, residual-based bootstrap methods are introduced for asymptotically refined approximations to the finite sample critical values … conditions are not fully met, bootstrap may lead to unstable critical values that change significantly with the alternative …, whereas when all conditions are met, bootstrap critical values are very stable, approximate much better the finite sample …

In this paper, we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient … hypothesis, a sequence of local alternatives and global alternatives, and propose a wild-bootstrap procedure to obtain the … bootstrap p-values. A set of Monte Carlo simulations are conducted to evaluate the finite sample behavior of both the estimator …

We propose an instrumental variable quantile regression (IVQR) estimator for spatial autoregressive (SAR) models. Like …

linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to …

bootstrap procedure that leads to a robust estimate of the variance-covariance matrix. Monte Carlo results reveal that these … estimates perform well in finite samples, and that the gains by using bootstrap procedure for inference can be enormous. …

, we propose a bootstrap procedure to obtain the bootstrap p-value. A small set of Monte Carlo simulations illustrates that …