conditional ranking. We also propose a test of Prospect Stochastic Dominance. Our method is based on subsampling and we show that …

This paper studies robustness of bootstrap inference methods for instrumental variable (IV)regression models. We … concludethat the implied probability bootstrap test using the statistic based on the GMTM estimator showsdesirable robustness …) estimator introduced by Cížek (2008, 2009),and compare the pairs and implied probability bootstrap approximations for these …

We investigate the use of subsampling for conducting inference about the quadratic variation of a discretely observed … diffusion process under an infill asymptotic scheme. We show that the usual subsampling method of Politis and Romano (1994) is … inconsistent when applied to our inference question. Recently, a type of subsampling has been used to do an additive bias …

data is unbalanced or incomplete. In this case, one can work only with the common sample, to which a standard HAC/Bootstrap …

parameters. Second, the consistency of the proposed residual-based block bootstrap is established based on a newly developed … asymptotic theory for this bootstrap. It is demonstrated by a set of Monte Carlo simulations that the Wald test exhibits …

We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression … responses are imputed using the semiparametric regression method the empirical log-likelihood is asymptotically a scaled chi … bootstrap empirical log-likelihood ratio is derived and its distribution is used to approximate that of the imputed empirical …