Despite the well-known static cost-inefficiency of uniform emission standards to control pollution, governments continue to use them in a variety of settings. In this paper, we show that inspection agencies can sometimes use their informational advantage to design monitoring strategies that...

Effluent limits are frequently based on a uniform emission standard, which applies to all polluting facilities within a single industry. However, the implementation of many environmental protection laws does not lead to uniform effluent limits due to considerations of local environmental...

Over time, inspection agencies gather information about firms’ pollution levels and this information may allow agencies to differentiate their monitoring strategies in the future. If a firm is less successful than its peers in reducing emissions, it faces the risk of being targeted for...

Many conservation programs offer financial compensation to farmers in exchange for socially desired services, such as soil conservation or biodiversity protection. Realization of the conservation objective at minimum cost requires payments to just cover the extra costs incurred by each...

We investigate the features of optimal regulatory policies composed of pollution standards and probabilities of inspection, where fines for non-compliance depend not only on the degree of violation but alson on nongravity factors.We show that optimal policies can induce either compliance or...

We study optimal policies composed of pollution standards, probabilities of inspection and fines dependant on the degree of noncompliance with the standards, in a context where regulated firms own private information.In contrast with previous literature, we show that optimal policies, being...

Investment subsidies are widely used to induce adoption of new technologies that can lower the (marginal) cost of reducing emissions. To economize on these subsidies, governments would like to distinguish between firms that need to receive a subsidy to adopt a new technology, and firms that...