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propensity score

A Curated List of Our Postings on Technical Topics – Your One-Stop Shop for Methodology

David McKenzie's picture
Rather than the usual list of Friday links, this week I thought I’d follow up on our post by Guido Imbens yesterday on clustering and post earlier this week by Dave Evans on Hawthorne effects with a curated list of our technical postings, to serve as a one-stop shop for your technical reading.

Tools of the trade: The covariate balanced propensity score

Jed Friedman's picture

The primary goal of an impact evaluation study is to estimate the causal effect of a program, policy, or intervention. Randomized assignment of treatment enables the researcher to draw causal inference in a relatively assumption free manner. If randomization is not feasible there are more assumption driven methods, termed quasi-experimental, such as regression discontinuity or propensity score matching. For many of our readers this summary is nothing new. But fortunately in our “community of practice” new statistical tools are developed at a rapid rate.