Prof. Songnian CHEN

Award Citation

Professor Songnian Chen is Chair Professor of Economics at The Hong Kong University of Science and Technology. He has made seminal contributions in numerous areas of econometrics, especially in developing quantitative tools to evaluate the effects of public policy and social programs. Professor Chen has served as HKUST IAS Senior Fellow and on the Advisory Committee of the Institute of Economics, Academia Sinica. He has been invited to give numerous keynote presentations.  Currently, he serves as an Associate Editor of the Journal of Econometrics. He has been named an RGC Senior Research Fellow for his project, “Quantile Regression Subject to Sample Selection with Continuous and Binary Outcomes”. 

Sample selection models and quantile regression are quantitative tools that are widely used in economics, business, and the social sciences to evaluate the effects of public policy and social programs. For example, in the study of wage gaps and wage inequality, only the wages of employed individuals are observed, and thus wage differences among working individuals based on observed wages provide a distorted picture. Sample selection models were developed to address such distortions. 

Quantile regression was also motivated by the desire to overcome drawbacks associated with traditional approaches. When analyzing the impact of public policies, traditional methods focus on average effects, whereas quantile regression techniques reveal the entire distribution of policy effects in the population well beyond simple average effects. For example, focusing on the bottom part of the income distribution when assessing the impact of poverty alleviation measures is more appropriate than average effects, and quantile regression provides an effective tool for doing so.

Despite the prevalence of non-random sample selection, little progress has been made in developing quantile regression that accounts for sample selection. This project proposes an innovative approach to address this gap.