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Indirect Inference Based on the Score

Author

Listed:
  • Peter Fuleky

    (University of Hawaii)

  • Eric Zivot

    (University of Washington)

Abstract

The Ecient 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 Gourieroux, Monfort and Renault (1993).

Suggested Citation

  • Peter Fuleky & Eric Zivot, 2010. "Indirect Inference Based on the Score," Working Papers UWEC-2010-08, University of Washington, Department of Economics.
  • Handle: RePEc:udb:wpaper:uwec-2010-08
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    File URL: http://faculty.washington.edu/ezivot/research/scorebasedindirectinference.pdf
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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. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(04), pages 657-681, October.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Gregory R. Duffee, 2008. "Evidence on Simulation Inference for Near Unit-Root Processes with Implications for Term Structure Estimation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(1), pages 108-142, Winter.
    8. 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.
    9. 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.
    10. Tripathi, Gautam, 2000. "Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(01), pages 139-142, February.
    11. Andersen, Torben G., 2000. "Simulation-Based Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(01), pages 131-138, February.
    12. repec:adr:anecst:y:2003:i:69:p:04 is not listed on IDEAS
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    More about this item

    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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