OPTIMAL TAXATION OF INCOME-GENERATING CHOICE

• 成果类型: Article
• 署名作者: Ales, Laurence; Sleet, Christopher
• 署名单位: Carnegie Mellon University; University of Rochester
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA18542
• 发表日期: 2022
• 页码: 2397-2436
• 关键词: models; elasticities; workers

摘要

Discrete location, occupation, skill, and hours choices of workers underpin their incomes. This paper analyzes the optimal taxation of discrete income-generating choice. It derives optimal tax equations and Pareto test inequalities for mixed logit choice environments that can accommodate discrete and unstructured choice sets, rich preference heterogeneity, and complex aggregate cross-substitution patterns between choices. These equations explicitly connect optimal taxes to societal redistributive goals and private substitution behavior, with the latter encoded as a substitution matrix that describes cross-sensitivities of choice distributions to tax-induced utility variation. In repeated mixed logit settings, the substitution matrix is exactly the Markov matrix of shock-induced agent transitions across choices. We describe implications of this equivalence for evaluation of prevailing tax designs and the structural estimation of optimal policy mixed logit models. We apply our results to two salient examples: spatial taxation and taxation of couples.