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最优税收与研发政策

Optimal Taxation and R&D Policies
Econometrica · 2022 · Ufuk Akcigit、Douglas Hanley、Stefanie Stantcheva

中文摘要

我们将企业税收与研发政策的最优设计作为一个存在溢出效应的动态机制设计问题加以研究。企业的研究生产率具有异质性,且这一研究生产率属于私人信息。企业之间存在未内部化的技术溢出,但信息不对称使政府无法以第一优方式予以纠正。我们强调,决定最优政策的关键参数包括:(i)可观测的研发投资、不可观测的研发投入与企业研究生产率之间的相对互补性;(ii)企业研究生产率的离散程度和持续性;以及(iii)企业间技术溢出的幅度。我们使用与专利数据匹配的企业层面数据估计模型,并量化最优政策。数据显示,高研究生产率企业从研发投资中获得的回报不成比例地高于研究生产率较低的企业。非常简单的创新政策,例如将线性企业税与非线性研发补贴相结合——该补贴在研发水平较高时提供较低的边际补贴——其效果几乎可以与不受限制的最优政策相媲美。我们的公式以及理论和数值方法还可更广泛地应用于信息不对称且存在溢出效应的动态环境中的企业激励设计,以及更一般的企业税收问题。

Abstract

We study the optimal design of corporate taxation and R&D policies as a dynamic mechanism design problem with spillovers. Firms have heterogeneous research productivity, and that research productivity is private information. There are non‐internalized technological spillovers across firms, but the asymmetric information prevents the government from correcting them in the first best way. We highlight that key parameters for the optimal policies are (i) the relative complementarities between observable R&D investments, unobservable R&D inputs, and firm research productivity, (ii) the dispersion and persistence of firms' research productivities, and (iii) the magnitude of technological spillovers across firms. We estimate our model using firm‐level data matched to patent data and quantify the optimal policies. In the data, high research productivity firms get disproportionately higher returns to R&D investments than lower productivity firms. Very simple innovation policies, such as linear corporate taxes combined with a nonlinear R&D subsidy—which provides lower marginal subsidies at higher R&D levels—can do almost as well as the unrestricted optimal policies. Our formulas and theoretical and numerical methods are more broadly applicable to the provision of firm incentives in dynamic settings with asymmetric information and spillovers, and to firm taxation more generally.
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