TSLS and LIML Estimators in Panels with Unobserved Shocks

Econometrics

Bin Jiang¹  Giovanni Forchini²  Bin Peng³ 

[1] Department of Econometrics and Business Statistics, Monash University, Clayton VIC 3800, Australia;Department of Economics, Umeå University, 901 87 Umeå, Sweden;Department of Economics, University of Bath, Bath BA2 7AY, UK;

关键词: two-stage least squares;    limited information maximum likelihood;    common shocks;   

DOI  :  10.3390/econometrics6020019

来源: DOAJ

【 摘 要 】

The properties of the two stage least squares (TSLS) and limited information maximum likelihood (LIML) estimators in panel data models where the observables are affected by common shocks, modelled through unobservable factors, are studied for the case where the time series dimension is fixed. We show that the key assumption in determining the consistency of the panel TSLS and LIML estimators, as the cross section dimension tends to infinity, is the lack of correlation between the factor loadings in the errors and in the exogenous variables—including the instruments—conditional on the common shocks. If this condition fails, both estimators have degenerate distributions. When the panel TSLS and LIML estimators are consistent, they have covariance-matrix mixed-normal distributions asymptotically. Tests on the coefficients can be constructed in the usual way and have standard distributions under the null hypothesis.

【 授权许可】

Unknown