Home | Jungbin Hwang

Research Interests

My research mainly focuses on the efficiency and approximation issues in Generalized Method of Moments (GMM) methods for economic data in the presence dependence and heterogeneity. I develop new, more accurate, and easy-to-use approximations to the nonparametric estimator of GMM weighting matrix. Besides the GMM context, I also apply the idea of new asymptotics to other modern econometric models such as triangular cointegration regression and long-horizon predictive regression. I am also interested in applied econometrics, financial econometrics, and Bayesian econometrics.

Publications

Asymptotic F and t Tests in an Efficient GMM Setting (with Yixiao Sun)
Journal of Econometrics 198, no. 2 (2017): 277-295 [Paper]
Simple, Robust, and Accurate F and t Tests in Cointegrated Systems (with Yixiao Sun)
Econometric Theory (2017): 1-36. doi:10.1017/S026646661700038X [Paper]
Should We Go One Step Further? An Accurate Comparison of One-step and Two-step Procedures in a Generalized Method of Moments Framework (with Yixiao Sun)
Journal of Econometrics (2018), 207(2), 381-405. [Paper]
Religiosity: Identifying the Effect of Pluralism (with Metin Cosgel, Thomas J. Miceli and Sadullah Yıldırım)
Journal of Economic Behavior & Organization (2019), 158, 219-235. [Paper]

Working Papers

Simple and Trustworthy Cluster-Robust GMM Inference (Revised 2020)
Accepted at Journal of Econometrics [Paper, Supplemental Appendix]
A Doubly Corrected Robust Variance Estimator for Linear GMM (with Byunghoon Kang and Seojeong Jay Lee, Revised 2020)
Revise and Resubmit at Journal of Econometrics [Paper]
Finite-sample Corrected Inference for Two-step GMM in Time Series (with Gonzalo Valdes, 2020)

Revise and Resubmit at Journal of Econometrics [Paper]
Low Frequency Cointegrating Regression in the Presence of Local to Unity Regressors and Unknown Form of Serial Dependence (with Gonzalo Valdes, July 2020)

[Paper]