Clustering for Multi-Dimensional Heterogeneity with an Application to Production Function Estimation

Xu Cheng (), Frank Schorfheide () and Peng Shao ()
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Xu Cheng: University of Pennsylvania
Frank Schorfheide: University of Pennsylvania
Peng Shao: Auburn University

PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania

Abstract: This paper studies the estimation of multi-dimensional heterogeneous parameters in a nonlinear panel data model with endogeneity. These heterogeneous parameters are modeled with group patterns. Through estimating multiple memberships for each unit, the proposed method is robust to limited information from a subset of clusters: either due to sparse interactions of characteristics or weak identification of some combinations of heterogeneous parameters. We estimate the memberships along with the group specific and common parameters in a nonlinear GMM framework and derive their large sample properties. Finally, we apply this approach to the estimation of heterogeneous firm-level production functions parameters which are converted into markup estimates.

Keywords: Clustering; GMM; K-means; Panel Data; Production Function Estimation (search for similar items in EconPapers)
JEL-codes: C13 C23 D22 D24 E23 (search for similar items in EconPapers)
Pages: 54 pages
Date: 2025-06-19
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