Innovation Networks and Economic Growth

该项目旨在建立一种方法，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，具有网络效应;也就是说，开发新产品或新工艺的公司、科学家或个人受到其他创新者的决策和发现的影响，反过来又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激发大量相关的创新。 该项目将利用专利申请数据来衡量各类专利之间的网络联系。 然后，该小组将设法将这些措施纳入一个整体经济增长模型，以考虑新技术对整体生产率增长和就业的影响。此外，研究人员还希望预测公共和私人研发活动对宏观经济的影响，并利用美国专利商标局（USPTO）1975年至2009年的数据，分析产业政策对美国宏观经济竞争力的影响。 他们正在模拟各种创新类型的创新网络结构，并包括创新质量的衡量标准。 目标是确定一个领域的专利如何增加（或减少）其他领域的创新概率。 网络描述将用于衡量溢出效应的大小（包括一阶和二阶效应）。 该网络产生的变化将用于调查新技术对各城市就业/产出/工资的影响。 创新网络还将被纳入总体经济中资源配置的结构模式。 PI将确定大学和公共研究实验室专利在创新网络中的位置;他们将使用结果来考虑公共资助的研发与私人资助的研发之间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.