Operations Management and Econometrics
IV Estimation of Factor Residuals
Dr Vasilis Sarafidis, The Discipline of Operations Management and Econometrics, The University of Sydney
13th Aug 2010 11:00 am - Room 498, Merewether Building
This paper considers panel data regression models with residuals generated by a multi-factor error structure and regressors that are not necessarily strongly exogenous. In such cases, the standard dynamic panel estimators fail to provide consistent estimates of the parameters. We propose a new estimation procedure, based on instrumental variables, which retains the traditional attractive features of method of moments estimators. The novelty of our approach is that we introduce new parameters to represent the unobserved covariances between the instruments and the factor component of the residual; these parameters are typically estimable when N is large. Some important estimation and identification issues are studied in detail. Our estimator permits unit roots and is robust to cases where the variance of the factor loadings is large. In the fixed-effects case, we show that modified versions of our estimator are asymptotically equivalent to the popular Arellano-Bond, Ahn-Schmidt and system GMM estimators. Therefore, our approach provides a unifying treatment of existing panel estimators. The finite-sample performance of our estimator is investigated using simulated data. The results show that proposed method produces reliable estimates of the parameters over various parametrizations.