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Combining Top-Down and Bottom-Up Approaches to Energy-Economy Modeling Using Discrete Choice Methods

Nic Rivers and Mark Jaccard

Year: 2005
Volume: Volume 26
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol26-No1-4
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Abstract:
Recently, hybrid models of the energy-economy have been developed with the objective of combining the strengths of the traditional top-down and bottom-up approaches by simulating consumer and firm behavior at the technological level. We explore here the application of discrete choice research and modeling to the empirical estimation of key behavioral parameters representing technology choice in hybrid models. We estimate a discrete choice model of the industrial steam generation technology decision from a survey of 259 industrial firms in Canada. The results provide behavioral parameters for the CIMS energy-economy model. We then conduct a policy analysis and show the relative effects of an information program, technology subsidy, and carbon dioxide tax on the uptake of alternative industrial steam generation technologies, including boilers and cogeneration systems. We also show how empirically derived estimates of parameter uncertainty can be propagated through the model to provide uncertainty estimates for major model outputs.



Towards General Equilibrium in a Technology-Rich Model with Empirically Estimated Behavioral Parameters

Chris Bataille, Mark Jaccard, John Nyboer and Nic Rivers

Year: 2006
Volume: Hybrid Modeling
Number: Special Issue #2
DOI: 10.5547/ISSN0195-6574-EJ-VolSI2006-NoSI2-5
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Abstract:
Most energy-economy policy models offered to policy makers are deficient in terms of at least one of technological explicitness, microeconomic realism, or macroeconomic completeness. We herein describe CIMS, a model which starts with the technological explicitness of the �bottom-up� approach and adds the microeconomic realism and macroeconomic completeness of the �topdown� CGE approach. This paper demonstrates CIMS� direct utility for policy analysis, and also how it can be used to better estimate the long run capital-forenergy substitution elasticity (ESUB) and autonomous energy efficiency index (AEEI) technology parameters used in top-down models. By running CIMS under several possible energy price futures and observing their effects on capital and energy input shares and energy consumption, we estimate an economy-wide ESUB of 0.26 and an AEEI of 0.57%, with significant sectoral differences for both parameters.





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