Asymptotic Efficient Estimation of the Change Point in Time Series Regression Models

Takayuki Shiohama, 敬之 塩浜 and タカユキ シオハマ

No 209, Discussion Paper from Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University

Abstract: This paper discusses the problem of estimating unknown change point in the trend function of a time series regression model. The error process considered here is a Gaussian stationary process with spectral density. The asymptotic properties of quasi maximum likelihood (QMLE) and quasi Bayes (QBE) estimators are studied. Consistency, limiting distributions and convergence of higher order moments of the estimators are obtained. It is also shown that the QBE is asymptotically efficient, and that the QMLE is not so general.

Keywords: Time series regression; change point; quasi maximum likelihood estimator; quasi Byes estimator; asymptotic efficiency; Whittle likelihood (search for similar items in EconPapers)
Pages: 19 pages
Date: 2004-03
Note: March 19, 2004
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Persistent link: https://EconPapers.repec.org/RePEc:hit:piedp1:209

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