-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than … in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias …

of bias of (generalized) MMestimators tends to increase with the number of moment conditions exploited. Forvarious … estimation procedures we examine the analytical effects of feedbacks andother model characteristics such as prominence of … feedbacks none of the techniques examined dominates. However, asimple bias corrected LS estimator which presupposes strict …

Approximation formulae are developed for the bias of ordinary andgeneralized Least Squares Dummy Variable (LSDV … with general covariancestructure. The focus is on estimation of both short- and long-runcoefficients. The results show that … proper modelling of thedisturbance covariance structure is indispensable. The biasapproximations are used to construct bias …

corrected versions of it are comparedwith IV and GMM regarding: coefficient bias, accuracy of varianceestimators - both of the … disturbances and of the coefficientestimators - and the actual size of coefficient tests. A reasonablysimple and consistent bias …

We propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order … reveals an intuitive formula for the remaining second order bias which is useful in empirical analyses. We analyze the … it reduces a considerable share of the bias due to grouping. …

-systematic impact of omitted variable bias in primary studies. Our results show that the mixed effects estimator is to be preferred to … non-systematic impact of omitted variable bias, using the mixed effects estimator may be suboptimal. We also address the … increasing the power of hypothesis testing than primary study sample size. …