Forecasting the Return Home of Non-US Citizens with US Ph.D.'s: Trends over time and why Non-US Citizens with US earned doctorates choose to return home

在过去20年里，持有临时签证的美国博士生人数稳步增加；这些人中约有一半在获得博士学位后留在美国。然而，经济、民族主义或科学影响对留欧决定的作用并未得到广泛理解。该项目的目标是1)生成拥有美国博士学位的临时美国签证持有者回国的基线预测，2)为这些人的回国决定建立一个解释性模型，3)使用模型的结果来增强我们预测临时签证持有者打算留在美国或回国的未来趋势的能力。这项工作的一个主要重点是提供政策相关信息和工具，说明海外经济和政治活动状况的变化如何影响个人离开美国的决定。此外，这项工作将有助于我们理解早期科学培训和培训质量如何影响回国决定。这项研究将使用博士生调查(SED)和博士学位获得者调查(SDR)的数据。根据这些数据做出的预测将提供证据，表明回报现象是稳定的、增长的还是随着时间的推移而下降的。解释性模型将提供一种机制，将与政策相关的变量(如博士教育的财政支持的性质、金额和条件、培训质量、外国政府的作用)与个人在获得美国学位后返回的可能性联系起来。最后，这些结果可以通过量化偏差来帮助提高从SED定期收集的信息的数据质量。值得注意的是，该项目将支持一名全日制博士生，他们将熟练使用SED和SDR数据。

The number of U.S. doctoral students with temporary visas has steadily increased over the last two decades; approximately half of these individuals stay in the U.S. after receipt of their doctorate. However, the roles of economic, nationalistic or scientific influences on the decision to stay or to leave are not widely understood. The objectives of this project are to 1) generate a baseline forecast of temporary U.S. visa holders with U.S. doctoral degrees who return home, 2) build an explanatory model for the decision to return home by these individuals, and 3) use the results of the model to enhance our ability to predict future trends about temporary visa holders intention to either stay in the U.S. or return home. A major focus of this work is to provide policy relevant information and tools on how the changing status of economic and political activity abroad influences individual decisions to leave the U.S. Further the work will contribute to our understanding of how early scientific training and the quality of training also influence the decision to return home. Data from the Survey of Earned Doctorates (SED) and the Survey of Doctorate Recipients (SDR) will be used for the study. The development of a forecast from this data will provide evidence as to whether or not the return phenomena is stable, growing or in decline over time. The explanatory model will provide a mechanism for linking policy relevant variables (e.g. nature, amount and conditions of financial support for doctoral education, quality of training, role of foreign governments) to individual likelihoods of return after receiving a U.S. degree. Finally, the results can help enhance data quality for regularly collected information from the SED by quantification of bias. It is also useful to note that this project will support one full time doctoral student who will become proficient using SED and SDR data.