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Constrained EMM and Indirect Inference Estimation. Versión Revisada

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  • Giorgio Calzolari
  • Gabriele Fiorentini
  • Enrique Sentana

Abstract

We develop generalised indirect inference procedures that handle equality and inequality constraints on the auxiliary model parameters. We obtain expressions for the optimal weighting matrices, and discuss as examples an MA(1) estimated as AR(1), an AR(1) estimated as MA(1), and a log-normal stochastic volatility process estimated as a GARCH(1,1) with Gaussian or t distributed errors. In the first example, the constraints have no effect, while in the second, they allow us to achieve full efficiency. As for the third, neither procedure systematically outperforms the other, but equality restricted estimators are better when the additional parameter is poorly estimated.

Suggested Citation

  • Giorgio Calzolari & Gabriele Fiorentini & Enrique Sentana, 2000. "Constrained EMM and Indirect Inference Estimation. Versión Revisada," Working Papers wp2000_0005, CEMFI.
    • Handle: RePEc:cmf:wpaper:wp2000_0005
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    Cited by:

    1. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.

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