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On Efficient Simulations in Dynamic Models

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  • Abadir, Karim

Abstract

Ways of improving the efficiency of Monte-Carlo (MC) techniques are studied for dynamic models. Such models cause the conventinal Antithetic Variate (AV) technique to fail, and will be proved to reduce the benefit from using Control Variates with nearly non-stationary series. This paper suggest modifications of the two conventional variance reduction techniques to enhance their efficiency. New classes of AV's are also proposed. Methods of reordering residuals are found to do less well than others wich rely on changing signs in the spirit of the traditional AV. Then, unconventional applications of these techniques of MC work for nearly nonstationary series. It generates econometric estimators at one and a half times the speed of conventional MC.

Suggested Citation

  • Abadir, Karim, 1995. "On Efficient Simulations in Dynamic Models," Discussion Papers 9521, University of Exeter, Department of Economics.
    • Handle: RePEc:exe:wpaper:9521
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    References listed on IDEAS

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    1. Giovanni Crespi & Ivan Ginchev & Matteo Rocca, 2006. "First-order optimality conditions in set-valued optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 63(1), pages 87-106, February.
    2. Johannes Jahn & Rüdiger Rauh, 1997. "Contingent epiderivatives and set-valued optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 46(2), pages 193-211, June.
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    Cited by:

    1. Lawford, Steve & Stamatogiannis, Michalis P., 2009. "The finite-sample effects of VAR dimensions on OLS bias, OLS variance, and minimum MSE estimators," Journal of Econometrics, Elsevier, vol. 148(2), pages 124-130, February.

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    More about this item

    Keywords

    ECONOMIC MODELS;

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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