Technology and Technical Change in the MIT EPPA Model

Joint Program Report
Technology and Technical Change in the MIT EPPA Model
Jacoby, H.D., J.M. Reilly, J.R. McFarland and S. Paltsev (2004)
Joint Program Report Series, 25 pages

Report 111 [Download]

Abstract/Summary:

Potential technology change has a strong influence on projections of greenhouse gas emissions and costs of control, and computable general equilibrium (CGE) models are a common device for studying these phenomena. Using the MIT Emissions Prediction and Policy Analysis (EPPA) model as an example, two ways of representing technology in these models are discussed: the sector-level description of production possibilities founded on social accounting matrices and elasticity estimates, and sub-models of specific supply or end-use devices based on engineering-process data. A distinction is made between exogenous and endogenous technical change, and it is shown how, because of model structure and the origin of key parameters, such models naturally include shifts in production process that reflect some degree of endogenous technical change. As a result, the introduction of explicit endogenous relations should be approached with caution, to avoid double counting.

Citation:

Jacoby, H.D., J.M. Reilly, J.R. McFarland and S. Paltsev (2004): Technology and Technical Change in the MIT EPPA Model. Joint Program Report Series Report 111, 25 pages (http://globalchange.mit.edu/publication/14471)
  • Joint Program Report
Technology and Technical Change in the MIT EPPA Model

Jacoby, H.D., J.M. Reilly, J.R. McFarland and S. Paltsev

Report 

111
25 pages
2004

Abstract/Summary: 

Potential technology change has a strong influence on projections of greenhouse gas emissions and costs of control, and computable general equilibrium (CGE) models are a common device for studying these phenomena. Using the MIT Emissions Prediction and Policy Analysis (EPPA) model as an example, two ways of representing technology in these models are discussed: the sector-level description of production possibilities founded on social accounting matrices and elasticity estimates, and sub-models of specific supply or end-use devices based on engineering-process data. A distinction is made between exogenous and endogenous technical change, and it is shown how, because of model structure and the origin of key parameters, such models naturally include shifts in production process that reflect some degree of endogenous technical change. As a result, the introduction of explicit endogenous relations should be approached with caution, to avoid double counting.