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Title: On choosing the resolution of normative models

Abstract

Long time horizon normative models are frequently used for policy analysis, strategic planning, and system analysis. Choosing the granularity of the temporal or spatial resolution of such models is an important modeling decision, often having a first order impact on model results. This type of decision is frequently made by modeler judgment, specifically when the predictive power of alternative choices cannot be tested. In this paper, we show how the implicit tradeoffs modelers make in these formulation decisions, in particular in the tradeoff between the accuracy of representation enabled by the available data and model parsimony, may be addressed with established information theoretic ideas. The paper provides guidance for modelers making these tradeoffs or, in certain cases, enables explicit tests for assessing appropriate levels of resolution. Here, we focus on optimization based normative models in the discussion, and draw our examples from the energy and climate domain.

Authors:
ORCiD logo [1];  [1]
  1. Stanford Univ., CA (United States)
Publication Date:
Research Org.:
Stanford Univ., CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1530702
Grant/Contract Number:  
SC0005171; SC0016162
Resource Type:
Accepted Manuscript
Journal Name:
European Journal of Operational Research
Additional Journal Information:
Journal Volume: 279; Journal Issue: 2; Journal ID: ISSN 0377-2217
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 96 KNOWLEDGE MANAGEMENT AND PRESERVATION; Problem structuring; Validation of OR computations; Information theory; Strategic planning; OR in environment and climate change

Citation Formats

Merrick, James H., and Weyant, John P. On choosing the resolution of normative models. United States: N. p., 2019. Web. doi:10.1016/j.ejor.2019.06.017.
Merrick, James H., & Weyant, John P. On choosing the resolution of normative models. United States. doi:10.1016/j.ejor.2019.06.017.
Merrick, James H., and Weyant, John P. Thu . "On choosing the resolution of normative models". United States. doi:10.1016/j.ejor.2019.06.017.
@article{osti_1530702,
title = {On choosing the resolution of normative models},
author = {Merrick, James H. and Weyant, John P.},
abstractNote = {Long time horizon normative models are frequently used for policy analysis, strategic planning, and system analysis. Choosing the granularity of the temporal or spatial resolution of such models is an important modeling decision, often having a first order impact on model results. This type of decision is frequently made by modeler judgment, specifically when the predictive power of alternative choices cannot be tested. In this paper, we show how the implicit tradeoffs modelers make in these formulation decisions, in particular in the tradeoff between the accuracy of representation enabled by the available data and model parsimony, may be addressed with established information theoretic ideas. The paper provides guidance for modelers making these tradeoffs or, in certain cases, enables explicit tests for assessing appropriate levels of resolution. Here, we focus on optimization based normative models in the discussion, and draw our examples from the energy and climate domain.},
doi = {10.1016/j.ejor.2019.06.017},
journal = {European Journal of Operational Research},
number = 2,
volume = 279,
place = {United States},
year = {2019},
month = {6}
}

Journal Article:
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This content will become publicly available on June 13, 2020
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