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.
This chapter was originally published in The New Palgrave Dictionary of Economics, 2nd edition, 2008. Edited by Steven N. Durlauf and Lawrence E. Blume
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Renault, E. (2008). Simulation-Based Estimation. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95121-5_2532-1
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DOI: https://doi.org/10.1057/978-1-349-95121-5_2532-1
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