Consistency properties of a simulation-based estimator for dynamic processes

Details Consistency properties of a simulation-based estimator for dynamic processes Consistency properties of a simulation-based estimator for dynamic processes

2010-01-13

arxiv.org/abs/1001.2173v1

Annals of Applied Probability 2010, Vol. 20, No. 1, 196-213

Mathematics

Probability

Published in at http://dx.doi.org/10.1214/09-AAP608 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Inst

Scientific paper

10.1214/09-AAP608

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.

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