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Finite-Sample Simulation-Based Tests in Seemingly Unrelated Regressions

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  • Dufour, Jean-Marie
  • Khalaf, Lynda

Abstract

In this paper, we propose finite and large sample likelihood based test procedures for possibly non-linear hypotheses on the coefficients of SURE systems. Two complementary approaches are described. First, we propose an exact Monte Carlo bounds test based on the standard likelihood ratio criterion. Second, we consider alternative Monte Carlo tests which can be run whenever the bounds are not conclusive. These include, in particular, quasi-likelihood ratio criteria based on non-maximum-likelihood estimators. Illustrative Monte Carlo experiments show that: (i) the bounds are sufficiently tight to yield conclusive results in a large proportion of cases, and (ii) the randomized procedures correct all the usual size distortions in such contexts. The procedures proposed are finally applied to test restrictions on a factor demand model.

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Bibliographic Info

Paper provided by GREEN in its series Cahiers de recherche with number 0105.

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Date of creation: 2001
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Handle: RePEc:lvl:lagrcr:0105

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Keywords: Multivariate Linear Regression; Seemingly Unrelated Regressions; Monte Carlo Test; Bounds Tests; Nonlinear Hypothesis; Finite-Sample Test; Exact Test; Bootstrap; Factor Demand; Cost Function;

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References

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  1. Theil, Henri & Shonkwiler, J. S. & Taylor, Timothy G., 1985. "A Monte Carlo test of Slutsky symmetry," Economics Letters, Elsevier, vol. 19(4), pages 331-332.
  2. Jean-Marie Dufour, 2005. "Monte Carlo tests with nuisance parameters: a general approach to finite-sample inference and non-standard asymptotics," CIRANO Working Papers 2005s-02, CIRANO.
  3. DUFOUR, Jean-Marie & FARHAT, Abdeljelil & GARDIOL, Lucien, 1998. "Simulation-Based Finite-Sample Normality Tests in Linear Regressions," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques 9811, Universite de Montreal, Departement de sciences economiques.
  4. DUFOUR, Jean-Marie & KHALAF, Lynda, 1998. "Simulation-Based Finite-and Large-sample Inference Methods in Multivariate Regressions and Seemingly Unrelated Regressions," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques 9813, Universite de Montreal, Departement de sciences economiques.
  5. Dufour, J.M. & Kiviet, J.F., 1995. "Exact Inference Methods for First-Order Autoregressive Distributed Lag Models," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques 9547, Universite de Montreal, Departement de sciences economiques.
  6. Dufour, Jean-Marie & Kiviet, Jan F., 1996. "Exact tests for structural change in first-order dynamic models," Journal of Econometrics, Elsevier, Elsevier, vol. 70(1), pages 39-68, January.
  7. Jean-Marie Dufour & Lynda Khalaf, 2000. "Simulation Based Finite and Large Sample Tests in Multivariate Regressions," CIRANO Working Papers 2000s-15, CIRANO.
  8. Berndt, Ernst R & Savin, N Eugene, 1977. "Conflict among Criteria for Testing Hypotheses in the Multivariate Linear Regression Model," Econometrica, Econometric Society, Econometric Society, vol. 45(5), pages 1263-77, July.
  9. Meisner, James F., 1979. "The sad fate of the asymptotic Slutsky symmetry test for large systems," Economics Letters, Elsevier, vol. 2(3), pages 231-233.
  10. Kenneth Stewart, 1997. "Exact testing in multivariate regression," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 16(3), pages 321-352.
  11. Breusch, T S, 1979. "Conflict among Criteria for Testing Hypotheses: Extensions and Comments," Econometrica, Econometric Society, Econometric Society, vol. 47(1), pages 203-07, January.
  12. Rilstone, Paul & Veall, Michael, 1996. "Using Bootstrapped Confidence Intervals for Improved Inferences with Seemingly Unrelated Regression Equations," Econometric Theory, Cambridge University Press, vol. 12(03), pages 569-580, August.
  13. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, Elsevier, vol. 60(1-2), pages 65-99.
  14. Taylor, Timothy G. & Shonkwiler, J. S. & Theil, Henri, 1986. "Monte Carlo and bootstrap testing of demand homogeneity," Economics Letters, Elsevier, vol. 20(1), pages 55-57.
  15. Harvey, Andrew C & Phillips, Garry D A, 1982. "Testing for Contemporaneous Correlation of Disturbances in Systems of Regression Equations," Bulletin of Economic Research, Wiley Blackwell, vol. 34(2), pages 79-91, November.
  16. Laitinen, Kenneth, 1978. "Why is demand homogeneity so often rejected?," Economics Letters, Elsevier, vol. 1(3), pages 187-191.
  17. Phillips, Peter C B, 1985. "The Exact Distribution of the SUR Estimator," Econometrica, Econometric Society, Econometric Society, vol. 53(4), pages 745-56, July.
  18. Bera, A. K. & Byron, R. P. & Jarque, C. M., 1981. "Further evidence on asymptotic tests for homogeneity and symmetry in large demand systems," Economics Letters, Elsevier, vol. 8(2), pages 101-105.
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Cited by:
  1. Jouneau-Sion, Frederic & Torres, Olivier, 2006. "MMC techniques for limited dependent variables models: Implementation by the branch-and-bound algorithm," Journal of Econometrics, Elsevier, Elsevier, vol. 133(2), pages 479-512, August.

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