On the climate policy implications of substitutability and flexibility in the economy: An in-depth integrated assessment model diagnostic
Abstract
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.
- Authors:
-
- Huang Engineering Center, Stanford, CA (United States)
- Publication Date:
- Research Org.:
- Energy Modeling Forum at Stanford Univ., Stanford, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1373113
- Alternate Identifier(s):
- OSTI ID: 1549557
- Grant/Contract Number:
- SC0005171; SC00051571
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Technological Forecasting and Social Change
- Additional Journal Information:
- Journal Volume: 125; Journal ID: ISSN 0040-1625
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; integrated assessment; model diagnostic; substitutability; technology expansion; climate policy
Citation Formats
Craxton, Melanie, Merrick, James, Makridis, Christos, and Taggart, John. On the climate policy implications of substitutability and flexibility in the economy: An in-depth integrated assessment model diagnostic. United States: N. p., 2017.
Web. doi:10.1016/j.techfore.2017.07.003.
Craxton, Melanie, Merrick, James, Makridis, Christos, & Taggart, John. On the climate policy implications of substitutability and flexibility in the economy: An in-depth integrated assessment model diagnostic. United States. https://doi.org/10.1016/j.techfore.2017.07.003
Craxton, Melanie, Merrick, James, Makridis, Christos, and Taggart, John. Wed .
"On the climate policy implications of substitutability and flexibility in the economy: An in-depth integrated assessment model diagnostic". United States. https://doi.org/10.1016/j.techfore.2017.07.003. https://www.osti.gov/servlets/purl/1373113.
@article{osti_1373113,
title = {On the climate policy implications of substitutability and flexibility in the economy: An in-depth integrated assessment model diagnostic},
author = {Craxton, Melanie and Merrick, James and Makridis, Christos and Taggart, John},
abstractNote = {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.},
doi = {10.1016/j.techfore.2017.07.003},
journal = {Technological Forecasting and Social Change},
number = ,
volume = 125,
place = {United States},
year = {Wed Jul 12 00:00:00 EDT 2017},
month = {Wed Jul 12 00:00:00 EDT 2017}
}