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 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 crosssectional 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.
Original language  English 

Pages (fromto)  15431579 
Number of pages  37 
Journal  Econometrica 
Volume  83 
Issue number  4 
DOIs 

Publication status  Published  2015 Jul 1 
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All Science Journal Classification (ASJC) codes
 Economics and Econometrics
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Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects. / Moon, Hyungsik Roger; Weidner, Martin.
In: Econometrica, Vol. 83, No. 4, 01.07.2015, p. 15431579.Research output: Contribution to journal › Comment/debate
TY  JOUR
T1  Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects
AU  Moon, Hyungsik Roger
AU  Weidner, Martin
PY  2015/7/1
Y1  2015/7/1
N2  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 crosssectional 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.
AB  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 crosssectional 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.
UR  http://www.scopus.com/inward/record.url?scp=84938149024&partnerID=8YFLogxK
UR  http://www.scopus.com/inward/citedby.url?scp=84938149024&partnerID=8YFLogxK
U2  10.3982/ECTA9382
DO  10.3982/ECTA9382
M3  Comment/debate
AN  SCOPUS:84938149024
VL  83
SP  1543
EP  1579
JO  Econometrica
JF  Econometrica
SN  00129682
IS  4
ER 