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Least squares estimation and tests of breaks in mean and variance under misspecification

Least squares estimation and tests of breaks in mean and variance under misspecification
Least squares estimation and tests of breaks in mean and variance under misspecification
In this paper we investigate the consequences of misspecification on the large sample properties of change-point estimators and the validity of tests of the null hypothesis of linearity versus the alternative of a structural break. Specifically this paper concentrates on the interaction of structural breaks in the mean and variance of a time series when either of the two is omitted from the estimation and inference procedures. Our analysis considers the case of a break in mean under omitted-regime-dependent heteroscedasticity and that of a break in variance under an omitted mean shift. The large and finite sample properties of the resulting least-squares-based estimators are investigated and the impact of the two types of misspecification on inferences about the presence or absence of a structural break subsequently analysed.
1368-4221
32-54
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51

Pitarakis, Jean-Yves (2004) Least squares estimation and tests of breaks in mean and variance under misspecification. The Econometrics Journal, 7 (1), 32-54. (doi:10.1111/j.1368-423X.2004.00120.x).

Record type: Article

Abstract

In this paper we investigate the consequences of misspecification on the large sample properties of change-point estimators and the validity of tests of the null hypothesis of linearity versus the alternative of a structural break. Specifically this paper concentrates on the interaction of structural breaks in the mean and variance of a time series when either of the two is omitted from the estimation and inference procedures. Our analysis considers the case of a break in mean under omitted-regime-dependent heteroscedasticity and that of a break in variance under an omitted mean shift. The large and finite sample properties of the resulting least-squares-based estimators are investigated and the impact of the two types of misspecification on inferences about the presence or absence of a structural break subsequently analysed.

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More information

Published date: June 2004

Identifiers

Local EPrints ID: 33491
URI: http://eprints.soton.ac.uk/id/eprint/33491
ISSN: 1368-4221
PURE UUID: eac4dcb0-967f-4a25-85c5-09c5a59af08c
ORCID for Jean-Yves Pitarakis: ORCID iD orcid.org/0000-0002-6305-7421

Catalogue record

Date deposited: 15 May 2006
Last modified: 16 Mar 2024 03:32

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