CAREER: Understanding Economic Growth: Firms, Inventors, and Ideas

这项研究的主要重点是了解创新、技术进步和经济增长之间的联系，并研究改善美国经济增长和福利的最佳产业政策。具体地说，本研究侧重于创新和经济增长的三个主要组成部分：(I)发明者、(Ii)公司和(Iii)想法(专利)。该项目的第一部分通过进行一项重大的数据匹配工作，将美国专利记录与1880年至1940年联邦人口普查的数据联系起来，作为未来的指南，从而考察了美国创新的黄金时代。然后研究专利发明与长期经济增长之间的关系，并勾勒出一个分析创新和增长的关键宏观和微观决定因素的框架。在过去的几十年里，整个经济的开工率下降了超过12%，而衡量要素重新分配和分散在公司增长率中的指标下降了超过20%。该项目的第二部分研究了美国经济的这些变化。该项目的这一部分侧重于了解美国经济的增长和创新模式，并使用美国经济的微观数据将各种经验规律联系在一起。目标是了解这些变化的原因，并提出能够重建创业精神和创造就业机会的政策。本项目的第三部分研究专利市场。非执业实体(NPE)如何影响创新和技术进步？该项目为这一课题提供了新的理论和实证证据。在这样做的过程中，该项目向辩论提供了信息，这些辩论将NPE描绘成良性的中间人，帮助将知识产权重新配置到最具生产力的地方，或者利用专利制度榨取租金、从而损害创新的强盗艺术家。作为该项目的一部分，PI还计划准备一套全面的关于经济增长的在线教育材料，每个人都可以免费获取。其目标是将高质量但免费的材料传播给广泛的学生，包括那些没有机会进入顶尖学府学习的学生。这项研究的结果将有助于经济增长、创造就业机会和美国经济的竞争力。将微观和宏观相结合，可以显著提高我们对宏观经济增长和技术进步的理解。宏观经济是由许多微观公司组成的，这些公司雇佣发明家来产生新的创新想法。因此，这项建议--通过关注想法、发明者和企业行为的微观经济学--旨在通过利用关于创新和企业行为的丰富信息，在企业层面捕捉创新行为中的丰富异质性，从而揭示宏观经济增长。此外，正式的模型允许我们将口头概念付诸实施，并用数据与它们对抗。因此，这项建议还侧重于将一般均衡增长理论与数百万美国专利、发明家和公司的丰富微观数据结合起来。通过使用结构估计技术，这一建议将使PI不仅能够理解潜在的机制，而且还可以进行反事实的政策练习，PI可以在其中研究最优产业政策设计。

The main focus of this research is to understand the links between innovation, technical progress, and economic growth and to study the best industrial policies to improve economic growth and welfare in the U.S. Specifically, this research focuses on three major components of innovation and economic growth: (i) inventors, (ii) firms, and (iii) ideas (patents). The first part of this project examines the golden age of American innovation by undertaking a major data matching exercise linking U.S. patent records with data from Federal Censuses between 1880 and 1940 as a guide to the future. Then it studies the relationship between patented inventions and long-run economic growth, and outlines a framework for analyzing key macro- and micro-level determinants of innovativeness and growth. Over the last several decades economy-wide startup rates have declined in excess of twelve percent, while measures of factor reallocation and dispersion in firm growth rates have declined in excess of twenty percent. The second part of the project studies these changes in the U.S. economy. This part of the project focuses on understanding patterns of growth and innovation in the U.S. economy and ties together various empirical regularities using micro data from the U.S. economy. The goal is to understand the reasons for these changes and propose policies that can reconstruct entrepreneurship and job creation. The third part of this project studies the market for patents. How do non-practicing entities (NPEs) impact innovation and technological progress? This project provides new theoretical and empirical evidence on the subject. In doing so the project informs the debate that has portrayed NPEs alternatively as benign middlemen that help to reallocate intellectual property to where it is most productive or stick-up artists that exploit the patent system to extract rents, thereby hurting innovation. As part of the project, the PI also plans to prepare a comprehensive set of online education materials on economic growth that will be freely accessible to everyone. The goal is to disseminate high-quality, but free materials to a broad range of students, including those who did not get the chance to study at a top institution. The results of this research will contribute to economic growth, job creation and competitiveness of the U.S. economy.Our understanding of macroeconomic growth and technological progress can be significantly improved by combining micro and macro perspectives. A macroeconomy is made of lots of micro firms that hire inventors to produce new innovative ideas. Therefore, this proposal--by focusing on the microeconomics of ideas, inventors, and firm behavior--aims to shed light on macroeconomic growth by capturing the rich heterogeneity in innovation behavior at the firm level by using the wealth of information on innovation and firm behavior. In addition, formal models allow us to make verbal notions operational and confront them with data. Therefore, this proposal also focuses on combining general equilibrium growth theories with rich micro data on millions of U.S. patents, inventors, and firms. By also using structural estimation techniques, this proposal will allow the PI not only to understand the underlying mechanisms, but also to do counterfactual policy exercises where the PI can study optimal industrial policy design.