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Asymptotically Optimal Tests Using Limited Information and Testing for Exogeneity

Published online by Cambridge University Press:  11 February 2009

Richard J. Smith
Affiliation:
Gonville and Caius College and University of Cambridge

Abstract

By appropriately partitioning the joint hypothesis of weak exogeneity and the maintained overidentifying restrictions in the linear dynamic simultaneous equations model and showing that the component subhypotheses are separable, asymptotically optimal tests for the weak exogeneity hypothesis may be constructed using limited information statistics. A necessary and sufficient condition for the separability of parametric hypotheses of the mixed implicit function and constraint equation type is derived which generalizes conditions previously obtained in the literature. Consequently, limited and full information procedures for testing the weak exogeneity hypothesis are asymptotically equivalent. The impact of these results for testing strong exogeneity in the linear dynamic simultaneous equations model is also explored.

Type
Articles
Copyright
Copyright © Cambridge University Press 1994

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