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 …

In our analysis we discuss several dynamic panel data estimators proposed in the literature and assess their … estimator is biased in the context of dynamic estimation. The estimators taking into account the resulting bias can be grouped … broadly into the class of instrumental estimators and the class of direct bias corrected estimators. The simulation results …

and size-distorted when some of the factors are weak. We propose estimators with improved rates of convergence and bias … interactive fixed effects. We use the obtained estimate to construct a bias-aware CI taking into account the remaining bias due to …

the German Socio-Economic Panel Study and the British Household Panel Survey. …

In the presence of selection bias, traditional estimators of pseudo panel data are inconsistent. In this paper, the … authors derive the conditions under which consistence is achieved in pseudo-panel estimation and propose a simple test of … selection bias. Specifically, they propose a Wald test for the null hypothesis that there is no selection bias. Under rejection …

This paper introduces bias-corrected estimators for nonlinear panel data models with both time invariant and time …

Many approaches to estimation of panel models are based on an average or integrated likelihood that assigns weights to … that such bias-reducing weights must depend on the data unless an orthogonal reparameterization or an essentially …. Finally, we show that random effects estimators are not bias reducing in general and discuss important exceptions. Three …

This paper introduces bias-corrected estimators for nonlinear panel data models with both time invariant and time …/selection bias. We then estimate the primary equation by fixed effects including an appropriately constructed control function from … both steps might employ nonlinear fixed effects procedures it is necessary to bias adjust the estimates due to the …

largely free of bias arising from an association between treatment status and observable variables. However, matching methods … are not robust against 'hidden bias' arising from unobserved variables that simultaneously affect assignment to treatment … resultieren. Matchingverfahren sind allerdings anfällig für Schätzverzerrungen aufgrund von 'hidden bias' durch unbeobachtete …