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 CWP31/18, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

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.

Keywords: Winner's Curse; Selective Inference (search for similar items in EconPapers)
JEL-codes: C12 C13 (search for similar items in EconPapers)
Date: 2018-05-10
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (10)

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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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