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

Xu Cheng (), Frank Schorfheide and Peng Shao ()
Additional contact information
Xu Cheng: University of Pennsylvania
Peng Shao: Boston 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 sparse interactions; in other words, certain combinations of unobserved features are less common compared to other combinations. 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 production function and re-evaluate the trajectory of the aggregate markup.

Keywords: Clustering; GMM; K-mean; 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: 53 pages
Date: 2023-09-19
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://economics.sas.upenn.edu/system/files/worki ... per%20Submission.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pen:papers:23-016

Access Statistics for this paper

More papers in PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania 133 South 36th Street, Philadelphia, PA 19104. Contact information at EDIRC.
Bibliographic data for series maintained by Administrator ().