order. Combining these equations with sample splitting yields higher-order bias-corrected estimators of target parameters …

We consider the bias of the 2SLS estimator in the linear instrumental vari-ables regression with one endogenous … regressor only. By using asymptotic expansion techniques we approximate 2SLS coefficient estimation bias under various scenarios … regarding the number and strength of instruments.The resulting approximation encompasses existing bias approximations, which are …

sources of asymptotic bias of the LS estimator: bias due to correlation or heteroscedasticity of the idiosyncratic error term …, and bias due to predetermined (as opposed to strictly exogenous) regressors. We provide an estimator for the bias and a … bias corrected LS estimator for the case where idiosyncratic errors are independent across both panel dimensions …

parameter problem. We develop analytical and jackknife bias corrections for nonlinear models with both individual and time … effects introduce additional incidental parameter bias. As the existing bias corrections apply to models with only individual …, probit, ordered probit, Tobit and Poisson models. Our analysis therefore extends the use of large-T bias adjustments to an …

parameter problem. We develop analytical and jackknife bias corrections for nonlinear models with both individual and time … effects introduce additional incidental parameter bias. As the existing bias corrections apply to models with only individual … large-T bias adjustments to an important class of models. We also analyze the properties of fixed effects estimators of …

well additional bias terms in the asymptotic expansion of the estimator. If R does not increase as fast as T, the leading … bias term dominates the leading variance term and the asymptotic distribution might not be centered at 0. This paper … suggests methods to eliminate the leading bias term from the asymptotic expansion. Furthermore, an adjustment to the asymptotic …

Standard approaches to constructing nonparametric confidence bands for functions are frustrated by the impact of bias … overcome this problem it is common practice to either undersmooth, so as to reduce the impact of bias, or oversmooth, and … thereby introduce an explicit or implicit bias estimator. However, these approaches, and others based on nonstandard smoothing …