We examine the asymptotic efficiency of OLS and IV estimators in a simple dynamic structural model with a constant and two explanatory variables: the lagged dependent variable and an explanatory variable, which is also autoregressive and may include lagged or instantaneous feedbacks from the...

In practice structural equations are often estimated by least-squares, thus neglecting any simultaneity. This paper reveals why this may often be justifiable and when. Assuming data stationarity and existence of the first four moments of the disturbances we find the limiting distribution of the...

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...

By combining two alternative formulations of a test statistic with two alternative resamplingschemes we obtain four different bootstrap tests. In the context of static linear regression modelstwo of these are shown to have serious size and power problems, whereas the remaining two areadequate...

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...