This paper develops a stochastic dynamic programming model to investigate a type of dynamic enforcement strategy where the penalties for violations of environmental regulations are based on not only the current level of violations but also the firms’ past noncompliance records. The results show that firms’ optimal level of noncompliance would be a decreasing function of their accumulated noncompliance record and that a more stringent enforcement strategy can reduce the expected fines due to the reduced violations. Comparisons with the repeated static enforcement strategy indicate that the dynamic enforcement strategy can be superior in terms of reducing both violations and enforcement efforts.
A Dynamic Enforcement Strategy to Improve Compliance with Environmental Regulations
Working Paper by Xiao-Bing Zhang, and Jing Xu — May 27, 2016Download
Resources Radio: Energy Inefficiency, with RFF's Joshua Blonz
Host Daniel Raimi and Joshua Blonz, a postdoctoral fellow at RFF, talk about his recent research on an energy efficiency program in California, the...
The Welfare Costs of Misaligned Incentives: Energy Inefficiency and the Principal-Agent Problem
I measure the welfare costs of the principal-agent problem in the context of an energy efficiency appliance upgrade program. I find that the principal-agent problem turns an otherwise welfare-increasing program into a welfare-reducing program.
Buyer Beware: An Analysis of the Latest Flawed Carbon Tax Report
Not all economic analyses are created equal. Those that do not meet fundamental scientific standards should be ignored by policymaking communities.