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Consistency Properties of a Simulation-Base Estimator for Dynamic Processes

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  • Manuel S. Santos

    () (Department of Economics, University of Miami)

Abstract

This paper considers a simulation-based estimator for a general class of Markovian processes and explores some strong consistency properties of the estimator. These results are of interest for various kinds of simulation-based estimation methods typically used in economics and finance. The estimation problem is defined over a continuum of invariant distributions indexed by a vector of parameters. A key step in the method of proof is to show the uniform convergence (a.s.) of a family of sample distributions over the domain of parameters. This uniform convergence holds under mild continuity and monotonicity conditions on the dynamic process.

Suggested Citation

  • Manuel S. Santos, 2007. "Consistency Properties of a Simulation-Base Estimator for Dynamic Processes," Working Papers 0613, University of Miami, Department of Economics.
  • Handle: RePEc:mia:wpaper:0613
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    More about this item

    Keywords

    Markov process; simulation-based estimation; invariant probability; sample distribution; monotonicity; strong consistency;

    JEL classification:

    • J12 - Labor and Demographic Economics - - Demographic Economics - - - Marriage; Marital Dissolution; Family Structure
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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