Evaluating Ex Ante Counterfactual Predictions Using Ex Post Causal Inference
We derive a formal, decision-based method for comparing the performance of counterfactual treatment regime predictions using the results of experiments that give relevant information on the distribution of treated outcomes. Our approach allows us to quantify and assess the statistical significance of differential performance for optimal treatment regimes estimated from structural models, extrapolated treatment effects, expert opinion, and other methods. We apply our method to evaluate optimal treatment regimes for conditional cash transfer programs across countries where predictions are generated using data from experimental evaluations in other countries and pre-program data in the country of interest.

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docs.google.com/spreadsheets/d/1B5eDfd-p_oFWK5FiVvLebyit0ZQTQ6lkjUzbAFYDhUw/edit#gid=0

Link to paper:
arxiv.org/abs/1806.07016
Date: 31 May 2019, 14:15 (Friday, 5th week, Trinity 2019)
Venue: Manor Road Building, Manor Road OX1 3UQ
Venue Details: Seminar Room C
Speaker: Michael Gechter (Penn State University)
Organising department: Department of Economics
Part of: Nuffield Econometrics Seminar
Booking required?: Not required
Audience: Members of the University only
Editor: Melis Clark