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自选择任务分配模型中的技术变革、工资不平等与最优税收

Technical change, wage inequality, and optimal taxes in an assignment model
Quantitative Economics · 2026 · Been-Lon Chen、Fei-Chi Liang

中文摘要

本文在基于自选择的人才—任务分配模型中研究收入不平等与最优税收政策。我们的模型考虑了各任务之间相对的资本—技能互补性, 由此导致资本和技术按任务复杂度出现极化, 进而推动岗位与工资增长按人才水平出现极化。就最优税收政策而言, 工资压缩渠道依然有效, 其通过补贴高工资收入者并对低工资收入者征税的涓滴效应发挥作用。然而, 旨在缩小工资不平等、经由资本税、企业所得税与研发税的工资压缩渠道, 并非通过涓滴效应起作用, 而是通过对高任务复杂度部门的资本收入和研发投资征税、同时补贴低任务复杂度部门的资本收入和研发投资来发挥作用。此外, 我们识别出一个为应对溢出效应而产生的庇古效应, 该效应会修正针对劳动收入、资本收入、企业利润和研发投资的边际税率。

Abstract

This paper studies income inequality and optimal taxation policies in a talent‐to‐task assignment model of self‐selection. Our model considers relative capital‐skill complementarities across tasks, leading to the polarization of capital and technology by task complexity, which in turn drives the polarization of job and wage growth by talent levels. Regarding optimal tax policy, the wage compression channel remains effective through the trickle‐down effect of subsidizing high‐wage earners and taxing low‐wage earners. Yet, the wage compression channel via capital, corporate, and R&D taxes, aimed at reducing wage inequality, does not operate via a trickle‐down effect. Instead, it works by taxing capital income and R&D investments in high‐task‐complexity sectors while subsidizing those in low‐task‐complex sectors. Moreover, we identify a Pigouvian effect that arises to address spillovers, which modifies the marginal tax rates on labor income, capital income, firm profits, and R&D investments.
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