Doctoral Dissertation Research in Economics: Essays on Migrant Self-Selection and Productivity.

移民对接受国经济来说是一种资产还是一种负担？移民是否剥夺了来源地人口中最熟练和受教育程度最高的劳动力，还是为最贫困的人提供了其他方式无法获得的机会？回答这些广泛和基本的移徙经济学问题的第一步是研究移徙者在原籍地和目的地的生产力的性质和决定因素。本项目侧重于这方面的三个具体问题。第一，移徙者是根据生产力从其原籍人口中进行积极的还是消极的自我选择？也就是说，移民的生产力一般比留在国内的人高还是低？第二，这种自我选择如何受到输出国和接受国经济状况的影响？最后，与移民的特质特征相比，移民的原籍地特征是否更能预测接收劳动力市场的结果和生产率？也就是说，能力能弥补贫穷的背景吗？这些问题的研究与援助的一个新的数据集构建的PI。该数据集将包括1907年至1925年期间抵达纽约港的意大利乘客的个人特征，如存储在埃利斯岛的乘客清单所报告的那样。这些清单中的个人也将与十年一度的美国人口普查手稿相关联，以恢复有关他们移民后劳动力市场结果的信息，以及他们在美国出生的孩子的劳动力市场结果。该数据集的三个特征允许PI改进先前研究的缺点。首先，一个人体测量的措施，平均身高，是用来量化移民生产力。众所周知，对于与个人劳动生产率密切相关的许多变量（例如，健康、技能和教育），并且不受使用诸如识字率和职业等生产力常用衡量标准所带来的许多问题的影响。第二，这些数据有助于确定移徙者在意大利境内的具体原籍地，从而与意大利高度分类的身高数据进行匹配和比较。因此，可以将移民直接与其当地原籍人口进行比较。即使在国家一级，也很少有可能用任何其他措施或在任何其他研究时期进行这种分类。最后，这些数据使我们有可能观察移民在移民前后的特点，从而对移民同化进行全面的研究。现代背景下的移徙者自我选择被一些阻止某些类型移徙者移徙的法律的障碍所掩盖。因此，关于现代移徙者的数据不能代表在没有法律的障碍的情况下选择移徙的全部人口。此外，历史数据不受限制现代数据研究的保密限制，使得创建拟议数据集-特别是结合移民和人口普查记录-成为可能。因此，对历史移民的研究可以使研究人员更好地了解推动移民流动组成的力量以及移民在接受国的劳动力市场结果。因此，这项研究的结果可以为政策制定者提供有价值的见解，而这是仅靠现代数据无法实现的。

Are immigrants an asset or a burden to the receiving economy? Does emigration deprive source populations of the most skilled and educated portions of their labor force, or does it provide otherwise-unavailable opportunities to the most deprived? A first step in answering these broad and fundamental questions of the economics of migration is to study the nature and determinants of the productivity of migrants in their place of origin and in their destination. This project focuses on three specific questions in this vein. First, are migrants positively or negatively self-selected from within their populations of origin on the basis of productivity? That is, are migrants generally more or less productive than stayers? Second, how is such self-selection affected by the state of the economy in the sending and receiving countries? Finally, are locality-of-origin-specific characteristics of migrants more powerful predictors of outcomes and productivity in the receiving labor market than are migrants' idiosyncratic characteristics? That is, does ability compensate for a poor background?These questions are studied with the aid of a novel data set to be constructed by the PI. This data set will consist of the personal characteristics of Italian passengers arriving in the Port of New York between 1907 and 1925, as reported on the passenger manifests stored at Ellis Island. Individuals in these manifests will also be linked to decennial US Census manuscripts in order to recover information on their post-migration labor market outcomes, as well as the labor market outcomes of their US-born children. Three features of this data set allow the PI to improve on the shortcomings of prior studies. First, an anthropometric measure, average stature, is used to quantify migrant productivity. This measure is known to be a very good proxy on average for many variables that are strongly correlated with individual labor productivity (e.g., health, skill, and education), and is not subject to many of the problems that accompany the use of common measures of productivity, such as literacy and occupation. Second, the data enable the identification of migrants' specific place of origin within Italy, and thus their matching with and comparison to highly disaggregated stature data from Italy. It is therefore possible to compare migrants directly to their local population of origin. Such disaggregation is rarely possible with any other measure or in any other time period of study, even on the national level. Finally, these data make it possibleto observe both the post-migration and pre-migration characteristics of migrants, enabling a comprehensive study of migrant assimilation.The study of historical migration has several advantages over the study of modern migration. Migrant self-selection in modern contexts is masked by a number of legal barriers that prevent the migration of certain types of migrants. Data on modern migrants are therefore not representative of the entire population that would choose to migrate in the absence of legal barriers. Moreover, historical data are not subject to the confidentiality restrictions that constrain research with modern data, making the creation of the proposed dataset - particularly the combination of migration and census records - possible. The study of historical migration can therefore equip researchers with a better understanding of the forces driving the composition of migratory flows and the labor market outcomes of migrants in the receiving country. Results from this research can therefore provide valuable insights to policy makers that would be unattainable through the use of modern data alone.