How much information will persuade people to dispose of Household Hazardous Waste (HHW) properly? How many grants should be distributed to local agencies for improving the HHW management? How do pro-environmental activities, such as HHW recycling programs, influence the activities in nearby areas or regions? These are the questions that we attempt to answer using policy analytics that are essential in supporting more informed policy-making to enhance environmental management for sustainability.
The first study introduces a new construct: household informedness that is the degree to which households know enough to make utility-maximizing decisions about the handling of their waste. To measure the effects of household informedness on HHW collection and recycling activities, we investigated two influential variables: the provision of HHW public education and environmental quality information. The second study considers the pro-environmental spatial spillovers, based on agency actions and waste collection behavior that is occurring in other counties, that represent the influence of HHW-related practices in close-by regions. With this consideration in mind, we evaluate the impact of grants on the HHW collection activities using a research design that emphasizes spatial variations and controls for confounding factors.
The impacts of household informedness and grants on HHW collection were estimated by employing advanced econometric models. We developed fixed-effects models and a system of equations model to represent the relationships between household informedness and the amount of HHW collected and recycled. To model the relationships among HHW grants, spatial spillovers, and HHW collection output, we employed a spatial panel data model that explicitly consider spatial effects from neighboring counties that may influence HHW collection activities.
The main findings of the empirical research using county-level panel data on 39 counties in California from 2004 to 2012 are: (1) provision of HHW public education had a generally positive effect on the amount of HHW collected and recycled, but may have a negative effect on HHW collected under some conditions; (2) environmental quality information about the contamination of drinking water is negatively associated with the amount of HHW collected; and (3) when information is sent directly via mail to households, an increase in the number of contaminant level violations is positively related to the amount of HHW collected. Using Californian spatio-temporal data from 2004 to 2015, we also discovered: (4) HHW grants had positive effects on the amount of HHW collected; and (5) positive spatial spillover effects occurred for the HHW collection activities.
The results on the impact of household informedness enable the calculation of a new measure for effectiveness: the elasticity of the output quantities of HHW collected and recycled for differences in household informedness at the county level. The measure is useful to gauge the responsiveness of households in term of HHW collection and recycling output as more educational and environmental information become available to households. So this will support policy-makers in assessing the value of their investments in informational related programs for HHW. The research also contributes data analytics methods to discover causal relationships for HHW grant and spatial effects of HHW collection activities on the amount of HHW collected that will be useful in counterfactual impact evaluations. Most importantly, we demonstrated the power of such data analytics in uncovering policy insights for planning next policies and strategies in HHW management.
Kustini LIM-WAVDE is a PhD candidate in the School of Information System, 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.
