Jungbin Hwang
Assistant Professor at University of Connecticut
Email: jungbin.hwang at uconn.edu
Mailing Address:
University of Connecticut
Department of Economics
365 Fairfield Way, Unit 1063
Storrs, CT 06269-1063
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.
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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, Forthcoming [Paper]
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Asymptotic Theory for GMM Inference with Fixed Number of Clusters (Previously Circulated as Simple and Trustworthy Cluster-Robust GMM Inference)
Revise and Resubmit at Journal of Econometrics [Paper] -
Low-Frequency Robust Cointegrated Regression in the Presence of Near-Unity Regressor (with Gonzalo Valdes, 2018)
- A Doubly Corrected Robust Variance Estimator for Linear GMM (with Byunghoon Kang and Seojeong Jay Lee, 2018)
- Religiosity: Identifying the Effect of Pluralism (with Metin Cosgel, Thomas J. Miceli and Sadullah Yıldırım, 2018)