the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading …

bootstrapalgorithms. The bootstrap testing procedure is applied to data fromItaly, France and the United States. We find evidence of …

, 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 …

violation of such assumptions can lead to serious modelling flaws. We propose here a bootstrap-corrected conditional moment …

We propose a bootstrap method for statistics that are a function of multivariate high frequency returns such as … realized regression, covariance and correlation coefficients. We show that the finite sample performance of the bootstrap is … superior to the existing first-order asymptotic theory. Nevertheless, and contrary to the existing results in the bootstrap …

This paper is concerned with the use of the bootstrap for statistics in spatial econometric models, with a focus on the …, the bootstrap can be studied based on linear–quadratic (LQ) forms of disturbances. By proving the uniform convergence of … the cumulative distribution function for LQ forms to that of a normal distribution, we show that the bootstrap is …

, 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 …

regression model. Monte Carlo simulations in two settings where the bootstrap fails show the accuracy and robustness of the …