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@techreport{LaborHubJ2,
 title = "The Micro and Macro Implications of Multidimensional Skill Uncertainty",
 author = "De Dominicis, Piero",
 institution = "Cornell University ILR School",
 type = "Discussion Paper",
 series = "Labor Hub Discussion Paper Series",
 number = "J2",
 year = "2026",
 month = "October",
 URL = "https://laborhub.ilr.cornell.edu/publications/11/",
 abstract = {What are the consequences of multidimensional skill uncertainty for workers’ wages and aggregate output? I develop and estimate a general equilibrium dynamic Roy model in which workers have imperfect information about their multidimensional skills and accumulate task-specific human capital. Estimated on Portuguese administrative data, the model rationalizes key patterns of occupational mobility, with learning about comparative advantage playing a central role in occupational reallocation among young and poorly matched workers. Removing information frictions raises aggregate output by 5.1%, primarily through better skill allocation across occupations, while generating the largest wage gains early in workers’ careers and among the most mismatched. A feasible information treatment about comparative advantage across tasks recovers about 19% of this output loss. Finally, job transformation induced by Large Language Model adoption raises output while widening the output gap between the imperfect- and perfect-information economies along the transition path and in the new long run.},
}