The investigator studies optimal tax policy for innovation through a new theoretical framework that enables thorough quantitative assessments of tax reforms, and further provides new empirical evidence on the effects of taxes on the key agents for innovation, namely inventors and firms, based on new large-scale data linking administrative tax, labor market, and patent data and on historical inventor and tax data. By exploring this link between taxes and innovation, this project yields rigorously studied policy lessons to inform tax and innovation policy, which is key for the improvement of living standards and for competitiveness. The project has a strong educational outreach component through the creation of an interactive website on "Taxes and innovation", and an open-source online free textbook developed collaboratively with students.
To study the optimal design of R&D policies and firm taxation, this project first develops a new theoretical framework that encompasses a dynamic firm model with spillovers from innovation, uncertainty, and asymmetric information between firms and the government. This project further estimates the model in the data to yield concrete policy recommendations and to quantify the losses or gains from non-optimal policies. In particular, the investigator studies the effects of tax incentives on entrepreneurs and inventors using a newly constructed dataset linking entrepreneurs and inventors to their tax records and to local labor market conditions. Lastly, the project studies the effects of personal income and corporate taxation on innovation by firms and inventors in the U.S. from 1880 to 2006 using new historical data on patents, inventors, firms and their R&D labs, and state-level personal and corporate income taxes. This can improve our understanding of the long-run effects of taxes -- both on corporate and personal income -- on the quantity and quality of innovation by both inventors and firms.