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On Monte Carlo Estimation of Relative Power

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  • Paruolo Paolo

    (Department of Economics, University of Insubria, Italy)

Abstract

This paper derives standard errors for Monte Carlo (MC) estimators of (relative) power of tests when the critical values under the null have also been estimated. This situation is common e.g. in unit root and cointegration tests. The associated issue of MC design is discussed. The results are illustrated on likelihood based tests for cointegration rank determination.

Suggested Citation

  • Paruolo Paolo, "undated". "On Monte Carlo Estimation of Relative Power," Economics and Quantitative Methods qf0112, Department of Economics, University of Insubria.
    • Handle: RePEc:ins:quaeco:qf0112
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    Cited by:

    1. Bertocco Giancarlo, 2006. "Are banks special? A note on Tobin’s theory of financial intermediaries," Economics and Quantitative Methods qf0605, Department of Economics, University of Insubria.
    2. Jurgen A. Doornik & Rocco Mosconi & Paolo Paruolo, 2017. "Formula I(1) and I(2): Race Tracks for Likelihood Maximization Algorithms of I(1) and I(2) Cointegrated VAR Models," Econometrics, MDPI, vol. 5(4), pages 1-30, November.
    3. Cavaliere Giuseppe & Fanelli Luca & Paruolo Paolo, 2001. "Determining the number of cointegrating relations under rank constraints," Economics and Quantitative Methods qf0109, Department of Economics, University of Insubria.
    4. Giuseppe Cavaliere & Luca Fanelli & Paolo Paruolo, 2009. "Tests for cointegration rank and choice of the alternative," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(2), pages 169-191, July.

    More about this item

    Keywords

    Monte Carlo; design of experiments; (local) power; cointegration; likelihood ratio; unit roots;
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