Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity

Abstract

This paper provides methods for flexibly capturing unobservable heterogeneity from longitudinal data in the context of an exponential family of distributions. The group memberships of individual units are left unspecified, and their heterogeneity is influenced by group-specific unobservable structures, as well as heterogeneous regression coefficients. We discuss a computationally efficient estimation method and derive the corresponding asymptotic theory. The established asymptotic theory includes verifying the uniform consistency of the estimated group membership. To test the heterogeneous regression coefficients within groups, we propose the Swamy-type test, which considers unobserved heterogeneity. We apply the proposed method to study the market structure of the taxi industry in New York City. Our method reveals interesting important insights from large-scale longitudinal data that consist of over 450 million data points.

About the presenter's visit

Prof Tomohiro Ando will be visiting the School of Economics on Friday 1^st April 2022.  While here he will be using room 520A Colin Clark Building.  If you would like to meet with Prof Ando or have lunch with him please contact Prof Valentin Zelenyuk who will be his host while at The University of Queensland.  Prof Zelenyuk can be contacted on v.zelenyuk@uq.edu.au.