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Efficient estimation with many weak instruments using regularization techniques

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  • Guy Tchuente
  • Marine Carrasco

Abstract

The problem of weak instruments is due to a very small concentration parameter. To boost the concentration parameter, we propose to increase the number of instruments to a large number or even up to a continuum. However, in finite samples, the inclusion of an excessive number of moments may be harmful. To address this issue, we use regularization techniques as in Carrasco (2012) and Carrasco and Tchuente (2013). We show that normalized regularized 2SLS and LIML are consistent and asymptotically normally distributed. Moreover, their asymptotic variances reach the semiparametric efficiency bound unlike most competing estimators. Our simulations show that the leading regularized estimators (LF and T of LIML) work very well (is nearly median unbiased) even in the case of relatively weak instruments.

Suggested Citation

  • Guy Tchuente & Marine Carrasco, 2013. "Efficient estimation with many weak instruments using regularization techniques," CIRANO Working Papers 2013s-21, CIRANO.
    • Handle: RePEc:cir:cirwor:2013s-21
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    File URL: https://cirano.qc.ca/files/publications/2013s-21.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Vincent Boucher & Yann Bramoullé, 2020. "Binary Outcomes and Linear Interactions," Working Papers halshs-03031767, HAL.
    2. Berriel, Tiago & Medeiros, Marcelo C. & Sena, Marcelo J., 2016. "Instrument selection for estimation of a forward-looking Phillips Curve," Economics Letters, Elsevier, vol. 145(C), pages 123-125.
    3. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
    4. Guy Tchuente, 2021. "A Note on the Topology of the First Stage of 2SLS with Many Instruments," Papers 2106.15003, arXiv.org.
    5. Vincent Boucher & Yann Bramoullé, 2020. "Binary Outcomes and Linear Interactions," AMSE Working Papers 2038, Aix-Marseille School of Economics, France.
    6. Dakyung Seong, 2025. "Binary Response Model With Many Weak Instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(2), pages 214-230, March.
    7. Nandana Sengupta & Fallaw Sowell, 2019. "The Ridge Path Estimator for Linear Instrumental Variables," Papers 1908.09237, arXiv.org.
    8. Nandana Sengupta & Fallaw Sowell, 2020. "On the Asymptotic Distribution of Ridge Regression Estimators Using Training and Test Samples," Econometrics, MDPI, vol. 8(4), pages 1-25, October.

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    More about this item

    Keywords

    Many weak instruments; LIML; 2SLS; regularization methods;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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