Doctoral Dissertation Research in Economics - Dissertation Enhancement Project:The Geography of Innovation: Patents in Early America

本项目探讨了19世纪美国城市化与创新之间的关系，以专利数量为衡量标准。pi将编译并使用一个基于文本的专利数据集，该数据集与使用地理信息系统（GIS）技术的地图相关联。该项目通过研究创新的地理分布和概念上的相互联系，为创新文献做出了贡献。研究创新历史和经济地理学中的这些关系将有助于分离出刺激技术发展的潜在因素。人员、货物和信息在各地之间的流动在19世纪急剧增加，尤其是在美国国内。该项目考察了“交通革命”促进创新活动的假设，这将通过专利率和来自不同地方的专利的结构相似性来揭示。该项目绘制了从1790年到1900年美国所有县的专利和人口之间的关系，而不仅仅是人口稠密或创新的地区。PIs的地理定位（与经纬度坐标匹配）专利是1836年以前在美国发布的，方法是将其城镇和县的信息与AniMap 3.0.2县边界历史地图集中的历史城镇名称数据库合并。该项目将使用光学字符识别技术从文件图片中创建的文本与1836年后专利的位置联系起来。通过使用文本分析，这个项目将有助于我们理解创新的其他不可观察的方面。它将在1838-1870年和1880-1897年之间发布的所有专利的全文数据库中搜索语言关系，以探索相关思想的产生和传播。通过地理信息系统将这种可搜索的全文专利数据与交通和人口数据联系起来，将绘制出一幅地图，使人们能够更清晰、更复杂地了解创新集群。一大批经济模型假定，技术变革与城市密度和庞大人口相结合的思想传播有关。很明显，大而密集的城市比其他地方更具创新性，但规模和密度并不大；有效地诱导技术改进。pi研究了一种假设，即增加市场准入会通过交通基础设施的扩展加速创新，以及另一种假设，即增加通信会导致主要城市地区以外的创新增加。找到基础设施、市场准入和创新之间的因果关系，将有助于解决经济史上有关美国发展过程的突出问题。本研究的结果可用于辅助建模。内生生长困难的特点。这种分析将通过建立创新历史过程的年表，并通过测量贡献因素影响的幅度和时间，帮助理清这些因素。这里汇集的数据集也可以用于解决历史创新研究中的相关问题；工业和城市群；创新与经济增长的空间关系并根据经济地理学和创新经济学来回答行业特定的问题。

This project explores the relationship between urbanization and innovation in nineteenth-century America as measured by number of patents issued. The PIs will compile and use a text-based dataset of patents linked to maps using Geographic Information Systems (GIS) techniques. The project contributes to the literature on innovation by examining the geographical spread and conceptual interconnectedness of innovations. Examining these relationships in the history of innovation and economic geography will help isolate the underlying factors that spur technological development.The movement of people, goods, and information among places increased dramatically over the nineteenth century, particularly within the United States. The project examines the hypothesis that the "transportation revolution" facilitated innovative activity, and this will be revealed through rates of patenting and also textural similarities in patents originating in different places. The project maps the relationship between patents and population for all counties in the US from 1790 to 1900, not just populous or innovative locations. The PIs geo-locate (matching with latitude and longitude coordinates) patents issued in the US before 1836 by merging their town and county information with a database of historical town names from the AniMap 3.0.2 County Boundary Historical Atlas. The project links the text, created from pictures of the documents using optical character recognition, with the location of post-1836 patents.By using textual analysis, this project will contribute to our understanding of otherwise unobservable aspects of innovation. It will search for linguistic relationships within a full-text database of all patents issued between 1838-1870 and 1880-1897 to explore the generation and spread of interrelated ideas. Linking this searchable, full-text patent data with transportation and population data through GIS will give a mapping that allows a clearer and more sophisticated understanding of innovative agglomerations. A large class of economic models has assumed that technological change is related to the spread of ideas through combination of urban density and large populations. It is clear that large, dense cities are more innovative than other places, but size and density are not su;fficient to induce technological improvements. The PIs study the hypothesis that increasing market access leads to an acceleration of innovation through the spread of transportation infrastructure, as well as the alternate hypothesis that increased communication led to increasing innovation outside of the major urban areas.Finding the direction of causality among infrastructure, market access, and innovation will help solve outstanding questions in economic history about the development process of the United States. The results of this study may be used to assist in modeling an otherwise di;fficult feature of endogenous growth. This analysis will help disentangle these factors by establishing the chronology of the historical process of innovation, and by measuring the magnitude and timing of the effects of the contributing factors. The dataset assembled here can also be used to address related issues, in the study of historical innovation; industrial and urban agglomerations; the spatial relationship between innovation and economic growth; and to answer industry-specific questions informed by both economic geography and the economics of innovation.