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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 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 and offer further performance gains that are attractive relative to existing alternatives.
Authors
Research Associate University College London and Brown University
Toru is a Research Associate of the IFS, a Professor of Economics at UCL and an Associate Professor in the Department of Economics at Brown University
Isaiah Andrews
Adam McCloskey
Working Paper details
- DOI
- 10.1920/wp.cem.2018.3118
- Publisher
- The IFS
Suggested citation
I, Andrews and T, Kitagawa and A, McCloskey. (2018). Inference on winners. London: The IFS. Available at: https://ifs.org.uk/publications/inference-winners-0 (accessed: 19 April 2024).
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