Using machine learning and causal inference for evaluating air pollution control policies (In person)

Date: Wednesday 13 November 2024, 12.00PM
Location: University of Birmingham
UNIH-G07 University House G07, University of Birmingham
Section Group Meeting


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Traffic emissions are one of the most important sources of urban air pollution. One widely adopted strategy for mitigating urban air pollution is traffic management through Low Emission Zones (LEZs). As many other UK cities are either considering or already implementing similar policies, a rigorous evaluation of its effectiveness is crucial.  Using Birmingham's Clean Air zone and London's Ultra Low Emission Zone as case studies, we propose a two-step data driven approach to assess the causal impact of these interventions on local air quality. Our goal is to develop a quantitative, user-friendly tool for evaluating the effects of clean air policies on air pollution levels based on observational data. 
 
Dr. Bowen Liu, Assistant Professor in Industrial Economics, Department of Management, Birmingham Business School, University of Birmingham

Dr. Bowen Liu is an applied economist whose research interests lie in the areas of Industrial Economics, Environmental Economics, Climate Change Economics. Bowen is interested in policy evaluation using interdisciplinary methods that combining Econometrics and Machine Learning, with a particular focus on policies and interventions that promote innovation, economic development, environmental protection and sustainable development. His work has been published in economics journals (like Environmental and Resource Economics) and leading science journals (like Science Advances, Environmental Science and Technology, EST Letters, Environmental Modelling & Software). 
 
 
Jia Shao for Finance and Economics Section Group
 
Member - free to attend

Non member - £10