RIDIR: A Big Data Approach to Understanding American Growth

该项目使用大数据方法来找出十九世纪和二十世纪美国经济巨大增长背后的原因。 该奖项支持耶鲁大学的Costas Arkolakis和Michael Peters以及哥伦比亚大学的Sun Kyoung Lee研究团队，他们采用人工智能和机器学习技术来链接并分析大量美国联邦人口普查、劳工部和劳工统计局的历史数据。美国经济在这一时期的转型是引人注目的，从世纪初的农村经济到19世纪末的工业国家。更引人注目的是，在19世纪的大部分时间里，美国都落后于技术前沿，但在进入21世纪时，美国成为了全球技术领导者和世界上最富有的国家。 这个项目的结果将使美国人了解人们是如何生活和商业是如何运作的。 它将揭示过去的情况，这些情况包括人口、地理、价格和工资、财富、收入、产出、资本、工人数量和类型、城市化、移民和工业化。在这个项目中，涉及家庭状况、年龄、种族、职业、文化程度和收入等变量的多个数据集被联系起来。这使研究人员能够建立一个强大的图片的因素，塑造了美国的经济地理，并阐明美国的经济增长的主要方面在“第二次工业革命”（1850年至1940年），一个时期的特点是欧洲血统的人涌入。 其中一项分析构建了父母-子女数据对，并调查了随着时间的推移，孩子相对于父母的晋升机会是如何演变的。另一项研究揭示了经济冲击和政策如何影响代际流动趋势。第三份报告使用数字化的工厂级制造业普查数据，探讨在企业层面促进制造业增长的因素，以及这反过来如何影响美国的总体经济增长。这些数据将与经济学、历史学和社会学等领域的其他研究人员共享，使他们能够揭示美国非凡的经济转型和增长的潜在力量。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project uses a big data approach to find out what lies behind the tremendous growth in the American economy in the nineteenth and twentieth centuries. This award supports a team of researchers, Costas Arkolakis and Michael Peters at Yale University, and Sun Kyoung Lee at Columbia University, who employ artificial intelligence and machine learning technologies to link and then analyze massive amounts of historical US federal census, Department of Labor, and Bureau of Labor Statistics data. The transformation of the US economy during this time period was remarkable, from a rural economy at the beginning of the 19th century to an industrial nation by the end. More strikingly, after lagging behind the technological frontier for most of the nineteenth century, the United States entered the twenty-first century as the global technological leader and the richest nation in the world. Results from this project will allow Americans to understand how people lived and how business operated. It will reveal the past that led us to where we are now in terms of people, geography, prices and wages, wealth, revenue, output, capital, numbers and types of workers, urbanization, migration, and industrialization.In this project, multiple data sets, involving variables such as family status, age, ethnicity, occupation, literacy, and income, are linked. This enables researchers to build a robust picture of the factors that shaped the American economic geography and to illuminate major aspects of America's economic growth during the "Second Industrial Revolution" (1850-1940), a period characterized by an influx of people of European origin. One analysis constructs pairs of parent-child data and investigates, over time, how a child's chance of moving up relative to the child's parents has evolved. Another reveals how economic shocks and policies affected trends in intergenerational mobility. A third uses digitized plant-level Census of Manufactures data to explore the factors that contributed to manufacturing growth at the firm level and how this, in turn, affected America's aggregate economic growth. The data will be shared with other researchers in fields such as economics, history and sociology, enabling them to uncover the underlying forces of America's remarkable economic transition and growth.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.