International environmental agreements with a stock pollutant, uncertainty and learning. Southampton, University of Southampton
(Discussion Papers in Economics and Econometrics, 0207).
I analyse how the possibility of future resolution of uncertainty about damage costs affects incentives to join a self-enforcing international environmental agreement. Unlike earlier literature, the model allows many countries, uses a solution concept which does not restrict the size of a stable IEA, and, since it is dynamic, analyses different membership rules: fixed (countries commit) or variable (countries decide each period whether to join). With fixed membership, learning yields at least as high membership and global welfare as no learning, unless both expected damage costs and uncertainty are high. With variable membership, learning leads to higher future membership but lower global welfare than no learning. Fixed membership leads to higher global welfare than variable membership if there are at least as many signatories who abate pollution in each period and state of the world as variable membership. This occurs for only 20% of parameter values with no learning and 2% with learning.
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