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Maintaining symmetry of simulated likelihood functions

Author

Listed:
  • Laura Mørch Andersen

    (Institute of Food and Resource Economics, University of Copenhagen)

Abstract

This paper suggests solutions to two different types of simulation errors related to Quasi-Monte Carlo integration. Likelihood functions which depend on standard deviations of mixed parameters are symmetric in nature. This paper shows that antithetic draws preserve this symmetry and thereby improves precision substantially. Another source of error is that models testing away mixing dimensions must replicate the relevant dimensions of the quasi-random draws in the simulation of the restricted likelihood. These simulation errors are ignored in the standard estimation procedures used today and this paper shows that the result may be substantial estimation- and inference errors within the span of draws typically applied.

Suggested Citation

  • Laura Mørch Andersen, 2010. "Maintaining symmetry of simulated likelihood functions," IFRO Working Paper 2010/16, University of Copenhagen, Department of Food and Resource Economics.
    • Handle: RePEc:foi:wpaper:2010_16
    as

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    File URL: http://okonomi.foi.dk/workingpapers/WPpdf/WP2010/WP_2010_16_maintaining_symmetry.pdf
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    References listed on IDEAS

    as
    1. Chiou, Lesley & Walker, Joan L., 2007. "Masking identification of discrete choice models under simulation methods," Journal of Econometrics, Elsevier, vol. 141(2), pages 683-703, December.
    2. Ben-Akiva, M. & Bolduc, D. & Bradley, M., 1993. "Estimation of Travel Choice Models with Randomly Distributed Values of Time," Papers 9303, Laval - Recherche en Energie.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Quasi-Monte Carlo integration; Antithetic draws; Likelihood Ratio tests; simulated likelihood; panel mixed multinomial logit; Halton draws;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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