Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects

• 成果类型: Article
• 署名作者: Moon, Hyungsik Roger; Weidner, Martin
• 署名单位: University of Southern California; University of Southern California; Yonsei University; University of London; University College London
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA9382
• 发表日期: 2015
• 页码: 1543-1579
• 关键词: PRINCIPAL COMPONENTS; LARGEST EIGENVALUE; SPECTRAL DISTRIBUTIONS; RANDOM MATRICES; DIVORCE RATES; data models; CONVERGENCE; marriage; eigenvectors; limit

摘要

In this paper, we study the least squares (LS) estimator in a linear panel regression model with unknown number of factors appearing as interactive fixed effects. Assuming that the number of factors used in estimation is larger than the true number of factors in the data, we establish the limiting distribution of the LS estimator for the regression coefficients as the number of time periods and the number of cross-sectional units jointly go to infinity. The main result of the paper is that under certain assumptions, the limiting distribution of the LS estimator is independent of the number of factors used in the estimation as long as this number is not underestimated. The important practical implication of this result is that for inference on the regression coefficients, one does not necessarily need to estimate the number of interactive fixed effects consistently.