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Title: 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:
ORCiD logo [1]; ORCiD logo [1];  [1];  [1]
  1. 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
Grant/Contract Number:
SC0005171
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Technological Forecasting and Social Change
Additional Journal Information:
Journal Name: Technological Forecasting and Social Change; 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. doi:10.1016/j.techfore.2017.07.003.
Craxton, Melanie, Merrick, James, Makridis, Christos, and Taggart, John. 2017. "On the climate policy implications of substitutability and flexibility in the economy: An in-depth integrated assessment model diagnostic". United States. doi:10.1016/j.techfore.2017.07.003.
@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 = ,
place = {United States},
year = 2017,
month = 7
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on July 12, 2018
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