Paper #600

Title:

Subsampling the mean of heavy-tailed dependent observations

Authors:

Piotr Kokoszka and Michael Wolf

Date:

February 2002

Abstract:

We establish the validity of subsampling confidence intervals for the mean of a dependent series with heavy-tailed marginal distributions. Using point process theory, we study both linear and nonlinear GARCH-like time series models. We propose a data-dependent method for the optimal block size selection and investigate its performance by means of a simulation study.

Keywords:

Heavy tails, linear time series, subsampling

JEL codes:

C10, C14, C32

Area of Research:

Statistics, Econometrics and Quantitative Methods

Published in:

Journal of Econometrics, 127, 201-224, 2005

Download the paper in PDF format