Which econometric method should you use for causal inference of health policy?

Healthcare Economist October 24, 2024
Jason Shafrin

TL;DR

A paper by Ress and Wild (2024) provide the following recommendations in answering this question.

1. When aiming to control for a large covariate set, consider using the superlearner to estimate nuisance parameters.
2. When employing the superlearner to estimate nuisance parameters, consider using doubly robust estimation approaches, such as AIPW and TMLE.
3. When faced with a small covariate set, consider using regression to estimate nuisance parameters.
4. When employing regression to estimate nuisance parameters, consider using singly robust estimation approaches, such as propensity score matching or IPW.

How did they arrive at these recommendations? To find out, read on.

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