R. Dimand, Terrence Hines, Olivia Gong, M. O’reilly, Tom Velk, Mengyue Zhao
{"title":"Measuring U.S. 19th Century Economic Activity Using Unexploited Railway and Postal Micro-level Data","authors":"R. Dimand, Terrence Hines, Olivia Gong, M. O’reilly, Tom Velk, Mengyue Zhao","doi":"10.15353/rea.v12i1.1691","DOIUrl":null,"url":null,"abstract":"For the past several years, we have presented and published studies based on postal related data, from postmaster cash books and the Official Register, where we use postmaster salary data as a measure of local, highly disaggregate proxies for general economic activity at town and village level. Using micro-level, high frequency, nationally uniform and previously unknown data, we will report on the outcome of measuring levels of economic activity, political influence and social mobility phenomena. In our latest work, we will use a recently published work of railroad history investments in the 19th century. The railroad history we have is highly detailed, naming particular towns and routes. Our own micro data will allow us to associate our postmaster data with railway town information at the same micro level. Our data will also allow us to report the economic activity of non-railway towns. We will then have, at the micro-level, bi-annual comparisons made over the life of the railway routes. The relative economic, political and demographic impact of railway investment will be examined. For example, as we have the names, birthplaces and ethnic origins of postmasters in addition to their salaries. We can measure not just differences in economic activity between railway and non-railway towns but even examine questions like: \"Are the railway towns places where new immigrants get to be postmasters more quickly than elsewhere?\" Our larger purpose is to advertise our ever-expanding postal based dataset, which provides information of interest to economists, sociologists, historians and political scientists.","PeriodicalId":42350,"journal":{"name":"Review of Economic Analysis","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2019-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Economic Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15353/rea.v12i1.1691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
For the past several years, we have presented and published studies based on postal related data, from postmaster cash books and the Official Register, where we use postmaster salary data as a measure of local, highly disaggregate proxies for general economic activity at town and village level. Using micro-level, high frequency, nationally uniform and previously unknown data, we will report on the outcome of measuring levels of economic activity, political influence and social mobility phenomena. In our latest work, we will use a recently published work of railroad history investments in the 19th century. The railroad history we have is highly detailed, naming particular towns and routes. Our own micro data will allow us to associate our postmaster data with railway town information at the same micro level. Our data will also allow us to report the economic activity of non-railway towns. We will then have, at the micro-level, bi-annual comparisons made over the life of the railway routes. The relative economic, political and demographic impact of railway investment will be examined. For example, as we have the names, birthplaces and ethnic origins of postmasters in addition to their salaries. We can measure not just differences in economic activity between railway and non-railway towns but even examine questions like: "Are the railway towns places where new immigrants get to be postmasters more quickly than elsewhere?" Our larger purpose is to advertise our ever-expanding postal based dataset, which provides information of interest to economists, sociologists, historians and political scientists.