TSLS and LIML estimators in panels with unobserved shocks

Artikel

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 6 ; Year: 2018 ; Issue: 2 ; Pages: 1-12 ; Basel: MDPI

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation ; Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
• Subject: two-stage least squares ; limited information maximum likelihood ; common shocks

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Forchini, Giovanni ; Jiang, Bin ; Peng, Bin
• Event: Veröffentlichung
• (who): MDPI
• (where): Basel
• (when): 2018

Further information

• DOI: doi:10.3390/econometrics6020019
• Handle: http://hdl.handle.net/10419/195456
• Last update: 10.03.2025, 11:41 AM CET