We consider the bootstrapped empirical process of long‐range dependent data. It is shown that this process converges to a semi‐degenerate limit, where the random part of this limit is always Gaussian. Thus the bootstrap might fail when the original empirical process accomplishes a noncentral...

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative...

Extensive prior literature has studied how young organizations are impacted by and often benefit from embeddedness in key industry networks. Indeed, some research advises that entrepreneurs “don't go it alone” (Baum, Calabrese, and Silverman, 2000). This literature has also highlighted a...

In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (EDF) for residuals. It is known that the approximation error...

This paper examines the linkages between population growth and standard-of-living growth in 21 countries over the period of 1870-2013. We apply the bootstrap panel causality test proposed by Kónya (2006), which accounts for both dependency and heterogeneity across countries. We find one-way...

This paper evaluates the predictive ability of dividend yield for stock return using a new bootstrap test for the significance of predictive coefficients. The predictive model is expressed as a restricted vector autoregressive model, and the bootstrap is conducted with resampling based on...