Presented by Stern Economics, FAS Economics, and C.V. Starr Center for Applied Economics.
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"Optimal Taxation and R&D Policies" - Stefanie Stantcheva, Ufuk Akcigit, John Grigsby, and Tom Nicholas
We study the optimal design of R&D policies and corporate taxation as a dynamic mechanism design with externalities using the tools of public economics. Firms are heterogeneous in their research productivity, i.e., in the efficiency with which they convert a given set of R&D inputs into successful innovations. There are non-internalized technology spillovers across firms, but the asymmetric information about firms' research productivity prevents the first best solution. We characterize the optimal policies for firms of different sizes and ages. We highlight that key parameters for these policies are i) the relative complementarities between observable R&D investments, unobservable R&D inputs, and firm productivity, and ii) the dispersion and persistence of firm productivity. We estimate our model using firm-level data matched to patent data and quantify the optimal policies. Simpler innovation policies, such as linear R&D subsidies and linear profit taxes, lead to large revenue losses relative to the optimal mechanism. 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.