塑造不平等:人力资本积累下的累进税

Danial Ali Akbari, Thomas G. Fischer
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引用次数: 0

摘要

为了设计影响收入分配的最佳政策工具,我们需要现实的收入模型。对几种流行的收入随机过程的比较表明,它们中的大多数都无法匹配美国的不平等,尤其是顶层的不平等。然而,具有重置的几何布朗运动在分布的两端产生现实的结果,同时仍然允许清晰的分析结果。在这一观察的基础上,我们开发了一个符合当前美国证据的内生收入不平等微观模型。它还允许在个人调整其劳动力供给和人力资本积累时,讨论税收改革的福利影响和权衡。我们将其推广到一个不完全的市场结构中,在这个结构中,个人既可以形成预防性储蓄,又可以调整自己的劳动力供给。经过校准的版本显示,美国所得税累进率比福利最优水平低约6个百分点。
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Shaping inequality: Progressive taxation under human capital accumulation
In order to design optimal policy instruments that shape the distribution of income we require realistic income models. A comparison between popular stochastic processes for income shows that most of them fail to match inequality in the US, especially at the top. The Geometric Brownian Motion with reset, however, produces realistic outcomes at both ends of the distribution, while still permitting clear analytic results. Building on this observation, we develop a micro-founded model for endogenous income inequality that fits the current US evidence. It also permits discussing the welfare effects and trade-offs of tax reforms as individuals adjust their labor supply and human capital accumulation. We extend it in an incomplete market setup solved numerically, in which individuals can both form precautionary savings and adjust their labor supply. A calibrated version suggests that the progressivity of US income taxes is below its welfare optimum by around six percentage points.
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