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A New Form of the Information Matrix Test

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  • Davidson, Russell
  • MacKinnon, James G

Abstract

A new form of the information matrix test is developed for a wide variety of statistical models. The test is constructed against an explicit alternative with random parameter variation. It is computed using a double-length artificial regression instead of the more conventional outer-product-of-the-gradient regression, which is known to have very poor finite-sample properties. In Monte Carlo experiments for the case of univariate linear regression models, the new form performs remarkably well. Some approximate finite-sample distributions are also calculated for this case and lend support to the use of the new form. Copyright 1992 by The Econometric Society.

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Bibliographic Info

Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 60 (1992)
Issue (Month): 1 (January)
Pages: 145-57

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Handle: RePEc:ecm:emetrp:v:60:y:1992:i:1:p:145-57

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Cited by:
  1. Teodosio Perez Amaral, 1994. "Una aplicación de los contrastes M y de la matriz de información dinámica: el caso de la demanda de dinero norteamericana 1960-1984," Investigaciones Economicas, Fundación SEPI, vol. 18(1), pages 193-201, January.
  2. Russell Davidson & James G. MacKinnon, 1994. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," Working Papers 903, Queen's University, Department of Economics.
  3. Christian Bontemps & Nour Meddahi, 2002. "Testing Normality: A GMM Approach," CIRANO Working Papers 2002s-63, CIRANO.
  4. Francisco Cribari-Neto, 1996. "On the Corrections to Information Matrix Tests," Econometrics 9601001, EconWPA.
  5. Joachim Zietz, 2006. "Detecting neglected parameter heterogeneity with Chow tests," Applied Economics Letters, Taylor & Francis Journals, vol. 13(6), pages 369-374.
  6. Wanling Huang & Artem Prokhorov, 2010. "A Goodness-of-fit Test for Copulas," Working Papers 10002, Concordia University, Department of Economics, revised Apr 2010.
  7. Russell Davidson & James G. MacKinnon, 2001. "Artificial Regressions," Working Papers 1038, Queen's University, Department of Economics.
  8. Kaiser, Ulrich & Spitz, Alexandra, 2000. "Quantification of qualitative data using ordered probit models with an application to a business survey in the German service sector," ZEW Discussion Papers 00-58, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  9. Geert Dhaene & Dirk Hoorelbeke, 2002. "The Information Matrix Test with Bootstrap-Based Covariance Matrix Estimation," Center for Economic Studies - Discussion papers ces0211, Katholieke Universiteit Leuven, Centrum voor Economische Studiën.
  10. Riccardo Lucchetti & Claudia Pigini, 2013. "A test for bivariate normality with applications in microeconometric models," Statistical Methods and Applications, Springer, vol. 22(4), pages 535-572, November.
  11. Dirk Hoorelbeke, 2004. "Bootstrap correcting the score test," Econometric Society 2004 North American Summer Meetings 228, Econometric Society.
  12. Chesher, Andrew & Dumangane, Montezuma & Smith, Richard J., 2002. "Duration response measurement error," Journal of Econometrics, Elsevier, vol. 111(2), pages 169-194, December.
  13. Stomberg, Christopher & White, Halbert, 2000. "Bootstrapping the Information Matrix Test," University of California at San Diego, Economics Working Paper Series qt158451cr, Department of Economics, UC San Diego.

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