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Efficient Estimation Using Regularized Jackknife IV Estimator


  • Marine CARRASCO
  • Mohamed DOUKALI


We consider instrumental variables (IV) regression in a setting with many (possibly weak) instruments. In finite samples, the inclusion of an excessive number of moments may increase the bias of IV estimators. We propose a Jackknife instrumental variables estimator (RJIVE) combined with regularization techniques based on Tikhonov (T), Principal Components (PC) and Landweber Fridman (LF) methods to stabilize the projection matrix. We prove that the RJIVE is consistent and asymptotically normally distributed. Moreover, it reaches the semi parametric efficiency bound under certain conditions. We derive the rate of the approximate mean square error and propose a data-driven method for selecting the tuning parameter. Simulation results show that our proposed estimators provide more reliable confidence intervals than other regularized estimators.

Suggested Citation

  • Marine CARRASCO & Mohamed DOUKALI, 2017. "Efficient Estimation Using Regularized Jackknife IV Estimator," Annals of Economics and Statistics, GENES, issue 128, pages 109-149.
  • Handle: RePEc:adr:anecst:y:2017:i:128:p:109-149 DOI: 10.15609/annaeconstat2009.128.0109

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    References listed on IDEAS

    1. Sokullu, Senay, 2016. "Network effects in the German magazine industry," Economics Letters, Elsevier, vol. 143(C), pages 77-79.
    2. Frédérique Fève & Jean-Pierre Florens, 2010. "The practice of non-parametric estimation by solving inverse problems: the example of transformation models," Econometrics Journal, Royal Economic Society, vol. 13(3), pages 1-27, October.
    3. S. Darolles & Y. Fan & J. P. Florens & E. Renault, 2011. "Nonparametric Instrumental Regression," Econometrica, Econometric Society, vol. 79(5), pages 1541-1565, September.
    4. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
    5. Qi Li & Jeffrey Scott Racine, 2006. "Density Estimation, from Nonparametric Econometrics: Theory and Practice," Introductory Chapters,in: Nonparametric Econometrics: Theory and Practice Princeton University Press.
    6. repec:cup:etheor:v:33:y:2017:i:04:p:839-873_00 is not listed on IDEAS
    7. Florens, Jean-Pierre & Sokullu, Senay, 2017. "Nonparametric Estimation Of Semiparametric Transformation Models," Econometric Theory, Cambridge University Press, vol. 33(04), pages 839-873, August.
    8. Joel L. Horowitz, 2011. "Applied Nonparametric Instrumental Variables Estimation," Econometrica, Econometric Society, vol. 79(2), pages 347-394, March.
    9. Senay Sokullu, 2012. "Nonparametric Analysis of Two-Sided Markets," Bristol Economics Discussion Papers 12/628, Department of Economics, University of Bristol, UK.
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    More about this item


    Many Instruments; Mean Square Error; Jackknife; Regularization Methods.;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection


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