Elmer Zongyang Li (Cornell)

Optimal Skill Mixing Under Technological Advancements

Abstract: Using worker surveys and online job posting data, I document that the U.S. economy has seen a substantial increase in the mixing of skill requirements from 2005-2018, both for incumbent jobs and newly posted vacancies. American workers increasingly work in occupations that demand mixtures of analytical, computer, and interpersonal skills rather than specializing in one of them, even within granular occupations. This change occurred primarily in low- to medium-wage occupations, and the return to working in occupations or studying college majors with more mixed skills also has increased. To understand the sources of these shifts, I build a directed search model with multi-dimensional skills in which firms optimally choose occupations’ skill intensities before producing with a worker, delivering endogenous specialization in skill demand. Counterfactual analysis shows that the rise in the complementarity of skills in production and in the cost of skills
for occupation operation are the main drivers of skill mixing shifts and corresponding wage and employment dynamics in this period.