Decision-based model selection

Arnoud V. den Boer and Dirk D. Sierag

European Journal of Operational Research, 2021, vol. 290, issue 2, 671-686

Abstract: A key step in data-driven decision making is the choice of a suitable mathematical model. Complex models that give an accurate description of reality may depend on many parameters that are difficult to estimate; in addition, the optimization problem corresponding to such models may be computationally intractable and only approximately solvable. Simple models with only a few unknown parameters may be misspecified, but also easier to estimate and optimize. With such different models and some initial data at hand, a decision maker would want to know which model produces the best decisions. In this paper we propose a decision-based model-selection method that addresses this question.

Keywords: Analytics; Model selection; Data-driven optimization; Decision making under uncertainty (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:290:y:2021:i:2:p:671-686

DOI: 10.1016/j.ejor.2020.08.025

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