cpe/29.causal-impact-bayesian-structural-ts-models/

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cpe/29.causal-impact-bayesian-structural-ts-models/

Our topic for this session is Inferring causal impact using Bayesian structural time-series models (arXiv:1506.00356).
Abstract
Abstract of Inferring causal impact using Bayesian structural time-series models (arXiv:1506.00356):
An important problem in econometrics and marketing is to infer the causal impact that a designed market intervention has exerted on an outcome metric over time. This paper proposes to infer causal impact on the basis of a diffusion-regression state-space model that predicts the counterfactual market response in a synthetic control that would have occurred had no intervention taken place.

https://neuronstar.kausalflow.com/cpe/29.causal-impact-bayesian-structural-ts-models/