Jungbin Hwang, Ph.D. (Economics)

Jungbin Hwang, Ph.D. (Economics)

Associate 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

Research Interests : Econometrics Theory and Applied Econometrics
  • Robust inference for GMM and quantile regression involving dependent data, including time series, cross-sectional, and panel
  • Robust inference for persistent (non-stationary) data, investigating linear and non-linear cointegration relationships, and (quantile) predictability of stock and bond returns
  • Robust inference for time series (quantile) regressions where regressors are extracted from large datasets
  • (Quasi-) Bayesian approaches for non-parametric and non-smooth time series regressions
  • Applied econometrics and causal analysis of energy markets, sports markets, bond markets, financial risk, environmental data, and country panels
Working Papers
  • HAR Inference for Quantile Regression in Time Series (with Gonzalo Valdés) [Paper] Submitted
  • Across the Grid: How Generation Entry Shapes Congestion and Locational Price Dispersion (with Harim Kim) [Paper] Submitted
  • Higher-order Accuracy of HAR Inference and Testing-Oriented Smoothing Parameter for Over-identified GMM (with Gonzalo Valdés)​ Submitted
  • Asymptotic F and t Tests in Cointegrating Regressions with Asymptotically Homogeneous Functions (with Yixiao Sun) [Paper] R&R, Journal of Business & Economic Statistics
  • Central Limit Theorem for Fixed Number of Large-sized Clusters (with Gonzalo Valdés) [Paper] R&R, Economic Letters
  • Sieve Bootstrap Approach to Robust Term Premia Analysis (with Feifan Wang) [Paper] R&R, Journal of Empirical Finance
  • Effect of Anthem Protests on NFL Attendance (with Oskar Harmon) [Paper] R&R, Southern Economic Journal

 

 

Publications 
  • Low Frequency Cointegrating Regression with Local to Unity Regressors and Unknown Form of Serial Dependence (with Gonzalo Valdés)
    Journal of Business & Economic Statistics (2024), 42(1), 160-173 [Paper Link]
  • Finite-sample Corrected Inference for Two-step GMM in Time Series (with Gonzalo Valdés)
    Journal of Econometrics (2023), 234(1), 327-352 [Paper Link]
  • A Doubly Corrected Robust Variance Estimator for Linear GMM (with Byunghoon Kang and Seojeong Jay Lee)
    Journal of Econometrics (2022), 229(2), 276-298  [Paper Link]
  • Simple and Trustworthy Cluster-Robust GMM Inference
    Journal of Econometrics (2021), 222(2), 993-1023  [Paper linkLong version]
  • 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 link]
  • 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 link]
  • Simple, Robust, and Accurate F and t Tests in Cointegrated Systems (with Yixiao Sun)
    Lead article at Econometric Theory (2018), Vol 34, Issue 5, 949-984  [Paper link]
  • Asymptotic F and t Tests in an Efficient GMM Setting (with Yixiao Sun)
    Journal of Econometrics 198, no. 2 (2017): 277-295     [Paper link] [Erratum]
  • Extreme risk spillover in financial markets: Evidence from the recent financial crisis (with Jae-Young Kim)
    Seoul Journal of Economics, 28, (2015): 171-198.

Teaching Experience at UConn – Total 12 preps (subjects) since Fall 2016
  • ECON 2311: Undergraduate Econometrics I [Syllabus]
  • ECON 2312Q: Undergraduate Econometrics II
  • ECON 3313: Undergraduate Elementary Economic Forecasting
  • ECON 6310: Ph.D. Econometrics I [Syllabus]
  • ECON 6311: Ph.D. Econometrics II
  • ECON 6498: Ph.D. Topics in Econometrics
    • Asymptotic theory on series and sieve estimations [Syllabus Fall 2018 (Half semester)]
    • Edgeworth expansion and asymptotic refinements on bootstrap method [Fall 2019 (Half semester)]
    • Double machine learning for causal inference [Fall 2020 (Half semester)]
    • Asymptotic theory on LASSO methods [Fall 2021 (Half semester)]
Ph.D. Advising (as Major Advisor)