Our Model

We partner directly with government agencies to identify and test promising regulatory approaches to environmental problems and to help scale proven solutions. Our methodological toolkit includes rigorous impact evaluation methods, advanced monitoring technologies, predictive analytics, and other sophisticated data analysis techniques. This model makes our Lab uniquely suited not only to identify and test promising regulatory approaches with the most rigorous research methods available, but to drive proven approaches into action. Our work is fundamentally altering the form and conduct of environmental enforcement by helping ground environmental services, incentive programs, and enforcement tactics in rigorous evidence.  

We have identified several needs in energy and environmental policymaking that we are uniquely suited to address. We collaborate with local, state, and federal agencies on research in the following three core areas: 

  1. Improving regulatory enforcement and compliance: Current inspection targeting and pollutant monitoring systems often rely on methods that are decades old and not data driven. Leveraging technological advancements in remote sensing, air monitoring, computing capabilities, and analytic methods can transform the way regulatory agencies implement environmental enforcement and compliance and enforce regulations to protect public health. 

  2. Harnessing big data to promote regulatory efficiency: Government agencies increasingly have at their disposal large databases with rich information—from historical data on facility compliance and emissions to high-frequency data on individual customer water usage. Yet, agencies rarely possess the ability and capacity to fully utilize this data in their decision-making. 

  3. Testing programs before scaling: Too often new programs are put in place before we know their true impact. Testing these programs before adopting them as policy has tremendous potential to establish policies that can better enhance public wellbeing and address disparities while being credible and cost-effective.