applications, small sample bias in the estimation of autoregressive coefficients is transmitted to the recoloring filter, leading … the effects of small sample autoregressive bias. Moreover, a commonly-used restriction rule on the prewhitening estimates …

applications, small sample bias in the estimation of autoregressive coefficients is transmitted to the recoloring filter, leading … the effects of small sample autoregressive bias. Moreover, a commonly-used restriction rule on the prewhitening estimates …

bias of the robust standard error estimator. This approach contrasts with the conventional bandwidth choice rule for … squared asymptotic bias. It turns out that the optimal bandwidth for interval estimation has a different expansion rate and is …

lag augmented VAR (LA-VAR) estimator to exclude the quasiasymptotic bias, which is associated with the term Op(T-1), using …

covariates. Analytic expressions for the first-order bias and second-order mean squared error function for the maximum likelihood … results for the single covariate case. For various data distributions, the bias of the estimator is signed the same as the … covariate’s coefficient, and both the absolute bias and the mean squared errors increase symmetrically with the absolute value …

parameters problem, that is, the asymptotic bias in the estimation of typical fixed effects panel models generally results in … estimator after analytical bias correction is robust to the incidental parameters bias and reduces the bias order from O(T−1) to … results suggest that, in the static case, the bias corrected estimator performs comparably to the quasi-maximum likelihood …

generalized Rayleigh distribution family. Using these expressions to bias-correct the estimators is found to be extremely … effective in terms of bias reduction, and generally results in a small reduction in relative mean squared error. In general, the … analytic bias-corrected estimators are also found to be superior to the alternative of bias-correction via the bootstrap. …