IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpem/9612006.html
   My bibliography  Save this paper

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, EconWPA.
  • Handle: RePEc:wpa:wuwpem:9612006
    Note: Type of Document - PostScript; prepared on IBM PC ; to print on PostScript; pages: 13 ; figures: included. None.
    as

    Download full text from publisher

    File URL: http://econwpa.repec.org/eps/em/papers/9612/9612006.pdf
    Download Restriction: no

    File URL: http://econwpa.repec.org/eps/em/papers/9612/9612006.ps.gz
    Download Restriction: no

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    More about this item

    Keywords

    Number of replications; Monte-Carlo; accuracy; binomial distribution.;

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpem:9612006. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA). General contact details of provider: http://econwpa.repec.org .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.