Accuracy of simulations for stochastic dynamic models

By Manuel S. Santos, Adrian Alva. 2005

74 citations recorded by the source corpus.

This paper provides a general framework for the simulation of stochastic dynamic models. Our analysis rests upon a continuity property of invariant distributions and a generalized law of large numbers. We then establish that the simulated moments from numerical approximations converge to their exact values as the approximation errors of the computed solutions converge to zero. These asymptotic results are of further interest in the comparative study of dynamic solutions, model estimation, and derivation of error bounds for the simulated moments.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/7a6f3e9e924f5173d59c1158fdc14809fad82e02

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Citations in the corpus

Comparison of Solutions to the Incomplete Markets Model with Aggregate Uncertainty (2008, background): “Reiter (2001) and Santos and Peralta-Alva (2005) construct a relationship between the size of the errors found and upperbounds on the errors of objects that economists are interested in such as the obtained utility level or moments.”
Assessing the accuracy of the aggregate law of motion in models with heterogeneous agents (2010, unknown): “…text, the di¤erences between the true and the approximating law of22 motion are much larger when shocks occur at low values of mt.23 28 B Relation to Santos and Peralta-Alva (2005)24 Some motivation for using the maximum prediction error in the accuracy test is found in1 Santos and Peralta-Alva…”
Perturbation Methods for Markov-Switching DSGE Models (2014, methodology): “This procedure is justified by Santos and Peralta-Alva (2005).”
Estimating Nonlinear DSGE Models by the Simulated Method of Moments (2010, unknown): “[27]”
Estimating Macroeconomic Models: A Likelihood Approach (2007, unknown): “In general, since we cannot evaluate p (S0; γ), it is not possible to draw from it with an McMc. Santos and Peralta-Alva (2005) solve this problem by showing how to sample from p (S0; γ) using the transition and measurement equations (1) and (2).”
Macroeconomics and Volatility: Data, Models, and Estimation (2010, background): “As described in Santos and Peralta-Alva (2005), given some parameter values Ψ, we can simulate the model for a suffi ciently large path (to wash out the effect of the initial conditions, which we can make equal to the steady state just for simplicity, although other starting points are admissible…”