Understanding Family Income and Consumption Dynamics in the U.S.

这个项目研究了一个具有科学价值的大型数据集，以开发家庭收入和消费在多年来如何变化的新衡量标准。首席研究员和他的团队将检查收入动态小组研究(PSID)的数据，这是一项长期研究，收集了自1968年以来几代美国家庭的样本数据。他将比较最初参与者的女儿组成的家庭和儿子组成的家庭，以确定这两个群体在收入和收入的动态模式上是否不同。这是一项重要的研究，因为这些模式对于宏观经济学和劳动经济学中的许多研究问题都很重要。衡量美国家庭在收入和收入方面的变化，对于了解失业等收入冲击将如何影响总消费非常重要。政府中的许多专家也使用这些衡量标准来评估政府政策如何影响美国经济的整体增长和竞争力。首席调查员将把PSID数据与行政数据记录结合起来，测试对观察到的两组家庭之间差异的可能解释。使用PSID数据获得的消费保险标准衡量标准意味着，相对于标准不完全市场模型的预测，永久性收入冲击的超额保险。初步结果表明，一旦这些措施以每个群体的收入动态为条件，每个子样本中的保险程度与主力模型的预测是一致的。这对于将这两个样本结合起来以获得美国家庭可获得的保险金额的汇总衡量标准的工作具有重要意义。因此，该项目有助于劳动经济学和宏观经济学，并可能揭示在家庭层面上衡量收入和收入动态的新的、更好的方法的必要性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project examines a large and scientifically valuable data set to develop new measures of how household income and consumption vary over years. The principal investigator and his team will examine data from the Panel Study of Income Dynamics (PSID), a long term study that has gathered data on a sample of U.S. families over several generations since 1968. He will compare households formed by the daughters of the original participants with households formed by sons, to determine whether or not these two groups differ in the dynamic patterns of earnings and income. This is important research, because these patterns are important for many research questions in macroeconomics and labor economics. Measuring how American families have experienced changes in earnings and income is important for understanding how income shocks like unemployment will affect aggregate consumption. These measurements are also used by many experts in government to evaluate how government policies can affect the overall growth and competitiveness of the U.S. economy.The principal investigator will combine PSID data with administrative data records to test possible explanations for observed differences between the two sets of households. Standard measures of consumption insurance obtained using PSID data imply excess insurance of permanent income shocks relative to the predictions of a standard incomplete markets model. Preliminary results suggest that once these measures are made conditional on the income dynamics of each group, the degree of insurance in each subsample is consistent with the predictions of the workhorse model. This has important implications for work that combines the two samples to get aggregate measures of the amount of insurance available to U.S. households. The project therefore contributes to labor economics and macroeconomics and may uncover the need for new and better ways to measure income and earning dynamics at the household level.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.