LIANG CHEN (陈亮)
Associate Professor
Peking University HSBC Business School
Email: chenliang@phbs.pku.edu.cn
[Resume] [Google Scholar]
Associate Professor
Peking University HSBC Business School
Email: chenliang@phbs.pku.edu.cn
[Resume] [Google Scholar]
Econometric Theory (Factor Models, Panel Data, Quantile Regressions)
Applied Econometrics
2020 to 2025: Assistant Professor, Peking University HSBC Business School
2016 to 2020: Assistant Professor, Shanghai University of Finance and Economics
2013 to 2016: Postdoctral Research Fellow, Nuffield College, University of Oxford
2007 to 2013: Ph.D in Economics, Universidad Carlos III de Madrid
2003 to 2007: B.S. in Economics, Huazhong University of Science and Technology
Faster uniform convergence rates for deconvolution estimators from repeated measurements, with M. Zhang, Econometric Theory, forthcoming.
Common correlated effects estimation of nonlinear panel data models, with M. Zhang, The Econometrics Journal, 28.2 (2025): 295-317.
Two-step estimation of quantile panel data models with interactive fixed effects, Econometric Theory, 40.2 (2024): 419-446.
Heterogeneous predictive association of CO2 with global warming, with J. J. Dolado, J. Gonzalo and A. Ramos, Economica, 90.360 (2023): 1397-1421.
A simple estimator for quantile panel data models using smoothed quantile regressions, with Y. Huo, The Econometrics Journal 24 (2021): 247-263.
Quantile factor models, with J. J. Dolado and J. Gonzalo, Econometrica 89.2 (2021): 875-910. [Correction]
Set identification of panel data models with interactive effects via quantile restrictions, Economics Letters 137 (2015): 36-40.
Estimating the common break date in large factor models, Economics Letters 131 (2015): 70-74.
Detecting big structural breaks in large factor models, with J. J. Dolado and J. Gonzalo, Journal of Econometrics 180.1 (2014): 30-48.
Estimation of characteristic-based quantile factor models, with J. J. Dolado, J. Gonzalo and H. Pan.
Nonparametric quantile regressions for panel data models with large T, PHBS Working Paper No20210104.