Coarse decision making and overfitting

• 成果类型: Article
• 署名作者: Al-Najjar, Nabil I.; Pai, Mallesh M.
• 署名单位: Northwestern University; University of Pennsylvania
• 刊物名称: JOURNAL OF ECONOMIC THEORY
• ISSN/ISSBN: 0022-0531
• DOI: 10.1016/j.jet.2013.12.003
• 发表日期: 2014
• 页码: 467-486
• 关键词: Coarse decision making; Statistical learning; Overfitting; VC-dimension; bounded rationality

摘要

We study decision makers who willingly forgo decision rules that vary finely with available information, even though these decision rules are technologically feasible. We model this behavior as a consequence of using classical, frequentist methods to draw robust inferences from data. Coarse decision making then arises to mitigate the problem of over-fitting the data. The resulting behavior tends to be biased towards simplicity: decision makers choose models that are statistically simple, in a sense we make precise. In contrast to existing approaches, the key determinant of the level of coarsening is the amount of data available to the decision maker. The decision maker may choose a coarser decision rule as the stakes increase. (C) 2013 Elsevier Inc. All rights reserved.