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.
- Publication Date:
- Research Org.:
- Stanford Univ., CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1530702
- Alternate Identifier(s):
- OSTI ID: 2325398
- 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. https://doi.org/10.1016/j.ejor.2019.06.017
Merrick, James H., and Weyant, John P. Thu .
"On choosing the resolution of normative models". United States. https://doi.org/10.1016/j.ejor.2019.06.017. https://www.osti.gov/servlets/purl/1530702.
@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 = {Thu Jun 13 00:00:00 EDT 2019},
month = {Thu Jun 13 00:00:00 EDT 2019}
}
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