从大学到职场的过渡:分组数据的持续时间模型

Pub Date : 2024-07-16 DOI:10.3390/stats7030043
Manuel Salas‐Velasco
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引用次数: 0

摘要

劳动力市场调查通常以时间间隔来衡量失业持续时间。在这种情况下,传统的持续时间模型,如 Cox 回归和参数生存模型,并不适合研究失业持续时间。为了解决上述问题,我们使用 Han 和 Hausman 的有序对数模型来研究分组持续时间,该模型比标准规范更具灵活性。特别是,它的灵活性来自于我们不需要为基线危险函数指定任何函数形式--这也规避了与异质性相关的问题。我们关注的重点是高等教育毕业生的首次失业持续时间。分析是通过西班牙大学毕业生调查的一个大型数据集完成的。结果表明,高等教育毕业生从大学到工作的转变与毕业生的年龄、参加实习项目的情况、学习领域、大学类型和性别有很大关系。具体而言,参加过实习计划的毕业生、工科毕业生和私立大学毕业生的过渡比较顺利。
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Transitioning from the University to the Workplace: A Duration Model with Grouped Data
Labor market surveys usually measure unemployment duration in time intervals. In these cases, traditional duration models such as Cox regression and parametric survival models are not suitable for studying the duration of unemployment spells. In order to deal with this above issue, we use Han and Hausman’s ordered logit model for grouped durations, which has more flexibility than standard specifications. In particular, its flexibility arises from the fact that we do not need to specify any functional form for the baseline hazard function—it also circumvents problems associated with heterogeneity. The focus of interest is on the first unemployment duration of higher education graduates. The analysis is accomplished by using a large dataset from a graduate survey of Spanish university graduates. The results show that the university-to-work transition of higher education graduates is significantly associated with the graduate’s age, participation in internship programs, field of study, type of university, and gender. Specifically, graduates who participated in internship programs, engineering graduates, and graduates from private universities experience a smooth transition.
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