for selection bias and shrinkage estimation and is to be contrasted with deconvolution. Simulation results confirm the … bias in the empirical distribution arising from the presence of noise. The leading bias in the empirical quantile function …

-parametric and easy to implement. Our approach can be connected to corrections for selection bias and shrinkage estimation and is to … bias in the empirical distribution arising from the presence of noise. The leading bias in the empirical quantile function … mean and variance have been derived. Given a closed-form expression for the bias, bias-corrected estimator of the …

Pseudo-panels allow estimation of panel models when only repeated cross-sections are available. This involves grouping … bias. We show that grouping can also create substantial aggregation bias, calling into question how well pseudo-panels can … mimic panel estimates. We create two metrics for assessing the grouping process, one for each potential source of bias. If …

to panel attrition, which are thought to worsen the bias resulting from initial nonresponse. However, under certain … conditions an initial wave nonresponse bias may vanish in later panel waves. We study such a "Fade away" of an initial … nonresponse bias in the context of regression analysis. By using a time series approach for the covariate and the error terms we …

The paper explores the effect of measurement errors on the estimation of a linear panel data model. The conventional … fixed effects estimator, which ignores measurement errors, is biased. By correcting for the bias one can construct …. -- Panel regression ; multiplicative measurement errors ; bias correction ; asymptotic variance ; disclosure control …