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Choosing Wisely: A Multibidding Approach
In: American economic review, Band 92, Heft 5, S. 1577-1587
ISSN: 1944-7981
Moral Hazard: Base Models and Two Extensions
In: CESifo Working Paper Series No. 5851
SSRN
Working paper
Optimal monitoring to implement clean technologies when pollution is random
We consider a model of polluting firms subject to tax on emissions, monitoring, and penalties in case of underreporting and which face a choice between a more expensive clean and a less expensive dirty technology. Moreover, emissions are subject to random events.We show that the optimal monitoring is a cut-off policy, where all reports below a threshold are inspected with the same probability, while reports above the threshold are not monitored. If the adoption of the technology is firms' private information, too few firms will adopt the clean technology under the optimal monitoring policy. However, when the environmental agency can check the technology adopted by the firms, the optimal policy may induce overswitching or underswitching to the clean technology.
BASE
Optimal monitoring to implement clean technologies when pollution is random
We analyze a model where firms chose a production technology which, together with some random event, determines the final emission level. We consider the coexistence of two alternative technologies: a "clean" technology, and a "dirty" technology. The environmental regulation is based on taxes over reported emissions, and on penalties over unreported emissions. We show that the optimal inspection policy is a cut-off strategy, for several scenarios concerning the observability of the adoption of the clean technology and the cost of adopting it. We also show that the optimal inspection policy induces the firm to adopt the clean technology if the adoption cost is not too high, but the cost levels for which the firm adopts it depend on the scenario.
BASE
Optimal Monitoring to Implement Clean Technologies when Pollution is Random
In: CESifo Working Paper Series No. 1966
SSRN
Settlement in Tax Evasion Prosecution
In: Economica, Band 71, Heft 283, S. 349-368
ISSN: 1468-0335
It is often argued that, even if optimal ex post, settlement dilutes deterrence ex ante. We analyse the interest for the tax authority of committing, ex ante, to a settlement strategy. We show that to commit to the use of settlements is ex ante optimal when the tax authority receives signals that provide statistical information about the taxpayers' true tax liability. The more informative the signal, the larger the additional expected revenue raised by the tax authority when using settlement as a policy tool.
SSRN
Copyright Licensing Under Asymmetric Information
In: Review of Economic Research on Copyright Issues, Band 2014, Heft 11(2)
SSRN
Firms' Innovation Strategy under the Shadow of Analyst Coverage
In: CESifo Working Paper Series No. 6574
SSRN
Values for Environments with Externalities - The Average Approach
In: CESifo Working Paper Series No. 6002
SSRN
Private versus Social Incentives for Pharmaceutical Innovation
In: CESifo Working Paper Series No. 5672
SSRN
Stable Multilateral Trade Agreements
In: Economica, Band 65, Heft 258, S. 161-177
ISSN: 1468-0335
We analyse multilateral tariff negotiations as a game in coalition form. In a model with three identical countries that produce and trade an homogeneous commodity, and where countries' aggregated welfare can weight differently their different components, we analyse how changes in the countries' objective affects the stability of coalitions. In other words, we characterize what tariff‐agreements, if any, are stable (i.e. lie in the core).
Les étapes du financement de la recherche académique : de la soumission en partenariat jusqu'à l'attribution et aux publications
In: Revue économique, Band 70, Heft 5, S. 625-653
ISSN: 1950-6694
Les agences de financement de la recherche allouent des ressources (rares) selon un processus bottom-up concurrentiel. Cet article analyse les déterminants et les conséquences des choix réalisés à chaque étape du processus de financement. En mobilisant des recherches passées (Banal-Estañol, Macho-Stadler et Pérez-Castrillo [2013], [2018] et [2019]), nous présentons de nouveaux résultats en utilisant une base de données provenant de l'une des plus grandes agences de financement dans le monde, l'Agence anglaise de recherche en sciences physiques et de l'ingénieur (EPSRC). Classification JEL : O32, I23.
Evaluation in research funding agencies: Are structurally diverse teams biased against?
In: Research policy: policy, management and economic studies of science, technology and innovation, Band 48, Heft 7, S. 1823-1840
ISSN: 1873-7625