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Maximum Simulated Likelihood: A Brief Introduction For Practitioners

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  • Arias, Carlos
  • Cox, Thomas L.

Abstract

This paper discusses the increasing importance of probability simulation methods in the context of Maximum Simulated Likelihood. Three probability simulators are analyzed following their chronological order of appearance. This analysis provides an intuitive approach to the basic idea behind probability simulation, the successive improvements and probable future developments. The paper pays special attention to the role of simulation noise in Maximum Simulated Likelihood.

Suggested Citation

  • Arias, Carlos & Cox, Thomas L., 1999. "Maximum Simulated Likelihood: A Brief Introduction For Practitioners," Staff Papers 12662, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    • Handle: RePEc:ags:wisagr:12662
    DOI: 10.22004/ag.econ.12662
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    File URL: https://ageconsearch.umn.edu/record/12662/files/stpap421.pdf
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    References listed on IDEAS

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    6. Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
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    Cited by:

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    5. Ozturk, Erdogan & Irwin, Elena G., 2001. "Explaining Household Location Choices Using A Spatial Probit Model," 2001 Annual meeting, August 5-8, Chicago, IL 20626, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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