Investing in science, research and technology: where is the biggest bang for the buck?

投资科学、研究和技术：最划算的地方在哪里？

• 批准号: 1158172
• 负责人: Sandy Dall'erba
• 金额: $ 32.87万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1158172&HistoricalAwards=false
• 关键词: Investing; science; research; technology; where

As regional economies increasingly compete at the national and international levels to develop their innovative edge, helping regions identify and support the factors at the origin of innovation has become one of the most important tasks of regional economic developers. This project is based upon the knowledge production function literature which relies on a statistical approach to estimate the impact of investments in R&D (Research and Development) on the production of innovation. Because this project focuses on the production of innovation at the regional level, it requires us explicitly to account for the role of knowledge externalities between regions, a phenomenon brought to the fore by the new literature in economic geography. As of today, however, only a handful of studies use the appropriate statistical techniques to model and measure interregional knowledge externalities; when they do, they make global (not local) measurements which mask significant variations in the characteristics of innovation across regions. As such, this work improves upon the traditional approach by providing measurements of knowledge spillovers at the local level, i.e. for every single region. This work also investigates the dynamics of regional knowledge creation for four "high-technology" sectors to better substantiate differences in knowledge externalities across sectors. In addition, the statistical analysis is performed on three different spatial scales (US counties, Metropolitan Statistical Areas and States), making this work more complete and informative to local governments than traditional approaches. Another contribution is a method of measuring the amount of income and jobs created by R&D investments, i.e. their social returns. This contribution is accounted for through the modeling of interregional externalities by means of two complementary techniques called spatial econometrics and multi-regional input-output. Last but not least, the dataset used in this project significantly improves upon previous studies. Not only do the investigators rely on the most recent private R&D investment data from the US Patent and Trademark Office, but they also use the Consolidated Federal Funds Report of the Census Bureau to estimate, for the first time, the role of federally funded R&D investments on knowledge creation at the regional level. Overall, this project aims at showing where to maximize R&D investments and help regional governments tailor appropriate policies to promote knowledge creation. The broader impacts of this project are threefold: first, the thorough statistical approach used in this project will help local policymakers identify the key economic characteristics they should rely on to stimulate knowledge creation in their locality. Second, a clear estimation of the relative returns on public investments is essential to support evidence-based fiscal policy. The private and social returns on R&D investments evaluated in this work can thus be directly compared with the returns from other public investments such as education, transportation and defense, for instance. Finally, in addition to the usual scholarly publications and in-class presentations, the results of this project will be accessible online and for free in the frame of a dynamic WebGIS (Geographic Information System). Because it is able to give a large audience access to all the results, this dissemination method promotes transparency, objectivity and accountability in the research at hand.

随着区域经济在国内和国际层面发展创新优势的竞争日益激烈，帮助区域识别和支持创新的起源因素已成为区域经济发展的重要任务之一。该项目基于知识生产函数文献，该文献依赖于统计方法来估计研发投资对创新生产的影响。由于本项目侧重于区域层面的创新生产，因此它要求我们明确考虑区域间知识外部性的作用，这是经济地理学新文献所带来的一种现象。然而，到目前为止，只有少数研究使用适当的统计技术来模拟和衡量区域间知识外部性；当他们这样做的时候，他们做的是全球（而不是地方）衡量，这掩盖了各地区创新特征的显著差异。因此，这项工作在传统方法的基础上进行了改进，提供了地方层面（即每个地区）的知识溢出度量。本研究还研究了四个“高技术”部门的区域知识创造动态，以更好地证实部门间知识外部性的差异。此外，统计分析是在三个不同的空间尺度（美国县、大都市统计区和州）上进行的，这使得这项工作比传统方法更完整，对地方政府来说也更有用。另一个贡献是一种衡量研发投资所创造的收入和就业数量的方法，即它们的社会回报。这一贡献是通过空间计量经济学和多区域投入产出两种互补技术对区域间外部性进行建模来解释的。最后但并非最不重要的是，本项目中使用的数据集比以前的研究有了显著的改进。调查人员不仅依靠美国专利商标局最新的私人研发投资数据，而且还使用人口普查局的联邦综合基金报告，首次估计联邦资助的研发投资在地区层面上对知识创造的作用。总的来说，这个项目旨在展示在哪里可以最大限度地增加研发投资，并帮助地方政府制定适当的政策来促进知识创造。该项目的广泛影响有三个方面：首先，该项目使用的全面统计方法将帮助当地政策制定者确定他们应该依赖的关键经济特征，以刺激当地的知识创造。其次，明确估算公共投资的相对回报，对于支持基于证据的财政政策至关重要。因此，在这项工作中评估的研发投资的私人和社会回报可以直接与其他公共投资（例如教育、交通和国防）的回报进行比较。最后，除了通常的学术出版物和课堂报告之外，这个项目的结果将在动态的WebGIS（地理信息系统）框架中在线免费提供。因为它能够让大量的受众接触到所有的结果，这种传播方法促进了手头研究的透明度、客观性和问责性。