Statistical resampling methods have become feasible for parametric estimation, hypothesis testing, and model validation now that the computer is a ubiquitous tool for statisticians. This essay focuses on the resampling technique for parametric estimation known as the Jackknife procedure. To outline the usefulness of the method and its place in the general class of statistical resampling techniq...

This study estimates technical efficiency obtained from both Data Envelopment Analysis (DEA) and stochastic frontier approach using household survey data for rice farming households in Vietnam. A bootstrap method is used to provide statistical precision of DEA estimator. Bootstrap methods have not commonly used in empirical analysis despite being an important statistical tool for improving the ...

A general method is proposed for the construction of valid simultaneous confidence sets in the context of stationary GARCH models. The proposed method proceeds by numerically inverting the conventional likelihood ratio test. In order to hedge against the risk of a spurious rejection, candidate points that are rejected by the conventional test undergo a finite-sample parametric bootstrap test. A...

The process capability indices are widely used by quality professionals as an estimate of process capability. The lower confidence limits of PCIs are difficult to be estimated by parametric methods for some non-normal distributed processes. The non-parametric but computer intensive Bootstrap techniques are utilized for these cases. The Percentile-t Bootstrap (PTB) method is used to estimate the...

If a data set suffers from selection bias then, ordinary regression estimators must be adapted in order to achieve consistency. Consequently, it is necessary to modify any goodness of fit tests based on distances between parametric and non-parametric residuals. More particularly, any bootstrap approximation to these tests must be re– designed. Our first approach to this latter task is based on ...

Despite an abundance of semiparametric estimators of the transformation model, no procedure has been proposed yet to test the hypothesis that the transformation function belongs to a finite-dimensional parametric family against a nonparametric alternative. In this paper we introduce a bootstrap test based on integrated squared distance between a nonparametric estimator and a parametric null. As...

This paper introduces a bootstrap procedure, accounting for data dependence and parameter estimation error, which facillitates the construction of parametric speci ̄cation tests of di®usion processes. The bootstrap method hinges on a twofold extension of the Politis and Romano (1994) stationary bootstrap. First we provide an empirical process version of this bootstrap, and second, we account for...

Parametric dummy variable-based tests for event studies using multivariate regression are not robust to nonnormality of the residual, even for arbitrarily large sample sizes. Bootstrap alternatives are described, investigated, and compared for cases where there are nonnormalities, cross-sectional and time series dependencies. Independent bootstrapping of residual vectors from the multivariate r...