Testing parameter constancy in linear models against stochastic stationary parameters

doi:10.1016/S0304-4076(98)00041-4

Testing parameter constancy in linear models against stochastic stationary parameters

1999-06-01

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DOI：10.1016/S0304-4076(98)00041-4

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This paper considers testing parameter constancy in a linear model when the alternative is that a subset of the parameters follows 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 statisfactory. The test retains its power when the alternative to parameter constancy is a random walk parameter process, (C) 1999 Elsevier Science S.A. All rights reserved. JEL classification: C22; C52.

Keywords:

lack of identification

Lagrange multiplier test

parameter stability

return

to normalcy

time varying parameters

vector autoregressive process

Testing parameter constancy in linear models against stochastic stationary parameters

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