Sorting Multidimensional Types: Theory and Application
构建了一个工人与工作在认知和体力技能上的多维匹配理论模型，推导出均衡解，并利用美国数据估计模型，发现近二十年认知技能互补性增强、体力技能互补性减弱，这些技术变化解释了工资极化与不平等加剧。
This article studies multidimensional matching between workers and jobs. Workers differ in manual and cognitive skills and sort into jobs that demand different combinations of these two skills. To study this multidimensional sorting problem, I develop a theoretical framework that generalizes the unidimensional notion of assortative matching and sufficient conditions on the technology under which sorting obtains. I derive the equilibrium in closed form and use this explicit solution to study biased technological change. The main finding is that an increase in worker-job complementarities in cognitive relative to manual inputs leads to more pronounced sorting and wage inequality across cognitive relative to manual skills. This can trigger wage polarization and boost aggregate wage inequality. I then estimate the model for the U.S. and identify sizable technology shifts: during the last two decades, worker-job complementarities in cognitive inputs strongly increased, whereas complementarities in manual inputs decreased. In addition to this bias in complementarities, there has been a cognitive skill-bias in production. Counterfactual exercises suggest that these technology shifts (as opposed to changes in skill supply and demand) can account for observed changes in worker-job sorting, wage polarization and a significant part of the increase in U.S. wage dispersion.