Optimal Monitoring to Implement Clean Technologies when Pollution is Random
Ines Macho-Stadler and
David Perez-Castrillo
No 1966, CESifo Working Paper Series from CESifo
Abstract:
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.
Keywords: production technology; random emissions; environmental taxes; optimal monitoring policy (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.cesifo.org/DocDL/cesifo1_wp1966.pdf (application/pdf)
Related works:
Working Paper: Optimal monitoring to implement clean technologies when pollution is random (2015) 
Journal Article: Optimal monitoring to implement clean technologies when pollution is random (2010) 
Working Paper: Optimal Monitoring to Implement Clean Technologies when Pollution is Random (2007) 
Working Paper: Optimal monitoring to implement clean technologies when pollution is random (2006) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_1966
Access Statistics for this paper
More papers in CESifo Working Paper Series from CESifo Contact information at EDIRC.
Bibliographic data for series maintained by Klaus Wohlrabe ().