manner, we propose a model-based (semiparametric)bootstrap method to approximate critical values of the test and verify its …

disturbances,where the heteroskedasticity and autocorrelation are of unknown form. A particular version of the wild bootstrap can … dependent wild bootstrap. Here, we extend this new method, and link it to the well-known HAC covariance estimator, in much the … same way as one can link the wild bootstrap to the HCCME. It works very well even with sample sizes smaller than 50, and …

asymptotically. Such bands are based on a certain bootstrap procedure from the multiple-testing literature. We compare the finite … endogenizing the lag order in our bootstrap procedure on the finite-sample properties. Furthermore, an empirical application to a …

asymptotically. Such bands are based on a certain bootstrap procedure from the multiple testing literature. We compare the finite … endogenizing the lag order in our bootstrap procedure on the finite-sample properties. Furthermore, an empirical application to a …

heteroskedastic SVAR-GARCH model and propose a bootstrap-based inference procedure on structural impulse responses. We compare the … finite-sample properties of our bootstrap method with those of two competing bootstrap methods via extensive Monte Carlo …

bootstrap methods. Specifically, since standard wild bootstrap procedures deliver inconsistent inference, we propose a local … Gaussian (LG) bootstrap, establish its first‐order asymptotic validity, and use Edgeworth expansions to show that the LG … bootstrap inference achieves second‐order asymptotic refinements. Moreover, we provide new Laplace transform‐based estimators of …