Consistency Properties of a Simulation-Based Estimator for Dynamic Processes Articles uri icon

authors

  • SANTOS SANTOS, MANUEL

publication date

  • January 2010

start page

  • 196

end page

  • 213

issue

  • 1

volume

  • 20

International Standard Serial Number (ISSN)

  • 1050-5164

abstract

  • This paper considers a simulation-based estimator for a general class of Markovian processes and explores some strong consistency properties of the estimator. 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. The
    estimator is applied to an asset pricing model with technology adoption. A
    challenge for this model is to generate the observed high volatility of stock
    markets along with the much lower volatility of other real economic aggregates.