期刊
ANNALS OF STATISTICS
卷 42, 期 1, 页码 142-170出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/13-AOS1183
关键词
Factor error structure; factors; factor loadings; maximum likelihood; principal components; within-group estimator; simultaneous equations
资金
- NSF [SES-0962410]
- NSFC [71201031]
- Humanities and Social Sciences of Chinese Ministry of Education [12YJCZH109]
- Direct For Social, Behav & Economic Scie
- Divn Of Social and Economic Sciences [0962410] Funding Source: National Science Foundation
This paper considers the maximum likelihood estimation of panel data models with interactive effects. Motivated by applications in economics and other social sciences, a notable feature of the model is that the explanatory variables are correlated with the unobserved effects. The usual within-group estimator is inconsistent. Existing methods for consistent estimation are either designed for panel data with short time periods or are less efficient. The maximum likelihood estimator has desirable properties and is easy to implement, as illustrated by the Monte Carlo simulations. This paper develops the inferential theory for the maximum likelihood estimator, including consistency, rate of convergence and the limiting distributions. We further extend the model to include time-invariant regressors and common regressors (cross-section invariant). The regression coefficients for the time-invariant regressors are time-varying, and the coefficients for the common regressors are cross-sectionally varying.
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