Satisficing, aggregation, and quasilinear utility

• 成果类型: Article
• 署名作者: Allen, Roy; Rehbeck, John
• 署名单位: Western University (University of Western Ontario); University System of Ohio; Ohio State University
• 刊物名称: QUANTITATIVE ECONOMICS
• ISSN/ISSBN: 1759-7323
• DOI: 10.3982/QE2025
• 发表日期: 2026
• 关键词: nonparametric analysis; money pump; welfare; inference; identification; INDEPENDENCE; BEHAVIOR; demand

摘要

This paper studies approximation error in the quasilinear utility model. Error arises because individuals do not perfectly optimize, and instead satisfice. We investigate the consequences of individual satisficing for modeling aggregate demand, providing an approximate aggregation theorem. We present a simple method for statistical inference on the minimal level of satisficing needed to explain aggregate data. In an illustrative application to scanner panel data, we find that individual-level data require a nontrivial degree of satisficing, but aggregate data admit a representative agent that maximizes a quasilinear utility function.