This paper develops a consistent heteroskedasticity robust Lagrange Multiplier (LM) type specification test for …. Compared with the recent test in Gupta (2018), I use a different way of accounting for heteroskedasticity. I demonstrate using …

functionals of kernel-type estimators (1 < p < ∞) and is easy to implement in general, mainly due to its recourse to the bootstrap … method. The bootstrap procedure is based on nonparametric bootstrap applied to kernel-based test statistics, with estimated … "contact sets". We provide regularity conditions under which the bootstrap test is asymptotically valid uniformly over a large …

coverage for small sample sizes, a simple bootstrap procedure is designed based on the leading term of the Bahadur … demonstrated that the bootstrap procedure considerably outperforms the asymptotic bands in terms of coverage accuracy. Finally, the … bootstrap confidence corridors are used to study the efficacy of the National Supported Work Demonstration, which is a …

the test statistics or using bootstrap methods to obtain critical values. Our simulation results indicate that our tests …

tails and time dependence in the return data. In particular, we will promote a studentized time series bootstrap procedure …

In the presence of conditional heteroskedasticity, inference about the coefficients in a linear regression model these … days is typically based on the ordinary least squares estimator in conjunction with using heteroskedasticity consistent … standard errors. Similarly, even when the true form of heteroskedasticity is unknown, heteroskedasticity consistent standard …

Conditional heteroskedasticity can be exploited to identify the structural vector autoregressions (SVAR) but the … 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 …