Colin Caines, Florian Hoffmann, Gueorgui KambourovWe document a strong, positive relationship between occupational problem complexity, measured from US data on problem-solving requirements, and occupational wage growth since 1980. In contrast, employment shifts toward more complex occupations have been modest, suggesting a race between the demand for and supply of complex skills. We rationalize these findings by formulating and structurally estimating a quantitative general equilibrium model on the granular occupational level. In our model, workers have heterogeneous comparative advantages in solving complex problems and physical capital admits capital-skill complementarity in occupation space. The equilibrium features Positive Assortative Matching of worker skills to occupational problem complexity, and the model quantitatively explains the evolution of the occupational wage- and employment structure over the last four decades. The model estimates uncover two distinct periods of technological change. Until around 2000, rising complexity premia were driven by capital-skill complementarity and declining equipment capital prices. Post-2000 patterns reflect supply-side technological change whereby occupations became more efficient in utilizing worker skills for complex problem-solving. Our framework helps unify distinct approaches to studying task automation and task augmentation on the one hand and skill-biased technological change on the other.
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