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Optimal Similar Tests For Structural Change For The Linear Regression Model

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  • Forchini, G.

Abstract

This paper analyzes similar tests for structural change for the normal linear regression model in finite samples. Using the approach of Wald (1943, American Mathematical Society Transactions 54, 426–482), Hillier (1987, Econometric Theory 3, 1–44), Andrews and Ploberger (1994, Econometrica 62, 1382–1414), and Andrews, Lee, and Ploberger (1996, Journal of Econometrics 70, 9–36), we characterize a class of optimal similar tests for the existence of (possibly multiple) changepoints at unknown times. We extend the analysis of Andrews et al. (1996) by deriving weighted optimal similar tests for the case where the error variance is not known. We also show that when the sample size is large, the tests of Andrews et al. constructed by replacing the error variance with an estimate are equivalent to the optimal test derived in this paper. Power comparisons are provided by a small simulation study.

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  • Forchini, G., 2002. "Optimal Similar Tests For Structural Change For The Linear Regression Model," Econometric Theory, Cambridge University Press, vol. 18(4), pages 853-867, August.
    • Handle: RePEc:cup:etheor:v:18:y:2002:i:04:p:853-867_18
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    Cited by:

    1. Elliott, Graham & Muller, Ulrich K., 2007. "Confidence sets for the date of a single break in linear time series regressions," Journal of Econometrics, Elsevier, vol. 141(2), pages 1196-1218, December.
    2. Marine Carrasco, 2004. "Chi-square Tests for Parameter Stability," RCER Working Papers 508, University of Rochester - Center for Economic Research (RCER).
    3. Giovanni Forchini, 2005. "Weighted Average Power Similar Tests for Structural Change for the Gaussian Linear Regression Model," Monash Econometrics and Business Statistics Working Papers 20/05, Monash University, Department of Econometrics and Business Statistics.
    4. Elliott, Graham & Mueller, Ulrich K., 2004. "Optimally Testing General Breaking Processes in Linear Time Series Models," University of California at San Diego, Economics Working Paper Series qt58n33447, Department of Economics, UC San Diego.

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