On the climate policy implications of substitutability and flexibility in the economy: An in-depth integrated assessment model diagnostic

Journal Article · Wed Jul 12 00:00:00 EDT 2017 · Technological Forecasting and Social Change

DOI:https://doi.org/10.1016/j.techfore.2017.07.003· OSTI ID:1373113

Craxton, Melanie ^[1]; Merrick, James ^[2]; Makridis, Christos ^[2]; Taggart, John ^[2]

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1. Huang Engineering Center, Stanford, CA (United States); Stanford University, Department of Management Science and Engineering
2. Huang Engineering Center, Stanford, CA (United States)

This paper conducts an in-depth model diagnostic exercise for two parameters, 1) the elasticity of substitution between the capital/labour aggregate and the energy aggregate in the Integrated Assessment Model (IAM) MERGE's production function and 2) the rate at which new technologies can be deployed within the energy system. We show that in a more complementary world the model's ability to adjust the carbon intensity of its energy sector is more important whereas in a more substitutable world the ability to expand carbon free technologies is of lesser relative importance. The uncertainty in the literature surrounding the elasticity of substitution parameter, its interaction with the mechanisms of technical change, and the associated danger of grounding forward-looking analyses in historically based parameters lend support to the importance of such a diagnostic exercise. Building on work from model intercomparison studies, we investigate whether a given model's choice of strategy is primarily a function of the choice of its parameter values or its structure. As a result, a deeper understanding of what drives model behaviour is beneficial to both modellers and the policymakers who utilise their insights and output.

• Research Organization: Energy Modeling Forum at Stanford Univ., Stanford, CA (United States)
• Sponsoring Organization: USDOE; USDOE Office of Science (SC)
• Grant/Contract Number: SC0005171
• OSTI ID: 1373113
• Alternate ID(s): OSTI ID: 1549557
• Journal Information: Technological Forecasting and Social Change, Journal Name: Technological Forecasting and Social Change Vol. 125; ISSN 0040-1625
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
climate policy
integrated assessment
model diagnostic
substitutability
technology expansion