Optimal tests for nested model selection with underlying parmeter instability

Published

Journal Article

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 test 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. © 2005 Cambridge University Press.

Full Text

Cited Authors

  • Rossi, B

Published Date

  • October 1, 2005

Published In

Volume / Issue

  • 21 / 5

Start / End Page

  • 962 - 990

Electronic International Standard Serial Number (EISSN)

  • 1469-4360

International Standard Serial Number (ISSN)

  • 0266-4666

Digital Object Identifier (DOI)

  • 10.1017/S0266466605050486

Citation Source

  • Scopus