Optimal Nonlinear Income Taxation with Learning-by-Doing
Optimal Nonlinear Income Taxation with Learning-by-Doing
复制标题
通过边做边学的最优非线性所得税
DOI：
10.1016/j.jpubeco.2009.06.003
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发表时间：
2009
影响因子：
9.8
通讯作者：
Alan J. Krause
中科院分区：
文献类型：
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作者：
Alan J. Krause
本文研究了一个两阶段的最优非线性所得税模型，其中第二阶段的工资是第一阶段劳动供给的增函数。我们考虑的情况下，政府可以和不能承诺其第二阶段的税收政策。在这两种情况下，关于最优边际税率的经典Mirrlees/Stiglitz结果通常不再适用。特别是，如果政府不能承诺，而每个消费者的技能类型都被揭示出来，那么最好通过正的边际税率来降低高技能类型的劳动力供给，以放松激励相容性约束。因此，我们的分析确定了一种设置，在这种设置中，对最高技能个人的正边际税率是合理的，尽管它对劳动力供应和工资都有抑制作用。
This paper examines a two-period model of optimal nonlinear income taxation with learning-by-doing, in which second-period wages are an increasing function of first-period labour supply. We consider the cases when the government can and cannot commit to its second-period tax policy. In both cases, the canonical Mirrlees/Stiglitz results regarding optimal marginal tax rates generally no longer apply. In particular, if the government cannot commit and each consumer's skill-type is revealed, it is optimal to distort the high-skill type's labour supply downwards through a positive marginal tax rate to relax an incentive-compatibility constraint. Our analysis therefore identifies a setting in which a positive marginal tax rate on the highest-skill individual can be justified, despite its depressing effect on both labour supply and wages.