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Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification. / Lee, S.; Kang, B.; Song, J.
In: Seoul Journal of Economics, Vol. 38, No. 1, 2025, p. 29-50.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Lee, S, Kang, B & Song, J 2025, 'Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification', Seoul Journal of Economics, vol. 38, no. 1, pp. 29-50. https://doi.org/10.22904/sje.2025.38.1.002

APA

Lee, S., Kang, B., & Song, J. (2025). Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification. Seoul Journal of Economics, 38(1), 29-50. https://doi.org/10.22904/sje.2025.38.1.002

Vancouver

Lee S, Kang B, Song J. Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification. Seoul Journal of Economics. 2025;38(1):29-50. doi: 10.22904/sje.2025.38.1.002

Author

Lee, S. ; Kang, B. ; Song, J. / Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification. In: Seoul Journal of Economics. 2025 ; Vol. 38, No. 1. pp. 29-50.

Bibtex

@article{fe086e639872496e99f2d60b93d5f528,
title = "Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification",
abstract = "The asymptotic behavior of generalized method of moments (GMM) estimators depends critically on whether the underlying moment condition model is correctly specified. Hong and Li (2024) showed that GMM estimators with nonsmooth (nondirectionally differentiable) moment functions are at best n1/3 consistent under misspecification. Through simulations, we verify the decelerated convergence rate of GMM estimators in such cases. For the two-step GMM estimator with an estimated weight matrix, our results align with the theory. However, for the one-step GMM estimator with the identity weight matrix, the convergence rate remains n even under severe misspecification.",
author = "S. Lee and B. Kang and J. Song",
year = "2025",
doi = "10.22904/sje.2025.38.1.002",
language = "English",
volume = "38",
pages = "29--50",
journal = "Seoul Journal of Economics",
number = "1",

}

RIS

TY - JOUR

T1 - Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification

AU - Lee, S.

AU - Kang, B.

AU - Song, J.

PY - 2025

Y1 - 2025

N2 - The asymptotic behavior of generalized method of moments (GMM) estimators depends critically on whether the underlying moment condition model is correctly specified. Hong and Li (2024) showed that GMM estimators with nonsmooth (nondirectionally differentiable) moment functions are at best n1/3 consistent under misspecification. Through simulations, we verify the decelerated convergence rate of GMM estimators in such cases. For the two-step GMM estimator with an estimated weight matrix, our results align with the theory. However, for the one-step GMM estimator with the identity weight matrix, the convergence rate remains n even under severe misspecification.

AB - The asymptotic behavior of generalized method of moments (GMM) estimators depends critically on whether the underlying moment condition model is correctly specified. Hong and Li (2024) showed that GMM estimators with nonsmooth (nondirectionally differentiable) moment functions are at best n1/3 consistent under misspecification. Through simulations, we verify the decelerated convergence rate of GMM estimators in such cases. For the two-step GMM estimator with an estimated weight matrix, our results align with the theory. However, for the one-step GMM estimator with the identity weight matrix, the convergence rate remains n even under severe misspecification.

U2 - 10.22904/sje.2025.38.1.002

DO - 10.22904/sje.2025.38.1.002

M3 - Journal article

VL - 38

SP - 29

EP - 50

JO - Seoul Journal of Economics

JF - Seoul Journal of Economics

IS - 1

ER -