We explore the design of self-financing tax-subsidy schemes to solve hold-up problems in environmental regulation. The announcement of the tax rate seems to be preferable to solve hold-up problems with respect to the investment in environmental Ramp;D. In contrast, only the announcement of the...

We explore the design of self-financing tax/subsidy mechanisms to solve hold-up problems in environmental regulation. Under Cournot competition, announcing the subsidy rate seems to be preferable to announcing the tax rate. Moreover, for constant marginal damage the hold-up problem can always be...

MCDM methods are useful to obtain information and generate knowledge useful for decision-making processes in multidisciplinary contexts. Particularly, when conflicts occur, knowledge is the key to start negotiation processes between stakeholders in order to achieve consensual solutions. The...

Like many common-pool resources, the Lake Victoria fisheries are characterized by poor compliance with production input regulations that are intended to reduce overexploitation. To explore the use of input subsidies to increase compliance, we determine the subsidy level required to induce demand...

Lake Victoria, globally the second-largest freshwater Lake by surface area, houses an artisanal Nile Perch Fishery that directly involves around 200K people. While the 10 whole Lake surface is potentially available to fishing activities, the fishing vessels' operational and technical...

We investigate the optimal regulation of energy production reflecting the long-term goals of the Paris Climate Agreement. We analyze the optimal regulatory incentives to foster the development of non-emissive electricity generation when the demand for power is served either by a monopoly or by...

This paper focuses on decentralized energy in Germany and how households' environmental behavior in terms of energy consumption is shaped in these contexts. It sets out to gain a more precise understanding of whether decentralized energy initiatives are a good tool to promote the adoption of...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

Large-scale data show promise to provide efficiency gains through individualized risk predictions in many business and policy settings. Yet, assessments of the degree of data-enabled efficiency improvements remain scarce. We quantify the value of the availability of a variety of data...