Multi-dimensional Latent Group Structures with Heterogeneous Distributions
33 Pages Posted: 8 Jul 2020 Last revised: 20 May 2021
Date Written: June 1, 2020
This paper aims to identify the multi-dimensional latent grouped heterogeneity of distributional effects. We consider a panel quantile regression model with additive cross-section and time fixed effects. The cross-section effects and quantile slope coefficients are both characterized by grouped patterns of heterogeneity, but each unit can belong to different groups for cross-section effects and slopes. We propose a composite-quantile approach to jointly estimate multi-dimensional group memberships, slope coefficients, and fixed effects. We show that using multiple quantiles improves clustering accuracy if memberships are quantile-invariant. We apply the methods to examine the relationship between managerial incentives and risk-taking behavior.
Keywords: Composite quantile estimation, distributional heterogeneity, latent groups, panel quantile regressions, two-way fixed effects
JEL Classification: C31, C33, C38, G31, J33
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