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Testing Parameter Constancy in Linear Models against Stochastic Stationary Parameters
Working paper

Testing Parameter Constancy in Linear Models against Stochastic Stationary Parameters

Chien-Fu Lin and Timo Teräsvirta
Vol.1995(54)
SSE/EFI Working Paper Series in Economics and Finance, 54, Economic Research Institute (EFI)/Stockholm School of Economics (SSE)
1995

Abstract

lack of identification Lagrange multiplier test parameter stability return to normalcy time-varying parameters vector autoregressive process C22
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 null 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.

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