Bayesian and Non-Bayesian Tests of Independence in Seemingly Unrelated Regressions
AbstractBayesian and non-Bayesian statistics are derived for testing whether or not two blocks of seemingly unrelated regressions are independent. The non-Bayesian statistics are the likelihood ratio test (LRT), Wald's test (WT), and the Lagrange multiplier test (LMT). The authors interpret the LMT and WT as differences in the log of likelihoods conditioned on estimates of nuisance parameters. The Bayesian test is a highest posterior density region test that can also be derived as a Bayes factor. The four tests are compared in sampling experiments. Copyright 1988 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.
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Bibliographic InfoArticle provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.
Volume (Year): 29 (1988)
Issue (Month): 2 (May)
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- DUFOUR, Jean-Marie & KHALAF, Lynda, 2000.
"Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions,"
Cahiers de recherche
2000-11, Universite de Montreal, Departement de sciences economiques.
- Dufour, Jean-Marie & Khalaf, Lynda, 2002. "Exact tests for contemporaneous correlation of disturbances in seemingly unrelated regressions," Journal of Econometrics, Elsevier, vol. 106(1), pages 143-170, January.
- Jean-Marie Dufour & Lynda Khalaf, 2000. "Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions," CIRANO Working Papers 2000s-16, CIRANO.
- Dufour, J.M. & Khalaf, L., 2000. "Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions," Cahiers de recherche 2000-11, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Tsay, Wen-Jen, 2004. "Testing for contemporaneous correlation of disturbances in seemingly unrelated regressions with serial dependence," Economics Letters, Elsevier, vol. 83(1), pages 69-76, April.
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