This survey gives a brief overview of the literature on the difference-in-difference (DiD) estimation strategy and discusses major issues using a treatment effect perspective. In this sense, this survey gives a somewhat different view on DiD than the standard textbook discussion of the...

This survey gives a brief overview of the literature on the difference-in-difference (DiD) estimation strategy and discusses major issues using a treatment effects perspective. In this sense, this survey gives a somewhat different view on DiD than the standard textbook discussion of the DiD...

The aim of the paper is to relax distributional assumptions on the error terms, often imposed in parametric sample selection models to estimate causal effects, when plausible exclusion restrictions are not available. Within the principal stratification framework, we approximate the true...

Over two dozen different terms for identification appear in the econometrics literature, including set identification, causal identification, local identification, generic identification, weak identification, identification at infinity, and many more. This survey: 1. gives a new framework...

Past research on the associations between area-level/contextual social capital and health has produced conflicting evidence. However, interpreting this rapidly growing literature is difficult because estimates using conventional regression are prone to major sources of bias including residual...

This article aims to answer to what extent fertility has a causal effect on households’ economic wellbeing—an issue that has received considerable interest in development studies and policy analysis. However, only recently has this literature begun to give importance to adequate modelling...

John Snow and causal inference -- RStudio and R -- Regression and simulation -- Potential outcomes -- Causal graphs -- Experiments -- Matching -- Instrumental Variables -- Regression Discontinuity Design -- Panel Data and fixed effects -- Difference-in-Differences -- Integrating and generalizing...