stochastic expansion and bootstrap. Working with concentrated estimating equation simplifies greatly the high-order expansions … for bias and variance; a simple bootstrap procedure overcomes a major difficulty in analytically evaluating expectations … analytical approach, the proposed approach is much simpler and has a much wider applicability. The validity of the bootstrap …

test is a consistent test. We also establish the asymptotic validity of a bootstrap procedure which is used to better …

function representations computed on each bootstrap sample, thereby reducing computational time considerably. This method is … improvement in the numerical speed of the fast bootstrap method. …

function in the limit. Two-step residual-based i.i.d. bootstrap and wild bootstrap procedures are proposed for the robust tests …

In this paper, a bootstrap algorithm for a reduced rank vector autoregressive (VAR) model which also includes … stationary regressors, is analyzed. It is shown that the bootstrap distribution for estimating the rank converges to the … parameters, bootstrap distributions are of considerable interest in this context. The result of an application and some Monte …

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

uniform confidence band and show that the bootstrap can be used to obtain the required critical values. Monte Carlo …

-nested alternatives. The test is an extension of the classical J test for non-nested regression models. I also provide a bootstrap version …