Eliaz, Kfir;
Spiegler, Ran;
(2022)
On incentive-compatible estimators.
Games and Economic Behavior
, 132
pp. 204-220.
10.1016/j.geb.2022.01.002.
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Abstract
An estimator is incentive-compatible (for a given prior belief regarding the model's true parameters) if it does not give an agent an incentive to misreport the value of his covariates. Eliaz and Spiegler (2019) studied incentive-compatibility of estimators in a setting with a single binary explanatory variable. We extend this analysis to penalized-regression estimation in a simple multi-variable setting. Our results highlight the incentive problems that are created by the element of variable selection/shrinkage in the estimation procedure.
| Type: | Article |
|---|---|
| Title: | On incentive-compatible estimators |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.geb.2022.01.002 |
| Publisher version: | https://doi.org/10.1016/j.geb.2022.01.002 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Incentive-compatible estimators, Penalized regression, Lasso, Online platforms |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics UCL > Provost and Vice Provost Offices > UCL SLASH UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10144954 |
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