Essays on labor market dynamics
Author(s)Patterson, Christina Hyde.
Massachusetts Institute of Technology. Department of Economics.
Daron Acemoglu, David Autor and Heidi Williams.
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This thesis consists of three chapters on labor market dynamics. In the first chapter, I show empirically that the unequal incidence of recessions is a core channel through which aggregate shocks are amplified. I show that the aggregate marginal propensity to consume (MPC) is larger when income shocks disproportionately hit high-MPC individuals, and I define the Matching Multiplier as the increase in the output multiplier originating from the matching of workers to jobs with different income elasticities - a greater matching multiplier translates into more powerful amplification in a range of business cycle models. Using administrative data from the United States, I document that the earnings of individuals with a higher marginal propensity to consume are more exposed to recessions.I show that this covariance between worker MPCs and the elasticity of their earnings to GDP is large enough to increase shock amplification by 40 percent over a benchmark in which all workers are equally exposed. Using local labor market variation, I validate this amplification mechanism by showing that areas with higher matching multipliers experience larger employment fluctuations over the business cycle. Lastly, I derive a generalization of the matching multiplier in an incomplete markets model and show numerically that this mechanism is quantitatively similar within this structural framework. In the second chapter, joint with David Autor, David Dorn, Lawrence Katz, and John Van Reenen, we explore the well-documented fall of labor's share of GDP in the United States and many other countries. Existing empirical assessments typically rely on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S.Economic Census since 1982 and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of "superstar firms." If globalization or technological changes advantage the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms. Since these firms have high markups and a low labor share of firm value-added and sales, this depresses the aggregate labor share.We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all firms; (iv) the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity and innovation; (vi) the aggregate markup will rise more than the unweighted firm markup; and (vii) these patterns should be observed not only in U.S. firms, but also internationally. We find support for all of these predictions. In the third chapter, I explore how the distribution of tasks across industries affects labor market responses to shocks.I present a model in which task-level wages connect industries employing the same tasks, meaning that the distribution of tasks across industries insures some workers against shocks and alters their labor market experiences. Workers trained in more dispersed tasks (e.g. accountants) face less unemployment risk from industry-specific shocks than workers who do tasks that are concentrated in few industries (e.g. petroleum engineers). Using industry and regional data, I show empirical evidence that supports the model's predictions - industries that employ more specialized labor contract less in response to demand shocks than industries with less specialized labor. JEL Classifications: E21, J23, D33
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2019Cataloged from PDF version of thesis.Includes bibliographical references.
DepartmentMassachusetts Institute of Technology. Department of Economics
Massachusetts Institute of Technology