Big Data in Macro and Labor Economics: New Insights into Open Questions

宏观和劳动经济学中的大数据：对开放问题的新见解

• 批准号: 1357874
• 负责人: Fatih Guvenen
• 金额: $ 28.42万
• 依托单位: National Bureau of Economic Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-03-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1357874&HistoricalAwards=false
• 关键词: Big; Data; Macro; Labor; Economics

Abstract: The PI will use "big data" to measure important economic variables in a unique way. The project uses a data set drawn from government administrative records; the data include over 30 years of annual earnings for a sample of millions of American men. With these data, the PI will be able to measure the year-to-year risk of changes in annual earned income. In particular, he will be able to determine whether or not common assumptions used in other economic models (for example, that the risk of an income shock is normally distributed) are correct. This is potentially transformative research; the PI is making innovative use of existing data and his results could overturn the conventional understanding of how business cycles, industry-specific factors, occupation, and skill set determine the risk of large year-to-year changes in income. The results will be broadly useful as well for economic policy. To understand how recessions affect American families, we need to understand how recessions affect earnings. Our current evidence here is based on small samples of the US population, and the data from these samples are not rich enough to answer the full range of questions.

翻译后摘要：PI将使用“大数据”，以独特的方式来衡量重要的经济变量。 该项目使用了来自政府行政记录的数据集;这些数据包括数百万美国男性样本30多年的年收入。 有了这些数据，PI将能够衡量年度收入变化的年度风险。 特别是，他将能够确定其他经济模型中使用的常见假设（例如，收入冲击的风险是正态分布的）是否正确。 这是一项潜在的变革性研究; PI正在创新性地利用现有数据，他的研究结果可能会颠覆人们对商业周期、行业特定因素、职业和技能组合如何决定收入逐年大幅变化风险的传统理解。 研究结果也将对经济政策产生广泛的影响。 要了解经济衰退如何影响美国家庭，我们需要了解经济衰退如何影响收入。 我们目前的证据是基于美国人口的小样本，这些样本的数据还不足以回答所有问题。