A New Form of the Information Matrix Test
AbstractWe develop a new form of the information matrix test for a wide variety of statistical models, and present full details for the special case of univariate nonlinear regression models. Chesher (1984) showed that the implicit alternative of the information matrix test is a model with random parameter variation. We exploit this fact by constructing the test against an explicit alternative of this type. The new test is computed using a double-length artificial regression, instead of the more conventional outer product of the gradient regression, which, although easy to use, is known to give test statistics with distributions very far from the asymptotic nominal distribution even in rather large samples. The new form on the other hand performs remarkably well, at least in the context of regression models. Some approximate finite-sample distributions are calculated and lend support to the use of the new form of the test.
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Bibliographic InfoPaper provided by Queen's University, Department of Economics in its series Working Papers with number 724.
Length: 30 pages
Date of creation: 1988
Date of revision:
Publication status: Published in Econometrica, 60, 1992
information matrix; IM test; double-length regression; DLR;
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- 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.
- Joachim Zietz, 2006.
"Detecting neglected parameter heterogeneity with Chow tests,"
Applied Economics Letters,
Taylor & Francis Journals, vol. 13(6), pages 369-374.
- Joachim Zietz, 2005. "Detecting Neglected Parameter Heterogeneity with Chow Tests," Working Papers 200503, Middle Tennessee State University, Department of Economics and Finance.
- Francisco Cribari-Neto, 1996. "On the Corrections to Information Matrix Tests," Econometrics 9601001, EconWPA.
- Dirk Hoorelbeke, 2004. "Bootstrap correcting the score test," Econometric Society 2004 North American Summer Meetings 228, Econometric Society.
- 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.
- 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.
- 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.
- Dhaene, Geert & Hoorelbeke, Dirk, 2004. "The information matrix test with bootstrap-based covariance matrix estimation," Economics Letters, Elsevier, vol. 82(3), pages 341-347, March.
- 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.
- Davidson, Russell & MacKinnon, James G, 1998.
"Graphical Methods for Investigating the Size and Power of Hypothesis Tests,"
The Manchester School of Economic & Social Studies,
University of Manchester, vol. 66(1), pages 1-26, January.
- 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.
- Chesher, Andrew & Dumangane, Montezuma & Smith, Richard J., 2002. "Duration response measurement error," Journal of Econometrics, Elsevier, vol. 111(2), pages 169-194, December.
- Prokhorov, Artem, 2008.
"A goodness-of-fit test for copulas,"
9998, University Library of Munich, Germany.
- Russell Davidson & James G. MacKinnon, 2001.
1038, Queen's University, Department of Economics.
- Christian Bontemps & Nour Meddahi, 2002.
"Testing Normality: A GMM Approach,"
CIRANO Working Papers
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