Optimal tests for nested model selection with underlying parameter instability
نویسنده
چکیده
This paper develops optimal tests for model selection between two nested models in the presence of underlying parameter instability. These are joint tests for both parameter instability and a null hypothesis on a subset of the parameters. They modify the existing tests for parameter instability to allow the parameter vector to be unknown. These tests statistics are useful if one is interested in testing a null hypothesis on some parameters but is worried about the possibility that the parameters may be time varying. The paper provides the asymptotic distributions of this class of test statistics and their critical values for some interesting cases. JEL: C52, C53.
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