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The Economic Research Institute, Stockholm School of Economics SSE/EFI Working Paper Series in Economics and Finance

No 54:
Testing Parameter Constancy in Linear Models against Stochastic Stationary Parameters

Chien-Fu Lin and Timo Teräsvirta ()

Abstract: This paper considers testing parameter constancy in linear models when the alternative is that a subset of the parameters follow a stationary vector autoregressive process of known finite order. This kind of a linear model is only identified under the alternative, which usually precludes finding a test statistic with an analytic nuyll distribution. In the present situation, however, it is still possible to derive a test statistic with an asymptotic chi-squared distribution under the null hypothesis and this is done in the paper. The small-sample properties of the test statistic are investigated by simulation and found satisfactory. The test retains its power when the alternative to parameter constancy is a random walk parameter process.

Keywords: Lack of identification; Lagrange multiplier test; parameter stability; return to normalcy; time-varying parameters; vector autoregressive process; (follow links to similar papers)

JEL-Codes: C22; (follow links to similar papers)

33 pages, May 1995

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This paper is published as:
Lin, Chien-Fu and Timo Teräsvirta, (1999), 'Testing Parameter Constancy in Linear Models against Stochastic Stationary Parameters', Journal of Econometrics, Vol. 90, pages 193-213



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