Abstract: We show that propensity score matching (PSM), an enormously popular method of preprocessing data for causal inference, often accomplishes the opposite of its intended goal — thus increasing
When making causal inferences, post-treatment confounders complicate analyses of time-varying treatment effects. Conditioning on these variables naively to estimate marginal effects may inappropriatel
Ishimaru, Shoya, (2024) “Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects.” Review of Economics and Statistics 106:2, 505–520.
Some background materials and R code for the paper: Li, F., Ding, P. and Mealli, F. (2023). Bayesian causal inference: a critical review. Philosophical Transactions of the Royal Society A, 381, 202201