Inference on winners

Isaiah Andrews (), Toru Kitagawa () and Adam McCloskey
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Isaiah Andrews: Institute for Fiscal Studies and Harvard University
Toru Kitagawa: Institute for Fiscal Studies and University College London

No CWP73/18, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: Many empirical questions 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 confidence intervals are unreliable. This paper develops optimal confidence 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 confidence sets to offer further performance gains relative to existing alternatives.

Keywords: winner's curse; selective inference (search for similar items in EconPapers)
Date: 2018-12-31
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Inference on Winners* (2024)
Working Paper: Inference on winners (2020)
Working Paper: Inference on Winners (2019)
Working Paper: Inference on winners (2018)
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