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Graphical Methods for Investigating the Size and Power of Hypothesis Tests

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  • Russell Davidson
  • James G. MacKinnon

Abstract

Simple techniques for the graphical display of simulation evidence concerning the size and power of hypothesis tests are developed and illustrated. Three types of figures - called P value plots, P value discrepancy plots, and size-power curves - are discussed. Some Monte Carlo experiments on the properties of alternative forms of the information matrix test are used to illustrate these figures. Tests based on the OPG regression are found to perform poorly in terms of both size and power.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_903.pdf
File Function: First version 1994
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 903.

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Length: 25 pages
Date of creation: Jun 1994
Date of revision:
Handle: RePEc:qed:wpaper:903

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  1. West, Kenneth D & Wilcox, David W, 1996. "A Comparison of Alternative Instrumental Variables Estimators of a Dynamic Linear Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 281-93, July.
  2. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  3. Davidson, Russell & MacKinnon, James G, 1992. "A New Form of the Information Matrix Test," Econometrica, Econometric Society, vol. 60(1), pages 145-57, January.
  4. Fischer, N. I. & Mammen, E. & Marron, J. S., 1994. "Testing for multimodality," Computational Statistics & Data Analysis, Elsevier, vol. 18(5), pages 499-512, December.
  5. Orme, Christopher, 1988. "The Calculation of the Information Matrix Test for Binary Data Models," The Manchester School of Economic & Social Studies, University of Manchester, vol. 56(4), pages 370-76, December.
  6. Russell Davidson & James G. MacKinnon, 1996. "The Size and Power of Bootstrap Tests," Working Papers 932, Queen's University, Department of Economics.
  7. Lancaster, Tony, 1984. "The Covariance Matrix of the Information Matrix Test," Econometrica, Econometric Society, vol. 52(4), pages 1051-53, July.
  8. Hall, A.R., 1984. "The Information Matrix Test for the Linear Model," The Warwick Economics Research Paper Series (TWERPS) 250, University of Warwick, Department of Economics.
  9. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
  10. Taylor, Larry W., 1987. "The size bias of White's information matrix test," Economics Letters, Elsevier, vol. 24(1), pages 63-67.
  11. Davidson, Russell & MacKinnon, James G, 1984. "Model Specification Tests Based on Artificial Linear Regressions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(2), pages 485-502, June.
  12. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976 Elsevier.
  13. Chesher, Andrew, 1983. "The information matrix test : Simplified calculation via a score test interpretation," Economics Letters, Elsevier, vol. 13(1), pages 45-48.
  14. Chesher, Andrew & Spady, Richard, 1991. "Asymptotic Expansions of the Information Matrix Test Statistic," Econometrica, Econometric Society, vol. 59(3), pages 787-815, May.
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