Coefficient constancy test in AR-ARCH models
In this article, we consider the problem of testing the coefficient constancy in the AR-ARCH model: yt=([phi]+bt)yt-1+[var epsilon]t, where [var epsilon]t=[eta]t-1[xi]t, [eta]t-1=([alpha]0+[alpha]1[var epsilon]t-12)1/2 and [xi]t are iid r.v.'s. Under the assumption that bt and [xi]t are Gaussian, a locally best invariant test is provided for testing whether bt are identically zero or not. Since the exact distribution of the test statistic is hard to obtain, its limiting distribution is investigated. It is shown that the test statistic depends upon the parameter estimators and is asymptotically normal under the null hypothesis.
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Volume (Year): 57 (2002)
Issue (Month): 1 (March)
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References listed on IDEAS
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- Tanaka, Katsuto, 1983. "Non-Normality of the Lagrange Multiplier Statistic for Testing the Constancy of Regression Coefficients," Econometrica, Econometric Society, vol. 51(5), pages 1577-82, September.
- Conlisk, John, 1976. "A Further Note on Stability in a Random Coefficient Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 17(3), pages 759-64, October.
- McCabe,B.P.M. & Tremayne,A.R., 1995. "Testing a Time-Series for Difference Stationarity," Cambridge Working Papers in Economics 9420, Faculty of Economics, University of Cambridge.
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