Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification

• 발행기관: 서울대학교 경제연구소
• 저자명: Byunghoon Kang Seojeong Lee Juha Song
• 간행물 정보: 『Seoul Journal of Economics』Volume 38 No.1, 29~49쪽, 전체 21쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2025.02.28

국문 초록

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.

목차

I. Introduction

II. Model and Estimator

III. Nonsmooth Location Model

IV. Quantile Regression with Endogeneity

V. Conclusion

References

키워드

Generalized method of moments Nondifferentiable moment Instrumental variables quantile regression