Frank Schorfheide - University of Pennsylvania

Shrinkage Estimation of Fixed Effects on Matched Data

Abstract

This paper develops an empirical Bayes estimator for a panel data model with two- way fixed effects. The hyperparameters that control the variance (degree of shrinkage) and the location of the prior are determined by minimizing an unbiased risk estimate. We established optimality of the proposed estimator by showing that it asymptotically attains the same loss as an oracle estimator with a hyperparameter that is chosen based on the knowledge of the fixed effects. In a Monte Carlo study we show that the proposed estimator outperforms a number of competitors, including the least squares estimator. The method will be applied to the estimation of teacher values-added from a linked student-teacher data set obtained from the North Carolina Education Research Data Center.

Additional information:

  • Speaker: Frank Schorfheide
  • Time: Thursday, 14.12.2023, 16:00 - 17:00
  • Location: Faculty Room
  • Further links:
  • Organizer: Statistics Group
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