@article{6775295a443340198ecd25ad3397cc8a,
title = "On incentive-compatible estimators",
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.",
keywords = "Incentive-compatible estimators, Lasso, Online platforms, Penalized regression",
author = "Kfir Eliaz and Ran Spiegler",
note = "Publisher Copyright: {\textcopyright} 2022 Elsevier Inc.",
year = "2022",
month = mar,
doi = "10.1016/j.geb.2022.01.002",
language = "אנגלית",
volume = "132",
pages = "204--220",
journal = "Games and Economic Behavior",
issn = "0899-8256",
publisher = "Academic Press Inc.",
}