An Interview with John M. Abowd

IF 1.7 3区 数学 Q1 STATISTICS & PROBABILITY International Statistical Review Pub Date : 2022-02-20 DOI:10.1111/insr.12489
Ian Schmutte, Lars Vilhuber
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Abstract

John M. Abowd is the Chief Scientist and Associate Director for Research and Methodology, US Census Bureau. He completed his AB in Economics at Notre Dame in 1973 and his PhD in Economics at University of Chicago in 1977 under Arnold Zellner. During his academic career, John has held faculty positions at Princeton, the University of Chicago, and, since 1987 at Cornell University where he is the Edmund Ezra Day Professor Emeritus of Economics, Statistics and Data Science. John was trained as a statistician and labor economist, and his economic research has focused on the rigorous empirical evaluation of labor market institutions. In the late 1990s, he began working with the Census Bureau on projects that would end up leveraging administrative and survey records into official statistical products. Through that work, he has developed a research agenda focused on issues necessary to generate those products, including data privacy, synthetic data, total error analysis, data linkage, and missing data problems, among others.

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采访约翰·m·鲍德
John M. Abowd是美国人口普查局首席科学家和研究与方法论副主任。他于1973年在圣母大学获得经济学学士学位,1977年在芝加哥大学获得经济学博士学位,师从阿诺德·泽尔纳。在他的学术生涯中,约翰曾在普林斯顿大学、芝加哥大学担任教职,并自1987年起在康奈尔大学担任经济学、统计学和数据科学埃德蒙·埃兹拉·戴名誉教授。约翰是一名统计学家和劳动经济学家,他的经济研究侧重于对劳动力市场制度的严格实证评估。上世纪90年代末,他开始与人口普查局合作,开展一些项目,最终将行政和调查记录转化为官方统计产品。通过这项工作,他制定了一个研究议程,重点关注生成这些产品所需的问题,包括数据隐私、合成数据、总错误分析、数据链接和丢失数据问题等。
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来源期刊
International Statistical Review
International Statistical Review 数学-统计学与概率论
CiteScore
4.30
自引率
5.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: International Statistical Review is the flagship journal of the International Statistical Institute (ISI) and of its family of Associations. It publishes papers of broad and general interest in statistics and probability. The term Review is to be interpreted broadly. The types of papers that are suitable for publication include (but are not limited to) the following: reviews/surveys of significant developments in theory, methodology, statistical computing and graphics, statistical education, and application areas; tutorials on important topics; expository papers on emerging areas of research or application; papers describing new developments and/or challenges in relevant areas; papers addressing foundational issues; papers on the history of statistics and probability; white papers on topics of importance to the profession or society; and historical assessment of seminal papers in the field and their impact.
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