The synthesis of bottom-up and top-down approaches to climate policy modeling: Electric power technologies and the cost of limiting US CO2 emissions

Journal Article
The synthesis of bottom-up and top-down approaches to climate policy modeling: Electric power technologies and the cost of limiting US CO2 emissions
Sue Wing, I. (2006)
Energy Policy, 34(18): 3847-3869

Abstract/Summary:

“Hybrid” climate policy simulations have sought to bridge the gap between “bottom-up” engineering and “top-down” macroeconomic models by integrating the former's energy technology detail into the latter's macroeconomic framework. Construction of hybrid models is complicated by the need to numerically calibrate them to multiple, incommensurate sources of economic and engineering data. I develop a solution to this problem following Howitt's [Howitt, R.E., 1995. Positive Mathematical Programming, American Journal of Agricultural Economics 77: 329-342] positive mathematical programming approach. Using data for the U.S., I illustrate how the inputs to the electricity sector in a social accounting matrix may be allocated among discrete types of generation so as to be consistent with both technologies' input shares from engineering cost estimates, and the zero profit and market clearance conditions of the sector's macroeconomic production structure.

Copyright © 2006 Elsevier B.V.

Citation:

Sue Wing, I. (2006): The synthesis of bottom-up and top-down approaches to climate policy modeling: Electric power technologies and the cost of limiting US CO2 emissions. Energy Policy, 34(18): 3847-3869 (http://dx.doi.org/10.1016/j.eneco.2006.06.004)
  • Journal Article
The synthesis of bottom-up and top-down approaches to climate policy modeling: Electric power technologies and the cost of limiting US CO2 emissions

Sue Wing, I.

34(18): 3847-3869

Abstract/Summary: 

“Hybrid” climate policy simulations have sought to bridge the gap between “bottom-up” engineering and “top-down” macroeconomic models by integrating the former's energy technology detail into the latter's macroeconomic framework. Construction of hybrid models is complicated by the need to numerically calibrate them to multiple, incommensurate sources of economic and engineering data. I develop a solution to this problem following Howitt's [Howitt, R.E., 1995. Positive Mathematical Programming, American Journal of Agricultural Economics 77: 329-342] positive mathematical programming approach. Using data for the U.S., I illustrate how the inputs to the electricity sector in a social accounting matrix may be allocated among discrete types of generation so as to be consistent with both technologies' input shares from engineering cost estimates, and the zero profit and market clearance conditions of the sector's macroeconomic production structure.

Copyright © 2006 Elsevier B.V.