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A method of moments estimator for semiparametric index models

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  • Donkers, Bas
  • Schafgans, Marcia M. A.

Abstract

We propose an easy to use derivative based two-step estimation procedure for semi-parametric index models. In the first step various functionals involving the derivatives of the unknown function are estimated using nonparametric kernel estimators. The functionals used provide moment conditions for the parameters of interest, which are used in the second step within a method-of-moments framework to estimate the parameters of interest. The estimator is shown to be root N consistent and asymptotically normal. We extend the procedure to multiple equation models. Our identification conditions and estimation framework provide natural tests for the number of indices in the model. In addition we discuss tests of separability, additivity, and linearity of the influence of the indices.

Suggested Citation

  • Donkers, Bas & Schafgans, Marcia M. A., 2005. "A method of moments estimator for semiparametric index models," LSE Research Online Documents on Economics 6815, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:6815
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    References listed on IDEAS

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    1. P. M. Robinson, 1989. "Hypothesis Testing in Semiparametric and Nonparametric Models for Econometric Time Series," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 56(4), pages 511-534.
    2. Powell, James L. & Stoker, Thomas M., 1996. "Optimal bandwidth choice for density-weighted averages," Journal of Econometrics, Elsevier, vol. 75(2), pages 291-316, December.
    3. Donkers, A.C.D. & Schafgans, M., 2003. "A derivative based estimator for semiparametric index models," Econometric Institute Research Papers EI 2003-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Lavergne, Pascal & Vuong, Quang H, 1996. "Nonparametric Selection of Regressors: The Nonnested Case," Econometrica, Econometric Society, vol. 64(1), pages 207-219, January.
    5. Phillips, Peter C B, 1994. "Some Exact Distribution Theory for Maximum Likelihood Estimators of Cointegrating Coefficients in Error Correction Models," Econometrica, Econometric Society, vol. 62(1), pages 73-93, January.
    6. Whitney K. Newey, 2004. "Efficient Semiparametric Estimation via Moment Restrictions," Econometrica, Econometric Society, vol. 72(6), pages 1877-1897, November.
    7. Hardle W. & Sperlich S. & Spokoiny V., 2001. "Structural Tests in Additive Regression," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1333-1347, December.
    8. Serge Darolles & Christian Gourieroux & Joanna Jasiak, 2001. "Compound Autoregressive Models," Working Papers 2001-21, Center for Research in Economics and Statistics.
    9. Lee, Lung-fei, 1995. "Semiparametric maximum likelihood estimation of polychotomous and sequential choice models," Journal of Econometrics, Elsevier, vol. 65(2), pages 381-428, February.
    10. Lewbel, Arthur, 1997. "Semiparametric Estimation of Location and Other Discrete Choice Moments," Econometric Theory, Cambridge University Press, vol. 13(1), pages 32-51, February.
    11. Barnett,William A. & Powell,James & Tauchen,George E. (ed.), 1991. "Nonparametric and Semiparametric Methods in Econometrics and Statistics," Cambridge Books, Cambridge University Press, number 9780521424318, September.
    12. Yingcun Xia & Howell Tong & W. K. Li & Li‐Xing Zhu, 2002. "An adaptive estimation of dimension reduction space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 363-410, August.
    13. Picone, Gabriel A. & Butler, J.S., 2000. "Semiparametric Estimation Of Multiple Equation Models," Econometric Theory, Cambridge University Press, vol. 16(4), pages 551-575, August.
    14. Newey, Whitney K & Stoker, Thomas M, 1993. "Efficiency of Weighted Average Derivative Estimators and Index Models," Econometrica, Econometric Society, vol. 61(5), pages 1199-1223, September.
    15. Thomas M. Stoker, 1989. "Tests of Additive Derivative Constraints," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 56(4), pages 535-552.
    16. P. Lavergne & Q.H. Vuong, 1996. "Nonparametric selection of regressors : the nonnested case [[Sélection non paramétrique de régresseurs : le cas de régressions non emboîtées]]," Post-Print hal-02689500, HAL.
    17. Chunrong Ai & Xiaohong Chen, 2003. "Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions," Econometrica, Econometric Society, vol. 71(6), pages 1795-1843, November.
    18. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    19. Delecroix, Michel & Härdle, Wolfgang & Hristache, Marian, 2003. "Efficient estimation in conditional single-index regression," Journal of Multivariate Analysis, Elsevier, vol. 86(2), pages 213-226, August.
    20. Barnett,William A. & Powell,James & Tauchen,George E. (ed.), 1991. "Nonparametric and Semiparametric Methods in Econometrics and Statistics," Cambridge Books, Cambridge University Press, number 9780521370905, September.
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    Cited by:

    1. Victoria Zinde-Walsh & Marcia M.A. Schafgans, 2007. "Robust Average Derivative Estimation," Departmental Working Papers 2007-12, McGill University, Department of Economics.

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    More about this item

    Keywords

    semiparametric estimation; multiple index models; average derivative functionals; generalized methods of moments estimator; rank testing;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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