报告摘要：
Marginal abatement cost (MAC) is a critically important concept for efficient environmental policy and management. However, most empirical studies using frontier estimation methods tend to overestimate MACs. There are three sources of upward bias due to the limited set of abatement options, inefficiency, and noisy data. To address the bias, a MAC estimation approach based on convex quantile regression (CQR) is proposed by Kuosmanen and Zhou (2021, EJOR), which has gained increased popularity in the empirical assessment of MACs and the identification of least-cost pathways. This seminar will introduce the CQR approach, before reviewing its recent applications and methodological developments. Future research avenues will also be discussed.
嘉宾简介：
Dr Xun Zhou is a Senior Lecturer in Business Analytics at Surrey Business School (SBS),University of Surrey, UK. Prior to joining SBS, he was a Lecturer (Assistant Professor) in Environmental Economics at the University of York, UK (2021-2023) and a Postdoctoral Senior Researcher at the Technical University of Munich, Germany (2020-2021). In 2019, he received his PhD (Econ) in Management Science from Aalto University School of Business, Finland. He has been focusing on shadow pricing undesirable outputs within the frontier estimation framework and evaluating the causal effects of policy interventions. He has published in journals such as European Journal of Operational Research, World Development, Energy Economics, Journal of Environmental Management, Economics Letters, and Internet Research.