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Sensitivity of Regular Estimators

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  • Yaroslav Mukhin

Abstract

This paper studies local asymptotic relationship between two scalar estimates. We define sensitivity of a target estimate to a control estimate to be the directional derivative of the target functional with respect to the gradient direction of the control functional. Sensitivity according to the information metric on the model manifold is the asymptotic covariance of regular efficient estimators. Sensitivity according to a general policy metric on the model manifold can be obtained from influence functions of regular efficient estimators. Policy sensitivity has a local counterfactual interpretation, where the ceteris paribus change to a counterfactual distribution is specified by the combination of a control parameter and a Riemannian metric on the model manifold.

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  • Yaroslav Mukhin, 2018. "Sensitivity of Regular Estimators," Papers 1805.08883, arXiv.org.
    • Handle: RePEc:arx:papers:1805.08883
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    1. Sueishi, Naoya, 2016. "A simple derivation of the efficiency bound for conditional moment restriction models," Economics Letters, Elsevier, vol. 138(C), pages 57-59.
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    Cited by:

    1. Isaiah Andrews & Matthew Gentzkow & Jesse M. Shapiro, 2020. "On the Informativeness of Descriptive Statistics for Structural Estimates," Econometrica, Econometric Society, vol. 88(6), pages 2231-2258, November.
    2. Philipp Eisenhauer & Janos Gabler & Lena Janys, 2021. "Structural Models for Policy-Making: Coping with Parametric Uncertainty," ECONtribute Discussion Papers Series 082, University of Bonn and University of Cologne, Germany.
    3. Stéphane Bonhomme & Martin Weidner, 2020. "Minimizing Sensitivity to Model Misspecification," CeMMAP working papers CWP37/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Eisenhauer, Philipp & Gabler, Janos & Janys, Lena, 2021. "Structural Models for Policy-Making: Coping with Parametric Uncertainty," IZA Discussion Papers 14317, Institute of Labor Economics (IZA).
    5. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    6. Timothy B. Armstrong & Michal Kolesár, 2021. "Sensitivity analysis using approximate moment condition models," Quantitative Economics, Econometric Society, vol. 12(1), pages 77-108, January.
    7. Claudia Noack, 2021. "Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption," Papers 2106.06421, arXiv.org.
    8. Timothy Christensen & Benjamin Connault, 2023. "Counterfactual Sensitivity and Robustness," Econometrica, Econometric Society, vol. 91(1), pages 263-298, January.

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