中文摘要
我们提出一个用于理解自动化及其他类型技术变革对劳动需求影响的框架，并运用该框架解读近期美国就业的变化。该框架的核心是任务在资本与劳动之间的配置——即生产的任务构成。自动化使资本能够在劳动力原先从事的任务中替代劳动力，并通过替代效应使生产的任务构成转向不利于劳动力的方向。因此，自动化总会降低增加值中的劳动份额，并且即使在提高生产率的同时，也可能降低劳动需求。自动化的影响被劳动力具有比较优势的新任务的创造所抵消。新任务的引入通过重新吸纳效应使生产的任务构成转向有利于劳动力的方向，并总会提高劳动份额和劳动需求。我们说明了如何利用行业层面的数据，推断由自动化和新任务引起的生产任务构成变化所发挥的作用。我们的实证分解表明，过去三十年就业增长放缓可归因于替代效应加速（尤其是在制造业）、重新吸纳效应减弱，以及生产率增速低于此前数十年。
Abstract
We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor—the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added and may reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect, and always raises the labor share and labor demand. We show how the role of changes in the task content of production—due to automation and new tasks—can be inferred from industry-level data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades.