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Inference on winners

Authors: Isaiah Andrews , Toru Kitagawa and Adam McCloskey
Date: 10 May 2018
Type: cemmap Working Paper, CWP31/18
DOI: 10:1920/wp.cem.2018.3118

Abstract

Many questions in econometrics can be cast as inference on a parameter selected through optimization. For example, researchers may be interested in the effectiveness of the best policy found in a randomized trial, or the best-performing investment strategy based on historical data. Such settings give rise to a winner's curse, where conventional estimates are biased and conventional confi dence intervals are unreliable. This paper develops optimal con fidence sets and median-unbiased estimators that are valid conditional on the parameter selected and so overcome this winner's curse. If one requires validity only on average over target parameters that might have been selected, we develop hybrid procedures that combine conditional and projection con fidence sets and offer further performance gains that are attractive relative to existing alternatives.

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