专业复杂性指数与高校技能产出

Xiaoxiao Li, S. Linde, Hajime Shimao
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引用次数: 3

摘要

我们提出了一个易于计算的衡量标准,称为专业复杂性指数(MCI),它捕捉了不同专业教授的潜在技能。通过将反射方法应用于专业到职业网络,我们构建了专业相对复杂性的标量度量。我们的测量对主要平均收入和就业提供了很强的解释力。进一步的证据表明,MCI与诸如定量解决问题和使用计算技术等高级技能密切相关。我们还提供了一种两阶段算法来对可观察对象进行部分选择,这为在各种情况下应用复杂性度量提供了可能性。
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Major Complexity Index and College Skill Production
We propose an easily computable measure called the Major Complexity Index (MCI) that captures the latent skills taught in different majors. By applying the Method of Reflections to the major-to-occupation network, we construct a scalar measure of the relative complexity of majors. Our measure provides strong explanatory power of major average earnings and employment. Further evidence suggests that the MCI is strongly associated with advanced skills such as quantitative problem-solving, and the use of computing technology. We also provide a two-stage algorithm to partial out selection on observables which opens up possibilities of applying the complexity measure in various contexts.
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