The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Simulation-Based Estimation

  • Eric Renault
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2532

Abstract

For a parametric econometric model with possibly latent variables, the simulation tool and Monte Carlo integration provide a versatile minimum distance estimation principle. The general approach is dubbed simulation-based indirect inference. It can take advantage of any instrumental piece of information that identifies the structural parameters. Examples include the simulated method of moments and its simulated-score-matching version. Monte Carlo integration also allows numerical assessment of the criterion to maximize for M-estimation. Asymptotic efficiency is reached by the simulated maximum likelihood or a simulated score technique. Since the simulator is provided by the structural model, the classical trade-off between efficiency and robustness to misspecification must be revisited.

Keywords

Bias correction Bootstrap Efficient method of moments Extremum estimation GARCH models Generalized method of moments Indirect inference Indirect least squares Maximum likelihood Monte Carlo methods Parameter-matching estimators Score-matching estimators Simulated expectation maximization Simulated maximum likelihood Simulated method of moments Simulated score matching Simulation-based estimation Simulation-based indirect inference Statistical estimation Stochastic volatility models White noise 

JEL Classifications

C14 C15 
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© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Eric Renault
    • 1
  1. 1.