Linear regression for panel with unknown number of factors as interactive fixed effects

Hyungsik Moon () and Martin Weidner

No CWP35/14, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: 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 e ffects. 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 crosssectional units jointly go to infi nity. 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 eff ects consistently. Supplementary material for this paper is available here.

Date: 2014-08-21
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Related works:
Journal Article: Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects (2015)
Working Paper: Linear regression for panel with unknown number of factors as interactive fixed effects (2013)
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