An Examination of the Impact of Health on Families' Financial Status

该奖项是美国国家科学基金会社会、行为和经济科学博士后研究奖学金（SPRF）计划的一部分。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学事业准备有前途的早期职业博士级科学家。SPRF奖励包括在知名科学家的赞助下进行为期两年的培训，并鼓励博士后进行独立研究。美国国家科学基金会寻求促进科学界各阶层的科学家，包括那些未被充分代表的群体的科学家，参与其研究项目和活动；博士后阶段被认为是实现这一目标的一个重要的专业发展阶段。每个博士后必须解决各自学科领域的重要科学问题。文献中一个明显的主题是，健康方面的差异会影响其他社会结果，包括金融财富方面的差异。美国国家科学基金会的使命强调需要进行能够促进国家健康、繁荣和福利的研究。为了响应这一呼吁，本项目利用收入动态小组研究（PSID）的数据，考察了关于健康状况与金融篮子之间联系的传统观点。探索人的心理/身体健康与金融篮子（又名投资组合配置，即分配给股票、债券、共同基金的家庭财富的一部分）之间的联系是一个相对较新的研究方向。然而，在以前的研究中，重点只放在个人或户主的健康状况上。这种对个人的关注实际上可能低估了投资组合配置的健康程度。该项目改进了现有知识，重点关注户主的健康状况与其兄弟姐妹、父母和祖父母之间的联系。大家庭可以作为一种积极或消极的社会力量对家庭的幸福作出贡献。先前的研究表明，家谱中的经济困难，例如兄弟姐妹和父母之间的经济困难，有助于削弱中产阶级家庭积累净财富的能力，并且大大降低了在其投资组合中持有股票或银行账户的可能性。尤其是黑人中产阶级家庭，他们的亲戚更有可能面临这样的困难。更重要的是，先前的调查发现，相对年轻和年长的黑人家庭，与白人家庭相比，倾向于将更低比例的资产投入到风险投资中，例如股票和共同基金。然而，这些学者没有考虑到这种差异背后的力量。这个项目的基本假设是，家谱中的疾病可能是导致投资组合选择中黑人与白人差异的一个独特因素。为了验证这一命题，本项目依赖于Bogan等人（2013）使用的视角和统计方法。该项目使用的一个经验模型是二元数据的逻辑回归。逻辑回归是一种模型，可以估计家庭健康状况对特定资产类型所有权的权重，例如股票、银行账户、共同基金的财富所有权。这个项目建议运行的另一个模型是tobit模型。tobit模型是合适的，因为它可以估计健康对分配给特定金融资产的财富份额的影响。Bogan等人（2013）使用tobit回归模型估计了自我报告的健康状况对家庭财富的影响。如果在控制了收入、教育等因素后，某些人口统计数据似乎由于大家庭中的疾病而拥有较低的财富前景，那么这种不平等就需要被了解。这个项目可能会引起人们对家谱中健康状况对不同人口统计数据的不成比例影响的关注，以及为什么某些资产没有包含在个人的投资组合中。

This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. A theme that is evident in the literature is that disparities in health affect other social outcomes, including the disparities in financial wealth. The NSF mission emphasizes the need for research that can advance the national health, prosperity and welfare. This project responds to this call by using data from the Panel Study of Income Dynamics (PSID) to examine the conventional wisdom on the link between health status and the financial basket. Explorations on the link between mental/physical health of the person and financial basket (aka portfolio allocation, i.e. portion of household wealth allocated to stocks, bonds, mutual funds) is a relatively new line of inquiry. In previous research, however, the focus is only on the health status of the individual or head of the household. Such a focus on the individual may in fact underestimate the full extent of health on portfolio allocation. This project improves upon existing knowledge and focuses on connections between the health status of the head of household and their siblings, parents and grandparents. The extended family can contribute as a positive or negative social force to the well being of a household. Previous research indicates that economic hardship in the family tree, e.g. among siblings and parents, helps to undermine the ability of middle-class households to accumulate net wealth, and it substantially lowers the probability of carrying stocks or a bank account in their portfolio. Middle-class black households, in particular, are far more likely to have relatives that face such hardship. What is more, previous investigations find that relatively younger and elderly black households tend to devote a much lower proportion of their assets to risky investments, e.g. stocks and mutual funds, compared to their white counterparts. These scholars do not, however, consider the forces behind such disparity. The underlying hypothesis of this project is that sickness in the family tree may be a unique contributor to the black-white disparity in portfolio selection. To test this proposition, this project relies on perspectives and statistical methods used by Bogan et al (2013). One empirical model that the project uses is the logistic regression for binary data. The logistic regression is a model that can estimate the weight of health status in the family on ownership of a particular asset type, e.g. wealth ownership of stocks, bank account, mutual funds. Another model that this project proposes to run is the tobit model. A tobit model is appropriate because it can estimate the impact of health on the share of wealth allocated to a particular financial asset. Bogan et al (2013) estimate the influence of self-reported health status on household wealth by using a tobit regression model. If after controlling for income, education, etc., certain demographics appear to have lower wealth prospects due to illness in the extended family, such inequality needs to be made known. Potentially, this project could draw attention to the disproportionate effect that health status in the family tree has on different demographics and why certain assets are not contained in an individual's portfolio.