Oxford Events, the new replacement for OxTalks, will launch on 16th March. The two-week OxTalks freeze period starts on Monday 2nd March. During this time, there will be no facility to publish or edit events. The existing OxTalks site will remain available to view during this period. Once Oxford Events launches, you will need a Halo login to submit events. Full details are available on the Staff Gateway.
Estimates of treatment effects using observational data can be biased due to confounding, model misspecification, and other reasons. A placebo test offers a complementary diagnostic for evaluating these threats to inference by checking for a relationship that should be found in the data if the main estimates were biased, but should be absent otherwise. Drawing on a comprehensive survey of recent empirical work in political science, this paper defines placebo tests, introduces a typology of tests, and analyzes what makes them informative (both in ideal and non-ideal circumstances). We discuss examples of placebo tests that effectively address different types of bias; we also point out tests and types of tests that we argue are largely uninformative, and we highlight the problem of null hacking in the design of placebo tests.
