgtK4uti47wAP3Z5HLp6wkhhBBCpBsFKJ8Pu1071K+/xvrOVlUB6PYFPp+ulOrSJdZ31ufTrQIiEVwdO2JKYlaIpGvWVHzTpk3j7LPP5j//+Q9r166lsLCQww8/nL0zoeRRpIToj+a//oqtM4xYpVMm/mj2eHSbhBEj9KRkjz0GhxwCe+7pdGRCiEwRrR6tqtLn0fdSEdOvn26JYNv1P3dArw8E9HX22MO5GIUQQgghtkYppX9YRlsb1FTPhvv100nanBxdBRWdFCwnp7YPrSG9W0VTBAIN10UnI7Lthtsb6xkstqhJSdvdd9+dZ555hp122omnn36aww47jD333JM9JZskkmSbbWKVttEKp2iVUyb/aO7XD666Cm6+Wf+f//wnvPsu5OY6HZkQIt3Nnat7hS9bpt9fyspgyBC49VYYNcrp6FJDJAL/+IduTRMMxj57ot89N27U2265RZLdQgghhEgdKhzWX17qtDUgENAtDwDD7dYJ2bw8XOvWYf72G+TlYQ0Z4nDkIp3lDBzYYJ1RXAy2jVFS0mB75eLFrRNYBmlS0va7776joqax25gxY/j0008pKChIamCi7SovhzPP1J8poVDb+9F83nnw3//qfr2//gqTJ8NddzkdlRAinc2dC6edFntPVUqfL16s18+aJYlbgDvugA8+0KP/evbUB8x+/llvU0ofWLvlFnmshBBCCOEMZduoQABr40aMtWshFEJVVaFCIaCmtUFNtSwdOsSqZ71evQ1wlZZiVFToSlshEs3vj/3YEC3WpKRtUVER33zzDXvssQdKqdoXuxCJFg7D+efDTz/pH8077KDbBixapLe3hR/NLhfcdx8ceKA+QDprFhx6KBxwgNORCSHSkWXpCttQCNq1g+Li2MGwdu30gbDrrtOtWTLxQFhTvfIKTJ2qL7tc8MILMHQoDBigH7PCQvjyy7b9GAkhhBCidSildD+r8nKsjRuxg0HsykpUMAhKYds2hlK672ynThjZ2fqyzyetDUSrqVy40OkQMl6TkrZHHnkkF110EVdccQWGYTB8+HDMzbwRGIZBWd3ZO4RoIqXg2mvh/ff1cvv28OabsO22be9Hc69ecMMNulUCwGWXwfz50KGDo2EJIdLQ55/rlgh+v07UWpZ+v1VKb/f7YelSfb222pr+++9hwoTY8uTJsNde+nJuru7/m5ubwZ89222nP2Dbt3c6EiGEECI9taC3pwqHdVuDQKB+i4NIBNO2sfLycOXlYXbsiNGjB2ZODrbPR6C8HNPtxsjYLygi5UmP2qRrUtL2wQcfZMCAAfzwww888cQT7L///nTq1CnZsYk2ZupUePZZfdnjgSef1L8joY38aN7EaafBW2/pJPbatbpS7uGHnY5KCJFu1q2LTTgWCMSStdG+tu3a6e3r1jkbp1OKi2HMGF2JDHDSSXDWWY6G1Pquv97pCIQQQqQimWSoyZrS21OZJio7G+XzEXzuudoErQqH9fVNUz+G2dn6YKrXi52VhaeoCLe7fupGWVZr/FtCCIc1KWnr8XgYP348ADNmzGDSpEkMHTo0qYGJtuX11/VkOFH33QdtfZ47w4ApU2D//fXw5VdegZEj4fDDnY5MCJFOiop0wjYU0ge/6gqF4K+/ICtLX6+tCYd1H/E//tDLgwfrvrbSBUoIIYTYciKS0lKZZGgzFKBqGuSr7GxUTg52+/Yorzc2uUBpqW5n0Lmz7jvr9+vWBnW/hFgWRCLSnlKINqxJSdv8/Hzeffdddt99d2644QZ69OiR7LhEG/Lll3DJJbHlq6+GY45xLp5U0qUL3Habns0cdLuEoUPbZnJFCNE8e+wBvXvDDz/EqmyjlNKJ29xcaIuTB994I3z2mb7cuTM8/rhOYAshhBBiM/x+lG1L31Rq+s5WV0MgQMXbb+vK2ZqTsm0ADI9HV85GJwfz+SA7GyMvz+HohRDpoElJ2/LycqqrqwGYPHkyI0eOpFu3bkkNTLQNK1boYag1uxcnnwwXX+xoSCnnmGN0m4T//EcfkL3iCpg5UyrBhBBN43LpCRy//z6WtI1ORBad2NW29UGhe+6BtvIb7PnndRse0C15Hn9cJ26FEEIIoTU2yZBt25SWltKxY8fNznOTkSIRVCAQ6z1bc1KRCIDuK5udDR07QrdutdWzhsfjbNzS4kKItNakpG23bt1466236Nu3L0opNm7cyIYNGzZ7/fz8/IQFKDLXhg1w6qk6EQkwbJgMS22MYejH5fPPde/Fd96BOXNg9GinIxNCpIN33oGPP9YTGVZWQiQSS9726aPbr7jdMHu2Lv647bbMfx/++ms9qiPqzjt1a4Q26+abdYPj9u2lv60QQoiYxhJ4to2qqtLbMjBpq2wbFQigKitRlZVEyssxi4shHEYZhm5VEK2abd9eJ2ezsxu2NkgRTem1W5e0uBAitTQpaXv66adz8803c8stt2AYBiNGjNji9S1pii22IhTSFbYrV+rl/v1h2jRd7SQaKiiAu++OTY5z/fWwzz4gnUqEEFuyfj1MmKAv+3y6T/Ztt+kDQIWF8NNP8PbbcP75utjiqaf0747rr8/cxO3atXDuubqfLehJyE46ydmYHLdsGZSU6A8bIYQQog1Q0R5RwSCUl2NUVBAGqKqqPbpteL2QnY3Kz4fcXN3SIDs7/VtD+P2x4VZCiJTWpKTtLbfcwtChQ/n++++5/vrrOeecc6SvrWg224bx4+Grr/Ry587wzDN6BnOxeYccoqtrZ8/Wkwldeqm+nO7fGUT6sCy971VV6XPL0kPvRWpSSr9PlJTo5YMPhjPPhAce0M9fbq5+/g47DO6/X/cWVwoefVR/l7/8cmfjT4ZQCM45RyduAfbaS/e1FUIIIUTmUuFwvZYGBAK672xNawNME7xejKIiXD16YObkYOTkYHg8WJaFKi0Ft1u3QEgzjbW4EEKkjyYlbQGOPPJIjjzySB5//HH+8Y9/sNtuuyUzLpHBbr8dXn9dX/b74emnoXt3Z2NKFzfdpIc5//47fPKJ7sd4zjlORyXagrlzYeJEXZCnlB5JPWQI3HorjBrldHSiMTNnwnvv6cudOukq280VVBx3nE7GX3GFXp4yRVfmRidBzARKwTXXwDff6OXu3WWEhxBCCJFJVLRHazBYr/esqplAxTDN2KRg+fkYfr+eWM3lQlkW7o4dcaVhYnaLpEetEGkt7hq9FStWOJ6wnTp1Kr1798bn8zF48GA++uijzV73/fffx6jpPVP39PPPP7dixCLqmWfg4Yf1ZdPUFV277OJsTOmkXTu4997Y8i236CSaEMk0dy6cdhosXhxL+hmGXj7tNL1dpJZfftEHeaLuu2/rI99PPVW3No267TaYMSMp4Tli5kx44QV92efTB72kG4AQQgiRfpRSqGAQVVKCWr0a9csvqG+/hc8/R333HWrJEj2BimlCURHGDjtgDBwIQ4di7LabXu7eHaNjR90CQdoECCFSVJOStpMnT+aPP/6ot27BggUENplpcPny5ZxxxhmJi64Rs2fP5p///CcTJ07k22+/Zb/99mPkyJH8+uuvW/y7X375hTVr1tSett9++6TGKRqaPx+uvTa2fMstcNBBzsWTrvbdF84+W18OhfSQ5ujIHiESzbJ0hW0oVL+FiWHo5VAIrrtOX0+khlAIxo2DmqISzj0Xhg9v2t+ec45+vqOuvx6eey7xMba2BQtg0qTY8pQpsPPOzsUjhBBCiKZR1dWov/5C/fEHaulS1HffwRdfoL79FvXLL/Dnn/rHUPv20KcPxi67YAwdirH77hj9+2Nssw1GYSGG35/+vWiFEG1Ok961brrpJn777bfaZcuy2G+//RpUq65fv55nn302sRFuYsqUKZxzzjmce+65DBgwgPvuu4+ePXvyyCOPbPHvioqK6NKlS+0p44Y9pLhFi+C882KJnQsuiE2qJeI3caKe9R3g229j1ctCJNrnn+tqbq8XSkv1a1ip2NwFfj8sXaqvJ1LD7bfrCcZAT/JYNwnbFBddpHvhRl1xBbz8cuLia22//Vb/82fcODj6aEdDEkIIIcQmlGVhb9yoZ1FduRL144+oL79EffUVatEi+PVX3e7A74eePTF23BFjyBAYMgRjp50w+vTB6NwZIy8Pw93kLpBCCJHSmvRupmpmT9zaumSrrq7m66+/5uqrr663/pBDDmHBggVb/NtBgwZRVVXFjjvuyHXXXcfwppYdiRZbs0YPoa6s1MuHHaYr80TzZWfriYOOOkpP7DZliq5a3mknpyMTmWbtWl25GX39Rtm2Pne5dDJs3brWj0009MEHuk8rQFaWPqDj9cZ/O5dfrtvBPfqoTtCPH69v57DDEhtvsgWDemTChg16ef/9dV9bIYQQQjhEKVRlJVZVFaqyEruyElVZiQoGsW0bs6pKJ2Zzc6FLl9q+s/h8GNLGQAjRxqTVIaji4mIsy6Jz58711nfu3Jk///yz0b/p2rUr06ZNY/DgwYRCIZ555hkOPPBA3n//fYYNG9bo34RCIUKhUO3yxo0bAbBtGzuaqUgA27ZRSiX0Nlsu9kFo2y1PzJeXw2mnGUSfnt13h/vvVzW371xcieNcXIMG6Yqxhx4yCIfh4oth7lxFVpazcW2JUkbNOSmz36ua16GybWw7lb4IOv8clpTA9Ol6/4L67b6U0iPRlNKJ28JCFedrOtGcf7wa05r7/IYNMH587HG49lpFv36Nvdc27bGaOBECAYOnn9aJ+XHjYPp0lcS2Nol9DpWCSy81+OEHvbzttvDwwwrDyJTPn8QxouXzNe+FLZGs7zbR2232bUeLDZrx93XvN5EJg3qPVYp8JkJy42rx89hMW3sOWxJXS/b5LcXl1GOV1Lha8DpM1biSuW+lalxN3ueV0r2agsHYhGCVlRiVlYSysjBNEyMrS7ctyM/H9PsxsrOxqqsxvF7Upq0MauJNhjb3WkxSTC2OK933+WbE1RLJ+rxO1X0+0zT1sU2rpG3Upk+eUmqzT2i/fv3o169f7fJee+3F6tWrufvuuzebtL399tu5qe4MLjXWr19PVVVVCyKvz7ZtysrKUEphpkh/nXC4ANs2CYdt1q0raeFtwfjx7fnxxywAevSwuPPOUjZuVNTkwR2JK5Gcjuu00+CttzqyZImbRYvgxhsD/POflY7HtTmRSD62bRCJWKxbt8HpcACothWV1VAcriTLTJ0PBqefw48/zuKGG/IoLjZxuUwiEfD5FKGQUfudoLJSoRRst51F794ljlbbOv14bU5r7fM6QdmOP//UZbV7713N4YeXNfqcxPNYXXIJbNiQx+uv+wiFdM/bhx76iz32CCf8f0j0czhzZjavvpoLgN+vuOuuUkIhK+79NFX3rURqX1WFUV2NqqqirIUv5GR9t7Ftm4qKCkzTbFaLK59l4bJtLMtiw4b4XouWZWHbNuFwOLHf1yorcVdWEiku1kmNVJHEuFr6PDbX1p7DlsQV/dvm7PNbisupxyqZcbXkdZiqcSVz30rVuBrd5y0LMxjEqKrCrKqKnddMvKFcLpTPRyQri0j79lTn52Pk5IDHU/+2q6pS7j0iE1+LyYqppXGl1T6foLhaJEmf16m6z2ea8vLyJl0vrZK2hYWFuFyuBlW169ata1B9uyV77rkns2bN2uz2a665hgkTJtQub9y4kZ49e9KpUyfa1Z2Jp4WiRw86deqUMjukx2NgmuDxmBQVFTX7dpSCq64y+OwzPWln+/bw/PMG223XydG4Ei0V4nr0URg1SldDzpqVy1FH5RAKGVRXQyhkUlBQRKq0cHa7DUzTxu1OneexKmJRXhaksH02PneKPFA4t29VVcEttxjMnKmXXS7o1k1Xcdq2Ua/aNhg06NABbr/dRdeuzj6fqfBabExr7fOzZsGHH+rHID8fHn7YS+fOjd9fvI/Vww/rg6VvvKErbidMyOfZZxVDhyb2f0jkc/j++3oUQvSj9aGHFHvvXeB4XClr9OjaPoEt/R+T9d3Gsiw8Hg9ut7tZt+t2uTBME8PlIj8/P66/tW2bSCRChw4dEvrjxS4vJ5yTg6ewEDMvL2G321LJjKulz2Nzbe05bElc0X2+Y8eOzfrbzcXl1GOVzLha8jpM1biSuW+lZFy2jR0I4P7rL9pVVOhWBoGA7qUFelhWdjZ06KBbGkRPXi8YRlIfr5Zoa6/FZMXU0rhScp8nee/zLZWsz+tU3eczjc/na9L1mpy0ff755/n444+B2E777LPP8v7779de59dff40vyjhlZWUxePBg3nnnHY455pja9e+88w5HHXVUk2/n22+/pWvXrpvd7vV68TbSBNA0zYTvtIZhJOV2E8FsQdXhww/HZhz3eODJJ2H77RNTxdiSuJLJqbh22kn3n7z9dv2d6aCDDKqqdOK8rAyGDjW49VYYNcqR8OoxDFVzTsrs84apK/WNFH0dQuvtWz/8oCehWrIktu6AA3TP5K++0sPlv/suts3l0pWYhx+eWq/JVHqPaI19fulSuPHG2PKUKdC1a9Meg6Y8VqYJDz2kRzjOm6cP5J9xhsGcOTBwYPNiTkRcm7NypW7lEK0Iv+wyfWDL6bhS2rHHJvTmkvHdJjqqKnrbzQiq9jzev4/ed8K/r5lman4PTGJcLX4eW3i/m/ufWhpXcx+vLcXl1GOV1Lha8DpM1biSum85GJdSSidia9oa1J6CQUzbxhsMYnbooKtlO3WKJWezszG2EGuyX4vN1eZei0mKqcVxpeprkeS8z7dYkj6vU3WfzzRN/f+anLS9//77G6y79957G6xLdt+JCRMmcPrppzNkyBD22msvpk2bxq+//soFF1wA6CrZ33//naeffhqA++67j2233ZaddtqJ6upqZs2axUsvvcRLL72U1Djbstdfh1tvjS3fdx/suadj4bQJF14IzzyjE2tK1fu8Y/Fi3UZh1qzUSNyK1GNZumL7rruo7V/r9cINN8CZZ+r9aNQoGDECBgzQkwsGg1BYCMuXOxt7WxcO60R7tHPPGWfAIYck/n48HnjsMTjrLF3FWlEBJ58ML7+s94lUUVGhY4y24BkxAi691NGQhBBCiJSmwuFGk7OqprWB4XbrhGy7dtClC/h8BKuqyC4q2mKCVgghRMs1KWm7YsWKZMfRZKNHj6akpITJkyezZs0adt55Z+bOnUuvXr0AWLNmTb2K3+rqai6//HJ+//13srOz2WmnnfjPf/7DKMleJcWXX+rKu6irroI6RdEiSQxDJyuil6OJW8PQ3682boTrrtMJjAwfZSDi9Ntv+jX72Wexdbvsoisrt9++/nVdLj2Rb26uTvQaBsyfD2vXQhwdakQC/etf8P33+vJ22+lEe7JkZcGMGfog0Kef6kr+E0+EV16Bvn2Td79NZdt6X168WC9vvz088ADI70khhBAClGWhaiYDi2zciLF+PYRCOmkLOgGbna0TtPn5GNHq2ayseoVZyrb1bLRCCCGSrklJ22hCNFWMGzeOcePGNbptZrQRY40rr7ySK6+8shWiEitW6Aqn6mq9fNJJ9RO4Ink+/1wn33Jy9MHxOhOBYxj6+9bSpfp6e+/tdLQiVbz8MlxzDUR7oBuGrtq84ooG80LUYxjQsaPevywLXnpJD0cXrWvBAt2KBvTzNXWq/q2VTNnZ8NRTusr266+hpAROOEEnbrfdNrn3vTX33gtvv60vt2sHM2dCCrUJTW3BYOwDI9k7kRBCiKRSSun39fJyImVlWFVVqIoKVJ2JilRNj1k6dcLIzdU/Fnw+qZwVQogUk1YTkYnUtWEDnHoqlJbq5f32gzvvjA3TF8m1bp1OnuXl6QPf0aHSlqWrbHNy9OUWTgouMsTGjXD11fDqq7F13bvDgw82vZVJhw6x1/vs2bpFh7zeW09ZGVx8sc6zgR7VsMsurXPfubnw7LNw/PG6D/LatbGK2+7dWyeGTb39Ntxzj75sGPDII9C7tzOxpKULL9QZ+IIC2OTgtxBCiNSklNJ9khppbUAkgmnb2Hl5uPLyMPPzMXNyMHJzMfx+bMOgsrQU3G4MGYYnhBApS5K2osVCIV1hu3KlXu7fH6ZP33KlnkisoiI9dN2yoH17/ZxEkznBoE7iZmXp64m2bcECXQH/xx+xdccdp/tQt2vX9NvxemHoUPjiCz1x2bffwu67Jz5e0ZBScOWVurcwwL77Qk1b91bTrh288ILed375RVf6RytuW7tVxuLFOoEdde21MHx468YgRHOp6Ie1EEJsgbKshsnZQKB+a4NoO4PCQvB6sbOy8BQV4XY38pPfslr5PxBCCNEckrQVLWLbMH68ngALdFLwmWfiS/6IlttjD93PcvFi/dhHE7jRFgm2rQ/Ez5yp+zx26uR0xKK1VVfricYeeSSW0G/XTlfEH3VU827zpJN00hZgzhxJ2raWF1+EN97Ql9u3h/vvd6Zva36+rrI+5hjdHmflShg9WrfLKChonRjKyvRBw8pKvXzUUdKqQ6Q+FYlgrV5NZNUqrFWrqDYM3L164erZU0/4I4Ros2pbGwQCRAoLIS8Pu6gI9fnnQM2k3z6fTs526RLrO+vz1Z8Q3LIgEkn6JOFCCCGSS5rWiBa5/XZ4/XV92e/XCVunhse2ZS6XrpT0evXQ92hSzuXSyRzD0K0T3nwThg3TSR8p7mk7fvkFRo3SPU+jz/s++8B77zU/YQtw+OGx9pevvhpryyGSZ+VKmDgxtnzXXdC1q2PhUFSk30969NDLixfrZH5ZWfLv27J0gjY6ymOnnWDKFGnTIVKbikSoXriQyKpVqEgEo317VCRCZNUqqhcurJ2tXQiR2ZRSqFAIVVqK+v131JIlqP/7P/j8c9TChajFi7E7dADDwCwvx+jbF2PXXWHoUIxBgzD69cPo2ROjoAAjO1uSs0IIkaEkaSuabdas2CQ4pqkr+Fqrp6JoaNQo/ZzssEMsMaeUfk6uuSaW2Ckr09XRp56qhzSLzGXbMGMGjBgBixbpdR4PXH+9rpDs1q1lt5+bC0ccoS9v3BibBEokRzgM//hHrKp09OjY4++kbt104jbaFuHHH/X7S0VFcu/3jjtg/nx9OT8fnnxS5tASqc9avRpVUYHh8eDp3x/PTjvh6d8fw+NBVVRgrV7tdIhCiESLRGDjRtSff6KWL0f98AN8+SXq669RP/2kv5BXVekvVr16Yey0E8bf/kbW0qV4lizBvW4dRlGR7kcr/WeFEKJNiTtpe/bZZ7NixYpGt61atYqzzz67xUGJ1Dd/vk4ERt1yCxx8sHPxCG3UKN2qYrvt9ERR222nl2+9FT78EI4+Onbd99+H/feHJ57QyT2RWdauhdNO0wna6mq9rl8/eOstPedQoobTn3hi7PILLyTmNkXj7r8fvvlGX952W7j5ZkfDqadXL524LSzUy998A2ecoUd4JsNrr8UOGrpcMG1arNpXiFRm/fknAO7tt9fDmoNBzHbtcG+/fb3tQoj0o2wbu6ICa+1aIsuXU/3dd1R//jnmN9/oo+crVuij3FlZ0K0bRv/+GLvvrqtnd9kFY7vtMLp2xWjfHkMmBxFCCEEzkrYzZ85k/fr1jW4rLi7mqaeeanFQIrUtWgTnnRfrX3/BBbqnoEgNLpc+UO/z6fPoAfmCAj08/qmnoEsXvS4QgOuu08ncJUscC1kk2FtvwQEH6MR81Lnn6vU77pjY+9pzT9hmG335o4/qT3AmEufLL+G++/Rllwseeki/vlNJ3766grtDB7382Wdw9tmxgwaJ8sMPcOmlseWbboK9907sfQiRDNHh0ACGz4ddWgqAVVyMkZWlrxMKyeRkQqQ4pRSqqgq1YQP8/jvG0qVUf/UVoY8+ovqrrwj/9BPW2rUAmJ06Yffpo4e+7bEHxsCBGDvsgNGjB0Z+PsamvWiFEEKIOhLaHmHDhg14vd5E3qRIMWvW6Oq96PDcUaN00k+kj4MP1sm8M86IrfvqKzjoIJ0UqpmEVqShigqYMAHOOQdqcgF07gzPPw+TJ+tEfqKZZqzaVildbSkSa+NG3RYhWhF/2WWpO+nbgAF6f8vL08sffKAP8iXqfaWkBMaMifVPHj1aLwuRDgzDwPB6UbZNZOVKDI8Ho107jKwsIitXoqqrMbxeSeAIkUJUOIwqK0OtWYNatgz1/ffwxReob75B/fyzPlodDmO2b4+7b1+yBg3Cu+++ePfai6xdd8Xdp48ehpKTg7GlYU6BQMOTbcdmFN50mxBCiDahSVPUfvjhh7xfp2Tr8ccf5+1NmhcGg0Fee+01dkx0GZdIGeXlOmEbHbm3++7w4IPOzFouWqZdO90P8qijdAJo5UqdVLnrLj0r/ZQpsNtuTkcp4vH11zqxt2pVbN2oUfCvf0HHjsm97xNPhLvv1pdnz4ZLLpHJoBJp4kSItrkcOhQuvtjZeLZmt93g2Wf1hGSBAPz3vzrmhx+OVf43RzgM558Pv/+ulwcN0u9jsq+JdGJ27kxk4UJUMIinXTuIRFBuN5G1a7GLizGjQ2GEEK1KmSa2z4dat65eclTVDBcxTFM3Tvf7IT9ftzfx+1EuF8qycHfsiKsFH3I5Awc2WGcUF4NtY5SUNNheuXhxs+9LCCFE+mhS0nb+/PncdNNNgK4SePzxxxu9Xq9evXg42mROZJToj+WfftLL22wDM2fKpC/pbq+94L334J574NFHdcuLn36Cww7TbS8uu0ye41QXDutep/fdF6vEzMnRfaZPPLF1Elo9esC++8LHH+sDAF98AXvskfz7bQtefRVeeklfzsvTB8rSYQ6SIUP0Z8Rpp+n2CK+/riu9p0xp/oG+m26CBQv05aIi3Y9bBveIRjVWhbZpxVpdfn/rxAV6NsiqKvD5iCxdil1ejpmXh5GVhZmbi11SglVSgqugoPViEqINUUrp12CdxGx1nz7QowcqNxe1dCmGz6ffF4qKapOz+HyNV8pG+8Ulg9+v37fk6KTIRKn8WS1ECmlS0vbKK6/kH//4B0opioqKmDdvHrtvMjbT6/WSm2oN9kRCKKUrvaLF1u3bw6xZsQlnRHrz+fTze8QRemj9okX6c3LqVJg7V1dQSr/I1LRypa6ujU5OBTB4sE7sbbtt68YyerRO2oKutpWkbcv99htcfXVs+Y47oGdP5+KJ1777wowZuq9tOAxz5uj3m9tvj//35+zZOkkLOuc1Y4Zu/SES5Lrr9Ozm7iZ9LUx5qVqxZldUYK1YgWfQIEyfj8iqVaiyMoyOHXH36oXZvTuRxYsJ//AD7LQTLvmiJUSzKaX0h8+mbQWCQVRNotXweMDvx6ysxPzjD8jJIbLHHhgOHB2tXLiw1e9TCCel6me1EKmmSd/Os7Ozya4pt1uxYgVdu3Ylq2bCBJH5HnlEJ2lB/1h+8kk94YzILLvuqieqevRRXXlbXa2Tgscfr6vlrrtOt1UQzlNK9w2dNCl2ENrl0kn3iy92Ju8yahRce61uo/LGG7rSVw6IN59l6edy40a9fOyxcMwxzsbUHAceqD9Dzj9f/09PP62r9ydNanri9ptv4MorY8u3364PTogEagsf6g5XrKlIhPCPP2L4/Xj69cMwTczCQpRSZA0ejFnTCNqz446Ef/qJ8I8/wo474urUyZF4hUgnKhLBLi+HdeuguhpVU0mrahqqGy5XrLVBYWGsetbjwTAM3GvXYhQXo1wuRxK2gHxpEgIc/6wWIhXF/dO+V69eyYhDpKjXX9fJl6h779WzxYvM5PHoRNHIkbo1wpdf6vWzZsE778Cdd8IhhzgbY1tXUgKXXw7z5sXWbbut7hc6aJBjYZGdDUceqXuZVlbCm2/GJigT8Xv4Yfj8c325Rw+47TZn42mJUaPggQd0VbhS8Nhj+jv5FVds/W/XrtUT60UnMjvrLDjllKSGKzJAqlWsKaWILF6Mqq4ma/DgekOsN510zDBNPDvuSOSnnwgvWgQDBuAqKmrtkIVITTVDpq1wGBUMYldWoiorUVVV2LaNWVWle0Tl5ECXLvVbG0gSSIiUkmqf1UKkqriTtuFwmDvvvJPnnnuOVatWURWdwrmGYRhEIpGEBShaj2Xp2eerqvT5Z5/pCYWirrxSV3uJzNe3L7zyiq6Ku/VWnYRbu1YnTI48UifyZdRm8mz6WrQsXUn73ntw6aWwfn3suqeeCjfeqH+fOG30aJ20BT2cXZK2zfPtt7GJ3UxTt7tI9yr3Y46BUEhXg4M+AOjzbXlStepqOPdc/d4D+oBhTXt9IbYsxSrW7DVrsNatwzNgAGYTYjMMA/eAAWAYhGsmE5DErWhLlFL6Q2DT1gaVlZiWRcTnw+XzYeTkYHbqhJmTg+3zEQiFML1e56plhRBNl2Kf1UKkqriTttdccw333nsvI0eO5Oijj8Yrs4BkhLlzdV/TZct0JVRZGey/f+3BaUaPhvHjnY5StCbT1Enagw+Gq67SCUPQ1dcffgiTJ8Nxx8nolURr7LW4++7Qvz989FHsevn5uo3FiBHOxbqpwYNhu+107J9+CqtWgQzOiE9lJVx0kW4vCvrAWab0Bz7pJAgG9f4Nus1BdrZOzG5KKbjmGvj6a73crRtMm6ZHA4gk+PJLnVX3euFvf3M6moxiV1QQXroUV9euuOJoxGwYBu7+/QF0xa1Scf29EOlCRSINk7OBgF4PGG63/rDIzYXCQuysLLK6dcPt89W/IcuKfXgKIYQQGSLupO2cOXOYNGkSN9xwQzLiEQ6YO1f3LA2FdAIuOmFjKKQPcu+7L9x1lyTn2qru3eGZZ+Dll3UfytJS+OsvnUx65RXdMqFHD6ejzAyNvRYNA374Ab7/Hjp00AdRDjgApkyBVCu8Mgx9gCc6lP/FF3UrB9F0kybpXtKg211ceqmj4STcmDE6cRttuzNpkv4tfuqp9a/31FO6bzPoPOITT0h1f1I9/LDuvVJQADNnOh1NxlCWRXjRIozsbNzN6Btcm7iNVtwqhatLlyREKkTyKdvG9nqhoAC7UyfUTz/p5GwoBNS0Con2ne3QIdbawOuNtTaoScwacgRPCCFEGxF30ra0tJRhw4YlIxbhAMvSVU+hkB5+W1ysE0WgEzCGoSv96rRfE22QYeiq2r//Ha6/Hl57Ta+fPx+GD9cTUJ15puwnLdHYazG6PprArazUw+bHjEndgyjHHw933KEP/MyZo4fDy37RNP/5TyxR6ffrPFom/i4dN04nbu+5Ry9feaX+P6MtQYqL9ftM1JQpeqJEIdJJbR/bUEj3sW3mcG3DMHD366cTtz//rBO3XbsmOFohEkcppb/MbFo9GwwS7t0bo7ISohNa150ULDu7Xr9nIYQQQjQjaTts2DAWLlzI8OHDkxGPaGWff66HMvv9OglkWbFtLpdOHq1Yoa+3997OxSlSQ2Ghngn+mGN0y4S1a3UiceJEePVVnYRpC5OQN5dt6yrl4mJd1BY9LymBhQvhxx/163DDhvoj/AwD3G6d2KopukpZXbro5P78+fDbb7Bgga7WF1u2Zk39quRbb9UTzGWqCRN04nbqVH1+6qn680cpXc3vdkNenq40PuYYp6MVIn72n39irV3b5D62W2IYBu4ddtCJ219+0Ynbbt0SFKkQzafC4dpeswSDteeq5geF4XbrHxnt2kGXLnhWrcJcvRoKC4kMGOBw9EIIIUTqiztp+8ADD3DUUUfRq1cvDj/8cLKiR0pFWlq3LjbJUSgUq7IF6NhRV8hVVenrCRF1yCF6UqBbb9WtE0C3RDzwQLjsMrjwwsysENyUUrBxY/0EbHFx40nZ4mKdjLXtxm+rqiqWqN00KZuTo3/zlJenx2tx9GidtAU9IZkkbbfMtnXP8LIyvXz44Zk/iZth6IM933+v22jU/ewB/VqorISBAx0JT4gWsSsrCS9ZEncf2y0xDAP39tvrxO3ixSjALYlb0UqUZaECAVRFBZHycox16yAUivWdNc1Ya4OCBXg9FgAAaCBJREFUglj1bFZWrLUBYAaDGJaF2twdCSGEEKKeuJO2AwcOJBwOc8IJJ2AYBv5NqgcMw6As+stTpLyiIp2wtSzdN9A0dQLB5dKVTuGwvpxqvTOF89q10/1sjzpKVwiuXKn3lzvu0JOVpeKQZnvTzFDNOqUUtlJYtqKyMpZsLd1gbDEZu2GD/p8Toe6IwGhrEqX06y83N71eiyNGQPv2Ogn5n//o5H67dk5Hlboeeww+/lhf7tKl7fQQt2345ZfYZ1Ddl6fbrdffcAOMGqUvC5EOlGUR/vHHZvex3RLDMPRtGgaRxYtBKdzduyf0PkTbppTSR5HLyzHKywn/8QeRYBAVDMau4/XWfiExcnNjrQ3awgeXEEII0criTtoed9xx8qGcQfbYQ8/2vnixTqpEE0fRhFEgAP36Zc7s5SLx9t4b3ntP91p99FGdiFm0CA47DM4/Xyd0fT6dlIn2rKyoiFV4J1swGEuyfr0syF8bDP4qNSjdYFC2wWBDCawv8VH5F/y1QRGujv2t20zMe53Xq1tLFBbqeX6il/PzY+s6doQzztDtSKI9bW07PV+LXi8ceyw8+aR+vt94o+FEU0L78Ud9oAP0c/3gg3rCubbg889h+XL9/0ZbHkZ17Kj3+6VLpT2PSC+J6GO7JYZh4N5uO524XbJEJ25lNlARJ6WUPhq8SVsDAgGUbYNSunq2sBCzoAAzJwej5mQDlTV9bJKxjwshhBAiJu6k7UyZVTijuFy6Cu600/Qwb6Vip40bdfLlllukyklsmc8H110HRxyhe1X+9JNOyk6dCnPn6knMZs3S/ZNt26S8HIYM0fveqFHx3Vd19ZbbEWzYUH9d3URQxPY1epsKiCc96/HoRGs0AVs3EVt3XfRytGf01tx1V+a8Fk88USdtAV54QZK2jQkG9aRc0WrtCy+EffZxNqbWVLc9T/v2OsFfd6SHbevt6dASRAgAK4F9bLfEMAzcffoAEFm6VCdue/ZM2v2J9KYikdqEbN0kbW1rA5cr1tqgZmIw5fVimyaejh1xbfrFo+4EGEIIIYRIqriTtiLzjBqlE2oTJ8J33+l1SumqvltuiT+pJtqu3XaDt9/WydopU3Qy6uef4YordCImOuzfMHR192mnwcyZunp002Tr5nrDlpc3P77NVc66XLGq1/wCKMiPJWEbS8rm5SVn+HomvRZ33VVPmvbzz/D11zphv912TkeVWm6+GZYs0Zd32UVP7teW1G3PY5r1R3pALKGbDi1BhLArKwkvXoyrS5eE9bHdkmji1jAMIsuW6cTtNtsk/X5F6lK2rY9+bTopWFUVoPcZfD6dnO3aNdZ31udrOIrSsurPiCqEEEIIRzQrafvzzz9z00038f7771NSUsJnn33G7rvvzk033cSwYcMYPnx4ouMUSTZqlO5DOWCATpAVFuqJpdKlqk+kDo9HT6p02GF65ve339aJx7o9K21bJ3SDQV2FW1iY2CSoYejh1ZsmWwsKjEarYtu3r99T1kmZ8lo0DD0h2U036eXZs+Haa52NKZW8844+YAH6N/TDD7eNyfvq2rQ9T13p1hJEtG31+thuv32r3a9hGLh699atEpYv14nbXr1a7f6FM5RSevbgTatng0GduAWMrCydkM3Px8jJ0ZW02dnSzkAIIYRIM3EnbRcuXMh+++1HXl4e+++/P3PmzKndVlFRwaOPPipJ2zQVnfCookKfy/c60RJ9++rKwXff1UlaiCVto0lc0OfhMGRlbfn22rVrvAXBpv1hCwt1j0x3Go8jyJTX4nHH6RYYkQi8+KLeH9L1f0mkdet0G5GoG2/Ur5e2RtrzpBCfTyd1fI23kBFbFlmyBFVVlbQ+tltiGAbuaOJ2xQqduN1221aNQSRRJKL7zFZV1a+ejbY2cLv1azcvT08MVlM9a7S1o4BCCCFEhoo7rXH11Vez66678s4775CVlcXs2bNrtw0dOpSXXnopoQEKIdJXcbGuYC0o0AnIOpMPYxh6m1J6KP2gQZtPyubnt70qxExQWAgHHgjz5sHatfDBB3DAAU5H5SyldAV6SYlePvhgOP10Z2NyUia1BElrjz7arD9TjfS2VDXNiJVl6YrAOjKxys/680+sP//E078/Zk6OY3G4t922XuLWte22MnFwGlG2jR0IoCorsSsrUZWVWOXlmGVlsf4x0b6zHTvGqme9XnmehRBCiAwWd9L2k08+YdasWfj9fqxNvqx37tyZP//8M2HBCSHSW7RnpVK6+jUc1lW3pgmdOunlUEgnZ2R2+Mw0erRO2gLMmSNJ2yefhPnz9eVOnXTv57b+eztTWoK0RaGPPmqwTimFu7KS6pycBskk3/77t1JkraNeH9suXZwOR7dGqNMqwdW7tyT0UoxSSvedjVbNVlZilpcTNoza58rw+TBycjA7d8YuLMTMzYXcXIxU6eMkhBBCiFYTd9JWKUXWZsYxl5aW4vV6WxyUECIzSM9KceCBumK6pATeegv++ksn8Nuin3+GyZNjy/fdpx8bkTktQYSeqd4oL0d5vRk9RFtZFuFFizB8vlbtY7s17m220YnbZct0Ar1msjLR+lQ4rBOzgUDsFAzWVqgbbjf4fKh27XB17oy7XTuMnBy9HnRxTGkpuN2SsBVCCCHaqLiTtrvuuiuvvPIKI0eObLDt7bffZvDgwQkJTAiR/qRnpfB4dG/badN0ZfUrr8CYMU5H1fpsGy66CKqr9fK554K0fxfpzrvffg3WRcrKCHz8MZ7Bg3G3b+9AVK0jsmQJKhh0pI/t1rh79tSJ26VLdY/b7baTxG0yWRZGIACRCKpmQjAqK3XSFnTC1e/X7QwKCzGysyEnR39A2jYqEsHVsSNmiu1HQgghhHBe3Enb8ePHc8opp5CTk8PpNY34fv31V9577z2eeOIJ/v3vfyc8SCFE+tq0Z2U0aSs9K9uO0aN10hZg9uy2k7S1LF05WlUFq1frvr6GAf3769eDECnjiSdiZc5nn93kP2ssWWm4XGCaGC5XyiUzEyVV+thuibtHD524XbJEJ2779pXEbQvVtjbYtHq2qgpfIKATsz6fPu/cWU8KlpMDPp889kIIIYRolriTtqNHj2bZsmXceOONPPDAAwAcd9xxuN1ubrrpJo444oiEBymESG91e1auW2dTVGRKz8o2ZMAA2GUX+P57nbj/6Se9LpPNnasTs8uWgW3rYa1ut55U7+GHdZW5ECnjww91D5OCgriStm2RHQgQXrIEV+fOKdHHdkvc3bvrxO3ixXpZErdNopTSwyI2aWtAIKAn2gPd+iMnBzp2hOxsqqqrye7aNaNbggghhBCi9cWdtAW49tprOeOMM5g3bx5r166lsLCQESNG0KtXr0THJ4TIENGelRs3Ss/Ktuikk3TSFvSEZDfc4Gw8yTR3rm4JEgrVn2QsEtHFjCtWZH7SWohMpCyLyI8/Yni9uHfYwelwmsTdrRuGYRD+5Rddcbv99pK4rUNFIqjKSqyNGzHWrtVv3FVVqEgEqKkcj7YzKCysrZ6tm5xVto3asEG+2AghhBAi4ZqVtAXo0aMH55xzTiJjEUIIkaGOOQZuvFH3tX3pJbj2Wt3OL9NYlq6wDYX05Htr18a2+Xz6/LrrdOW5/L4XIr1Yy5albB/bLXF17QoQS9zusEPbS9zaNgQCWOEwKhjErqxEVVSgQiFAV9caSkFeHnTsiJGTo5O10tpACCGEEA5qdtK2oqKCX3/9laqqqgbbdt999xYFJYQQIrN06ACHHgpvvAHFxfDeezpxmWk+/1y3RPD7detDpWLb2rfXSd2lS/X19t7buTiFEHEqLsZaswbvgAEp28d2S1xdu4JhEP75Z5247dcvI5ORSil91Kxua4Oak2lZRHw+XNnZGDk5mEVFmDk5GDk52D4flWVlmG53WiXkhRBCCJHZ4k7arl+/nrFjx/LGG2802KaUwjAMLMtKSHBCCCEyx4kn6qQtwAsvZGbSdt06nZg1TSgvj62vmZsJ0NvXrXMmPiFEMwSDmCtX4urZEzPF+9huiatLF524/eknnbjt3z+tE7cqHG6YnA0GY60N3G5dLduuHXTqhJ2VRVa3brijwx7q3pb8dhFCCCFECoo7aXv++efz3nvvMX78eAYMGEBWVlYy4hJCCJFh/v536NxZtwz43/90xW1hodNRJVZRkU7QlpXFqmwNI9bb1rL09qIi52IUQjSdsixYsgSysnBlQD9YV+fO9RO3Awak/P+kalobbHpS1dUAGKapk7PZ2ZCfr/vO+v2QlRX73ywLIhGZKEwIIYQQaSXupO17773HPffcw9ixY5MRjxBCiAzldsPxx8PDD+tJuV5+Gc47z+moEmuPPSA/H1atiiVqo+dK6VxDv376ekKINLBqFVRVYffvnzHD5l1FRTpxu2hRLHEbHQrgIKWU7iuzaYK2qkpvAwyfTydki4owohOE+XwpEb8QQgghRKLFnbTNycmhV69eyYhFCCFEhhs9WidtAWbPhrFjY0nNTFBcrBPShqGTtKapz5WCjRvB64VbbpFJyIRIB6q4GPXnn7DttjpRmEFcnTrBjjsSXrQI9dNPeFo7cVtdrScB27S1QU2bAsPt1gnZ9u2hWzddPZudrdcLIYQQQrQRcX/zOf3003nxxRc55JBDkhGPEEKIDNa3LwweDF9/DT/9BN9/D7vu6nRUiaEUXHmlnqS8QwedmN2wIZa07ddPJ2xHjXI6UiHE1qhgEJYtwygsRBUV6eH1GcbVqRPstBPhH38kvGgRnh13rE3cqrqzKLaAsixUZSWqshK7shJr40bM4mKwbZRh6PuLtjMoLIy1NvB4Ur5tgxBCCCFEssWdtL3llls455xzOOaYYzjssMPIz89vcJ1jjz02IcEJIYTIPKNH66Qt6GrbTEnavvoqvPOOvtyzJ7z3Huy1F6xbZ1NUZPLll1JhK1LU3/6mZ87Ly3M6kpSgbBsWL4asLOjTJ7OGA2zCVVgIO+9M+IcfqP7uO8y8PKzVq7FWraLaMHD36oWrZ8+tVrgqpVCBQL0EraqoQFVV1V7HqOk7q4qKIC8PIy9PtzbI4MdXCCGEEKIl4k7arlixgs8//5zFixfz2muvNdhuGAZWBlYjCCGESIwjj4RJk3TrwldegRtu0LmRdLZ+PUycGFu+4w4oKIDcXN0WITdXErYihV10kdMRpJaVKyEYhF120cnKDP9e6yooQO24I6F33wWPB7N9e4z27VGRCJFVq7BKSsgaOBDD7dYVuNXV2BUV9RO0gYAeZgAYWVkYOTmYhYWYOTkYubkYfj+Gy4VlWajSUnC7M6ZHsBBCCCFEssSdtD3vvPMoKyvjvvvuY8CAAWSl+y9tIYQQrapdO90i4OWX4a+/YN48OOIIp6NqmYkT9f8COik9cqSj4Qghminax9bo0wcjJ8fpcFpPRQVGx45gWbg6d8bVqxeGz4e1YgXW2rWEPv0UMzdXJ2ojEf03LhdmTg5mXh5Gly46QZuTgyG/DYQQQgghEiLupO3nn3/OjBkzOPnkk5MRjxBCiDZg9GidtAXdIiGdk7ZvvqlPAPn5cOutzsYjhGgeFQzC8uUYhYXQubPT4bQq688/MX0+3H36oCIRVHk5mCZmu3ZY69djVVTg2nlnzPx8XUWbkyOtDYQQQgghkizupG3nzp3p0KFDEkIRQgjRVuyzD3TvDr//Du+/D2vXpmeOZMMGuPba2PKtt+q2CEKI9KJsG5YsAbcb+vRpU8lIpRQqFALA1bkzqroaKxTCLCjA6NwZ66+/MAwD9447tqnHRQghhBDCaWa8f3DhhRfy2GOPJSMWIYQQbYRpwokn6su2Df/+t7PxNNekSVBcrC+PGKFbIwiRdi69FM46S5+3VStXQiAAO+yw1Um3Mo1hGBheLwB2WZnuSZudjen3o4LB2u2SsBVCCCGEaF1xfys1TZPvvvuO3XffnVGjRpGfn19vu2EYXNqWv/QLIYRokhNOgHvv1ZdfeAHGjUuvSdrfeSfW4qFdOz35WDrFL0St0lIoKXE6CseokpJYH9vcXKfDcYSrSxciq1YRWbIEV69eqHBYt0VYtap2uxBxCQQarrNtUEqfb7rd72+duIQQQog0EnfS9sorr6y9vHDhwgbbJWkrhBCiKbbdFvbcEz77DJYtg2++gcGDnY6qaTZuhDofh0yenJ7tHYRo61QwCMuWtck+tnW5evbEKilBVVQQ/vln7PJyPcGY242Rm4urZ0+nQxRpJmfgwAbrjOJisG2MkpIG2ysXL26dwCSZLIQQIo3EnbRdsWJFMuIQQgjRBo0erZO2oCckS5ek7Q036D68AAccoKuGhRDppS33sd2U4XaTNXAg1urVRFatQpWVYXTsiLtXL1w9e7a5lhEiSfx+nRx18LWWsslkIYQQohFxfwPr1atXMuIQQgjRBh1+OEycqAtbXnsNbroJsrOdjmrL3n9fJ5gBcnPhrrukLYIQaWnVKv3ms/POkpREJ27dvXtjFhailCJr8GDMvDynwxJpqrKREZkpKwWSyUIIIURj4v6G6nK5+PTTTxk6dGiDbV9//TVDhw7FsqyEBCeEECKz5eTAEUfoJGh5Obz1Fhx7rNNRbV55OVx+eWz5hhugWzfn4hFCNI8qKUGtWYPRu3eb7WO7JW256lgkSIq2FUirZLIQQog2z4z3D5RSm91m27Z8yRNCCBGX0aNjl194wbk4muLWW+GPP/TlffeFU05xNh4hRPxUVZXuY1tQADLBlhBti98f30kIIYRwUNxJW9j80fevv/6a9u3btyggIYQQbcsee+hJyQA++QR++83RcDbrk0/g6af1Zb8f7r5bRlIKkW6UbcPixbqP7XbbSbGBEEIIIYRIWU1qj3D//fdz//33Azphe/TRR+P1eutdJxgMsm7dOo4//vjERymEECJjGQaceKLuDasUvPgiXHqp01HVFwjUb4swcSJss41z8Qghmkn62AohhBBCiDTRpG+rRUVF7LTTTgCsXLmSPn360KFDh3rX8Xq97LLLLowfPz7hQQohhMhsJ5wA//qXTtrOmQPjx4PZrLEgyXHHHTrXA7oy+MwznY1HCBE/tWGD9LEVQgghhBBpo0lJ25NPPpmTTz4ZgOHDh/PII4/Qv3//pAYmhBCi7ejeXfeI/egjnRz9/HPYay+no9K+/BJmzNCXvV6YMiW1EspCtNiYMRAK6R08Q6mqKli6VPrYCiGEEEKItBH3uLD58+cnIw4hhBBt3Ekn6aTt/7d33/FRVfn/x99T0nuDJAgB6VKkSBFXKSqIigULLLvYVlFZ1/4TBRVQsevy3VUW24K6rrqui64uFlRAVFBAsAAiKB1CQgKppM09vz/GGTNMCOkzSV7PxyOPzNx758577j1zGD5zcq7kHm0bDEXbkhL3VA2ea3BOmyZ16hTYTECDGz480AkaFfPYAgAAoDmq81ihvLw8rV69Wp9++qnfT2ObN2+eOnXqpPDwcA0cOFArPP/LP4rly5dr4MCBCg8P1/HHH6/58+c3ekYAQO2MHSvFxrpvv/OOVFQU2DyS+2JjP//svj1ggHTNNYHNA6AOdu50z2PbtSvz2AIAAKDZqPUn14qKCl133XV66aWX5HK5qtzmaMsbwuuvv66bb75Z8+bN0ymnnKJnnnlGY8eO1caNG9WhiqvCbNu2TWeffbauueYa/eMf/9Dnn3+uqVOnKiUlRRdddFGj5QQA1E54uHT++dLLL7vrK+++K02YELg869ZJnu/4QkLc0yI4HIHLA6D2TG6uzN69snXsKFtMTKDjAAAAADVW65G2f/7zn/XOO+/o73//u4wxeuqpp/TMM8/opJNOUteuXfXee+81Rk6vJ598Un/4wx909dVXq2fPnpo7d67at2+vv/3tb1VuP3/+fHXo0EFz585Vz549dfXVV+uqq67S448/3qg5AQC1d+mlv95+7bXA5Sgrk269VbIs9/3bb5e6dQtcHqBR7dnjHo26Z0+gkzQo7zy2iYlSWlqg4wAAAAC1Uuui7csvv6wZM2Z4L0w2ZMgQXX311fryyy+VkZHRqHPelpWVae3atRo9erTP8tGjR+uLL76o8jErV670237MmDFas2aNysvLGy0rAKD2BgyQunRx3/7yS2n79sDkmDtX2rzZfbtPH+m66wKTA2gSM2ZIf/yj+3cLYSxL2rKFeWwBAADQbNV6eoSff/5ZJ554ouy/XDq7pKTEu+66667TTTfdpIceeqjhElZy4MABuVwutW3b1md527ZtlZmZWeVjMjMzq9y+oqJCBw4cUFoVIy9KS0tVWlrqvZ+fny9JysnJUVlZmXd5aGiooqOj5XK5lJeX57efxMRE7+MrKip81kVFRSkkJESlpaXKycnx+c9ESEiIYmJiZIzRwYMH/fYbHx8vu92ugoICv8JzZGSkwsPDVVZWpsLCQp91DodDcXFxkqSDBw/KeK6s8wv3OqeMMaqosHTgwCHvuvDwcEVGRqq8vFwFBQU+j7Pb7YqPj5ckHTp0SJZnaNovYmJiFBISouLiYp/2IklhYWGKioryOYbFxe51NptNCQkJkqTycksul01lZUY7d7pzRUdHKzQ0VHZ7iYo9DzriGFqWpUOHDulICQkJstls1R7D0tJSFR0xqabT6VTsL5Nu5ubmqqIiXpZlU0WF0YEDhxQXFyeHw6HCwkKftiJJERERioiIqPIYVj43VR3D2NhYOZ3Oao9hRUWFt61WzmVZ7vdqXl6e39QlnmN4+PBhHT582Gedp30f6xgerX2HhYX5HcOKijgZY5Mx7mlUqmvf1R3DurRvzzEsKiryeX9Lv7bvysfQo3L7ruoYetp3dcewLn2EZSVKssmyjA4cyPVZ19L7iHPPDdeTT0ZIkl5+uUIzZoRUeQwr9xEul+XzXpR+bd8lJbXrIzZtcuivf43/5ZgY3XtvnvLyfj3vtesj4n7JVaEDB/KCoo+o3D/k5OR5j2Gg+whPLpfL3W8dq303VR9RUREvY+ySbCorKw+aPsJzDKtr3zXtI6JLSmQvK5NVUiKruLhefYSxLJWXl+vgwYOyVep/6ttH2O12HT58WBUVFd7PoJ5jGBkZKZfL5bNf5549ch44oPCBAyWHQ/lVnJvIyEhvH3Hk+yYkJERRUVHe9u1yuWRZlve5G+pzhL24WIW5udIvbS4Y+ggVFXlz2crKGrSPsCxL+fn5cjgc3mNYWFjo174jIiK8fcSR+3U6nYqOjpYxpsr3TWxsrOx2u4qKirznxrIsuVwub6Yj27dlWSosLFRCQoIsy1JeXp5f+46OjvYew8rnxrIsHT58WJZlqaKiwu99Y7PZvOcmPz/f59xYlqWwsDBZlqWSkhKf1+rZb2xsbJXnXJL3fVPVMfS077ocQ8+6/Px8v3MeFhYmY4xKS0v92pLD4VDML9OQVHUMY2Ji5HA4/I6hZ78RERHVHkNP3srvRc9+a9tHVN6vJBUUFNSpj3C5XN73XOXn9bTvvLw8HTp0SA6Hw7ve077Lysr8+m/PuZFU5b+tnmNYuX17hIeHKzw83NteKvdbR/YRnve7J5enfR8+fNjvc7LnGHrOjed9LPn2PVUdQ8//eT3H0PNetCxL4eHhzaKP8GQKDQ31vtba9BFSzdq31Dz6CMuyFBkZ6e03j2yHgeojPJ97cnNz/b6orW8f4Xmtknwe2xB9RDB+jsjNzVVeXp5Pv1WbPqKqYyg1TB9RWV3qEZWPYaD/r1HVe7YqtS7aRkVFqaysTDabTYmJidqxY4eGDRvmfQE5OTm13WWtHfkmNMZUO4Kiqu2rWu7x0EMPafbs2X7L33vvPUVERHjvp6en68QTT1RRUVGVF2AbO3asJPdo3yMbWd++fZWWlqatW7dq586dPuuSk5M1aNAglZeX66OPPvLb76hRoxQWFqa1a9cqKyvLZ12PHj3UqVMn7du3T+vXr/dZFxsbq1NOOUWS9MEHH/h9oP/Nb36j8vKOKiuzlJdXqHfeece77vjjj1f37t2Vk5Ojr776yudx4eHhGjlypCRp6dKlfh3W4MGDlZSUpM2bN+tnzxV9fnHcccepT58+Kigo0GeffSZJuuUW9ySWNpsUFuY+VwcO2GVZUk6OTX37RkqSQkIccjiMFi36Rj/88IPPftu0aaOBAweqtLRUn3zyid8xPOOMMxQSEqLVq1frwIEDPutOOOEEZWRkaM+ePfr222991sXHx+vkXy5p/9577ykv7zyVlEQoL++w3nnnHZ122mmKiorSN998o7179/o8tkuXLuratauys7O1Zs0an3WRkZEa/svVuz/++GO/zmHo0KFKSEjQpk2btP2IoYcdOnRQr169lJeX5x1x7smVn39YWVnufwRWrFjh17EMGDBAbdu21U8//aQff/zRZ11qaqr69++vw4cPa9myZX7HcPTo0XI4HPryyy+Vm+tbVOzdu7fat2+vXbt26fvvv/cuz8s7T+XlkaqosJSZma0PP/zQb78jRoxQRESE1q1b5/dlTLdu3dS5c2ft379fX3/9tc+66OhonXrqqZKkJUuW+HXcw4YNU1xcnDZs2OD3nuvYsaN69uypgwcPatWqVT7rQkNDdfrpp0tyX9TwyA/XJ510klJSUrRlyxZt3brVZ119+oiSkgmyrDAdPlzi816UWn4fERoarrKy82RZNr38coWuuuqgiot/7SM87Ha7xowZI0kqKAhTSUmY970oSf369VNaWpq2bdtW4z6iosKmuXPPVFlZrGw26ayzftCPP36lym+P2vYRZWXhyssrCZo+onK/tXjxYp155pmSAt9HeHIVFpYpK6tELpcrKPoId78VrfJyu3766aeg6SP69u2rdu3aaceOHdq4caPPutr2Eb/ZvVthhYUqLSrSgW++qVcfEW2zKWv/fm386COVVJoEur59REJCgjZs2KDdu3f7fH5LS0tTz549VVhY6N1vdHm5OhQXa39EhE7s00fKzdVXX33l17579eqltm3baufOnX7nJjk5WX379lVZWZlWrFghY4yclS5i1hCfI5YuWaJOBQXatnev91gFQx8R7nJ5c1WEhTV4H1FRUSGbzaaRI0fKbrfr66+/9mvfPXr0UHp6uvbu3evXf8fHx2vAgAGyLKvKvmfYsGEKDw/Xd999p+zsbEnuz/7GGPXs2VNdunSpso8IDQ3VkCFD5HA4tHz5cr//WA4aNEgxMTHavHmz9lSaSsQYo5SUFIWFhamgoEBr1671eVxISIi371m5cqVPccQYo969e0uSfvrpJ792mJiYqF69eqm0tNSv75Hc72VJWrNmjd8XSieccIJSU1O1e/duv3OTmJiofv36qaKiosq+5+STT5bT6dSPP/7oPYYe3bt3V3Jysg4cOKBNmzb5rIuOjtbgwYMlud/LR/6HdfDgwYqOjtamTZu0b98+n3UZGRnq3LmzDh48qHXr1vmsCwsL0ymnnCKXy6UvvvjC79zUto/w8LRDSXXuIw4fPqzPP//cp3+Qfu0jvvrqK+3fv182m82bq1u3bjruuOOUmZnp13/HxsbqpJNOkqQq/w8zdOhQRUZGasOGDdq/f7/Puo4dO+r4449XTk6O1q9f79NvVdVHeN6LNptNAwcOVFxcnLZs2aJdu3b57Lddu3bq3r27CgoKtHr16l++vK+Q0+mU0+n07nfVqlV+/wb26dNHKSkp2r59u37++Wfve9HpdDarPqKiokJRUVHe/rs2fYQktW/fXl27dlVeXl6z7yOMMRo6dKhcLpfWrVvn93+NQPURQ4cOlWVZWrNmjV9Rsb59hGVZWr9+vUpLS30e2xB9RDB+jvjoo490+PBhn36rNn1EZQ6Ho8H7CI+61CMkd/seMmRIwP+vceSXJUdjM0e+U45h+PDh+t3vfqcpU6bovPPO0759+7Ro0SKFhoZq4sSJOnTokF/4hlJWVqbIyEi98cYbuvDCC73Lb7rpJq1fv17Lly/3e8xpp52m/v376//+7/+8yxYtWqRLL71UxcXFCgkJ8XtMVSNt27dvr59//tn7zZDUMCNt9+zZo8jIyKAZaTtkiFP79hmlpFj65JND3nVNOdK2d++EX9baZLe7j0tRkZEx7kJuRISn6G6XzSZt3Xq4SUbaFhf7f7N19tnxys62KSXFaPFi35G2TmfgRtqOGhWvrCyb2rQxWr8+eEbajhoVp/37bUpPd2jNGisoRtFJwTnS9owzEr3n8KOPgmekbVP1EVOnRuvTT0Nks9n06qvSKadUP9K2f39L+/e7j5cnV11G2s6fH66nnoqQ3W5Xz57S66/nS6r7t9+jRsUpM9Om1FSjTz4JjpG2lfuHpUuDZ6StJ1fbtkbr1gXPSNtRo+KVnW1XWppNq1a10JG2N9wg+8GDshISZP397/UbaVtYqJxly+Ts31+2X0aLSQ0z0jYzM/PYI2TKyhS2ebOsqChVHH+84n7Zb11H0VUeaesZnSU10AiZXbtk37BBVq9eUlSU9xg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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "=== Significance Summary ===\n", + "Pre-treatment significant: 12/14\n", + "Post-treatment significant: 14/18\n" + ] + } + ], + "source": [ + "def event_study(df, treatment_date='2021-05-15'):\n", + " \"\"\"\n", + " Event study analysis for difference-in-differences\n", + " \n", + " Parameters:\n", + " - df: DataFrame with columns [date, city, treated, downloads, post]\n", + " - treatment_date: The event date when treatment starts (default: '2021-05-15')\n", + " \"\"\"\n", + " df_es = df.copy()\n", + " \n", + " # Convert date to datetime if needed\n", + " if not pd.api.types.is_datetime64_any_dtype(df_es['date']):\n", + " df_es['date'] = pd.to_datetime(df_es['date'])\n", + " \n", + " treatment_date = pd.Timestamp(treatment_date)\n", + " \n", + " # Create relative time (days from treatment date)\n", + " df_es['rel_time'] = (df_es['date'] - treatment_date).dt.days\n", + " \n", + " # Set reference period as -1 (2021-05-14, day before treatment)\n", + " reference_period = -1\n", + " \n", + " # Create dummy variables for each relative time period (excluding reference)\n", + " time_dummies = pd.get_dummies(df_es['rel_time'], prefix='t', dtype=int)\n", + " \n", + " if f't_{reference_period}' in time_dummies.columns:\n", + " time_dummies = time_dummies.drop(f't_{reference_period}', axis=1)\n", + " \n", + " # Interact time dummies with treatment status\n", + " # Use Q() to escape variable names with special characters\n", + " for col in time_dummies.columns:\n", + " # Create interaction variable in dataframe\n", + " var_name = f'treated_x_{col}'\n", + " df_es[var_name] = df_es['treated'] * time_dummies[col]\n", + " \n", + " # Build formula using Q() for variable names with negative numbers\n", + " interaction_terms = []\n", + " for col in time_dummies.columns:\n", + " var_name = f'treated_x_{col}'\n", + " # Use Q() to quote variable names\n", + " interaction_terms.append(f'Q(\"{var_name}\")')\n", + " \n", + " formula = f\"downloads ~ {' + '.join(interaction_terms)} + C(city) + C(date)\"\n", + " \n", + " # Fit model with clustered standard errors\n", + " model = smf.ols(formula, data=df_es).fit(\n", + " cov_type='cluster',\n", + " cov_kwds={'groups': df_es['city']}\n", + " )\n", + " \n", + " # Extract results\n", + " results = []\n", + " for param_name in model.params.index:\n", + " if param_name.startswith('Q(\"treated_x_t_'):\n", + " # Extract rel_time from parameter name\n", + " rel_time_str = param_name.replace('Q(\"treated_x_t_', '').replace('\")', '')\n", + " rel_time = int(rel_time_str)\n", + " ci = model.conf_int().loc[param_name]\n", + " \n", + " results.append({\n", + " 'rel_time': rel_time,\n", + " 'att': model.params[param_name],\n", + " 'ci_low': ci[0],\n", + " 'ci_up': ci[1],\n", + " 'se': model.bse[param_name],\n", + " 'pvalue': model.pvalues[param_name]\n", + " })\n", + " \n", + " # Add reference period (normalized to 0)\n", + " results.append({\n", + " 'rel_time': reference_period,\n", + " 'att': 0.0,\n", + " 'ci_low': 0.0,\n", + " 'ci_up': 0.0,\n", + " 'se': 0.0,\n", + " 'pvalue': np.nan\n", + " })\n", + " \n", + " results_df = pd.DataFrame(results).sort_values('rel_time').reset_index(drop=True)\n", + " \n", + " return results_df, model\n", + "\n", + "\n", + "# 사용 예시\n", + "results_df, model = event_study(mkt_data, treatment_date='2021-05-15')\n", + "\n", + "\n", + "\n", + "# 결과 확인\n", + "print(\"=== Pre-treatment periods (2021-05-01 ~ 2021-05-14) ===\")\n", + "print(results_df[results_df['rel_time'] < 0])\n", + "\n", + "print(\"\\n=== Post-treatment periods (2021-05-15 onwards) ===\")\n", + "print(results_df[results_df['rel_time'] >= 0])\n", + "\n", + "\n", + "def plot_event_study(results_df, treatment_date='2021-05-15', alpha_level=0.05):\n", + " fig, ax = plt.subplots(figsize=(14, 7))\n", + " \n", + " # Reference lines\n", + " ax.axhline(y=0, color='gray', linestyle='--', linewidth=1, alpha=0.7)\n", + " ax.axvline(x=-0.5, color='red', linestyle='--', linewidth=2, \n", + " label=f'Treatment Start ({treatment_date})', alpha=0.7)\n", + " \n", + " # Split by significance\n", + " pre_treat = results_df[results_df['rel_time'] < 0].copy()\n", + " post_treat = results_df[results_df['rel_time'] >= 0].copy()\n", + " \n", + " # Pre-treatment - significant vs non-significant\n", + " pre_sig = pre_treat[pre_treat['pvalue'] > alpha_level]\n", + " pre_nonsig = pre_treat[pre_treat['pvalue'] <= alpha_level]\n", + " \n", + " # Post-treatment - significant vs non-significant \n", + " post_sig = post_treat[post_treat['pvalue'] < alpha_level]\n", + " post_nonsig = post_treat[post_treat['pvalue'] >= alpha_level]\n", + " \n", + " # Plot non-significant (lighter color, hollow markers)\n", + " if len(pre_nonsig) > 0:\n", + " ax.errorbar(pre_nonsig['rel_time'], pre_nonsig['att'],\n", + " yerr=[pre_nonsig['att'] - pre_nonsig['ci_low'],\n", + " pre_nonsig['ci_up'] - pre_nonsig['att']],\n", + " fmt='o-', color='lightblue', capsize=4, capthick=1.5,\n", + " markersize=5, alpha=0.5, linewidth=1,\n", + " markerfacecolor='white', markeredgewidth=1.5)\n", + " \n", + " if len(post_nonsig) > 0:\n", + " ax.errorbar(post_nonsig['rel_time'], post_nonsig['att'],\n", + " yerr=[post_nonsig['att'] - post_nonsig['ci_low'],\n", + " post_nonsig['ci_up'] - post_nonsig['att']],\n", + " fmt='o-', color='lightcoral', capsize=4, capthick=1.5,\n", + " markersize=5, alpha=0.5, linewidth=1,\n", + " markerfacecolor='white', markeredgewidth=1.5)\n", + " \n", + " # Plot significant (solid color, filled markers)\n", + " if len(pre_sig) > 0:\n", + " ax.errorbar(pre_sig['rel_time'], pre_sig['att'],\n", + " yerr=[pre_sig['att'] - pre_sig['ci_low'],\n", + " pre_sig['ci_up'] - pre_sig['att']],\n", + " fmt='o-', color='blue', capsize=4, capthick=1.5,\n", + " label='Pre-treatment (p<0.1)', markersize=6, alpha=0.9,\n", + " linewidth=2)\n", + " \n", + " if len(post_sig) > 0:\n", + " ax.errorbar(post_sig['rel_time'], post_sig['att'],\n", + " yerr=[post_sig['att'] - post_sig['ci_low'],\n", + " post_sig['ci_up'] - post_sig['att']],\n", + " fmt='o-', color='red', capsize=4, capthick=1.5,\n", + " label='Post-treatment (p<0.1)', markersize=6, alpha=0.9,\n", + " linewidth=2)\n", + " \n", + " # Add gray background for significant post-treatment periods\n", + " if len(post_sig) > 0:\n", + " for _, row in post_sig.iterrows():\n", + " ax.axvspan(row['rel_time']-0.4, row['rel_time']+0.4, \n", + " alpha=0.1, color='gray', zorder=0)\n", + " \n", + " # Legend\n", + " from matplotlib.patches import Patch\n", + " custom_lines = [\n", + " plt.Line2D([0], [0], color='blue', marker='o', linewidth=2, \n", + " markersize=6, label='Pre-treatment (p<0.1)'),\n", + " plt.Line2D([0], [0], color='red', marker='o', linewidth=2, \n", + " markersize=6, label='Post-treatment (p<0.1)'),\n", + " plt.Line2D([0], [0], color='gray', marker='o', linewidth=1, \n", + " markersize=5, markerfacecolor='white', markeredgewidth=1.5,\n", + " label='Not significant (p≥0.1)', alpha=0.5),\n", + " Patch(facecolor='gray', alpha=0.1, label='Significant period')\n", + " ]\n", + " ax.legend(handles=custom_lines, fontsize=10, loc='upper left')\n", + " \n", + " ax.set_xlabel('Days Relative to Treatment (2021-05-15)', fontsize=12)\n", + " ax.set_ylabel('Treatment Effect on Downloads', fontsize=12)\n", + " ax.set_title('Event Study: Dynamic Treatment Effects (Significance Highlighted)', \n", + " fontsize=14, fontweight='bold')\n", + " ax.grid(True, alpha=0.3)\n", + " \n", + " plt.tight_layout()\n", + " plt.show()\n", + " \n", + " # Print summary\n", + " print(f\"\\n=== Significance Summary ===\")\n", + " print(f\"Pre-treatment significant: {len(pre_sig)}/{len(pre_treat)}\")\n", + " print(f\"Post-treatment significant: {len(post_sig)}/{len(post_treat)}\")\n", + "\n", + "plot_event_study(results_df, treatment_date='2021-05-15')" ] }, { "cell_type": "code", - "execution_count": null, - "id": "3b6d7828", + "execution_count": 76, + "id": "187f9ba7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "================== DoubleMLData Object ==================\n", - "\n", - "------------------ Data summary ------------------\n", - "Outcome variable: y\n", - "Treatment variable(s): ['d']\n", - "Covariates: ['X1', 'X2', 'X3', 'X4']\n", - "Instrument variable(s): None\n", - "No. Observations: 1000\n", "\n", - "------------------ DataFrame info ------------------\n", - "\n", - "RangeIndex: 1000 entries, 0 to 999\n", - "Columns: 6 entries, X1 to d\n", - "dtypes: float64(6)\n", - "memory usage: 47.0 KB\n", - "\n", - "ATT estimate: [3.05836115]\n", - " 2.5 % 97.5 %\n", - "d 2.768038 3.348684\n" + "=== 통계적 유의성 ===\n", + "유의한 post-treatment 효과: 14/18 시점\n", + "유의한 시점들의 평균 ATT: 1.348\n" ] } ], "source": [ - "\n", - "ml_g = LGBMRegressor(n_estimators=50, num_leaves=5, verbose=-1)\n", - "ml_m = LGBMClassifier(n_estimators=50, num_leaves=5, verbose=-1)\n" - ] - }, - { - "cell_type": "markdown", - "id": "0f1d1714", - "metadata": {}, - "source": [ - "DoubleMLDID 추정" + "print(\"\\n=== 통계적 유의성 ===\")\n", + "post_treatment = results_df[results_df['rel_time'] >= 0].copy()\n", + "sig_post = post_treatment[post_treatment['pvalue'] < 0.05]\n", + "print(f\"유의한 post-treatment 효과: {len(sig_post)}/{len(post_treatment)} 시점\")\n", + "print(f\"유의한 시점들의 평균 ATT: {sig_post['att'].mean():.3f}\")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "12081d6e", + "execution_count": 174, + "id": "d0fa8ce2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "ATT estimate: [3.1189311]\n", - " 2.5 % 97.5 %\n", - "d 2.822394 3.415468\n" + "============================================================\n", + "PRE-TREATMENT PARALLEL TRENDS TEST (F-test)\n", + "============================================================\n", + "H0: All pre-treatment effects = 0\n", + "Number of pre-treatment periods tested: 13\n", + "\n", + "F-statistic: 4.7658\n", + "p-value: 0.0000\n", + "\n", + "✗ Reject H0 (p=0.0000 < 0.05)\n", + " → Pre-treatment parallel trends assumption is violated\n", + "============================================================\n", + "\n", + "=== Individual Pre-treatment Coefficients ===\n", + " rel_time att pvalue\n", + " -14 0.317460 0.414864\n", + " -13 0.642857 0.052014\n", + " -12 0.865079 0.057045\n", + " -11 0.452381 0.256666\n", + " -10 0.269841 0.562187\n", + " -9 0.857143 0.002710\n", + " -8 0.317460 0.519038\n", + " -7 0.515873 0.310327\n", + " -6 -0.230159 0.666800\n", + " -5 0.198413 0.574842\n", + " -4 0.595238 0.289147\n", + " -3 0.301587 0.395018\n", + " -2 0.650794 0.098023\n", + " -1 0.000000 NaN\n" ] } ], "source": [ + "def test_pretrend(model, results_df):\n", + " \"\"\"\n", + " F-test for pre-treatment parallel trends\n", + " Tests joint hypothesis that all pre-treatment coefficients = 0\n", + " \"\"\"\n", + " # Get pre-treatment interaction terms\n", + " pre_periods = results_df[results_df['rel_time'] < 0]['rel_time'].values\n", + " \n", + " # Build hypothesis string for F-test\n", + " hypotheses = []\n", + " for rel_time in pre_periods:\n", + " if rel_time != -1: # Exclude reference period\n", + " param_name = f'Q(\"treated_x_t_{rel_time}\")'\n", + " hypotheses.append(f'{param_name} = 0')\n", + " \n", + " hypothesis_str = ', '.join(hypotheses)\n", + " \n", + " # Conduct F-test\n", + " f_test = model.f_test(hypothesis_str)\n", + " \n", + " print(\"=\" * 60)\n", + " print(\"PRE-TREATMENT PARALLEL TRENDS TEST (F-test)\")\n", + " print(\"=\" * 60)\n", + " print(f\"H0: All pre-treatment effects = 0\")\n", + " print(f\"Number of pre-treatment periods tested: {len(hypotheses)}\")\n", + " print(f\"\\nF-statistic: {f_test.fvalue:.4f}\") # 인덱싱 제거\n", + " print(f\"p-value: {f_test.pvalue:.4f}\")\n", + " \n", + " if f_test.pvalue > 0.05:\n", + " print(f\"\\n✓ Cannot reject H0 (p={f_test.pvalue:.4f} > 0.05)\")\n", + " print(\" → Pre-treatment parallel trends assumption is satisfied\")\n", + " else:\n", + " print(f\"\\n✗ Reject H0 (p={f_test.pvalue:.4f} < 0.05)\")\n", + " print(\" → Pre-treatment parallel trends assumption is violated\")\n", + " print(\"=\" * 60)\n", + " \n", + " return f_test\n", "\n", - "dml_did = DoubleMLDID(dml_data,\n", - " ml_g=ml_g,\n", - " ml_m=ml_m,\n", - " score='observational',\n", - " n_folds=5)\n", - "dml_did.fit()\n", "\n", - "print(\"ATT estimate:\", dml_did.coef)\n", - "print(dml_did.confint(level=0.95))\n", - "\n" + "# 사용\n", + "results_df, model = event_study(mkt_data, treatment_date='2021-05-15')\n", + "f_test_result = test_pretrend(model, results_df)\n", + "\n", + "# 개별 계수도 확인\n", + "print(\"\\n=== Individual Pre-treatment Coefficients ===\")\n", + "pre_results = results_df[results_df['rel_time'] < 0].copy()\n", + "print(pre_results[['rel_time', 'att', 'pvalue']].to_string(index=False))" ] }, { "cell_type": "markdown", - "id": "23cde0a4", + "id": "fabc7e46", "metadata": {}, "source": [ - "Coverage 시뮬레이션" - ] - }, - { - "cell_type": "code", - "execution_count": 216, - "id": "e68e211d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration: 0/200\n", - "Iteration: 20/200\n", - "Iteration: 40/200\n", - "Iteration: 60/200\n", - "Iteration: 80/200\n", - "Iteration: 100/200\n", - "Iteration: 120/200\n", - "Iteration: 140/200\n", - "Iteration: 160/200\n", - "Iteration: 180/200\n", - "results from coverage simulation:\n", - "True ATT: 3.0\n", - "Estimated ATT: 2.991261797700492\n", - "Coverage: 0.91\n", - "Average CI length: 0.6293062710727478\n" - ] - } - ], - "source": [ - "\n", - "\n", - "n_rep = 200\n", - "ATTE_estimates = np.full((n_rep), np.nan)\n", - "coverage = np.full((n_rep), np.nan)\n", - "ci_length = np.full((n_rep), np.nan)\n", + "##### Event Study 결과 해석 \n", "\n", - "for i_rep in range(n_rep):\n", - " if (i_rep % int(n_rep/10)) == 0:\n", - " print(f'Iteration: {i_rep}/{n_rep}')\n", - " \n", - " data, true_att,_ = make_custom_did(n_obs=1000, n_time_periods=5, seed=i_rep)\n", - "\n", - " dml_data = did_to_dml_format(data)\n", - " \n", - " \n", - " dml_did = DoubleMLDID(dml_data, ml_g=ml_g, ml_m=ml_m, n_folds=5)\n", - " dml_did.fit()\n", + "T-검정 결과, 처치 이전 기간(Day –14 ~ –1)의 대부분 시점에서 신뢰구간이 0을 포함하였으며, 두 집단 간 통계적으로 유의한 차이가 관찰되지 않았습니다. 이는 평행추세 가정(parallel trends assumption) 이 충족되었음을 의미하며, DiD 분석의 인과추론 타당성이 확보된 것으로 보입니다.\n", "\n", - " ATTE_estimates[i_rep] = dml_did.coef.squeeze()\n", - " confint = dml_did.confint(level=0.95)\n", - " coverage[i_rep] = (confint['2.5 %'].iloc[0] <= true_att) & (true_att <= confint['97.5 %'].iloc[0])\n", - " ci_length[i_rep] = confint['97.5 %'].iloc[0] - confint['2.5 %'].iloc[0]\n", + "처치 효과는 즉각적으로 나타나지 않았습니다. 처치 직후(Day 0–3)에는 대부분의 시점에서 신뢰구간이 0을 포함해 통계적으로 유의하지 않았으나, 약 4일 후부터 유의한 양(+)의 효과가 발생하기 시작했습니다. 이는 정책이 인지되고 확산되는 데 일정한 시차가 존재함을 시사합니다. Day 4 이후에는 대부분의 시점에서 통계적으로 유의한 효과가 지속적으로 관찰되었으며, 평균적으로 다운로드 수를 약 1.2 ~ 1.5건 증가시키는 것으로 나타났습니다.\n", "\n", + "결론적으로, 처치는 다운로드 증가에 통계적으로 유의하고 실질적인 인과효과를 가지며, 그 효과는 일시적이지 않고 지속적으로 유지되었습니다. 다만 효과가 발현되기까지 약 4일의 시차가 존재하므로, 정책 평가 시에는 충분한 관찰 기간을 확보하는 것이 필요합니다.\n", "\n", - " \n", - "print(\"results from coverage simulation:\")\n", - "print(f'True ATT: {true_att}')\n", - "print(f'Estimated ATT: {np.mean(ATTE_estimates)}')\n", - "print(f'Coverage: {coverage.mean()}')\n", - "print(f'Average CI length: {ci_length.mean()}')" + "한편 F-검정 결과, 사전 13개 시점의 처치효과를 동시에 검정한 결과 F 통계량은 4.77, p-값은 0.0001 미만으로 나타나 평행추세 가정이 통계적으로 유의하게 위배되었습니다. 그러나 개별 t-검정으로 보면 14개 사전 시점 중 5% 유의수준에서 유의한 시점은 Day –9 (p = 0.003) 단 하나뿐이었고, Day –13 (p = 0.052) 과 Day –12 (p = 0.057) 는 경계선 수준이었으며, 나머지는 모두 비유의적이었습니다. 이는 F-검정이 여러 시점의 미세한 차이를 누적해 평가하기 때문에, 개별적으로는 문제가 적어 보이더라도 전체적으로는 평행추세 위반으로 판단될 수 있음을 의미합니다. " ] }, { - "cell_type": "code", - "execution_count": 215, - "id": "052565b9", + "cell_type": "markdown", + "id": "0b985fca", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "results from coverage simulation:\n", - "True ATT: 3.0\n", - "Estimated ATT: 2.991261797700492\n", - "Coverage: 0.91\n", - "Average CI length: 0.6293062710727478\n" - ] - } - ], "source": [ - "print(\"results from coverage simulation:\")\n", - "print(f'True ATT: {true_att}')\n", - "print(f'Estimated ATT: {np.mean(ATTE_estimates)}')\n", - "print(f'Coverage: {coverage.mean()}')\n", - "print(f'Average CI length: {ci_length.mean()}')" + "#### 3.9 DML을 이용한 DID\n", + "\n", + "- 공변량과 결과 변수, 공변량과 처치 변수 간의 복잡한 비선형 관계를 머신러닝 모델로 예측한 후, 이 잔차(residuals)를 사용하여 DiD 효과를 추정하는 방법입니다.\n", + "- 고차원적인 공변량을 유연하게 처리하고, 머신러닝의 예측력을 활용하여 잠재적인 편향을 줄입니다. 특히 이질적인 처치 효과를 다루는 데 강점이 있습니다.\n", + "- 유연성, 견고성, 고차원 데이터 처리 능력이 우수합니다.\n", + "- 다만, 모델 복잡성이 증가하고, 구현 및 해석이 어려울 수 있습니다." ] }, { "cell_type": "markdown", - "id": "124d75b8", + "id": "3d522a65", "metadata": {}, "source": [ - "본 시뮬레이션에서 설정된 진짜 ATT는 3.0이며, DoubleML-DID 추정량의 평균은 2.99로 거의 일치했습니다.\n", - "\n", - "또한, 95% 신뢰구간의 coverage는 약 91%로 나타났습니다. \n", - "\n", - "이는 신뢰구간이 다소 좁아 실제 모수를 포함하는 비율이 목표치(95%)보다 약간 낮다는 것을 의미합니다. \n", - "\n", - "즉, 추정이 다소 과신(overconfident) 되는 경향이 있습니다.\n", - "\n", - "그럼에도 불구하고, finite-sample 환경에서는 여전히 비교적 준수한 수준이며, 목표치인 95%에 근접한 결과입니다. \n", - "\n", - "따라서 DoubleML-DID 추정법은 반복 표본에서 신뢰할 만한 추정치와 적절한 불확실성 추정을 제공함을 확인할 수 있습니다." + " Data 생성" ] }, { "cell_type": "code", - "execution_count": 188, - "id": "cf32b307", + "execution_count": 119, + "id": "44baede5", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ + "from doubleml import DoubleMLData\n", "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", "\n", - "df_pa = pd.DataFrame(ATTE_estimates, columns=['Estimate'])\n", - "g = sns.kdeplot(df_pa, fill=True)\n", - "plt.show()" + "# region을 one-hot encoding (공변량으로 사용)\n", + "mkt_data_enc = pd.get_dummies(mkt_data_all, columns=['region'], drop_first=True)\n", + "\n", + "# DoubleMLData 구성\n", + "mkt_dml_data = DoubleMLData(\n", + " data=mkt_data_enc,\n", + " y_col='downloads',\n", + " d_cols='treated',\n", + " x_cols=['region_N', 'region_S', 'region_W', 'post']\n", + ")" ] }, { "cell_type": "markdown", - "id": "8867afe5", + "id": "dc414e35", "metadata": {}, "source": [ - "본 시뮬레이션에서 얻어진 ATT 추정치의 분포는 대체로 정규분포 형태를 보이며, 참값(3.0)을 중심으로 집중되어 있습니다. \n", - "\n", - "이는 DoubleML-DID 추정량이 점근적으로 정규분포에 수렴한다는 이론적 특성과 부합하며, 반복 표본에서도 편향 없이 안정적인 추정을 제공함을 시각적으로 확인할 수 있습니다." + "Learners 설정\n" ] }, { - "cell_type": "markdown", - "id": "a738a4c3", + "cell_type": "code", + "execution_count": 120, + "id": "3b6d7828", "metadata": {}, + "outputs": [], "source": [ - "사전 추세 검정하기" + "\n", + "ml_g = LGBMRegressor(n_estimators=50, num_leaves=5, verbose=-1)\n", + "ml_m = LGBMClassifier(n_estimators=50, num_leaves=5, verbose=-1)\n" ] }, { - "cell_type": "code", - "execution_count": 173, - "id": "f43a7643", + "cell_type": "markdown", + "id": "918e68d4", "metadata": {}, - "outputs": [], "source": [ - "n_estimators = 50\n", - "ml_g = LGBMRegressor(n_estimators=n_estimators, num_leaves=5, verbose=-1)\n", - "ml_m = LGBMClassifier(n_estimators=n_estimators, num_leaves=5, verbose=-1)" + "##### Canonical DML-DiD 추정" ] }, { "cell_type": "code", "execution_count": null, - "id": "23790ea8", + "id": "aff4394f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "======================================================================\n", + "Part 1: 전체 ATT 추정\n", + "======================================================================\n", + "\n", + "공변량 개수: 202\n", + "샘플 크기: 6400\n", + "처치군: 1376, 대조군: 5024\n", + "\n", + "======================================================================\n", + "추정 결과\n", + "======================================================================\n", + "ATT: 1.1148\n", + "표준오차: 0.1115\n", + "95% CI: [0.8962, 1.3333]\n", + "\n", + "True ATT: 1.7209\n", + "Bias: -0.6061\n" + ] + } + ], "source": [ - "n_time_periods=5\n", - "data, _,mu_means = make_custom_did(n_obs=1000, n_time_periods=5, seed=i_rep)\n", - "time_periods = (np.arange(2*n_time_periods) - n_time_periods)\n", "\n", - "df = pd.DataFrame(np.nan,\n", - " index=range(2*n_time_periods-1),\n", - " columns=['lower', 'effect', 'upper'])\n", - "df['time'] = time_periods[1:]\n", - "df[\"true effect\"] = mu_means[1:]\n", + "from doubleml import DoubleMLData, DoubleMLDID\n", + "from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n", + "import tqdm\n", + "\n", + "# Part 1: 전체 ATT 추정 \n", + "\n", + "\n", + "print(\"=\" * 70)\n", + "print(\"Part 1: 전체 ATT 추정\")\n", + "print(\"=\" * 70)\n", + "\n", + "# ① 범주형 변수 인코딩\n", + "mkt_data_enc = pd.get_dummies(mkt_data_all, \n", + " columns=['region', 'city'], \n", + " drop_first=True)\n", + "\n", + "# ② 공변량 선택 - post 제외! (DoubleMLDID가 자동으로 처리)\n", + "x_cols = [c for c in mkt_data_enc.columns \n", + " if c not in ['downloads', 'treated', 'tau', 'date', 'post']]\n", + "\n", + "print(f\"\\n공변량 개수: {len(x_cols)}\")\n", + "print(f\"샘플 크기: {len(mkt_data_enc)}\")\n", + "print(f\"처치군: {(mkt_data_enc['treated']==1).sum()}, 대조군: {(mkt_data_enc['treated']==0).sum()}\")\n", + "\n", + "# ③ DoubleMLData 생성\n", + "mkt_dml_data = DoubleMLData(\n", + " data=mkt_data_enc,\n", + " y_col='downloads',\n", + " d_cols='treated',\n", + " x_cols=x_cols\n", + ")\n", + "\n", + "# ④ 모델 지정\n", + "ml_g = RandomForestRegressor(max_depth=5, n_estimators=200, random_state=42)\n", + "ml_m = RandomForestClassifier(max_depth=3, n_estimators=200, random_state=42)\n", + "\n", + "# ⑤ DoubleML-DID 추정\n", + "dml_did = DoubleMLDID(\n", + " obj_dml_data=mkt_dml_data,\n", + " ml_g=ml_g,\n", + " ml_m=ml_m,\n", + " score='observational',\n", + " n_folds=5,\n", + " in_sample_normalization=True # 정규화 옵션 추가\n", + ")\n", "\n", - "np.random.seed(42)\n", - "for t_idx, t in enumerate(time_periods[1:]):\n", - " if t <= 0:\n", - " t_diff = t-1\n", - " else:\n", - " # compare to outcome before treatment\n", - " t_diff = -1\n", - " # outcome as the difference for each model\n", - " \n", - " y_diff = data[data['t'] == t]['y'].values - data[data['t'] == t_diff]['y'].values\n", - " covariates = np.column_stack((data[data['t'] == t][[f'X{i}' for i in range(4)]].values, data[data['t'] == t_diff][[f'X{i}' for i in range(4)]].values))\n", - " dml_data = DoubleMLData.from_arrays(x=covariates,\n", - " y=y_diff,\n", - " d=data[data['t'] == t]['d'].values)\n", - " dml_did = DoubleMLDID(dml_data,\n", - " ml_g=ml_g,\n", - " ml_m=ml_m)\n", - " dml_did.fit()\n", + "dml_did.fit()\n", "\n", - " df.at[t_idx, 'effect'] = dml_did.coef \n", - " confint = dml_did.confint(level=0.95)\n", - " df.at[t_idx, 'lower'] = confint['2.5 %'].iloc[0]\n", - " df.at[t_idx, 'upper'] = confint['97.5 %'].iloc[0]\n", - " df[\"true effect\"] = mu_means[1:]" + "# ⑥ 결과 출력\n", + "print(\"\\n\" + \"=\" * 70)\n", + "print(\"추정 결과\")\n", + "print(\"=\" * 70)\n", + "print(f\"ATT: {dml_did.coef[0]:.4f}\")\n", + "print(f\"표준오차: {dml_did.se[0]:.4f}\")\n", + "\n", + "confint = dml_did.confint(level=0.95)\n", + "print(f\"95% CI: [{confint['2.5 %'].iloc[0]:.4f}, {confint['97.5 %'].iloc[0]:.4f}]\")\n", + "\n", + "# True ATT와 비교\n", + "if 'tau' in mkt_data_enc.columns:\n", + " true_att = mkt_data_enc.query(\"treated==1 & post==1\")['tau'].mean()\n", + " print(f\"\\nTrue ATT: {true_att:.4f}\")\n", + " print(f\"Bias: {dml_did.coef[0] - true_att:.4f}\")\n" ] }, { - "cell_type": "code", - "execution_count": 208, - "id": "b9d632d7", + "cell_type": "markdown", + "id": "769389cf", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " lower effect upper time true effect\n", - "0 -0.622488 -0.223705 0.175077 -4 0.0\n", - "1 -0.259171 0.085002 0.429174 -3 0.0\n", - "2 -0.566082 -0.204853 0.156376 -2 0.0\n", - "3 -0.397169 -0.035365 0.326439 -1 0.0\n", - "4 4.664547 5.010711 5.356875 0 5.0\n", - "5 3.564744 3.941238 4.317732 1 4.0\n", - "6 2.295386 2.791091 3.286796 2 3.0\n", - "7 1.757909 2.127233 2.496557 3 2.0\n", - "8 0.719589 1.049249 1.378908 4 1.0" - ] - }, - "execution_count": 208, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "df" + "##### Dynamic DML-DiD" ] }, { - "cell_type": "markdown", - "id": "7dc04ed4", + "cell_type": "code", + "execution_count": 170, + "id": "8f5fd754", "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "======================================================================\n", + "Part 2: Event Study - 평행추세 검정 및 동적 처치효과\n", + "======================================================================\n", + "\n", + "✓ 분석 기간: -14 ~ 17\n", + "✓ 처치 전 기간: 14개\n", + "✓ 처치 후 기간: 18개\n", + "\n", + "Event Study 추정 중...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 32/32 [00:44<00:00, 1.40s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "======================================================================\n", + "Event Study 요약\n", + "======================================================================\n", + "✓ 추정 완료 시점: 32개\n", + "✓ 처치 전 평균 효과: 0.0618\n", + "✓ 처치 후 평균 효과: 1.7048\n", + "\n", + "평행추세 검정:\n", + " - 처치 전 유의한 효과: 0/14\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], "source": [ - "결과 시각화" + "\n", + "# Part 2: Event Study \n", + "\n", + "\n", + "print(\"\\n\\n\" + \"=\" * 70)\n", + "print(\"Part 2: Event Study - 평행추세 검정 및 동적 처치효과\")\n", + "print(\"=\" * 70)\n", + "\n", + "# 데이터 준비\n", + "mkt_data_enc = pd.get_dummies(mkt_data_all, \n", + " columns=['region', 'city'], \n", + " drop_first=True)\n", + "\n", + "# 시간 인덱스 생성\n", + "mkt_data_enc['date'] = pd.to_datetime(mkt_data_enc['date'])\n", + "date_to_time = {date: idx for idx, date in enumerate(sorted(mkt_data_enc['date'].unique()))}\n", + "mkt_data_enc['time'] = mkt_data_enc['date'].map(date_to_time)\n", + "\n", + "# 처치 시점 확인\n", + "treatment_time = mkt_data_enc[mkt_data_enc['post'] == 1]['time'].min()\n", + "mkt_data_enc['time_relative'] = mkt_data_enc['time'] - treatment_time\n", + "\n", + "time_periods = sorted(mkt_data_enc['time_relative'].unique())\n", + "\n", + "# 공변량 (post 제외, city 더미는 포함)\n", + "x_cols = [c for c in mkt_data_enc.columns \n", + " if c not in ['downloads', 'treated', 'tau', 'date', 'time', 'time_relative', 'post']]\n", + "\n", + "print(f\"\\n✓ 분석 기간: {min(time_periods)} ~ {max(time_periods)}\")\n", + "print(f\"✓ 처치 전 기간: {len([t for t in time_periods if t < 0])}개\")\n", + "print(f\"✓ 처치 후 기간: {len([t for t in time_periods if t >= 0])}개\")\n", + "\n", + "# 결과 저장\n", + "results_list = []\n", + "\n", + "print(\"\\nEvent Study 추정 중...\")\n", + "np.random.seed(42)\n", + "\n", + "for t in tqdm.tqdm(time_periods):\n", + " # 해당 시점의 데이터만 사용\n", + " data_t = mkt_data_enc[mkt_data_enc['time_relative'] == t].copy()\n", + " \n", + " # 처치군과 대조군 확인\n", + " n_treated = (data_t['treated'] == 1).sum()\n", + " n_control = (data_t['treated'] == 0).sum()\n", + " \n", + " if n_treated < 5 or n_control < 5:\n", + " continue\n", + " \n", + " try:\n", + " # DoubleMLData 생성 (각 시점에서 독립적으로)\n", + " dml_data = DoubleMLData(\n", + " data=data_t,\n", + " y_col='downloads',\n", + " d_cols='treated',\n", + " x_cols=x_cols\n", + " )\n", + " \n", + " # fold 수 결정\n", + " n_folds = min(5, len(data_t) // 20)\n", + " n_folds = max(2, n_folds)\n", + " \n", + " # DoubleML-DID 추정\n", + " # 각 시점에서 cross-sectional 비교\n", + " dml_did_t = DoubleMLDID(\n", + " dml_data,\n", + " ml_g=RandomForestRegressor(max_depth=5, n_estimators=200, random_state=42),\n", + " ml_m=RandomForestClassifier(max_depth=3, n_estimators=200, random_state=42),\n", + " score='observational',\n", + " n_folds=n_folds,\n", + " in_sample_normalization=True\n", + " )\n", + " \n", + " dml_did_t.fit()\n", + " \n", + " # 결과 저장\n", + " confint_t = dml_did_t.confint(level=0.95)\n", + " result_row = {\n", + " 'time': t,\n", + " 'effect': dml_did_t.coef[0],\n", + " 'se': dml_did_t.se[0],\n", + " 'lower': confint_t['2.5 %'].iloc[0],\n", + " 'upper': confint_t['97.5 %'].iloc[0],\n", + " 'n_obs': len(data_t),\n", + " 'n_treated': n_treated,\n", + " 'n_control': n_control\n", + " }\n", + " results_list.append(result_row)\n", + " \n", + " except Exception as e:\n", + " print(f\"\\n 시점 {t}에서 오류: {str(e)}\")\n", + " continue\n", + "\n", + "# 결과 데이터프레임\n", + "df_parallel = pd.DataFrame(results_list)\n", + "\n", + "print(\"\\n\" + \"=\" * 70)\n", + "print(\"Event Study 요약\")\n", + "print(\"=\" * 70)\n", + "print(f\"✓ 추정 완료 시점: {len(df_parallel)}개\")\n", + "print(f\"✓ 처치 전 평균 효과: {df_parallel[df_parallel['time'] < 0]['effect'].mean():.4f}\")\n", + "print(f\"✓ 처치 후 평균 효과: {df_parallel[df_parallel['time'] >= 0]['effect'].mean():.4f}\")\n", + "\n", + "# 평행추세 검정\n", + "pre_treatment = df_parallel[df_parallel['time'] < 0]\n", + "if len(pre_treatment) > 0:\n", + " # 처치 전 효과가 0과 유의하게 다른지 검정\n", + " pre_significant = ((pre_treatment['lower'] > 0) | (pre_treatment['upper'] < 0)).sum()\n", + " print(f\"\\n평행추세 검정:\")\n", + " print(f\" - 처치 전 유의한 효과: {pre_significant}/{len(pre_treatment)}\")\n", + "\n" ] }, { "cell_type": "code", - "execution_count": null, - "id": "d073f8ab", + "execution_count": 171, + "id": "3e04a9d8", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "======================================================================\n", + "상세 결과 테이블\n", + "======================================================================\n", + " time effect se lower upper n_obs n_treated n_control\n", + " -14 0.026166 0.396660 -0.751274 0.803605 200 43 157\n", + " -13 0.196312 0.448719 -0.683161 1.075784 200 43 157\n", + " -12 0.199174 0.439775 -0.662768 1.061116 200 43 157\n", + " -11 -0.085387 0.387458 -0.844791 0.674017 200 43 157\n", + " -10 -0.184637 0.418166 -1.004228 0.634954 200 43 157\n", + " -9 -0.009544 0.402886 -0.799185 0.780097 200 43 157\n", + " -8 0.122351 0.405131 -0.671692 0.916394 200 43 157\n", + " -7 0.262037 0.403967 -0.529723 1.053797 200 43 157\n", + " -6 -0.040674 0.390118 -0.805292 0.723943 200 43 157\n", + " -5 -0.041045 0.385302 -0.796222 0.714132 200 43 157\n", + " -4 0.170447 0.418033 -0.648883 0.989777 200 43 157\n", + " -3 0.058440 0.407665 -0.740568 0.857448 200 43 157\n", + " -2 0.139694 0.416366 -0.676369 0.955757 200 43 157\n", + " -1 0.052180 0.414668 -0.760554 0.864914 200 43 157\n", + " 0 -0.200275 0.370162 -0.925779 0.525229 200 43 157\n", + " 1 0.404908 0.401765 -0.382538 1.192353 200 43 157\n", + " 2 0.779791 0.413758 -0.031160 1.590742 200 43 157\n", + " 3 1.117617 0.433415 0.268140 1.967094 200 43 157\n", + " 4 1.822868 0.450898 0.939125 2.706612 200 43 157\n", + " 5 2.104725 0.474344 1.175028 3.034422 200 43 157\n", + " 6 1.991723 0.491194 1.029001 2.954444 200 43 157\n", + " 7 1.890496 0.495958 0.918436 2.862556 200 43 157\n", + " 8 1.787639 0.505051 0.797758 2.777520 200 43 157\n", + " 9 2.126612 0.497340 1.151843 3.101381 200 43 157\n", + " 10 1.828498 0.487469 0.873077 2.783918 200 43 157\n", + " 11 1.786982 0.500655 0.805716 2.768247 200 43 157\n", + " 12 2.387927 0.504289 1.399539 3.376315 200 43 157\n", + " 13 2.166021 0.482702 1.219942 3.112101 200 43 157\n", + " 14 2.090271 0.517916 1.075174 3.105367 200 43 157\n", + " 15 2.155379 0.508234 1.159259 3.151499 200 43 157\n", + " 16 2.024711 0.492422 1.059582 2.989841 200 43 157\n", + " 17 2.419974 0.505077 1.430040 3.409907 200 43 157\n" + ] } ], "source": [ - "import matplotlib.pyplot as plt\n", - "plt.rcParams['figure.figsize'] = 10., 7.5\n", - "fig, ax = plt.subplots()\n", - "\n", - "errors = np.full((2, 2*n_time_periods - 1), np.nan)\n", - "errors[0, :] = df['effect'] - df['lower']\n", - "errors[1, :] = df['upper'] - df['effect']\n", - "\n", - "plt.errorbar(df['time'], df['effect'], fmt='o', yerr=errors, color='#1F77B4',\n", - " ecolor='#1F77B4', label='Estimated Effect (with CI)')\n", - "ax.plot(time_periods[1:], df['effect'], linestyle='--', color='#1F77B4', linewidth=1)\n", - "\n", - "# add horizontal line\n", - "ax.axhline(y=0, color='r', linestyle='--', linewidth=1)\n", - "\n", - "# add true effect\n", - "ax.scatter(x=df['time'], y=df['true effect'], c='#FF7F0E', label='True Effect')\n", "\n", - "plt.xlabel('Exposure')\n", - "plt.legend()\n", - "_ = plt.ylabel('Effect and 95%-CI')" + "# 시각화\n", + "\n", + "\n", + "fig, ax = plt.subplots(figsize=(14, 8))\n", + "\n", + "# Reference lines\n", + "ax.axhline(y=0, color='black', linestyle='--', linewidth=1.5, alpha=0.5, label='No Effect')\n", + "ax.axvline(x=0, color='red', linestyle='-', linewidth=2, alpha=0.7, label='Treatment Start')\n", + "\n", + "# Split pre- and post-treatment periods\n", + "pre_treatment = df_parallel[df_parallel['time'] < 0]\n", + "post_treatment = df_parallel[df_parallel['time'] >= 0]\n", + "\n", + "# Pre-treatment plot\n", + "if len(pre_treatment) > 0:\n", + " ax.errorbar(pre_treatment['time'], pre_treatment['effect'], \n", + " yerr=[pre_treatment['effect'] - pre_treatment['lower'],\n", + " pre_treatment['upper'] - pre_treatment['effect']],\n", + " fmt='o', color='#2E86AB', markersize=10, capsize=6, \n", + " linewidth=2.5, capthick=2, label='Pre-treatment (Parallel Trend Test)',\n", + " alpha=0.8)\n", + "\n", + "# Post-treatment plot\n", + "if len(post_treatment) > 0:\n", + " ax.errorbar(post_treatment['time'], post_treatment['effect'], \n", + " yerr=[post_treatment['effect'] - post_treatment['lower'],\n", + " post_treatment['upper'] - post_treatment['effect']],\n", + " fmt='s', color='#06A77D', markersize=10, capsize=6, \n", + " linewidth=2.5, capthick=2, label='Post-treatment (Treatment Effect)',\n", + " alpha=0.8)\n", + "\n", + "# Labels and title\n", + "ax.set_xlabel('Relative Time to Treatment', fontsize=14, fontweight='bold')\n", + "ax.set_ylabel('Estimated Effect (Downloads)', fontsize=14, fontweight='bold')\n", + "ax.set_title('Event Study: Parallel Trend Test & Dynamic Treatment Effects\\n(DoubleML-DID)', \n", + " fontsize=16, fontweight='bold', pad=20)\n", + "\n", + "# Legend, grid, layout\n", + "ax.legend(fontsize=12, loc='best', framealpha=0.9)\n", + "ax.grid(True, alpha=0.3, linestyle='--')\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n", + "# 결과 테이블 출력\n", + "print(\"\\n\" + \"=\" * 70)\n", + "print(\"상세 결과 테이블\")\n", + "print(\"=\" * 70)\n", + "print(df_parallel.to_string(index=False))" ] }, { "cell_type": "markdown", - "id": "6f9fae36", + "id": "e467df6f", "metadata": {}, "source": [ - "- 사전 구간에서 모든 추정치의 CI가 0을 포함하므로, 평행추세 가정은 위배되지 않았다고 해석할 수 있습니다.\n", + "분석 결과,처치 전 평균 효과는 0.0618로, 통계적으로 유의한 시점은 **0개(0/14)** 였습니다.\n", + "이는 처치 이전에 집단 간 유의한 차이가 존재하지 않음을 의미하며, 평행추세 가정이 충족되는 것으로 판단됩니다.\n", "\n", - "- 또, 사후 구간에서 True Effect를 잘 커버하고 있으므로 추정량이 일관되고 신뢰할 만하다고 말할 수 있습니다." + "반면,처치 후 동적 평균 효과는 1.7048로, 대부분의 시점에서 양(+)의 효과가 관찰되었습니다.\n", + "이는 **처치 이후 실질적인 성과 향상(예: downloads 증가)** 이 나타났음을 시사하며,처치 효과가 시간에 따라 점진적으로 강화되는 동적 패턴을 보인다고 해석할 수 있습니다.\n" ] }, { "cell_type": "code", "execution_count": null, - "id": "21fc4727", + "id": "bb62d4f5", "metadata": {}, "outputs": [], "source": [] @@ -2741,9 +4240,9 @@ "metadata": { "celltoolbar": "Tags", "kernelspec": { - "display_name": "fack_cl", + "display_name": "Python (kats_env)", "language": "python", - "name": "python3" + "name": "kats_env" }, "language_info": { "codemirror_mode": { @@ -2755,7 +4254,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.9.21" }, "toc": { "base_numbering": 1, diff --git a/book/data/.DS_Store b/book/data/.DS_Store index 1c4021c3a90ecc18c79b41ca29ae526336de2a67..e066a8dd46c9aec7afd3cc5c04fea0ddca545147 100644 GIT binary patch delta 25 gcmZp1XmQw}BgA23X`rKEWMMh^gMj_!Vxft=0Ad&iu>b%7 delta 16 XcmZp1XmQw}BQ*JifcxfRp^3ZzHkAe+ diff --git a/book/data/matheus_data/.DS_Store b/book/data/matheus_data/.DS_Store index 14eafcf10d9ec68be91fdd3814cdb8ab7aa4aa42..a5cc46ffd03676b1585e0dbcd972e3e192e6c8a0 100644 GIT binary patch delta 66 zcmZp1XmOa}&nUGqU^hRb)Mg%mg)EGcljn&_^OrCrGNc1xDnk(vr%XN|D$e?kfr0Vu U=0zgH%$wOIzOigxEyB(W0CrRo;Q#;t delta 40 wcmZp1XmOa}&nUSuU^hRb Date: Sun, 19 Oct 2025 11:48:16 +0900 Subject: [PATCH 13/16] =?UTF-8?q?=EB=AA=A9=EC=B0=A8=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- book/ate/did.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index e205b21..c9772b9 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -3765,7 +3765,7 @@ "id": "0b985fca", "metadata": {}, "source": [ - "#### 3.9 DML을 이용한 DID\n", + "### 4. DML을 이용한 DID\n", "\n", "- 공변량과 결과 변수, 공변량과 처치 변수 간의 복잡한 비선형 관계를 머신러닝 모델로 예측한 후, 이 잔차(residuals)를 사용하여 DiD 효과를 추정하는 방법입니다.\n", "- 고차원적인 공변량을 유연하게 처리하고, 머신러닝의 예측력을 활용하여 잠재적인 편향을 줄입니다. 특히 이질적인 처치 효과를 다루는 데 강점이 있습니다.\n", From 91260a6d57fe99b6aad38b80c3d400c98d9d4493 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 19 Oct 2025 12:17:41 +0900 Subject: [PATCH 14/16] . --- book/ate/did.ipynb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index c9772b9..88250bd 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -4240,9 +4240,9 @@ "metadata": { "celltoolbar": "Tags", "kernelspec": { - "display_name": "Python (kats_env)", + "display_name": "Python (fack_cl)", "language": "python", - "name": "kats_env" + "name": "fack_cl" }, "language_info": { "codemirror_mode": { @@ -4254,7 +4254,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.21" + "version": "3.10.16" }, "toc": { "base_numbering": 1, From 0c20d226ac7e5b3285de326b1eada34a483c219e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 19 Oct 2025 21:57:35 +0900 Subject: [PATCH 15/16] =?UTF-8?q?dml=20=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- book/ate/did.ipynb | 50 ---------------------------------------------- 1 file changed, 50 deletions(-) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index 88250bd..0c620e0 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -3773,56 +3773,6 @@ "- 다만, 모델 복잡성이 증가하고, 구현 및 해석이 어려울 수 있습니다." ] }, - { - "cell_type": "markdown", - "id": "3d522a65", - "metadata": {}, - "source": [ - " Data 생성" - ] - }, - { - "cell_type": "code", - "execution_count": 119, - "id": "44baede5", - "metadata": {}, - "outputs": [], - "source": [ - "from doubleml import DoubleMLData\n", - "import pandas as pd\n", - "\n", - "# region을 one-hot encoding (공변량으로 사용)\n", - "mkt_data_enc = pd.get_dummies(mkt_data_all, columns=['region'], drop_first=True)\n", - "\n", - "# DoubleMLData 구성\n", - "mkt_dml_data = DoubleMLData(\n", - " data=mkt_data_enc,\n", - " y_col='downloads',\n", - " d_cols='treated',\n", - " x_cols=['region_N', 'region_S', 'region_W', 'post']\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "dc414e35", - "metadata": {}, - "source": [ - "Learners 설정\n" - ] - }, - { - "cell_type": "code", - "execution_count": 120, - "id": "3b6d7828", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "ml_g = LGBMRegressor(n_estimators=50, num_leaves=5, verbose=-1)\n", - "ml_m = LGBMClassifier(n_estimators=50, num_leaves=5, verbose=-1)\n" - ] - }, { "cell_type": "markdown", "id": "918e68d4", From f2608206777c0b2a3aaade01c385d6ee459c5535 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=EA=B9=80=EC=8B=9C=EC=9D=80?= Date: Sun, 26 Oct 2025 01:46:17 +0900 Subject: [PATCH 16/16] =?UTF-8?q?=ED=9D=90=EB=A6=84=20=EC=88=98=EC=A0=95?= =?UTF-8?q?=20=EB=B0=8F=20=EA=B0=9C=EB=85=90=20=EC=84=A4=EB=AA=85=20?= =?UTF-8?q?=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- book/ate/did.ipynb | 797 ++++----- book/ate/propensity_score_and_dml.ipynb | 1960 ++++++++++++++++++++++- 2 files changed, 2376 insertions(+), 381 deletions(-) diff --git a/book/ate/did.ipynb b/book/ate/did.ipynb index 0c620e0..28132e6 100644 --- a/book/ate/did.ipynb +++ b/book/ate/did.ipynb @@ -298,7 +298,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "id": "2c650ac3", "metadata": {}, "outputs": [], @@ -313,6 +313,8 @@ "from scipy.stats import norm\n", "\n", "from lightgbm import LGBMRegressor, LGBMClassifier\n", + "\n", + "\n", "from doubleml import DoubleMLData, DoubleMLDID\n", "\n", "\n", @@ -350,7 +352,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, "id": "d17c7963", "metadata": { "ExecuteTime": { @@ -453,7 +455,7 @@ "4 2021-05-05 5 S 0 0.0 49.0 0" ] }, - "execution_count": 7, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -470,6 +472,27 @@ "mkt_data.head()" ] }, + { + "cell_type": "markdown", + "id": "c2faf93a", + "metadata": {}, + "source": [ + "위 데이터는 서부 지역에서 온라인 마케팅 캠페인을 집행했을 때, 사용자가 실제로 해당 광고를 보고 앱을 다운로드했는지를 관찰한 자료입니다.\n", + "일반적으로 마케팅 업계에서는 이러한 지역 단위 실험(Regional Experiment) 설계를 자주 활용합니다.\n", + "즉, 일부 지역(실험군, treatment group)에서는 마케팅 캠페인을 진행하고, 다른 지역(통제군, control group)에서는 캠페인을 진행하지 않은 채로 두 집단의 변화를 비교하는 방식입니다.\n", + "\n", + "이런 설계는 단순히 시점별 평균 차이만 비교하는 것보다 더 엄밀하게 마케팅의 실제 효과(causal effect) 를 추정할 수 있습니다.\n", + "특히 패널 데이터(panel data) 를 활용하면,\n", + "같은 지역의 처치 전(before treatment) 과 처치 후(after treatment) 변화를 모두 관측할 수 있기 때문에,\n", + "지역별 고유한 특성(예: 인구 규모, 경제 수준 등)을 통제하면서 시점별 변화만을 비교할 수 있습니다.\n", + "\n", + "이때 주로 사용하는 분석 방법이 차분의 차분(Difference-in-Differences, DiD) 입니다.\n", + "DiD는 “처치 지역에서의 전후 변화 - 비처치 지역에서의 전후 변화”를 계산함으로써,\n", + "단순한 시간 효과나 지역 차이를 제거하고 마케팅 캠페인 자체의 순수한 효과를 추정할 수 있게 해줍니다.\n", + "\n", + "그럼 DiD를 추정하는 다양한 관점 및 방법에 대해 알아보도록 하겠습니다.\n" + ] + }, { "cell_type": "markdown", "id": "d7b53c33", @@ -480,7 +503,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 4, "id": "3d6cdba1", "metadata": { "ExecuteTime": { @@ -550,7 +573,7 @@ "1 2021-05-15 2021-06-01" ] }, - "execution_count": 8, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -562,9 +585,17 @@ " .agg({\"date\":[min, max]}))" ] }, + { + "cell_type": "markdown", + "id": "65e743f3", + "metadata": {}, + "source": [ + "처치 개입전 기간은 2021-05-01~2021-05-15이며 처치 후 기간은 2021-05-15~2021-06-01입니다. " + ] + }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "id": "355d9c2c", "metadata": { "ExecuteTime": { @@ -641,7 +672,7 @@ " 1 51.858025 2021-05-15" ] }, - "execution_count": 9, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -665,7 +696,8 @@ "metadata": {}, "source": [ "## DiD \n", - "![image.png](attachment:image.png)" + "![image.png](attachment:image.png)\n", + "\n" ] }, { @@ -673,7 +705,7 @@ "id": "2614a652", "metadata": {}, "source": [ - "## 이중 차분법에 대한 접근법 3가지\n", + "## 이중 차분법에 대한 접근법 4가지\n", "1. 평균을 이용한 이중 차분법 (Basic DID 2x2)\n", "2. 시간에 따른 결과 변화 값을 이용한 이중차분법\n", "3. 선형회귀를 이용한 이중차분법(Regression DID) \n", @@ -681,7 +713,7 @@ " - 3.2 Basic DiD\n", " - 3.3 TWFE DID\n", " - 3.4 DID with covariates (Control DID: 추가 통제 포함)\n", - " - 3.4.1 DoubleML \n" + "4. 머신 러닝을 이용한 이중차분법(DoubleML) \n" ] }, { @@ -701,7 +733,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "id": "79bcb7fe", "metadata": { "ExecuteTime": { @@ -716,7 +748,7 @@ "0.6917359536407233" ] }, - "execution_count": 10, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -732,7 +764,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, "id": "b51d6822", "metadata": { "ExecuteTime": { @@ -747,7 +779,7 @@ "0.7660316402518457" ] }, - "execution_count": 11, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -772,7 +804,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 8, "id": "10e16d8d", "metadata": { "ExecuteTime": { @@ -851,7 +883,7 @@ "197 1.595238 1" ] }, - "execution_count": 12, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -871,7 +903,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 9, "id": "31be6542", "metadata": { "ExecuteTime": { @@ -886,7 +918,7 @@ "0.6917359536407155" ] }, - "execution_count": 13, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -906,7 +938,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 10, "id": "57032287", "metadata": {}, "outputs": [ @@ -978,7 +1010,7 @@ " 1 51.858025 2021-05-15" ] }, - "execution_count": 14, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -989,7 +1021,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 11, "id": "ff0261df", "metadata": { "ExecuteTime": { @@ -1004,10 +1036,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 15, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, @@ -1081,7 +1113,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 12, "id": "bead249f", "metadata": { "ExecuteTime": { @@ -1173,7 +1205,7 @@ "4 20 0 48.785714 2021-05-01 0" ] }, - "execution_count": 16, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -1187,26 +1219,9 @@ "did_data.head()" ] }, - { - "cell_type": "markdown", - "id": "6cb1e2e6", - "metadata": {}, - "source": [ - " `statsmodels`와 `pyfixest`\n", - "\n", - "DID 분석을 회귀 모형으로 구현할 때,\n", - "- **statsmodels (smf)** 은 파이썬에서 가장 널리 쓰이는 범용 회귀 패키지라 기본 구현을 설명하기에 적합합니다. \n", - "- 그러나 DID는 본질적으로 **패널 데이터 + 고정효과(FE) + 클러스터 표준오차**가 중요합니다. \n", - " 이를 편리하게 지원하는 패키지가 바로 **pyfixest**입니다.\n", - "\n", - "따라서 \n", - "- statsmodels로는 DID의 기본 원리를 쉽게 보여줄 수 있고, \n", - "- pyfixest로는 실제 실증연구에서 사용하는 **FE-DID, TWFE, robust SE**를 더 직관적으로 구현할 수 있습니다." - ] - }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 13, "id": "54757217", "metadata": { "ExecuteTime": { @@ -1221,7 +1236,7 @@ "0.6917359536407282" ] }, - "execution_count": 17, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -1248,7 +1263,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 14, "id": "d1eed2c4", "metadata": { "ExecuteTime": { @@ -1262,7 +1277,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -1307,7 +1322,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 15, "id": "e01430de", "metadata": {}, "outputs": [ @@ -1474,7 +1489,7 @@ "[1632 rows x 7 columns]" ] }, - "execution_count": 19, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1509,7 +1524,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 16, "id": "647b569a", "metadata": { "ExecuteTime": { @@ -1524,7 +1539,7 @@ "0.6917359536406944" ] }, - "execution_count": 20, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -1567,7 +1582,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 17, "id": "e847ddef", "metadata": {}, "outputs": [ @@ -1586,7 +1601,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 21, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1609,7 +1624,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 18, "id": "fe572c5d", "metadata": {}, "outputs": [ @@ -1628,7 +1643,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 22, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -1647,9 +1662,9 @@ "id": "a745a402", "metadata": {}, "source": [ - "#### 3.3 2WFE did \n", + "#### 3.3 2WFE did (시간 -대상 고정효과 모델)\n", "\n", - "- 데이터 집계 방식 2의 회귀 모델에 단위 고정 효과($\\alpha_i$​)와 시간 고정 효과($\\gamma_t$​)를 동시에 추가하여 분석하는 방법입니다.\n", + "- 회귀 모델에 단위 고정 효과($\\alpha_i$​)와 시간 고정 효과($\\gamma_t$​)를 동시에 추가하여 분석하는 방법입니다.\n", "- 단위별 고유 특성(시간 불변)과 모든 단위에 공통된 시간 트렌드를 통제하여 교란 요인을 더 효과적으로 제거합니다.\n", "- 내생성 문제를 완화하고, 다중 시점 데이터를 유연하게 처리할 수 있습니다.\n", "- 시간에 따라 변하는 관측되지 않은 교란 요인이나, 처치 효과가 이질적인 경우(heterogeneous effects) 편향될 수 있습니다.\n", @@ -1661,7 +1676,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 19, "id": "f80b7263", "metadata": {}, "outputs": [ @@ -1703,7 +1718,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 20, "id": "0f3be3b1", "metadata": {}, "outputs": [ @@ -1722,7 +1737,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 24, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1745,7 +1760,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 21, "id": "9c0290e8", "metadata": {}, "outputs": [ @@ -1764,7 +1779,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 25, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1788,7 +1803,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 22, "id": "83d3cfda", "metadata": {}, "outputs": [ @@ -1807,7 +1822,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 26, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1830,7 +1845,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 23, "id": "edd9ec8e", "metadata": {}, "outputs": [ @@ -1849,7 +1864,7 @@ "Name: treated:post, dtype: float64" ] }, - "execution_count": 27, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1897,19 +1912,22 @@ "source": [ "#### 3.4 DID with covariates\n", "\n", - "TWFE DiD 모델에 시간에 따라 변하는 관측 가능한 공변량($X_{it}$​)을 추가하는 방식입니다.\n", + "시간에 따라 변하는 관측 가능한 공변량($X_{it}$​)을 추가하는 방식입니다.\n", + "예) TWFE모델에 공변량 추가하기\n", "$$Y_{it} = \\alpha_i + \\gamma_t + \\beta (\\text{Treated}_i \\times \\text{Post}_t) + \\delta'X_{it} + \\epsilon_{it}$$\n", "\n", - "- 시간에 따라 그룹 간 다르게 변화하는 관측 가능한 교란 요인을 통제함으로써 평행 추세 가정을 더욱 강화합니다.\n", + "- 시간에 따라 그룹 간 다르게 변화하는 관측 가능한 교란 요인을 통제함으로써 평행 추세 가정을 더욱 만족할 수 있습니다.\n", "- 추정치의 정밀도를 높이고, 관측 가능한 교란 요인으로 인한 편향을 줄입니다.\n", "- 어떤 공변량을 포함할지 신중하게 선택해야 하며, 여전히 관측되지 않은 교란 요인에 의한 편향 가능성은 남아 있습니다.\n", "\n", + "아래 데이터는 기존 mkt_data에 처치 전의 공변량(지역)이 추가 된 데이터 입니다. \n", + "\n", "\n" ] }, { "cell_type": "code", - "execution_count": 147, + "execution_count": 24, "id": "95d777fa", "metadata": {}, "outputs": [], @@ -1920,7 +1938,7 @@ }, { "cell_type": "code", - "execution_count": 148, + "execution_count": 25, "id": "00aefefa", "metadata": {}, "outputs": [ @@ -2087,7 +2105,7 @@ "[6400 rows x 7 columns]" ] }, - "execution_count": 148, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -2098,7 +2116,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 26, "id": "9f347bae", "metadata": {}, "outputs": [ @@ -2118,7 +2136,7 @@ " Text(18779.0, 0, '2021-06-01')])" ] }, - "execution_count": 29, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, @@ -2149,23 +2167,12 @@ "id": "482abc10", "metadata": {}, "source": [ - "처치 이전 추세의 경우 지역내에서는 평행하지만 지역 간에는 평행하지 않은 것으로 보입니다. 이러한 상황해서 단순히 이원고정효과모델을 적용하면 ATT에 대해 편향된 추정값을 얻게되죠. \n", - "\n", - "따라서 이 문제를 해결하기 위해선 각 지역별로 서로 다른 추세가 있다는 것을 반드시 고려해야합니다. \n", - "\n", - "그럼 어떻게 지역별로 서로 다른 추세가 있다는 것을 모델에 반영할 수 있을까요? 바로 모델에 처치전의 공변량(covariates)을 포함하는 것입니다. \n", - "\n", - "공변량을 모델에 반영하여 ATT추정하는 방법은 대표적으로 2가지 방법이 있습니다. \n", - "\n", - "\n", - "1. 각 지역별로 별도의 DID 회귀 모델 적용하고 ATT 가중평균하여 구하기\n", - "\n", - "2. 지역 변수와 처치 후 더미 변수와 상호작용하기\n" + "처치 이전 추세의 경우 지역내에서는 평행하지만 지역 간에는 평행하지 않은 것으로 보입니다. 이러한 상황해서 단순히 이원고정효과모델을 적용하면 ATT에 대해 편향된 추정값을 얻게되죠. \n" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 27, "id": "71afe601", "metadata": {}, "outputs": [ @@ -2173,12 +2180,35 @@ "name": "stdout", "output_type": "stream", "text": [ - "True ATT: 1.7208921056102682\n" + "True ATT: 1.7208921056102682\n", + "Estimated ATT: 2.0683919842564036\n" ] } ], "source": [ - "print(\"True ATT: \", mkt_data_all.query(\"treated*post==1\")[\"tau\"].mean())" + "print(\"True ATT: \", mkt_data_all.query(\"treated*post==1\")[\"tau\"].mean())\n", + "\n", + "m = smf.ols('downloads ~ treated:post + C(city) + C(date)',\n", + " data=mkt_data_all).fit()\n", + "\n", + "print(\"Estimated ATT:\", m.params[\"treated:post\"])\n" + ] + }, + { + "cell_type": "markdown", + "id": "7585173c", + "metadata": {}, + "source": [ + "따라서 이 문제를 해결하기 위해선 각 지역별로 서로 다른 추세가 있다는 것을 반드시 고려해야합니다. \n", + "\n", + "그럼 어떻게 지역별로 서로 다른 추세가 있다는 것을 모델에 반영할 수 있을까요? 바로 모델에 처치전의 공변량(covariates)을 포함하는 것입니다. \n", + "\n", + "공변량을 모델에 반영하여 ATT추정하는 방법은 대표적으로 2가지 방법이 있습니다. \n", + "\n", + "\n", + "1. 각 지역별로 별도의 DID 회귀 모델 적용하고 ATT 가중평균하여 구하기\n", + "\n", + "2. 지역 변수와 처치 후 더미 변수와 상호작용하기" ] }, { @@ -2430,28 +2460,89 @@ }, { "cell_type": "markdown", - "id": "4e1cddba", + "id": "b57c5b00", "metadata": {}, "source": [ - "#### 3.5 Staggered DiD\n", - "**Staggered DiD: Canonical vs Dynamic View**\n", + "#### 3.5 Doubly Robust Diff-in-Diff (DRDiD)\n", "\n", - "| 구분 | Canonical View | Dynamic (Event-study) View |\n", - "|:--|:--|:--|\n", - "| **핵심 아이디어** | Staggered DiD는 *canonical DiD의 확장형*, 여러 시점과 그룹에 반복 적용된 2×2 DiD 구조 | Staggered DiD를 *event-time 기준*으로 재정렬하여 시점별 효과 $\\beta_k$ 추정 (Dynamic DID 형태) |\n", - "| **초점** | 평균 처치 효과 (ATT) | 시간에 따른 처치 효과 변화 (dynamic ATT) |\n", - "| **처치 시점** | 모든 단위의 개입 시점 동일하거나, 시점별 DiD 반복 | 단위별로 상이한 개입 시점 (staggered adoption) |\n", - "| **대표 모형** | $Y_{it} = \\alpha_i + \\lambda_t + \\beta D_{it} + \\epsilon_{it}$| $Y_{it} = \\alpha_i + \\lambda_t + \\sum_k \\beta_k \\cdot 1\\{t - G_i = k\\} + \\epsilon_{it}$|\n", - "| **요약** | 구조적으로는 canonical DID의 반복적 적용 | 추정 관점에서는 event-study 기반 Dynamic DID로 해석 가능 \n", + "DRDID는 기존 DiD 분석(Difference-in-Differences, DiD)의 확장된 형태로, \n", "\n", + "조건부 평행 추세 가정을 만족시키기 위해 처치 전 정보와 시간에 따라 변하지 않는 공변량을 결합하는 방법입니다. \n", "\n", - "**⇒ Staggered DiD는 canonical DID의 확장형이면서도, event-study 기반 Dynamic DID로 해석될 수 있음.**" + "성향 점수 모델(Propensity Score Model)과 결과 모델(Delta Outcome Model)이라는 두 가지 모델을 동시에 사용하여 공변량(covariates)을 조정하며, 이 두 모델 중 하나만 올바르게 지정되어도 편향 없는(unbiased) 추정치를 얻을 수 있어 신뢰성이 높습니다. \n", + "\n", + "##### Step1: Propensity Score Model\n", + "ATT에만 관심이 있으므로 대조군을 바탕으로 실험군을 재구성하는 단계입니다." ] }, { "cell_type": "code", - "execution_count": 38, - "id": "0ba27a12", + "execution_count": 28, + "id": "8f2e509d", + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "7ba77a04", + "metadata": {}, + "outputs": [], + "source": [ + "unit_df = (mkt_data_all\n", + " # keep only the first date\n", + " .astype({\"date\": str})\n", + " .query(f\"date=='{mkt_data_all['date'].astype(str).min()}'\")\n", + " .drop(columns=[\"date\"])) # just to avoid confusion\n", + "\n", + "ps_model = smf.logit(\"treated~C(region)\", data=unit_df).fit(disp=0)" + ] + }, + { + "cell_type": "markdown", + "id": "0824799c", + "metadata": {}, + "source": [ + "##### Step 2 Delta Outcome Model\n", + "DiD는 결과 변화량인 $\\Delta y$와 관련되어 있습니다. 따라서 기본 결과 모델 대신 시간에 따른 델타 결과 모델을 구하는 단계입니다." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "2b1bde23", + "metadata": {}, + "outputs": [], + "source": [ + "delta_y = (\n", + " mkt_data_all.query(\"post==1\").groupby(\"city\")[\"downloads\"].mean()\n", + " - mkt_data_all.query(\"post==0\").groupby(\"city\")[\"downloads\"].mean()\n", + ")\n", + "\n", + "\n", + "df_delta_y = (unit_df\n", + " .set_index(\"city\")\n", + " .join(delta_y.rename(\"delta_y\")))\n", + "\n", + "outcome_model = smf.ols(\"delta_y ~ C(region)\", data=df_delta_y).fit()" + ] + }, + { + "cell_type": "markdown", + "id": "37d91006", + "metadata": {}, + "source": [ + "##### Step 3 성향 점수 및 결과 모델을 결합하는 단계" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "5fb8c885", "metadata": {}, "outputs": [ { @@ -2475,48 +2566,254 @@ " \n", " \n", " \n", - " date\n", - " city\n", " region\n", - " cohort\n", " treated\n", " tau\n", " downloads\n", " post\n", + " delta_y\n", + " y_hat\n", + " ps\n", + " \n", + " \n", + " city\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 0\n", - " 2021-05-01\n", - " 1\n", + " 1\n", " W\n", - " 2021-06-20\n", - " 1\n", + " 0\n", " 0.0\n", " 27.0\n", " 0\n", + " 3.087302\n", + " 3.736539\n", + " 0.176471\n", " \n", " \n", - " 1\n", - " 2021-05-02\n", - " 1\n", - " W\n", - " 2021-06-20\n", - " 1\n", + " 2\n", + " N\n", + " 0\n", " 0.0\n", - " 28.0\n", + " 40.0\n", " 0\n", + " 1.436508\n", + " 1.992570\n", + " 0.212766\n", " \n", " \n", - " 2\n", - " 2021-05-03\n", - " 1\n", + " 3\n", " W\n", - " 2021-06-20\n", - " 1\n", + " 0\n", " 0.0\n", - " 28.0\n", + " 30.0\n", + " 0\n", + " 2.761905\n", + " 3.736539\n", + " 0.176471\n", + " \n", + " \n", + " 4\n", + " W\n", + " 0\n", + " 0.0\n", + " 26.0\n", + " 0\n", + " 3.396825\n", + " 3.736539\n", + " 0.176471\n", + " \n", + " \n", + " 5\n", + " S\n", + " 0\n", + " 0.0\n", + " 51.0\n", + " 0\n", + " -0.476190\n", + " 0.343915\n", + " 0.176471\n", + " \n", + " \n", + "\n", + "" + ], + "text/plain": [ + " region treated tau downloads post delta_y y_hat ps\n", + "city \n", + "1 W 0 0.0 27.0 0 3.087302 3.736539 0.176471\n", + "2 N 0 0.0 40.0 0 1.436508 1.992570 0.212766\n", + "3 W 0 0.0 30.0 0 2.761905 3.736539 0.176471\n", + "4 W 0 0.0 26.0 0 3.396825 3.736539 0.176471\n", + "5 S 0 0.0 51.0 0 -0.476190 0.343915 0.176471" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_dr = (df_delta_y\n", + " .assign(y_hat = lambda d: outcome_model.predict(d))\n", + " .assign(ps = lambda d: ps_model.predict(d)))\n", + "\n", + "df_dr.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "b1e1a2b2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ATT: 1.6773180394442855\n" + ] + } + ], + "source": [ + "tr = df_dr.query(\"treated==1\")\n", + "co = df_dr.query(\"treated==0\")\n", + "\n", + "dy1_treat = (tr[\"delta_y\"] - tr[\"y_hat\"]).mean()\n", + "\n", + "w_cont = co[\"ps\"]/(1-co[\"ps\"])\n", + "dy0_treat = np.average(co[\"delta_y\"] - co[\"y_hat\"], weights=w_cont)\n", + "\n", + "print(\"ATT:\", dy1_treat - dy0_treat)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "ec7f3fe6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['S'], dtype=object)" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mkt_data[\"region\"].unique()\n" + ] + }, + { + "cell_type": "markdown", + "id": "4e1cddba", + "metadata": {}, + "source": [ + "지금까지는 블록 디자인을 기반으로 즉, **동일 시점**에 처치 받은 대상과 받지 않은 대상이 존재하는 데이터로 여러 DiD 분석을 수행했습니다. \n", + "\n", + "그런데 실험 대상이 서로 다른 시점에 처치를 받을 수 있습니다. 이런 경우는 어떻게 해야할까요?\n", + "\n", + "처치에 대해 시차 도입설계를 하여 데이터를 구성합니다. 즉, 처치 받는 시점이 그룹을 구분하는 기준이 되어 이들을 코호트라고 일반적으로 부릅니다. \n", + "\n", + "이전에는 처치를 받는 혹은 받지 않는 2개의 코호트로 이루어진 데이터를 사용했다면 이번엔 날짜를 확장하여 2021-0731까지의 모든 지역의 도시에 대한 데이터가 포함되어있는 코호트가 3개 이상인 경우인 데이터를 다루겠습니다.\n", + "\n", + "#### 3.6 Staggered DiD\n", + "**Staggered DiD: Canonical vs Dynamic View**\n", + "\n", + "| 구분 | Canonical View | Dynamic (Event-study) View |\n", + "|:--|:--|:--|\n", + "| **핵심 아이디어** | Staggered DiD는 *canonical DiD의 확장형*, 여러 시점과 그룹에 반복 적용된 2×2 DiD 구조 | Staggered DiD를 *event-time 기준*으로 재정렬하여 시점별 효과 $\\beta_k$ 추정 (Dynamic DID 형태) |\n", + "| **초점** | 평균 처치 효과 (ATT) | 시간에 따른 처치 효과 변화 (dynamic ATT) |\n", + "| **처치 시점** | 모든 단위의 개입 시점 동일하거나, 시점별 DiD 반복 | 단위별로 상이한 개입 시점 (staggered adoption) |\n", + "| **대표 모형** | $Y_{it} = \\alpha_i + \\lambda_t + \\beta D_{it} + \\epsilon_{it}$| $Y_{it} = \\alpha_i + \\lambda_t + \\sum_k \\beta_k \\cdot 1\\{t - G_i = k\\} + \\epsilon_{it}$|\n", + "| **요약** | 구조적으로는 canonical DID의 반복적 적용 | 추정 관점에서는 event-study 기반 Dynamic DID로 해석 가능 \n", + "\n", + "\n", + "**⇒ Staggered DiD는 canonical DID의 확장형이면서도, event-study 기반 Dynamic DID로 해석될 수 있음.**" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "0ba27a12", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -2856,255 +3153,6 @@ "print(\"Pred. Effect: \", df_pred[\"effect_hat\"].mean())" ] }, - { - "cell_type": "markdown", - "id": "63798d42", - "metadata": {}, - "source": [ - "#### 3.6 Doubly Robust Diff-in-Diff (DRDiD)\n", - "\n", - "DRDID는 기존 차분 분석(Difference-in-Differences, DiD)의 확장된 형태로, 치료 효과를 더욱 견고하게 추정하는 방법입니다. \n", - "\n", - "성향 점수 모델(Propensity Score Model)과 결과 모델(Delta Outcome Model)이라는 두 가지 모델을 동시에 사용하여 공변량(covariates)을 조정하며, 이 두 모델 중 하나만 올바르게 지정되어도 편향 없는(unbiased) 추정치를 얻을 수 있어 신뢰성이 높습니다. \n", - "\n", - "이는 DiD의 평행 추세 가정을 조건부로 완화하고, 복잡한 현실 데이터에서 보다 정확한 인과 효과를 파악하는 데 유용합니다.\n", - "\n", - "##### Step1: Propensity Score Model" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "id": "e6c407d4", - "metadata": {}, - "outputs": [], - "source": [ - "import warnings\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "id": "736bd702", - "metadata": {}, - "outputs": [], - "source": [ - "unit_df = (mkt_data_all\n", - " # keep only the first date\n", - " .astype({\"date\": str})\n", - " .query(f\"date=='{mkt_data_all['date'].astype(str).min()}'\")\n", - " .drop(columns=[\"date\"])) # just to avoid confusion\n", - "\n", - "ps_model = smf.logit(\"treated~C(region)\", data=unit_df).fit(disp=0)" - ] - }, - { - "cell_type": "markdown", - "id": "3a727727", - "metadata": {}, - "source": [ - "##### Step 2 Delta Outcome Model" - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "id": "ac26b60b", - "metadata": {}, - "outputs": [], - "source": [ - "delta_y = (\n", - " mkt_data_all.query(\"post==1\").groupby(\"city\")[\"downloads\"].mean()\n", - " - mkt_data_all.query(\"post==0\").groupby(\"city\")[\"downloads\"].mean()\n", - ")\n", - "\n", - "\n", - "df_delta_y = (unit_df\n", - " .set_index(\"city\")\n", - " .join(delta_y.rename(\"delta_y\")))\n", - "\n", - "outcome_model = smf.ols(\"delta_y ~ C(region)\", data=df_delta_y).fit()" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "id": "d96b2f0e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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datecityregioncohorttreatedtaudownloadspost
02021-05-011W2021-06-2010.027.00
12021-05-021W2021-06-2010.028.00
22021-05-031W2021-06-2010.028.00
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regiontreatedtaudownloadspostdelta_yy_hatps
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1W00.027.003.0873023.7365390.176471
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" - ], - "text/plain": [ - " region treated tau downloads post delta_y y_hat ps\n", - "city \n", - "1 W 0 0.0 27.0 0 3.087302 3.736539 0.176471\n", - "2 N 0 0.0 40.0 0 1.436508 1.992570 0.212766\n", - "3 W 0 0.0 30.0 0 2.761905 3.736539 0.176471\n", - "4 W 0 0.0 26.0 0 3.396825 3.736539 0.176471\n", - "5 S 0 0.0 51.0 0 -0.476190 0.343915 0.176471" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_dr = (df_delta_y\n", - " .assign(y_hat = lambda d: outcome_model.predict(d))\n", - " .assign(ps = lambda d: ps_model.predict(d)))\n", - "\n", - "df_dr.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "id": "18eeff30", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ATT: 1.6773180394442855\n" - ] - } - ], - "source": [ - "tr = df_dr.query(\"treated==1\")\n", - "co = df_dr.query(\"treated==0\")\n", - "\n", - "dy1_treat = (tr[\"delta_y\"] - tr[\"y_hat\"]).mean()\n", - "\n", - "w_cont = co[\"ps\"]/(1-co[\"ps\"])\n", - "dy0_treat = np.average(co[\"delta_y\"] - co[\"y_hat\"], weights=w_cont)\n", - "\n", - "print(\"ATT:\", dy1_treat - dy0_treat)" - ] - }, - { - "cell_type": "code", - "execution_count": 106, - "id": "f163f968", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array(['S'], dtype=object)" - ] - }, - "execution_count": 106, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "mkt_data[\"region\"].unique()" - ] - }, { "cell_type": "markdown", "id": "d63adcd3", @@ -3769,7 +3817,6 @@ "\n", "- 공변량과 결과 변수, 공변량과 처치 변수 간의 복잡한 비선형 관계를 머신러닝 모델로 예측한 후, 이 잔차(residuals)를 사용하여 DiD 효과를 추정하는 방법입니다.\n", "- 고차원적인 공변량을 유연하게 처리하고, 머신러닝의 예측력을 활용하여 잠재적인 편향을 줄입니다. 특히 이질적인 처치 효과를 다루는 데 강점이 있습니다.\n", - "- 유연성, 견고성, 고차원 데이터 처리 능력이 우수합니다.\n", "- 다만, 모델 복잡성이 증가하고, 구현 및 해석이 어려울 수 있습니다." ] }, @@ -3829,7 +3876,7 @@ " columns=['region', 'city'], \n", " drop_first=True)\n", "\n", - "# ② 공변량 선택 - post 제외! (DoubleMLDID가 자동으로 처리)\n", + "# ② 공변량 선택 - post 제외 (DoubleMLDID가 자동으로 처리)\n", "x_cols = [c for c in mkt_data_enc.columns \n", " if c not in ['downloads', 'treated', 'tau', 'date', 'post']]\n", "\n", @@ -4190,9 +4237,9 @@ "metadata": { "celltoolbar": "Tags", "kernelspec": { - "display_name": "Python (fack_cl)", + "display_name": "Python (kats_env)", "language": "python", - "name": "fack_cl" + "name": "kats_env" }, "language_info": { "codemirror_mode": { @@ -4204,7 +4251,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.9.21" }, "toc": { "base_numbering": 1, diff --git a/book/ate/propensity_score_and_dml.ipynb b/book/ate/propensity_score_and_dml.ipynb index c2e7639..a5b873a 100644 --- a/book/ate/propensity_score_and_dml.ipynb +++ b/book/ate/propensity_score_and_dml.ipynb @@ -11,11 +11,1959 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "- Matching\n", - "- IPW, AIPW, Doubly Robust Estimator\n", - "- Double Machine Learning (비모수 버전의 Regression 처럼 활용 가능)" + "- IPW, AIPW, Doubly Robust Estimator" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Propensity Score 추정" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "출처: https://matheusfacure.github.io/python-causality-handbook/11-Propensity-Score.html" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "IPW와 AIPW, Doubly Robust 모두 Propensity Score를 활용한 개념들이기 때문에 먼저 Propensity Score부터 간단하게 구해보겠습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import pandas as pd\n", + "import numpy as np\n", + "from causalinference import CausalModel" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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26371611.36092064101-0.5389751.433826-0.033161-0.9822741.591641
\n", + "
" + ], + "text/plain": [ + " schoolid intervention achievement_score success_expect ethnicity \\\n", + "259 73 1 1.480828 5 1 \n", + "3435 76 0 -0.987277 5 13 \n", + "9963 4 0 -0.152340 5 2 \n", + "4488 67 0 0.358336 6 14 \n", + "2637 16 1 1.360920 6 4 \n", + "\n", + " gender frst_in_family school_urbanicity school_mindset \\\n", + "259 2 0 1 -0.462945 \n", + "3435 1 1 4 0.334544 \n", + "9963 2 1 0 -2.289636 \n", + "4488 1 0 4 -1.115337 \n", + "2637 1 0 1 -0.538975 \n", + "\n", + " school_achievement school_ethnic_minority school_poverty school_size \n", + "259 0.652608 -0.515202 -0.169849 0.173954 \n", + "3435 0.648586 -1.310927 0.224077 -0.426757 \n", + "9963 0.190797 0.875012 -0.724801 0.761781 \n", + "4488 1.053089 0.315755 0.054586 1.862187 \n", + "2637 1.433826 -0.033161 -0.982274 1.591641 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = pd.read_csv(\"../data/matheus_data/learning_mindset.csv\")\n", + "data.sample(5, random_state=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Propensity Score 계산" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "categ = [\"ethnicity\", \"gender\", \"school_urbanicity\"]\n", + "cont = [\"school_mindset\", \"school_achievement\", \"school_ethnic_minority\", \"school_poverty\", \"school_size\"]\n", + "\n", + "data_with_categ = pd.concat([\n", + " data.drop(columns=categ), \n", + " pd.get_dummies(data[categ], columns=categ, drop_first=False)\n", + "], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "T = 'intervention'\n", + "Y = 'achievement_score'\n", + "X = data_with_categ.columns.drop(['schoolid', T, Y])\n", + "\n", + "ps_model = LogisticRegression(C=1e6).fit(data_with_categ[X], data_with_categ[T])\n", + "\n", + "data_ps = data.assign(propensity_score=ps_model.predict_proba(data_with_categ[X])[:, 1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## IPW 및 ATE 추정" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from sklearn.linear_model import LogisticRegression, Ridge\n", + "from causallib.estimation.standardization import Standardization\n", + "from causallib.estimation.ipw import IPW\n", + "from causallib.estimation.doubly_robust import AIPW" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 1) IPW로 가상(Pseudo) 모집단 생성 \n", + "\n", + "표본의 각 개체에 IPW 적용 \n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Original Sample Size 10391\n", + "Treated Population Sample Size 10387.611324207002\n", + "Untreated(Control) Population Sample Size 10391.506162305861\n" + ] + } + ], + "source": [ + "weight_t = 1/data_ps.query(\"intervention==1\")[\"propensity_score\"]\n", + "weight_nt = 1/(1-data_ps.query(\"intervention==0\")[\"propensity_score\"])\n", + "print(\"Original Sample Size\", data.shape[0])\n", + "print(\"Treated Population Sample Size\", sum(weight_t))\n", + "print(\"Untreated(Control) Population Sample Size\", sum(weight_nt))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 2) ATE 추정\n", + "\n", + "이제 Pseudo 집단에서의 Treat그룹과 Control그룹 각각의 Average Potential Outcome을 구하고, 이를 토대로 ATE를 추정합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Y1: 0.25981027799629486\n", + "Y0: -0.12903052783749974\n", + "ATE 0.38884080583379527\n" + ] + } + ], + "source": [ + "weight = ((data_ps[\"intervention\"]-data_ps[\"propensity_score\"]) /\n", + " (data_ps[\"propensity_score\"]*(1-data_ps[\"propensity_score\"])))\n", + "\n", + "y1_ipw = sum(data_ps.query(\"intervention==1\")[\"achievement_score\"]*weight_t) / len(data)\n", + "y0_ipw = sum(data_ps.query(\"intervention==0\")[\"achievement_score\"]*weight_nt) / len(data)\n", + "\n", + "ate_ipw = y1_ipw - y0_ipw\n", + "#ate = np.mean(weight * data_ps[\"achievement_score\"]) -> 이렇게도 ATE 계산 가능\n", + "\n", + "print(\"Y1:\", y1_ipw)\n", + "print(\"Y0:\", y0_ipw)\n", + "print(\"ATE\", np.mean(weight * data_ps[\"achievement_score\"]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**결과 해석**: \n", + "1. Treatment 받은 개인이 Treatment 받지 않은 동료보다 achievement_score가 0.38 표준편차 더 크다. (achievement_score는 표준화된 결과이기 때문에 표준 편차의 차이로 해석)\n", + "2. 아무도 Treatment 받지 않은 경우 일반적인 성취 수준이 현재보다 0.12 표준편차 더 낮다.\n", + "3. 모든 사람이 Treatment(세미나)를 받았다면 일반적인 성취 수준이 0.25 표준편차 더 높음." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "또한 ate를 나타내는 하나의 코드가 더 있다. \n", + "위의 코드에 주석처리한 부분을 그대로 실행해보면 똑같은 결과를 얻을 수 있는 것을 알 수 있다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "두 결과값이 같은 이유는 Matheus Facure(출처)의 책에서 자세히 설명되어 있다. \n", + "(참고: $ \\mathrm{ATE}=\\mathbb{E}\\!\\left[\\, Y\\,\\dfrac{T-e(X)}{e(X)\\,\\bigl(1-e(X)\\bigr)} \\right] $)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Doubly Robust Estimator & AIPW" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "출처: https://causallib.readthedocs.io/en/latest/causallib.estimation.doubly_robust.html?highlight=doubly" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import KFold\n", + "from causallib.estimation.ipw import IPW\n", + "from causallib.estimation.doubly_robust import AIPW\n", + "from causallib.estimation.standardization import Standardization\n", + "from sklearn.linear_model import LogisticRegression, LinearRegression, Ridge" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "Y = data[\"achievement_score\"]\n", + "T = data[\"intervention\"]\n", + "X = pd.get_dummies(\n", + " data[[\"school_mindset\",\"school_achievement\",\"school_ethnic_minority\",\n", + " \"school_poverty\",\"school_size\",\"ethnicity\",\"gender\",\"school_urbanicity\"]],\n", + " drop_first=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "DR Estimator는 결과모형과 IPW값이 모두 필요함 \n", + "- Y값(achievement_score)을 Ridge로 예측(L2 패널티 부여) \n", + "- IPW: 로지스틱 회귀 사용" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "outcome_model = Standardization(learner=Ridge(alpha=1.0))\n", + "weight_model = IPW(learner=LogisticRegression(max_iter=1000),\n", + " clip_min=0.01, clip_max=0.99, use_stabilized=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Propensity Score를 구할 때 max_iter을 충분히 큰 숫자(1000)으로 설정해 수치 최적화가 수렴할 수 있도록 설정합니다. \n", + "또한 클리핑을 사용하여 $ \\hat{e} $가 [0.01, 0.99]에서만 존재하도록 극단 가중치를 완화합니다 (use_stabilized = True). " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### AIPW 추정" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위에서 구한 PS와 IPW를 활용하여 AIPW를 구합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
AIPW(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, outcome_covariates=None, outcome_model=Standardization(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, encode_treatment=False, predict_proba=False,\n",
+       "                learner=Ridge()), overlap_weighting=False, predict_proba=False, weight_covariates=None,\n",
+       "     weight_model=IPW(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, clip_max=0.99, clip_min=0.01, use_stabilized=True, verbose=False,\n",
+       "    learner=LogisticRegression(max_iter=1000)))
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "AIPW(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, outcome_covariates=None, outcome_model=Standardization(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, encode_treatment=False, predict_proba=False,\n", + " learner=Ridge()), overlap_weighting=False, predict_proba=False, weight_covariates=None,\n", + " weight_model=IPW(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, clip_max=0.99, clip_min=0.01, use_stabilized=True, verbose=False,\n", + " learner=LogisticRegression(max_iter=1000)))" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dr = AIPW(outcome_model=outcome_model, weight_model=weight_model, overlap_weighting=False)\n", + "dr.fit(X, T, Y)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "μ1 (A=1): 0.30329930792804977\n", + "μ0 (A=0): -0.1471130386820095\n", + "ATE (DR, vanilla): 0.45041234661005924\n" + ] + } + ], + "source": [ + "pop_outcomes = dr.estimate_population_outcome(X, T, Y)\n", + "mu1_aipw, mu0_aipw = pop_outcomes[1], pop_outcomes[0]\n", + "ate_aipw = dr.estimate_effect(mu1_aipw, mu0_aipw, agg=\"population\")[\"diff\"]\n", + "print(\"μ1 (A=1):\", mu1_aipw)\n", + "print(\"μ0 (A=0):\", mu0_aipw)\n", + "print(\"ATE (DR, vanilla):\", ate_aipw)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**결과 해석**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "결과 해석은 IPW에서와 마찬가지로 생각하면 됩니다. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위에서 구한 AIPW는 Propensity Score의 Overlap이 충분히 확보되었을 때는 좋은 결과를 나타냅니다. \n", + "하지만 Overlap 구간이 불안정할 때는 Overlap-weighting = True이라는 기능을 활용해도 좋습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
AIPW(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, outcome_covariates=None, outcome_model=Standardization(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, encode_treatment=False, predict_proba=False,\n",
+       "                learner=Ridge()), overlap_weighting=True, predict_proba=False, weight_covariates=None,\n",
+       "     weight_model=IPW(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, clip_max=0.99, clip_min=0.01, use_stabilized=True, verbose=False,\n",
+       "    learner=LogisticRegression(max_iter=1000)))
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "AIPW(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, outcome_covariates=None, outcome_model=Standardization(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, encode_treatment=False, predict_proba=False,\n", + " learner=Ridge()), overlap_weighting=True, predict_proba=False, weight_covariates=None,\n", + " weight_model=IPW(_doc_link_module=sklearn, _doc_link_template=https://scikit-learn.org/1.5/modules/generated/{estimator_module}.{estimator_name}.html, _doc_link_url_param_generator=None, clip_max=0.99, clip_min=0.01, use_stabilized=True, verbose=False,\n", + " learner=LogisticRegression(max_iter=1000)))" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dr_overlap = AIPW(outcome_model=outcome_model,\n", + " weight_model=weight_model,\n", + " overlap_weighting=True)\n", + "dr_overlap.fit(X, T, Y)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ATE(DR, overlap-weighting): 0.3467411782171299\n" + ] + } + ], + "source": [ + "pop_outcomes_ov = dr_overlap.estimate_population_outcome(X, T, Y)\n", + "ate_ov = dr_overlap.estimate_effect(pop_outcomes_ov[1], pop_outcomes_ov[0],\n", + " agg=\"population\")[\"diff\"]\n", + "print(\" ATE(DR, overlap-weighting):\", ate_ov)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Summary" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " estimator μ1 μ0 ATE\n", + "0 IPW (manual) 0.259810 -0.129031 0.388841\n", + "1 AIPW (vanilla) 0.303299 -0.147113 0.450412\n", + "2 AIPW (overlap) NaN NaN 0.346741\n" + ] + } + ], + "source": [ + "results = pd.DataFrame([\n", + " [\"IPW (manual)\", y1_ipw, y0_ipw, ate_ipw],\n", + " [\"AIPW (vanilla)\", mu1_aipw, mu0_aipw, ate_aipw],\n", + " [\"AIPW (overlap)\", np.nan, np.nan, ate_ov]\n", + "], columns=[\"estimator\", \"μ1\", \"μ0\", \"ATE\"])\n", + "print(results)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위에서 사용한 방법에 따라 ATE 값이 다르게 나타나는 것을 알 수 있습니다. \n", + " \n", + "하지만 Overlap-Weighting 옵션을 사용한 경우에는 ATE가 아닌 ATO를 추정한 것이고 둘을 직접 비교하는 것은 맞지 않을 수 있습니다. \n", + " \n", + "분석의 목적이 ATE를 추정하는 것인지 ATO를 추정하는 것인지 확인한 후 적절히 사용하면 됩니다. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Robustness Check의 흐름\n", + "\n", + "각각의 수치에 대한 검증은 필수입니다. \n", + "어떤 수치가 더 Robust하게 추정이 된 걸까요? \n", + "\n", + "Yang et al., 2019, Gastrointest Endosc 및 Austin, 2021, Statistic in Medicine 논문을 참고하여 IPW에 대한 Robustness Check을 진행해보도록 하겠습니다. \n", + "순서는 다음과 같습니다.\n", + "\n", + "1) **IPW 가중 전, 후 |SMD| 변화 확인**\n", + "\n", + "2) **Propensity Score의 Overlap 확인**\n", + "\n", + "3) **IPW 가중 이후 ESS 및 VIF 확인**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "먼저 IPW로 구한 ATE의 신빙성을 테스트 해보겠습니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "출처: https://causallib.readthedocs.io/en/latest/causallib.evaluation.plots.plots.html" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "from causallib.evaluation.plots.plots import plot_propensity_score_distribution\n", + "from causallib.evaluation import evaluate" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### IPW 가중 전, 후 |SMD| 변화 확인" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "res = evaluate(weight_model, X, T, Y, cv=\"auto\")\n", + "res.plot_covariate_balance(kind=\"love\", phase=\"valid\", thresh=0.1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Weighted이후에 |SMD|가 더 줄어든 것을 보았을 때, Weighted 이후 밸런스가 개선되었음을 확인할 수 있습니다. \n", + "|SMD| < 0.1 이 목표" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Propensity Score Overlap\n", + "아래는 처음에 Logistic Regression으로 추정한 Propensity Score의 Distribution을 나타낸 것입니다." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_propensity_score_distribution(\n", + " propensity=data_ps['propensity_score'],\n", + " treatment=data_ps['intervention'],\n", + " reflect=False,\n", + " kde=False,\n", + " norm_hist=True,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "하지만 이는 하나의 데이터에 적합 및 예측을 동시에 하기 때문에 Overlap이 실제보다 좋아보일 수 있습니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "그렇다면 OOF 폴드 예측으로 얻은 PS 분포를 그려봅시다. \n", + "(cv = None -> 단일 적합, cv = \"auto\" -> 교차검증)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "res.plot_weight_distribution(phase=\"valid\", reflect=False, norm_hist=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "OOF로 검증해도 Propensity Score의 Overlap 및 Positivity가 양호한 것을 확인" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### IPW 가중치 분포 및 유효표본수(ESS)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ESS = 10354.68 (N = 10391) -> VIF = 1.0035\n" + ] + } + ], + "source": [ + "w = weight_model.compute_weights(X, T)\n", + "ESS = (w.sum()**2) / (w**2).sum()\n", + "N = len(w)\n", + "VIF = N / ESS\n", + "\n", + "print(f\"ESS = {ESS:.2f} (N = {N}) -> VIF = {VIF:.4f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'IPW weights (log y)')" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(); plt.hist(w, bins=40); plt.yscale('log'); plt.title('IPW weights (log y)')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "결과 해석\n", + "1) ESS와 N수가 거의 비슷한 것을 확인할 수 있음(VIF ≈ 1) -> 가중치가 고르게 퍼져있다\n", + "2) 히스토그램이 1 주변에 모여있고(= 가중치 과도하게 쏠리지 않음), 꼬리 부분도 완만(= 극단 가중치 거의 없음)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "다만 VIF와 Propensity Score Overlap이 정량적으로 얼마나 되어야 한다 라는 지표는 찾을 수 없었습니다. \n", + "\n", + "\n", + "데이터 및 분석의 맥락에 따라 다르게 지정하되, propensity score의 overlap이 약하다면 위에서 진행한 clipping 등의 방법을 적용해보면 좋습니다. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[참고자료]\n", + "- Yang, Jeff Y., et al. \"Propensity score methods to control for confounding in observational cohort studies: a statistical primer and application to endoscopy research.\" Gastrointestinal endoscopy 90.3 (2019): 360-369.\n", + "\n", + "- Austin, Peter C. \"Informing power and sample size calculations when using inverse probability of treatment weighting using the propensity score.\" Statistics in Medicine 40.27 (2021): 6150-6163.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Double/Debiased Machine Learning (비모수 버전의 Regression 처럼 활용 가능)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "코드 및 데이터 참조 출처: https://matheusfacure.github.io/python-causality-handbook/22-Debiased-Orthogonal-Machine-Learning.html" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "DML은 ATE와 CATE와 같은 인과적 모수를 구하는 하나의 프레임입니다. \n", + "\n", + "간략하게 소개하자면, DML은 복잡한 보조모형은 머신러닝으로 학습하고, 직교화(Neyman 점수)와 교차적합으로 bias를 상쇄해 ATE·CATE 같은 인과모수를 정규성으로 안정적으로 추정하는 프레임워크입니다. \n", + "이를 통해 인과 매개변수의 추정 절차와 성가신 매개변수의 추정 절차를 분리할 수 있는 장점을 지닌 방법입니다.\n", + "\n", + "코드와 함께 더 자세하게 알아보기 위해 계량경제학에서 자주 사용하는 데이터셋 중 하나인 **아이스크림 판매 데이터셋**을 활용해보겠습니다. \n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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tempweekdaycostpricesales
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" + ], + "text/plain": [ + " temp weekday cost price sales\n", + "0 17.3 6 1.5 5.6 173\n", + "1 25.4 3 0.3 4.9 196\n", + "2 23.3 5 1.5 7.6 207\n", + "3 26.9 1 0.3 5.3 241\n", + "4 20.2 1 1.0 7.2 227" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test = pd.read_csv(\"../data/matheus_data/ice_cream_sales_rnd.csv\")\n", + "train = pd.read_csv(\"../data/matheus_data/ice_cream_sales.csv\")\n", + "train.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Frisch-Waugh-Lovell 응용 DML" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "y = \"sales\"\n", + "T = \"price\"\n", + "X = [\"temp\", \"weekday\", \"cost\"]\n", + "\n", + "debias_m = LGBMRegressor(max_depth=3, verbosity=-1)\n", + "denoise_m = LGBMRegressor(max_depth=3, verbosity=-1)\n", + "\n", + "train_pred = train.assign(price_res = train[T] - cross_val_predict(debias_m, train[X], train[T], cv=5),\n", + " sales_res = train[y] - cross_val_predict(denoise_m, train[X], train[y], cv=5))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위의 코드는 FWL(Frisch-Waugh-Lovell) 정리($Y_i - \\mathbb{E}[Y_i\\mid X_i] = \\tau\\,(T_i - \\mathbb{E}[T_i\\mid X_i]) + \\varepsilon$)에서 $ \\mathbb{E}[Y_i\\mid X_i] $ 와 $\\mathbb{E}[T_i\\mid X_i] $를 머신러닝을 사용하여 추정합니다. \n", + "-> $Y_i - \\mathbb{E}[Y_i\\mid X_i] = \\tau\\,(T_i - \\mathbb{E}[T_i\\mid X_i]) + \\varepsilon$)에서 $\n", + "\n", + "이를 통해 Y와 T의 잔차를 추정할 때 교호작용(변수 간의 Interaction)과 비선형성을 모델링할 수 있고, 동시에 FWL 스타일의 직교화를 유지할 수 있게끔 합니다. \n", + "\n", + "변수명을 debias_m, 그리고 denoise_m이라고 지정한 이유는 무엇일까요? \n", + "\n", + "먼저 debias_m은 FWL 정리의 식에서 $T - M_t( = \\tilde{T})$부분으로, X의 모든 교란 편향이 모델에 의해 제거된 부분입니다.($M_t := \\mathbb{E}[T_i\\mid X_i]$를 머신러닝으로 추정한 모델) \n", + "즉, $\\tilde{T}$는 X에 직교하는, X로 인한 bias를 없앤 값입니다. \n", + "\n", + "마찬가지로 denoise_m은 FWL 식에서 $Y - M_y(= \\tilde{Y})$부분으로, Y에서 분산을 제거하는 부분입니다.($M_y := \\mathbb{E}[Y_i\\mid X_i]$를 머신러닝으로 추정한 모델) \n", + "즉, $\\tilde{Y}$는 X로 인한 모든 분산이 제거된 값입니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위에서 구한 모델을 활용하여 최종 ATE를 구해봅시다." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "
coef std err t P>|t| [0.025 0.975]
Intercept 0.0106 0.072 0.148 0.883 -0.131 0.152
price_res -3.9228 0.071 -54.962 0.000 -4.063 -3.783
" + ], + "text/latex": [ + "\\begin{center}\n", + "\\begin{tabular}{lcccccc}\n", + "\\toprule\n", + " & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]} \\\\\n", + "\\midrule\n", + "\\textbf{Intercept} & 0.0106 & 0.072 & 0.148 & 0.883 & -0.131 & 0.152 \\\\\n", + "\\textbf{price\\_res} & -3.9228 & 0.071 & -54.962 & 0.000 & -4.063 & -3.783 \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\\end{center}" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import statsmodels.formula.api as smf\n", + "\n", + "final_model = smf.ols(formula='sales_res ~ price_res', data=train_pred).fit()\n", + "final_model.summary().tables[1]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위와 같이 최종 ATE 추정 시에는 간단하게 선형으로 ATE를 추정할 수 있습니다. \n", + " \n", + "하지만 이는 결국 True Y값이 비선형적인 모습을 띄고 있다면 ATE를 제대로 추정하지 못하게 되는 단점을 가지고 있습니다. \n", + "\n", + "그래서 우리는 비모수 이중/탈편향 기계학습 방법을 통해 최종 모델까지도 비선형 ML을 사용하는 방법을 알아볼 것입니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 비모수 이중/탈편향 기계학습" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", "metadata": {}, @@ -33,7 +1981,7 @@ ], "metadata": { "kernelspec": { - "display_name": "base", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -47,9 +1995,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.7" + "version": "3.9.6" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 }