Expectations of linear functions with respect to truncazted multinormal distributions, with applications for uncertainty analysis in environmental modelling
Jason J Sharples () and
John Pezzey ()
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Jason J Sharples: Australian National University, Centre for Resource and Environmental Studies, http://cres.anu.edu.au/people/userprofile.php?user=sharples
Economics and Environment Network Working Papers from Australian National University, Economics and Environment Network
Uncertainty can hamper the stringency of commitments under cap and trade schemes. We assess how well intensity targets, where countries' permit allocations are indexed to future realised GDP, can cope with uncertainties in a post-Kyoto international greenhouse emissions trading scheme. We present some empirical foundations for intensity targets and derive a simple rule for the optimal degree of indexation to GDP. Using an 18-region simulation model of a 2020 global cap-and-trade treaty under multiple uncertainties and endogenous commitments, we estimate that optimal intensity targets could achieve global abatement as much as 20 per cent higher than under absolute targets, and even greater increases in welfare measures. The optimal degree of indexation to GDP would vary greatly between countries, including super-indexation in some advanced countries, and partial indexation for most developing countries. Standard intensity targets (with one-toone indexation) would also improve the overall outcome, but to a lesser degree and not in all cases. Although target indexation is no magic wand for a future global climate treaty, gains from reduced cost uncertainty might justify increased complexity, framing issues and other potential downsides of intensity targets.
Keywords: linear functions; truncazted multinormal distributions; uncertainty analysis; environmental modelling (search for similar items in EconPapers)
JEL-codes: Q00 (search for similar items in EconPapers)
Pages: 24 pages
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Persistent link: https://EconPapers.repec.org/RePEc:anu:eenwps:0503
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