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Indirect Inference Based on the Score

Author

Listed:
  • Peter Fuleky

    (Department of Economics, University of Hawaii at Manoa and University of Hawaii Economic Research Organization)

  • Eric Zivot

    (Department of Economics, University of Washington)

Abstract

The Efficient Method of Moments (EMM) estimator popularized by Gallant and Tauchen (1996) is an indirect inference estimator based on the simulated auxiliary score evaluated at the sample estimate of the auxiliary parameters. We study an alternative estimator that uses the sample auxiliary score evaluated at the simulated binding function which maps the structural parameters of interest to the auxiliary parameters. We show that the alternative estimator has the same asymptotic properties as the EMM estimator but in finite samples behaves more like the distance-based indirect inference estimator of Gouri�eroux, Monfort and Renault (1993).

Suggested Citation

  • Peter Fuleky & Eric Zivot, 2011. "Indirect Inference Based on the Score," Working Papers 2011-12, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    • Handle: RePEc:hae:wpaper:2011-12
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    References listed on IDEAS

    as
    1. Gallant, A. Ronald & Tauchen, George, 2002. "Simulated Score Methods and Indirect Inference for Continuous-time Models," Working Papers 02-09, Duke University, Department of Economics.
    2. Bansal, Ravi & Gallant, A. Ronald & Hussey, Robert & Tauchen, George, 1995. "Nonparametric estimation of structural models for high-frequency currency market data," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 251-287.
    3. Gouriéroux, Christian & Phillips, Peter C.B. & Yu, Jun, 2010. "Indirect inference for dynamic panel models," Journal of Econometrics, Elsevier, vol. 157(1), pages 68-77, July.
    4. Eric Ghysels & Lynda Khalaf & Cosmé Vodounou, 2003. "Simulation Based Inference In Moving Average Models," Annals of Economics and Statistics, GENES, issue 69, pages 85-99.
    5. Tripathi, Gautam, 2000. "Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(1), pages 139-142, February.
    6. Andersen, Torben G., 2000. "Simulation-Based Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(1), pages 131-138, February.
    7. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(4), pages 657-681, October.
    8. repec:adr:anecst:y:2003:i:69:p:04 is not listed on IDEAS
    9. Michaelides, Alexander & Ng, Serena, 2000. "Estimating the rational expectations model of speculative storage: A Monte Carlo comparison of three simulation estimators," Journal of Econometrics, Elsevier, vol. 96(2), pages 231-266, June.
    10. Smith, A A, Jr, 1993. "Estimating Nonlinear Time-Series Models Using Simulated Vector Autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 63-84, Suppl. De.
    11. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 85-118, Suppl. De.
    12. Gregory R. Duffee, 2008. "Evidence on Simulation Inference for Near Unit-Root Processes with Implications for Term Structure Estimation," Journal of Financial Econometrics, Oxford University Press, vol. 6(1), pages 108-142, Winter.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    2. Golombek, Rolf & Raknerud, Arvid, 2018. "Exit dynamics of start-up firms: Structural estimation using indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 204-225.

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    More about this item

    Keywords

    simulation based estimation; indirect inference; efficient method of moments;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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