Innovation Networks and Economic Growth

该项目寻求建立一种方法，以了解创新网络如何影响广泛的经济成果。我们知道，创新发生在网络环境中，并具有网络效应；也就是说，开发新产品或流程的公司、科学家或个人会受到其他创新者的决策和发现的影响，进而对其他人产生同样的影响。例如，一个特定领域的创新可能会刺激大量相关创新。该项目将使用专利申请的数据来衡量各类专利之间的网络联系。然后，该小组将寻求将这些措施纳入整体经济增长模型，以考虑新技术对整体生产率增长和就业的影响。他们还希望开发关于公共和私人研发如何以不同方式影响宏观经济的预测，以及可能有助于确定产业政策如何影响美国宏观经济竞争力的工具。该团队使用了美国专利商标局(USPTO)1975年至2009年的数据。它们正在对各种创新类型的创新网络结构进行建模，并包括创新质量的衡量标准。其目标是确定一个领域的专利如何增加(或减少)其他领域的创新可能性。网络描述将用来衡量溢出效应的大小(包括一阶和二阶效应)。该网络产生的差异将用于调查新技术对各个城市的就业/产出/工资的影响。创新网络还将融入总量经济中的资源配置结构模型。PIs将决定大学和公共研究实验室专利在创新网络中的位置；他们将利用这一结果来考虑公共资助的研发和私人资助的研发的网络效应是否存在系统性差异。

This project seeks to establish a method for understanding how innovation networks affect broad economic outcomes. We know that innovation happens in a network environment and has network effects; that is, a firm, scientist, or individual developing a new product or process is affected by the decisions and findings of other innovators, and in turn has that same effect on others. For example, an innovation in one specific area may spur a large number of related innovations. The project will use data from patent applications to develop measures of the network links between broad classes of patents. The team will then seek to incorporate these measures into a model of overall economic growth to consider questions about the implications of new technologies for overall productivity growth and employment. They also want to develop predictions about the ways in which public and private R&D affect the macroeconomy in different ways, and tools that may help to determine how industrial policy can affect the competitiveness of the US macroeconomy.The team uses data from the US Patent and Trademark Office (USPTO) for the years from 1975 to 2009. They are modeling the network structure of innovations across types of innovation, and are including measures of innovation quality. The goal is to determine how a patent in one area increases (or decreases) the probability of innovation in other areas. The network description will be used to measure the size of spillovers (including first-order and second-order effects). Variation generated by the network will be used to investigate implications of new technologies for employment/output/wages across cities. The innovation network will also be integrated into a structural model of resource allocation in the aggregate economy. The PIs will determine where university and public research lab patents sit in the innovation network; they will use the result to consider whether there are systematic differences between the network effects of publicly funded R&D vs. privately funded R&D.