Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

Agonistic behavior and environmental enrichment of cats communally housed in a shelter

Objective-To evaluate the presence of a dominance rank in a group of cats and the relation between agonistic behavior and the use of resources, including environmental enrichment, in these cats. Design-Observational analytic study. Animals-27 neutered cats in a shelter in Sao Paulo, Brazil. Procedures-The cats were video recorded for 4 consecutive days to obtain baseline data. Subsequently, a puzzle feeder was added as an enrichment device every other day over 8 days, for a total of 4 days with enrichment. Cats were also video recorded on these days. All pretreatment and posttreatment agonistic behaviors and interactions with the puzzle feeder were recorded by reviewing the videotapes. Results-143 agonistic encounters were recorded, of which 44 were related to resources and 99 were not. There were insufficient agonistic interactions to determine a dominance rank. Presence or absence of the puzzle feeder did not affect the rate of aggression. There was no significant effect of weight, sex, or coat color on the rate of aggression, and aggressive behavior did not correlate with time spent with the puzzle feeder. Twenty-three of the 27 cats interacted with the puzzle feeder. Conclusions and Clinical Relevance-In a stable group of communally housed cats, environmental enrichment did not cause increased aggression as a result of competition for the source of enrichment. Because environmental enrichment increases the opportunity to perform exploratory behaviors, it may improve the welfare of groups of cats maintained long-term in shelters, sanctuaries, or multicat households. (J Am Vet Med Assoc 2011239:796-802)