Stable international environmental agreements with a stock pollutant, uncertainty and learning
Ulph, Alistair (2004) Stable international environmental agreements with a stock pollutant, uncertainty and learning. Journal of Risk and Uncertainty, 29, (1), 53-73. (doi:10.1023/B:RISK.0000031445.13939.e4).
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In this paper I address the question of how uncertainty about damage costs and the possibility of resolving that uncertainty in the future affects the incentives for countries to join an international environmental agreement. I use a two-period model with a stock pollutant where the number of countries generating pollution can be arbitrarily large. The stability concept employed is such that size of the stable IEA can be anywhere between 2 and the grand coalition of all countries depending on parameter values. The dynamic structure allows two different membership rules for an IEA: fixed (countries commit at the outset to be members for both periods) or variable (countries decide each period whether to join). I show that with fixed membership learning results in at least as high membership and global welfare as no learning (unless both the expected value and variance of damage costs are high). With variable membership, learning leads to higher membership (in the second period) but lower global welfare than no learning. For most parameter values variable membership results in higher global welfare than fixed membership.
|Digital Object Identifier (DOI):||doi:10.1023/B:RISK.0000031445.13939.e4|
|Keywords:||international environmental agreements, uncertainty, learning, fixed membership, variable membership, self-enforcing agreements|
|Subjects:||H Social Sciences > H Social Sciences (General)
J Political Science > JZ International relations
G Geography. Anthropology. Recreation > GE Environmental Sciences
|Divisions :||University Structure - Pre August 2011 > School of Social Sciences > Economics
|Accepted Date and Publication Date:||
|Date Deposited:||16 May 2006|
|Last Modified:||06 Aug 2015 02:31|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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