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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.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_781.pdf
File Function: First version 1990
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 781.

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Date of creation: May 1990
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Handle: RePEc:qed:wpaper:781

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  1. Henry, D F & Trivedi, P K, 1972. "Maximum Likelihood Estimation of Difference Equations with Moving Average Errors: A Simulation Study," Review of Economic Studies, Wiley Blackwell, vol. 39(2), pages 117-45, April.
  2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  3. James G. MacKinnon & Halbert White, 1983. "Some Heteroskedasticity Consistent Covariance Matrix Estimators with Improved Finite Sample Properties," Working Papers 537, Queen's University, Department of Economics.
  4. 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.
  5. Tauchen, George, 1985. "Diagnostic testing and evaluation of maximum likelihood models," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 415-443.
  6. Davidson, Russell & MacKinnon, James G., 1981. "Efficient estimation of tail-area probabilities in sampling experiments," Economics Letters, Elsevier, vol. 8(1), pages 73-77.
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Cited by:
  1. James G. MacKinnon & Anthony A. Smith Jr., 1995. "Approximate Bias Correction in Econometrics," Working Papers 919, Queen's University, Department of Economics.

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