Year: 2025
Type: preprint
Abstract: We consider panel data models where coefficients change smoothly over time and follow a latent group structure, being homogeneous within but heterogeneous across groups. To jointly estimate the group membership and group-specific coefficient trajectories, we propose FUSE-TIME, a pairwise adaptive group fused-Lasso estimator combined with polynomial spline sieves. We establish consistency, derive the asymptotic distributions of the penalized sieve estimator and its post-selection version, and show oracle efficiency. Monte Carlo experiments demonstrate strong finite-sample performance in terms of estimation accuracy and group identification. An application to the CO2 intensity of GDP highlights the relevance of addressing both cross-sectional heterogeneity and time-variance in empirical exercises.
Authors: Haimerl, Paul, Smeekes, Stephan, Wilms, Ines
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6891829592
Cites:
Cited by:
Related to: