IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb373/199713.html
   My bibliography  Save this paper

Plug-in semiparametric estimating equations

Author

Listed:
  • Gutierrez, Roberto G.
  • Carroll, Raymond J.

Abstract

In parametric regression problems, estimation of the parameter of interest is typically achieved via the solution of a set of unbiased estimating equations. We are interested in problems where in addition to this parameter, the estimating equations consist of an unknown nuisance function which does not depend on the parameter. We study the effects of using a plug-in nonparametric estimator of the nuisance function (for example, a local-linear regression estimator) on the estimability of the parameter. In particular, we specify conditions on the functional estimator which ensure that the parametric rate of consistency for estimating the parameter of interest is preserved, and we give a general asymptotic covariance formula. We apply this theory to three examples.

Suggested Citation

  • Gutierrez, Roberto G. & Carroll, Raymond J., 1995. "Plug-in semiparametric estimating equations," SFB 373 Discussion Papers 1997,13, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:199713
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/66244/1/72832427X.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hardle, W. & Hall, P. & Ichimura, H., 1991. "Optimal smoothing in single index models," LIDAM Discussion Papers CORE 1991007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Newey, Whitney K., 1994. "Series Estimation of Regression Functionals," Econometric Theory, Cambridge University Press, vol. 10(1), pages 1-28, March.
    3. Carroll, R.J. & Fan, Jianqing. & Gijbels, Irene. & Wand, M.P., "undated". "Generalized Partially Linear Single-Index Models," Statistics Working Paper 95010, Australian Graduate School of Management.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339, Elsevier.
    2. Linton, Oliver, 1995. "Second Order Approximation in the Partially Linear Regression Model," Econometrica, Econometric Society, vol. 63(5), pages 1079-1112, September.
    3. Xia, Yingcun & Härdle, Wolfgang Karl & Linton, Oliver, 2009. "Optimal smoothing for a computationally and statistically efficient single index estimator," SFB 649 Discussion Papers 2009-028, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Alberto Abadie, 2000. "Semiparametric Estimation of Instrumental Variable Models for Causal Effects," NBER Technical Working Papers 0260, National Bureau of Economic Research, Inc.
    5. Bolancé, Catalina & Guillén, Montserrat & Pinquet, Jean, 2008. "On the link between credibility and frequency premium," Insurance: Mathematics and Economics, Elsevier, vol. 43(2), pages 209-213, October.
    6. Miller, Steve & Startz, Richard, 2019. "Feasible generalized least squares using support vector regression," Economics Letters, Elsevier, vol. 175(C), pages 28-31.
    7. Yukitoshi Matsushita & Taisuke Otsu, 2017. "Likelihood inference on semiparametric models: Average derivative and treatment effect," STICERD - Econometrics Paper Series 592, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    8. Jia Chen & Jiti Gao & Degui Li, 2013. "Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 928-955, November.
    9. Chatelain, Jean-Bernard & Teurlai, Jean-Christophe, 2001. "Pitfalls in investment Euler equations," Economic Modelling, Elsevier, vol. 18(2), pages 159-179, April.
    10. Juan Carlos Escanciano & Kyungchul Song, 2007. "Asymptotically Optimal Tests for Single-Index Restrictions with a Focus on Average Partial Effects," PIER Working Paper Archive 07-005, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    11. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    12. Su, Liangjun & Jin, Sainan, 2012. "Sieve estimation of panel data models with cross section dependence," Journal of Econometrics, Elsevier, vol. 169(1), pages 34-47.
    13. Gayle, George-Levi & Viauroux, Christelle, 2007. "Root-N consistent semiparametric estimators of a dynamic panel-sample-selection model," Journal of Econometrics, Elsevier, vol. 141(1), pages 179-212, November.
    14. Jaumandreu, Jordi & Moral, Maria Jose, 2006. "Identifying behaviour in a multiproduct oligopoly: Incumbents reaction to tariffs dismantling," MPRA Paper 1248, University Library of Munich, Germany.
    15. Härdle, W.K. & Mammen, E. & Müller, M.D., 1996. "Testing Parametric versus Semiparametric Modelling in Generalized Linear Models," Discussion Paper 1996-42, Tilburg University, Center for Economic Research.
    16. Chen, Linkun & Clarke, Philip M. & Petrie, Dennis J. & Staub, Kevin E., 2021. "The effects of self-assessed health: Dealing with and understanding misclassification bias," Journal of Health Economics, Elsevier, vol. 78(C).
    17. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    18. Daniela Climov & Michel Delecroix & Leopold Simar, 2002. "Semiparametric estimation in single index Poisson regression: A practical approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(7), pages 1047-1070.
    19. Liu, Jicai & Zhang, Riquan & Zhao, Weihua & Lv, Yazhao, 2015. "Variable selection in semiparametric hazard regression for multivariate survival data," Journal of Multivariate Analysis, Elsevier, vol. 142(C), pages 26-40.
    20. Müller, Ursula U. & Schick, Anton & Wefelmeyer, Wolfgang, 2014. "Testing for additivity in partially linear regression with possibly missing responses," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 51-61.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:sfb373:199713. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/sfhubde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.