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Is a small Monte Carlo analysis a good analysis? Checking the size, power and consistency of a simulation-based test

Author

Listed:
  • Ignacio Díaz-Emparanza

    (Universidad del País Vasco)

Abstract

In this paper we study the relationship between the number of replications and the accuracy of the estimated quantiles of a distribution obtained by simulation. A method for testing hypotheses on the quantiles of a theoretical distribution using the simulated distribution is proposed, as well as a method to check the hypothesis of consistency of a test.

Suggested Citation

  • Ignacio Díaz-Emparanza, 2000. "Is a small Monte Carlo analysis a good analysis? Checking the size, power and consistency of a simulation-based test," Econometrics 0004005, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpem:0004005
    Note: Type of Document - LaTex; prepared on PC-TEX; to print on PostScript; pages: 17 ; figures: none
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    References listed on IDEAS

    as
    1. 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.
    2. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    3. 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.
    4. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
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    More about this item

    Keywords

    Number of replications; Monte Carlo; accuracy.;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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