This paper quantifies the effects of discrepancies between local supply and demand for skills on wages, employment, and mobility rates of laid-off workers. I propose the concept of local skill remoteness to capture the degree of dissimilarity between the skill profiles of workers and jobs in a local labor market. I implement a measure of local skill remoteness at the occupation-city level, and find that higher skill remoteness at layoff is associated with lower re-employment rates and lower wages upon re-employment. Earnings differences between the top and bottom skill remoteness quartiles amount to a loss of 15% of the median worker’s annual income and persist for at least two years. Skill-remote workers also have a higher probability of changing occupation, a lower probability of being re-employed at jobs with similar skill profiles, a higher propensity to migrate to another city and, conditional on migration, a higher likelihood of becoming less skill-remote. Motivated by this evidence, I develop a search-and-matching model with two-sided heterogeneity that provides a natural framework to interpret my skill remoteness measure. I use a calibrated version of the model to show that subsidies to on-the-job training lower the average skill remoteness of unemployed workers, thus the aggregate unemployment rate. The marginal benefit of such a policy is increasing in the level of unemployment.
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|Published - Jan 2017