Identification in Models for Matched Panel Data with Two-Sided Random Effects

Abstract

This paper is concerned with models for matched worker-firm data in the presence of both worker and firm heterogeneity. We show that models with complementarity and sorting can be nonparametrically identified from short panel data while treating both worker and firm heterogeneity as discrete random effects. This paradigm is different from the framework of Bonhomme, Lamadon and Manresa (2019a), where identification results are derived under the assumption that worker effects are random but firm heterogeneity is observed. Our identification approach is constructive and our results appear to be the first of their kind in the context of matched panel data problems.

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Reference

Koen Jochmans, “Identification in Models for Matched Panel Data with Two-Sided Random Effects”, TSE Working Paper, n. 25-1649, June 2025, revised October 2025.