the 2SLS and the MLIML estimators.The approximations to the bias are then used to develop less biased estimators whose …

convergence rate of the QML estimators has not been formally studied, and methods for correcting finite sample bias of the QML … estimators have not been given. This paper fills in these gaps. Of the two, bias correction is particularly important to the … those for the SLD model in terms of the rate of convergence and the magnitude of bias. Monte Carlo results show that the …

average beer elasticities for heterogeneity, dependence, and publication selection bias. A sample of 191 estimates is obtained … estimates per study, author-restricted samples, and author-specific variables. Publication bias is addressed using a funnel … graph, trim-and-fill, and Egger's intercept model. Heterogeneity and selection bias are examined jointly in meta …

This paper studies an alternative bias correction for the M-estimator, which is obtained by correcting the moment … equations in the spirit of Firth (1993). In particular, this paper compares the stochastic expansions of the analytically-bias …-step bias correction by using the bias correction of moment equations. This finding suggests that the comparison between the one …

We assess the bias and the efficiency of state-of-the-art dynamic panel data estimators by means of model-based Monte …

This paper develops the approximate bias of the ordinary least squares estimator of the mean reversion parameter in … whether the initial condition is fixed or random. The approximate bias is used to construct a bias corrected estimator. The … performance of the approximate bias and the bias corrected estimator is examined using simulated data …