Optimal Contracts for Discouraging Deforestation with Risk Averse Agents

Charles Mason

No 7067, CESifo Working Paper Series from CESifo

Abstract: There is an emerging consensus that carbon emissions must be limited. An attractive approach to promoting carbon reductions is to encourage reductions in deforestation. But any such strategy must confront a basic problem: agents that might be induced to reduce their actions which would reduce forests have private information about their opportunity costs. This concern seems particularly likely to apply in situations where there are significant related risks, as agents seem highly likely to differ in their tolerance for risk. In this paper, I investigate a contracting scheme designed to mitigate the asymmetric information problem where agents are heterogeneous in their tolerance for risk. Mechanisms that recognize the potential insurance value associated with the acquisition of sequestration services, and that pay attention to landholders’ private information about risk tolerance, offer a sensible way to approach the problem. These contracts are generally a cheaper approach to maintenance of forests than a simple, constant per-unit subsidy.

Keywords: incentive contracting; risk aversion; deforestation (search for similar items in EconPapers)
JEL-codes: D04 D86 L15 Q54 (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-cta, nep-env and nep-ias
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.cesifo.org/DocDL/cesifo1_wp7067.pdf (application/pdf)

Related works:
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:_7067

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 ().