Index

• Introduction
• Folder structure
• Data cleaning
• Analysis steps

Project title

Collaborators: Giacomo Battiston, Jared Gars

LEAP example research repo with code and results

Data cleaning

Scripts go through each step, from cleaning raw data to analysis. The master .do files should completely replicate the analysis.

Pre-requisites

• Update: config.do
  This script defines path names; update location of working directory if needed
• Run: 0_setup.do
  This script installs dependencies (e.g., user-written Stata programs)
  It only needs to be run once and is not included in the master .do file

  Note: 0_setup.do defines a macro called adoUpdate; set it to 0 if you do not want to update all ado files

Link to Dropbox: https://www.dropbox.com/sh/w8zia84ubisk5md/AABdtfu-ToQAxlztwNJCjqIva?dl=0
Raw source files: "Dropbox/LEAP/data/"
Cleaned files: "Dropbox/LEAP/processed/"

Step 1: Clean raw data

The following stata script cleans auto.dta and other description: 1_cleaning.do

Input	Outputs
data/auto.dta	processed/auto_clean.dta

Analysis steps

Step 1: Run regressions

The following stata script runs regressions and outputs tables:

2_regressions.do

Input	Outputs
processed/auto_clean.dta	draft/tables/reg_price.tex

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Folder structure

The general repo structure looks as follows:

Code 
git/LEAP
├──README.md 
├──tutorial
│   └──gitting_started.md
└──analysis
    ├──masterDoFile.do
    ├──config.do       
        ├──scripts
           ├──stata
           └──python

Data
Dropbox/LEAP
├──data 
├──processed 
│  └──temp 
└──documentation
   └──questionnaire
   └──grants

Text
Dropbox/LEAP
└──draft
    ├──tables_and_figures.tex
    ├──tables
    ├──figures
    └──statistics

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