Optimal Taxation and R&D Policies
Optimal Taxation and R&D Policies
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DOI：
10.3386/w22908
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发表时间：
2016-12
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影响因子：
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通讯作者：
Ufuk Akcigit;Douglas Hanley;Stefanie Stantcheva
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文献类型：
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作者：
Ufuk Akcigit;Douglas Hanley;Stefanie Stantcheva
本文将企业税收和R&D政策的优化设计作为一个具有溢出效应的动态机制设计问题进行研究。企业具有异质性的研究生产力，研究生产力是私有信息。企业之间存在非内部化的技术溢出，但信息不对称使政府无法以最佳方式纠正这些溢出。我们强调，最优政策的关键参数是（一）可观察的R&D投资，不可观察的R&D投入，和企业的研究生产力之间的相对互补性，（二）分散和持久性的企业的研究生产力，和（三）跨企业的技术溢出的大小。我们使用与专利数据相匹配的公司级数据来估计我们的模型，并量化最优政策。在数据中，高研究生产率的公司比低生产率的公司获得了不成比例的更高的研发投资回报。非常简单的创新政策，如线性公司税与非线性R&D补贴相结合，在更高的R&D水平上提供更低的边际补贴，可以做得几乎和无限制的最优政策一样好。我们的公式和理论和数值方法更广泛地适用于提供企业激励措施的动态设置与不对称信息和溢出，并公司税收更普遍。
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.