Policy Analytics for Environmental Sustainability: Household Hazardous Waste and Water Impacts of Carbon Pollution Standards
Speaker (s): 
Kustini LIM-WAVDE
PhD Candidate
School of Information Systems
Singapore Management University | Date:
Time:
Venue: | | November 17, 2017, Friday
9:00am - 10:00am
Meeting Room 4.4, Level 4
School of Information Systems
Singapore Management University
80 Stamford Road
Singapore 178902 We look forward to seeing you at this research seminar. ![]()
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About the Talk
Policy analytics are essential in supporting more informed policy-making in environmental management. This dissertation employs a fusion of machine methods and explanatory empiricism that involves data analytics, math programming, optimization, econometrics, geospatial and spatiotemporal analysis, and other methodologies for assessing and evaluating current and future environmental policies.
Essay 1 introduces household informedness and its impact on the collection and recycling of household hazardous waste (HHW). Household informedness is the degree to which households have the necessary information to make utility-maximizing decisions about the handling of their waste. This essay contributes to the calculation of the elasticity of the output quantities of HHW collected and recycled for differences in household informedness at the county level. Essay 2 develops a random effects panel data model with instrumental variables to measure the causal effects of the effects of HHW grant on HHW collection activities while considering the spatial effects from the influence of the waste collection activities among close-by counties or regions. This model and the causality analysis that follows it are useful for a counterfactual assessment to develop a deeper understanding of how to make the allocation of grants more effective. Essay 3 assesses transition pathways in electricity generation and their future water impacts using an electricity generation capacity expansion model. Scenarios that do or do not comply with the U.S. Environmental Protection Agency's proposed carbon pollution standards – the New Source Performance Standards and Clean Power Plan – are considered.
These essays demonstrate the use of a variety of data analytics and management science methods that represent advances in policy analytics to overcome the research challenges, such as the data limitations, the uncertainties associated with the analysis of energy futures, and best practices establishing causal estimates in empirical research designs. This dissertation contributes to the growing body of research on policy analytics for environmental sustainability and improves our understanding of how to craft policies that enhance sustainability for the future.
About the Speaker
Kustini LIM-WAVDE is a PhD candidate in the School of Information Systems, Singapore Management University under the supervision of Prof. Robert J. Kauffman. She completed a 10-month PhD exchange program at Carnegie Mellon University (CMU) during Academic Year 2014-15. She received her B.Eng. degree in Electrical Engineering from University of Indonesia and MBA degree in International Management from International University of Japan. Her research lies in the interdisciplinary area of information, technology, sustainability, and policy analytics. She employs data analytics, econometrics, geospatial analysis, math programming, optimization and other relevant methodologies to support decision-makers in formulating policies for environmental sustainability. Her research has been published in Resources, Conservation and Recycling journal.
