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Selecting the Number of Replications in a Simulation Study

Author

Listed:
  • Ignacio Dmaz-Emparanza

    (Universidad del Pams Vasco)

Abstract

In order to approach a distribution by means of simulation it is necessary to determine a number of replications. The accuracy with which the distribution is calculated will rely on this number of replications. In this work, a relationship between the number of replications and the accuracy of the estimate is obtained, so that if it is wanted to get a prefixed value for the accuracy it is possible to determine which will be the minimum number of replications necessary for it.

Suggested Citation

  • Ignacio Dmaz-Emparanza, 1996. "Selecting the Number of Replications in a Simulation Study," Econometrics 9612006, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:9612006
    Note: Type of Document - PostScript; prepared on IBM PC ; to print on PostScript; pages: 13 ; figures: included. None.
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    References listed on IDEAS

    as
    1. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    2. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    3. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
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    Cited by:

    1. Camelia Minoiu & Sanjay Reddy, 2014. "Kernel density estimation on grouped data: the case of poverty assessment," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(2), pages 163-189, June.

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    More about this item

    Keywords

    Number of replications; Monte-Carlo; accuracy; binomial distribution.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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