论转移支付与所得税累进的优化设计

Axelle Ferrière, Philipp Grübener, Gaston Navarro, Oliko Vardishvili
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引用次数: 8

摘要

我们研究了收入调查转移和累进所得税的最优设计。在一个简单的分析模型中,我们表明,在对数线性税收中增加一笔转移支付,所带来的福利收益几乎与次优分配一样大。与边际税收和转移税率相比,转移税允许更多的累进平均税率,在保持效率的同时实现再分配。在一个丰富的动态模型中,我们量化了最优财政计划。我们使用了新的灵活函数,具有针对性的转移和累进所得税,在整个收入分配中提供了良好的经验拟合。转移支付应比美国目前的规模更大,并以适度的所得税累进税率提供资金。
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On the Optimal Design of Transfers and Income Tax Progressivity
We study the optimal design of means-tested transfers and progressive income taxes. In a simple analytical model, we show that adding a transfer to a log-linear tax induces welfare gains almost as large as in the second-best allocation. Transfers allow for more progressive average than marginal tax and transfer rates, achieving redistribution while preserving efficiency. In a rich dynamic model, we quantify the optimal fiscal plan. We use new flexible functions featuring targeted transfers and progressive income taxes, delivering a good empirical fit across the income distribution. Transfers should be larger than currently in the United States and financed with moderate income tax progressivity.
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