The Long Term Impact of Income Transfers During Childhood

描述(由申请人提供)：最近的文献证明，不利的早期生活条件可能会对教育、劳动力市场结果和死亡率产生负面的长期影响。然而，几乎没有证据表明，向贫困家庭转移收入等公共政策能否有效地改善年轻人的基本条件。我们通过评估母亲养老金计划对死亡率、残疾、收入和教育程度的影响，首次对现金转移(福利)对受助儿童的长期影响进行了分析。研究结果将使政策制定者更好地了解收入转移的可能性，以减少童年环境差异对社会经济地位和健康状况终身差异的影响。国会议员计划(1911-1935)是美国第一个由政府资助的针对有抚养子女的家庭的福利计划，也是目前被称为TANF的联邦计划的基础。在州方案中，在资格(仅丧偶与包括被遗弃/离婚的妇女)、每月养老金数额和期限以及领取条件(无条件、产妇工作或子女入学)方面存在相当大的差异。[我们收集了14个州8万多名被接受和被拒绝的下院议员申请者的信息，他们在1911年至1935年期间提出了申请。我们正在将这些个人数据与社会保障管理局的信息进行匹配，这些信息包括死亡日期、残疾申请/收据和收入，以及1940年人口普查和第二次世界大战(第二次世界大战)征兵记录中关于完成教育年限、职业、身高和智商以及1940年收入(目标1)的信息。据我们所知，这一数据集将构成第一个可将儿童早期状况与中长期结果联系起来的大规模记录集合，并将提供一个包含公共数据的未查明的关联数据集，用于研究目的。我们将使用这些数据来评估儿童时期现金转移对中期和长期结果的影响，使用依赖于建立适当的对照小组的识别技术。这些人包括同一县和年份被拒绝的申请者，在具有严格资格要求的县(例如，仅寡妇)不符合条件的母亲(例如，离婚或被遗弃的母亲)，以及在没有建立 或者很晚才建立母亲养老金计划(目标2)。最后，我们正在开发使用不完全匹配数据的新计量经济学技术。目前的技术状态是将分析仅限于完全或唯一匹配的数据，但这不必要地丢弃了大量信息(所有未匹配和多次匹配的数据)并且忽略了测量误差(一些个体被错误匹配)。我们正在开发计量经济学技术，通过使用合理的参数模型近似生成数据的过程并估计界限(目标3)，从而利用数据中的所有信息(唯一、多个和无匹配)。]

DESCRIPTION (provided by applicant): Recent literature documents that adverse early-life conditions can have negative long-term effects on education, labor market outcomes, and mortality. However, there is scant evidence as to whether public policies such as income transfers to poor families can effectively improve the underlying conditions of the young. We propose the first analysis of the long-term effects of cash transfers (welfare) on recipient children by evaluating the effects of Mothers' Pension (MP) programs on mortality, disability, earnings and educational attainment. The results will better inform policy-makers regarding the potential for income transfers to reduce the impact of disparities in childhood circumstances on lifetime differences in socioeconomic status and health. MP programs (1911-1935) were the first government sponsored welfare program for families with dependent children in the U.S. and served as the basis for the federal program that is currently known as TANF. Among the state programs, there was considerable heterogeneity in eligibility (widowed only vs. inclusion of abandoned/divorced women), amount of monthly pension and duration, and conditions of receipt (unconditional, maternal work, or child school attendance). [We have collected information on over 80,000 accepted and rejected MP applicants in 14 states who applied between1911 and1935. We are in the process of matching these individual data with information from the Social Security Administration that includes date of death, disability application/receipt, and earnings, as well as to information from the 1940 census and World War II (WWII) enlistment records on years of completed schooling, occupation, height and IQ, and 1940 income (Aim 1). To our knowledge, this dataset will constitute the first large-scale collection of records for which early conditions in childhood can be linked with medium and long-term outcomes and a de-identified linked dataset containing the public data will be made available for research purposes. We will use these data to evaluate the impact of cash transfers in childhood on medium and long-term outcomes using identification techniques that rely on the construction of appropriate control groups. These include rejected applicants in the same county and year, ineligible mothers (e.g., divorced or abandoned mothers) in counties with strict eligibility requirements (e.g., widows only), and widowed mothers in states that did not establish, or were very late to establish, a mothers pension program (Aim 2). Finally, we are developing new econometric techniques for using imperfectly matched data. The current state of the art is to limit analysis to only perfectly or uniquely matched data, but this unnecessarily discards a great deal of information (all unmatched and multiply matched data) and ignores measurement error (some individuals are incorrectly matched). We are developing econometric techniques that will make use all of the information in the data (unique, multiple and no matches) by approximating the process that generates the data using reasonable parametric models and also estimating bounds (Aim 3).]