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Semiparametric Efficiency Bounds for Microeconometric Models: A Survey

Author

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  • Severini, Thomas A.
  • Tripathi, Gautam

Abstract

In this survey, we evaluate estimators by comparing their asymptotic variances. The role of the efficiency bound, in this context, is to give a lower bound to the asymptotic variance of an estimator. An estimator with asymptotic variance equal to the efficiency bound can therefore be said to be asymptotically efficient. These bounds are also useful for understanding how the features of a given model affect the accuracy of parameter estimation.

Suggested Citation

  • Severini, Thomas A. & Tripathi, Gautam, 2013. "Semiparametric Efficiency Bounds for Microeconometric Models: A Survey," Foundations and Trends(R) in Econometrics, now publishers, vol. 6(3-4), pages 163-397, December.
    • Handle: RePEc:now:fnteco:0800000019
    DOI: 10.1561/0800000019
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    Citations

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    Cited by:

    1. Chen, Jiafeng & Chen, Xiaohong & Tamer, Elie, 2023. "Efficient estimation of average derivatives in NPIV models: Simulation comparisons of neural network estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1848-1875.
    2. Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021. "Efficient Estimation of Average Derivatives in NPIV Models: Simulation Comparisons of Neural Network Estimators," Cowles Foundation Discussion Papers 2319, Cowles Foundation for Research in Economics, Yale University.
    3. Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021. "Efficient Estimation in NPIV Models: A Comparison of Various Neural Networks-Based Estimators," Papers 2110.06763, arXiv.org, revised Oct 2022.
    4. Chen, Tao & Parker, Thomas, 2014. "Semiparametric efficiency for partially linear single-index regression models," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 376-386.

    More about this item

    Keywords

    Weak instruments; Linear simultaneous equation models; Instrument variables estimation; Large-sample asymptotic analysis; Finite-sample analysis; Hypothesis testing;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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