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

在过去的二十年里，持有临时签证的美国博士生人数稳步增加;其中大约一半的人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决定留下或离开的作用并没有得到广泛的理解。该项目的目标是：1）生成具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）为这些人回国的决定建立解释模型，以及3）使用模型的结果来提高我们预测临时签证持有者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的信息和工具，如何改变国外的经济和政治活动的状态影响个人决定离开美国进一步的工作将有助于我们了解如何早期的科学培训和培训质量也影响决定回国。本研究将使用获得博士学位调查（SED）和博士学位获得者调查（SDR）的数据。 根据这一数据进行预测，将提供证据，说明随着时间的推移，返回现象是稳定的、增长的还是下降的。解释性模型将提供一种机制，将政策相关变量（如博士教育财政支持的性质，数量和条件，培训质量，外国政府的作用）与个人获得美国学位后返回的可能性联系起来。 最后，研究结果可以帮助提高定期收集的信息，从SED的量化偏差的数据质量。 值得注意的是，该项目将支持一名全职博士生，他们将精通使用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.