Nothing Special   »   [go: up one dir, main page]
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, 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.
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/9612/9612006.pdf
    Download Restriction: no
    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cecchetti, Stephen G & Karras, Georgios, 1994. "Sources of Output Fluctuations during the Interwar Period: Further Evidence on the Causes of the Great Depression," The Review of Economics and Statistics, MIT Press, vol. 76(1), pages 80-102, February.
    2. Jansson Michael & Nielsen Morten Ørregaard, 2011. "Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-21, February.
    3. Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2007. "Efficient tests of the seasonal unit root hypothesis," Journal of Econometrics, Elsevier, vol. 141(2), pages 548-573, December.
    4. Diaz-Emparanza, Ignacio, 2014. "Numerical distribution functions for seasonal unit root tests," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 237-247.
    5. Cho, Sungwon, 1998. "Time-series implications of the permanent income hypothesis on durable goods consumption," ISU General Staff Papers 1998010108000012849, Iowa State University, Department of Economics.
    6. Antonio Aguirre & Andreu Sansó, 2002. "Using different null hypotheses to test for seasonal unit roots in economic time series," Económica, Instituto de Investigaciones Económicas, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 0(1-2), pages 3-26, January-D.
    7. Pınar GÖKTAŞ, 2019. "Asymmetric Transition Effects of the Exchange Rate on Consumer Prices in Turkey," Sosyoekonomi Journal, Sosyoekonomi Society, issue 27(42).
    8. Erten, Irem & Okay, Nesrin, 2012. "Re-examining Turkey's trade deficit with structural breaks: Evidence from 1989-2011," MPRA Paper 56191, University Library of Munich, Germany.
    9. Sandra G. Feltham & David E.A. Giles, 1999. "Testing for Unit Roots in Semi-Annual Data," Econometrics Working Papers 9912, Department of Economics, University of Victoria.
    10. Zafar, Raja Fawad & Qayyum, Abdul & Ghouri, Saghir Pervaiz, 2015. "Forecasting Inflation using Functional Time Series Analysis," MPRA Paper 67208, University Library of Munich, Germany.
    11. Chambers, Marcus J. & Ercolani, Joanne S. & Taylor, A.M. Robert, 2014. "Testing for seasonal unit roots by frequency domain regression," Journal of Econometrics, Elsevier, vol. 178(P2), pages 243-258.
    12. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics.
    13. Shin, Dong Wan & Oh, Man-Suk, 2000. "Semiparametric tests for seasonal unit roots based on a semiparametric feasible GLSE," Statistics & Probability Letters, Elsevier, vol. 50(3), pages 207-218, November.
    14. Paulo Rodrigues & Philip Hans Franses, 2005. "A sequential approach to testing seasonal unit roots in high frequency data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(6), pages 555-569.
    15. Bardsen, G. & Klovland, J.T., 1990. "Finding The Rigth Nominal Anchor: The Cointegration Of Money, Credit And Nominal Income In Norway," The Warwick Economics Research Paper Series (TWERPS) 350, University of Warwick, Department of Economics.
    16. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    17. Hans Franses, Philip & Koehler, Anne B., 1998. "A model selection strategy for time series with increasing seasonal variation," International Journal of Forecasting, Elsevier, vol. 14(3), pages 405-414, September.
    18. Smith, Jeremy & Otero, Jesus, 1997. "Structural breaks and seasonal integration," Economics Letters, Elsevier, vol. 56(1), pages 13-19, September.
    19. Beenstock, Michael & Reingewertz, Yaniv & Paldor, Nathan, 2016. "Testing the historic tracking of climate models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1234-1246.
    20. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).

    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

    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.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.