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Simulation Based Inference in Models with Heterogeneity

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  • Christian GOURIEROUX
  • Alain MONFORT

Abstract

In this paper we discuss the usefulness, for models with heterogeneity, of simulation techniques in inference procedures, like maximum likelihood method, generalized moments method or pseudo maximum likelihood methods. These procedures are studied from the point of view of consistency, asymptotic normality, convergence rates and possible asymptotic bias. We carefully distinguish the case where the simulations are different for all the observations from the case where they are identical.

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File URL: http://www.jstor.org/stable/20075807
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Bibliographic Info

Article provided by ENSAE in its journal Annals of Economics and Statistics.

Volume (Year): (1991)
Issue (Month): 20-21 ()
Pages: 69-107

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Handle: RePEc:adr:anecst:y:1991:i:20-21:p:04

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Cited by:
  1. Szabolcs Blazsek & Alvaro Escribano, 2009. "Knowledge spillovers in U.S. patents: a dynamic patent intensity model with secret common innovation factors," Economics Working Papers we098951, Universidad Carlos III, Departamento de Economía.
  2. Thiel, Hendrik & Thomsen, Stephan L., 2009. "Noncognitive skills in economics: Models, measurement, and empirical evidence," ZEW Discussion Papers 09-076, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  3. Szabolcs Blazsek & Alvaro Escribano, 2010. "Knowledge spillovers in U.S. patents: A dynamic patent intensity model with secret common innovation factors," Post-Print hal-00732533, HAL.

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