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Regression-Based Methods for Using Control and Antithetic Variates in Monte Carlo Experiments

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  • Russell Davidson
  • James G. Mackinnon

Abstract

Methods based on linear regression provide a very easy way to use the information in control and antithetic variates to improve the efficiency with which certain features of the distributions of estimators and test statistics are estimated in Monte Carlo experiments. We propose a new technique that allows these methods to be used when the quantities of interest are quantiles. Ways to obtain approximately optimal control variates in many cases of interest are also proposed. These methods seem to work well in practice, and can greatly reduce the number of replications required to obtain a given level of accuracy.

Suggested Citation

  • Russell Davidson & James G. Mackinnon, 1990. "Regression-Based Methods for Using Control and Antithetic Variates in Monte Carlo Experiments," Working Paper 781, Economics Department, Queen's University.
    • Handle: RePEc:qed:wpaper:781
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    File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_781.pdf
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    References listed on IDEAS

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    4. Davidson, Russell & MacKinnon, James G., 1981. "Efficient estimation of tail-area probabilities in sampling experiments," Economics Letters, Elsevier, vol. 8(1), pages 73-77.
    5. S. S. Lavenberg & P. D. Welch, 1981. "A Perspective on the Use of Control Variables to Increase the Efficiency of Monte Carlo Simulations," Management Science, INFORMS, vol. 27(3), pages 322-335, March.
    6. MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
    7. Tauchen, George, 1985. "Diagnostic testing and evaluation of maximum likelihood models," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 415-443.
    8. 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.
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    Cited by:

    1. MacKinnon, James G. & Smith Jr., Anthony A., 1998. "Approximate bias correction in econometrics," Journal of Econometrics, Elsevier, vol. 85(2), pages 205-230, August.

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