Paul Rilstone

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This paper develops a consistent test for the correct hazard rate specification within the context of random right hand censoring of the dependent variable. The test is based on comparing a parametric estimate with a kernel estimate of the hazard rate. We establish the asymptotic distribution of the test statistic under the null hypothesis of correct(More)
Bias reduction in kernel estimation has received considerable attention in the statistics literature. As Jones and Foster (1993, 1996) and Foster (1995) survey, most of the suggestions in this regard can be seen as special cases of generalized jackknifing in which linear combinations of kernels are constructed to reduce bias. Several authors have considered(More)
The usual standard errors for the regression coe cients in a Seemingly Unrelated Regression model have a substantial downward bias. Bootstrapping the standard errors does not seem to improve inferences. In this paper Monte Carlo evidence is reported which indicates that bootstrapping can result in substantially better inferences when applied to t-ratios(More)
Finite sample approximations for the distribution functions of Generalized Empirical Likelihood (GEL) are derived using Edgeworth expansions. The analytical results obtained are shown to apply to most of the common extremum estimators used in applied work in an i.i.d. sampling context. The GEL estimators considered include the Continuous Updating, Empirical(More)
CIRANO is a private non-profit organization incorporated under the Québec Companies Act. Its infrastructure and research activities are funded through fees paid by member organizations, an infrastructure grant from the Ministère de l’Industrie, du Commerce, de la Science et de la Technologie, and grants and research mandates obtained by its research teams.(More)
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