Paul Haimerl, Stephan Smeekes, Ines Wilms
arXiv 29 Mar 2025 · Econometrics
arXiv:2503.23165 · PDF · Extracted main text
We introduce a panel data model where coefficients vary both over time and the 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. We derive the asymptotic distributions of the penalized and post-selection estimators and show their oracle efficiency. 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.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Su, Liangjun and Shi, Zhentao and Phillips, Peter C. B (2016) Identifying Latent Structures in Panel Data | 0.950 | 7 | 4 | 86% |
| 2 | Junhui Qian and Liangjun Su (2016) Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso | 0.909 | 8 | 4 | 75% |
| 3 | Ali Mehrabani (2023) Estimation and identification of latent group structures in panel data | 0.874 | 15 | 6 | 67% |
| 4 | Bonhomme, Stéphane and Manresa, Elena (2015) Grouped Patterns of Heterogeneity in Panel Data | 0.843 | 3 | 3 | 100% |
| 5 | Liangjun Su and Xia Wang and Sainan Jin (2019) Sieve Estimation of Time-Varying Panel Data Models With Latent Structures | 0.783 | 25 | 8 | 48% |
| 6 | Jianhua Z. Huang and Colin O. Wu and Lan Zhou (2004) POLYNOMIAL SPLINE ESTIMATION AND INFERENCE FOR VARYING COEFFICIENT MODELS WITH LONGITUDINAL DATA | 0.754 | 7 | 4 | 43% |
| 7 | Haimerl, Paul and Smeekes, Stephan and Wilms, Ines and Mehrabani, Ali (2025) PAGFL: Joint Estimation of Latent Groups and Group-Specific Coefficients in Panel Data Models self | 0.737 | 4 | 4 | 50% |
| 8 | Zongwu Cai (2007) Trending time-varying coefficient time series models with serially correlated errors | 0.644 | 2 | 2 | 100% |
| 9 | Hannes Leeb and Benedikt M. Pötscher (2008) Sparse estimators and the oracle property, or the return of Hodges’ estimator | 0.644 | 2 | 2 | 100% |
| 10 | Peter M. Robinson (2012) Nonparametric trending regression with cross-sectional dependence | 0.644 | 2 | 2 | 100% |
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