Least Squares Estimation and Tests of Breaks in Mean and Variance Under Misspecification

23 Pages Posted: 14 Jul 2004

See all articles by Jean-Yves Pitarakis

Jean-Yves Pitarakis

University of Southampton - Division of Economics

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.

Keywords: Structural breaks, misspecification, variance shifts, bootstrapping

Suggested Citation

Pitarakis, Jean-Yves, Least Squares Estimation and Tests of Breaks in Mean and Variance Under Misspecification. Available at SSRN: https://ssrn.com/abstract=558832

Jean-Yves Pitarakis (Contact Author)

University of Southampton - Division of Economics ( email )

Southampton, SO17 1BJ
United Kingdom
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