INTERPRETATIONS AND TRANSFORMATIONS OF SCALE FOR THE PRATT-ARROW ABSOLUTE RISK AVERSION COEFFICIENT: IMPLICATIONS FOR GENERALIZED STOCHASTIC DOMINANCE: COMMENT

Research Methods/ Statistical Methods, Risk and Uncertainty,

Bioenergy in a Greenhouse Mitigating World

Environmental Economics and Policy, Resource /Energy Economics and Policy, Q1, Q4, Q54,

MATHEMATICAL PROGRAMMING FOR RESOURCE POLICY APPRAISAL UNDER MULTIPLE OBJECTIVES

Mathematical programming is one technique that can be used for resource policy appraisal. Multiple objectives are usually involved in resource policy considerations. This paper discusses issues regarding the use of mathematical programming techniques for the multiobjective resource policy arena. Theoretical models are introduced with a separation called for between producer response models and policy maker models due to a disparity of objectives. The paper draws on the literature citing cases where producer level models have been utilized to simulate the policy outcome implications of alternative policies.Resource /Energy Economics and Policy,

GENERALIZED STOCHASTIC DOMINANCE: AN EMPIRICAL EXAMINATION

Use of generalized stochastic dominance (GSD) requires one to place lower and upper bounds on the risk aversion coefficient. This study showed that breakeven risk aversion coefficients found assuming the exponential utility function delineate the places where GSD preferences switch between prospects. However, between these break points, multiple, overlapping GSD intervals can be found. Consequently, when one does not have risk aversion coefficient information, discovery of breakeven coefficients instead of GSD use is recommended. The investigation also showed GSD results are insensitive to wealth and data scaling but are sensitive to rounding.Research Methods/ Statistical Methods,

A NOTE ON FIXING MISBEHAVING MATHEMATICAL PROGRAMS: POST-OPTIMALITY PROCEDURES AND GAMS-RELATED SOFTWARE

Mathematical programming formulations can yield faulty answers. Models can be unbounded, infeasible, or optimal with unrealistic answers. This article presents techniques for theory-based discovery of the cause of faulty models. The approaches are demonstrated in the context of linear programming. They have been computerized and interfaced using the General Algebraic Modeling System (GAMS), and are distributed free of charge through new GAMS versions and an outline web page.Debugging, GAMS software, Mathematical programming, Research Methods/ Statistical Methods,

PREFERENCE AMONG RISKY PROSPECTS UNDER CONSTANT RISK AVERSION

Risk analyses often require a measure of individual risk aversion. Here a procedure is presented to calculate risk aversion parameter ranges wherein individuals would exhibit preference among a set of risky prospects.Risk and Uncertainty,

Climate Change and Texas Water Planning: an Economic Analysis of Inter-basin Water Transfers

Panel models with random effects are used to estimate how climate influences in-stream surface water supply, municipal water demand, crop yields and irrigation water use. The results are added into TEXRIVERSIM, a state wide economic, hydrological, environmental and inter-basin water transfer (IBTs) investment model, through the objective function and hydrological constraints. A climate change related scenario analysis from the Global Circulation Models (GCMs)--Hadley, Canadian, BCCR and NCAR with SRES scenarios A1B, B1, and A2 indicates that inter-basin water transfers not only greatly relax water scarcity problems for major cities and industrial counties, but also create growth opportunity for Houston. However, while destination basins receive the benefits, source basins will experience dramatic reduction in in-stream flow and water flows to bays and estuaries. Climate change requires accelerated water development with more IBTs proving economically feasible depending on the GCMs and SRES scenarios.Climate Change, Inter-basin Water Transfers, Water Scarcity, Environmental Stream Flows, Environmental Economics and Policy, Q25, Q54, Q58,

Economics of Biomass Fuels for Electricity Production: A Case Study with Crop Residues

In the past, studies on agricultural feedstocks for energy production were motivated by rising fossil fuel prices interpreted by many as caused by resource depletion. However, today's studies are mainly motivated by concerns for climate change and global warming. Currently, most studies concentrate on liquid fuels with little study devoted toward electricity. This study examines crop residues for electricity production in the context of climate change and global warming. We use sector modeling to simulate future market penetration for biopower production from crop residues. Our findings suggest that crop residues cost much more than coal because they have lower heat content and higher production/hauling costs. For crop residues to have any role in electricity generation either the carbon or carbon dioxide equivalent greenhouse gas price must rise to about 15 dollars per ton or the price of coal has to increase to about 43 dollars per ton. We find crop residues with higher heat content and lower production costs such as wheat residues have greater opportunities in biopower production than the residues with lower heat content and higher production costs. In addition, the analysis shows that improvements in crop yield do not have much impact on biopower production. However, the energy recovery efficiency does have significant positive impact but only if the carbon equivalent price rises substantially. The analysis also indicates the desirability of cofiring biomass as opposed to 100% replacement because this reduces hauling costs and increases the efficiency of heat recovery. In terms of policy implications, imposing carbon emission pricing could be an important step in inducing electric power producers to include agricultural biomass in their fuel-mix power generation portfolios and achieve greenhouse gas emission reductions.Resource /Energy Economics and Policy,

Inter-Temporal Investment in Climate Change Adaptation and Mitigation

Currently, different dimensions of mitigation strategies have been investigated in policy analysis. However, ambitious mitigation action aiming at reducing future climate change will not prevent much climate change before mid-century. Short-term and medium-term temperature as well as associated damages cannot be avoided completely. Increasingly there appears to be recognition of the need to simultaneously implement adaptation and mitigation. However, the optimal combination between adaptation and mitigation that can best address climate change over time is still an open question. Literature base is rather small, yet very diverse and inconsistent in conclusions. In this paper, we do an exploration of the temporal optimal investment mix between adaptation and mitigation and their relative contributions to climate change damage reduction. By proposing a conceptual framework that integrates both strategies and developing a more complete integrated assessment model, the temporal investment allocation between adaptation and mitigation is identified. Results suggest that adaptation is an effective climate change damages reduction strategy and a complement to mitigation. Adaptation investment tackles the short run reduction of damages in the first 250 years while mitigation dominates from thereon.Climate Change Damages, Adaptation, Mitigation, Temporal Investment, Integrated Assessment Model, Environmental Economics and Policy, Resource /Energy Economics and Policy, Risk and Uncertainty, Q54, Q58,

MEASURING ABATEMENT POTENTIALS WHEN MULTIPLE CHANGE IS PRESENT: THE CASE OF GREENHOUSE GAS MITIGATION IN U.S. AGRICULTURE AND FORESTRY

Mathematical programming is used to examine the economic potential of greenhouse gas mitigation strategies in U.S. agriculture and forestry. Mitigation practices are entered into a spatially differentiated sector model and are jointly assessed with conventional agricultural production. Competition among practices is examined under a wide range of hypothetical carbon prices. Simulation results demonstrate a changing portfolio of mitigation strategies across carbon price. For lower prices preferred strategies involve soil and livestock options, higher prices, however, promote mainly afforestation and biofuel generation. Results demonstrate the sensitivity of individual strategy potentials to assumptions about alternative opportunities. Assessed impacts also include market shifts, regional strategy diversity, welfare distribution, and environmental co-effects.Abatement Function, Agricultural Sector Model, Carbon Sequestration, Economic Potential, Greenhouse Gas Emission, Mathematical Programming, Multiple Technical Change, Policy Simulation