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Divergence in Post-Pandemic Earnings Growth: Evidence from Micro Data

by Do Lee , Sophia Chen

📖 The Scoop

We use a comprehensive employer-employee dataset to examine post-pandemic worker earnings in the US. Our findings reveal that earnings grew faster in counties that were less severely impacted at the onset of the pandemic. This divergence in growth was both substantial and persistent, particularly for lower-paid and nonmanagerial workers, as well as for those in smaller firms. Both wage increases and additional hours contributed to this earnings growth. This evidence aligns with a job-ladder framework, where labor market competition leads to a dispersion of earnings across counties but compresses earnings among workers in counties with strong labor markets. Our findings provide a microfoundation for the wage Phillips curve and have direct implications for stabilization policies.

Genre: No Category (fancy, right?)

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