nep-res New Economics Papers
on Resource Economics
Issue of 2007‒05‒19
three papers chosen by
Maximo Rossi
Universidad de la Republica

  1. Mechanisms for Abating Global Emissions Under Uncertainty By John C. V. Pezzey; Frank Jotzo
  2. Optimal Intensity Targets for Greenhouse Emissions Trading Under Uncertainty By Frank Jotzo; John C. V. Pezzey
  3. Fisheries Instrument Choice under Uncertainty By Tom Kompas; Tuong Nhu Che; R. Quentin Grafton

  1. By: John C. V. Pezzey (Australian National University,Centre for Resource and Environmental Studies); Frank Jotzo (Australian National University, Research School of Pacific and Asian Studies)
    Abstract: We give theoretical, partial equilibrium comparisons of a tax with thresholds, tradable targets ('emissions trading' or ET), and non-tradable targets, as mechanisms to abate well-mixed ('global') emissions from many parties, under independent uncertainties in both future business-as-usual emissions and marginal abatement costs. All three mechanisms are revenue-neutral, and use flexible thresholds or targets indexed continuously to parties' activity levels. We analyse both risk-neutral or risk-averse behaviour. Key theoretical results are that because of emissions uncertainty, there is no simple Weitzman (1974) rule for choosing between 'prices' (a tax) to 'quantities' (ET); under ET, marginal abatement cost uncertainty is a benefit, compared to certainty; and under risk aversion, any mechanism with more expected welfare also gives more expected abatement. We apply our theory to global greenhouse gas abatement in 2020, using an 18-region numerical simulation model with new uncertainty estimates. Key global, empirical results are that under either risk behaviour, a tax dominates ET, which hugely dominates non-tradable targets; and under risk aversion, an optimally indexed tax gives about 60% more welfare and 30% more abatement than unindexed ET, while optimally indexed ET achieves about two-fifths of these improvements.
    Keywords: emissions trading, global abatement, greenhouse gases, risk aversion, tax, uncertainty
    JEL: D81 H23 Q54 Q58
    Date: 2006–08
  2. By: Frank Jotzo (Australian National University, Research School of Pacific and Asian Studies); John C. V. Pezzey (Australian National University,Centre for Resource and Environmental Studies)
    Abstract: Uncertainty is an obstacle for 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 international greenhouse emissions trading. 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 cooperative, global cap-and-trade treaty in 2020 under multiple uncertainties and endogenous commitments, we show that optimal intensity targets could reduce the cost of uncertainty and achieve significant increases in global abatement. 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-to-one indexation) would also improve the overall outcome, but to a lesser degree and not in all individual cases. Although target indexation is no magic wand for a future global climate treaty, gains from reduced cost uncertainty and the potential for more stringent environmental commitments might justify the increased complexity and other potential downsides of intensity targets.
    Keywords: climate policy, emissions trading, uncertainty, flexible targets, intensity targets, optimality, simulation modelling
    JEL: Q00
    Date: 2006–08
  3. By: Tom Kompas (Australian National University, Asia Pacific School of Economics and Government); Tuong Nhu Che (Australian Bureau of Agricultural and Resource Economics); R. Quentin Grafton (Australian National University, Asia Pacific School of Economics and Government)
    Abstract: This paper uses data from an actual fishery to construct a tractable and dynamic model to compare expected profit and its variance, optimal stock size, optimal harvest rate and optimal fishing effort under different management regimes under uncertainty. The results provide a comparison of instrument choice between a total harvests control and a total effort control under uncertainty, an original method to evaluate the tradeoffs between profits and other criteria in a dynamic context, and provide guidance as to the relative merits of catch and effort controls in fisheries management.
    Keywords: fisheries management, uncertainty
    JEL: Q22 D81
    Date: 2006–08

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