arbiter
JournalsAccount

Optimal Shrinkage Estimation of Fixed Effects in Linear Panel Data Models

Soonwoo Kwon

Econometrica2026https://doi.org/10.3982/ecta22386article
FT50AJG 4*ABDC A*
Weight
0.37

Abstract

Shrinkage methods are frequently used to improve the precision of least squares estimators of fixed effects. However, widely used shrinkage estimators guarantee improved precision only under strong distributional assumptions. I develop an estimator for the fixed effects that obtains the best possible mean squared error within a class of shrinkage estimators. This class includes conventional shrinkage estimators and the optimality does not require distributional assumptions. The estimator has an intuitive form and is easy to implement. Moreover, the fixed effects are allowed to vary with time and to be serially correlated, in which case the shrinkage optimally incorporates the underlying correlation structure. I also provide a method to forecast fixed effects one period ahead in this setting.

1 citation

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.3982/ecta22386

Or copy a formatted citation

@article{soonwoo2026,
  title        = {{Optimal Shrinkage Estimation of Fixed Effects in Linear Panel Data Models}},
  author       = {Soonwoo Kwon},
  journal      = {Econometrica},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.3982/ecta22386},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Optimal Shrinkage Estimation of Fixed Effects in Linear Panel Data Models

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.