Effects of Social Mobility on Individual Well-Being, Attitudes, and Behavior

这项研究项目将开发新的统计模型来估计社会流动的影响。向下的社会流动，或个人从有利的社会经济地位转移到不利的社会经济地位，是一种越来越普遍的经历。向下流动被认为会导致不良结果，如精神健康恶化、暴力增加和过早死亡。由于现有方法的局限性，缺乏关于社会流动对各种与政策相关的结果的影响的有效经验证据。该项目将解决现有社会流动科学工作在方法上的弱点。利用NSF支持的两项研究的现有数据，研究人员还将检查社会流动对个人层面的影响。本项目中开发的方法的经验应用将为研究生提供培训机会。将开发一个用户友好的软件包和一个开放获取的在线工具，以增加研究人员、政策制定者和分析人员对新开发方法的获取和使用。这项研究项目将开发一种新的方法来部分识别社会流动的影响，包括原籍和目的地的影响。通过开发将社会流动性的影响与社会经济地位的后果分开的新技术，该项目将提供关于研究人员如何从应用于排名不足或高维数据的统计模型中获得可靠估计的见解。新方法将应用于综合社会调查和收入动态小组研究的数据。研究人员将考察流动经历对个人幸福感(如感知到的幸福感和压力)、态度(如社会信任和群体外偏见)和行为(如婚姻和生育)的影响。新开发的方法也将很容易适用于存在线性依赖问题的其他实质性应用。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 research project will develop new statistical models for estimating the effects of social mobility. Downward social mobility, or the movement of an individual from an advantaged to a disadvantaged socioeconomic position, is an increasingly common experience. Downward mobility is hypothesized to lead to undesirable outcomes, such as deteriorating mental health, increased violence, and early mortality. Due to limitations of existing methods, valid empirical evidence has been lacking on the effects of social mobility for a wide variety of policy-relevant outcomes. This project will address the methodological weaknesses of existing scientific work on social mobility. Using existing data from two NSF-supported studies, the investigators also will examine the individual-level consequences of social mobility. The empirical application of the approaches developed in this project will provide training opportunities for graduate students. A user-friendly software package and an open-access online tool will be developed to increase access to and use of the newly developed methods by researchers, policymakers, and analysts. This research project will develop a new approach to partially identify the effect of social mobility net of the effects of origin and destination. By developing new techniques to disentangle the effects of social mobility from the consequences of socioeconomic position, the project will provide insights on how researchers can obtain reliable estimates from statistical models applied to rank-deficient or high-dimensional data. The new methods will be applied to data from the General Social Survey and the Panel Study of Income Dynamics. Investigators will examine the effects of mobility experiences on individuals' well-being (such as perceived happiness and stress), attitudes (such as social trust and out-group bias), and behaviors (such as marriage and fertility). The newly developed methods also will be readily applicable to other substantive applications in which linear dependency problems exist.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.