Publication:
Weak convergence to a matrix stochastic integral with stable processes

Placeholder

Departments

School / College / Institute

Program

KU-Authors

KU Authors

Co-Authors

Publication Date

Language

Embargo Status

Journal Title

Journal ISSN

Volume Title

Alternative Title

Abstract

This paper generalizes the univariate results of Chan and Tran (1989, Econometric Theory 5, 354-362) and Phillips (1990, Econometric Theory 6, 44-62) to multivariate time series. We develop the limit theory for the least-squares estimate of a VAR(1) for a random walk with independent and identically distributed errors and for I(1) processes with weakly dependent errors whose distributions are in the domain of attraction of a stable law. The limit laws are represented by functionals of a stable process. A semiparametric correction is used in order to asymptotically eliminate the ''bias'' term in the limit law. These results are also an extension of the multivariate limit theory for square-integrable disturbances derived by Phillips and Durlauf (1986, Review of Economic Studies 53, 473-495). Potential applications include tests for multivariate unit roots and cointegration.

Source

Publisher

Cambridge Univ Press

Subject

Economics, Mathematics, Social sciences, Mathematical methods, Statistics, Probability

Citation

Has Part

Source

Econometric Theory

Book Series Title

Edition

DOI

10.1017/S0266466600005983

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

0

Views

0

Downloads

View PlumX Details