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Computing Numerical Distribution Functions in Econometrics

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  • MacKinnon, James

Abstract

Many test statistics in econometrics have asymptotic distributions that cannot be evaluated analytically. In order to conduct asymptotic inference, it is therefore necessary to resort to simulation. Techniques that have commonly been used yield only a small number of critical values, which can be seriously inaccurate. In contrast, the techniques discussed in this paper yield enough information to plot the distributions of the test statistics or to calculate P values, and they can yield highly accurate results. These techniques are used to obtain asymptotic critical values for a test recently proposed by Kiefer, Vogelsang, and Bunzel (2000) for testing linear restrictions in linear regression models. A program to compute P values for this test is available from the author’s web site.

Suggested Citation

  • MacKinnon, James, 2001. "Computing Numerical Distribution Functions in Econometrics," Queen's Economics Department Working Papers 273507, Queen's University - Department of Economics.
    • Handle: RePEc:ags:quedwp:273507
    DOI: 10.22004/ag.econ.273507
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    Cited by:

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    2. Imane El Ouadghiri & Remzi Uctum, 2020. "Macroeconomic expectations and time varying heterogeneity:evidence from individual survey data," Applied Economics, Taylor & Francis Journals, vol. 52(23), pages 2443-2459, May.
    3. Fan, Yanqin & Gençay, Ramazan, 2010. "Unit Root Tests With Wavelets," Econometric Theory, Cambridge University Press, vol. 26(5), pages 1305-1331, October.
    4. Peter Sephton, 2008. "Critical values of the augmented fractional Dickey–Fuller test," Empirical Economics, Springer, vol. 35(3), pages 437-450, November.

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    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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