Approximation formulae are developed for the bias of ordinary andgeneralized Least Squares Dummy Variable (LSDV) estimators in dynamicpanel data models. Results from Kiviet (1995, 1999) are extended tohigher-order dynamic panel data models with general covariancestructure. The focus is on...

Through Monte Carlo experiments the small sample behavior is examinedof various inference techniques for dynamic panel data models whenboth the time-series and cross-section dimensions of the data set aresmall. The LSDV technique and corrected versions of it are comparedwith IV and GMM...

This paper introduces two easy to calculate estimators with desirable properties for theautoregressive parameter in dynamic panel data models. The estimators are (nearly) unbiased andperform satisfactorily even for small samples in either the time-series or cross-section dimension.

This paper introduces a new estimator for the fixed effects dynamic panel data model withexogenous variables. This estimator does not share some of the drawbacks of recently developed IVand GMM estimators and has a good performance even in small samples. The nearly unbiased estimatoris derived...

The finite sample behaviour is analysed of particular least squares (LS) andmethod of moments (MM) estimators in panel data models with individual effectsand both a lagged dependent variabIe regressor and another explanatory variabIewhich may be affected by lagged feedbacks from the dependent...

The relative magnitudes are compared of successive terms in a higher-order asymptotic expansion of the bias of the LSDV estimator in dynamic panels. We find that the leading term accounts for the major part of the actual bias in small samples. This implies that bias correction procedures can be...