ISSN:
1573-1502
Keywords:
Computable general equilibrium (CGE)
;
Input-output (I-O)
;
life cycle analysis (LCA)
;
mass balance
;
process analysis
;
scenarios
;
thermodynamics
Source:
Springer Online Journal Archives 1860-2000
Topics:
Energy, Environment Protection, Nuclear Power Engineering
,
Economics
Notes:
Abstract Economists are increasingly interested in forecasting future costs and benefits of policies for dealing with materials/energy fluxes, polluting emissions and environmental impacts on various scales, from sectoral to global. Computable general equilibrium (CGE) models are currently popular because they project demand and industrial structure into the future, along an equilibrium path. But they are applicable only to the extent that structural changes occur in or near equilibrium, independent of radical technological (or social) change. The alternative tool for analyzing economic implications of scenario assumptions is to use Leontief-type Input-Output (I-O) models. I-O models are unable to endogenize structural shifts (changing I-O coefficients). However, this can be a virtue when considering radical rather than incremental shifts. Postulated I-O tables can be used independently to check the internal consistency of scenarios. Or I-O models can be used to generate scenarios by linking them to econometric ‘macro-drivers’ (which can, in principle, be CGE models). Explicit process analysis can be integrated, in principle, with I-O models. This hybrid scheme provides a natural means of satisfying physical constraints, especially the first and second laws of thermodynamics. This is important, to avoid constructing scenarios based on physically impossible processes. Process analysis is really the only available tool for constructing physically plausible alternative future I-O tables, and generating materials/energy and waste emissions coefficients. Explicit process analysis also helps avoid several problems characteristic of ‘pure’ CGE or I-O models, viz. (1) aggregation errors (2) inability to handle arbitrary combinations of co-product and co-input relationships and (3) inability to reflect certain non-linearities such as internal feedback loops.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00705980
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