A1324
Title: Estimation of latent group structures in time-varying panel data models
Authors: Paul Haimerl - Aarhus University (Denmark) [presenting]
Ines Wilms - Maastricht University (Netherlands)
Stephan Smeekes - Maastricht University (Netherlands)
Abstract: The purpose is to introduce a panel data model where coefficients vary both over time and over cross-section. Slope coefficients change smoothly over time and follow a latent group structure, being homogeneous within but heterogeneous across groups. The group structure is identified using a pairwise adaptive group fused-Lasso penalty. The trajectories of time-varying coefficients are estimated via polynomial spline functions. The asymptotic distributions of the penalized and post-selection estimators are derived, and their oracle efficiency is shown. A simulation study demonstrates excellent finite sample properties. An application to the emission intensity of GDP highlights the relevance of addressing cross-sectional heterogeneity and time variance in empirical settings.
