LABOR MARKET FLEXIBILITY DURING ECONOMIC DOWNTURNS: A MICRODATA-BASED STUDY FROM CPS AND ACS SOURCES

Abstract

Recessions frequently expose structural rigidities in labor employment, wage adjustment and labor mobility, often resulting in continued unemployment and disparate recovery trajectories across demographic groups. This paper investigates labor market flexibility through an interpretive synthesis of worker-level behavioral indicators derived from the Current Population Survey (CPS) data and American Community Survey (ACS) data, without economic estimation or creation of new data. The paper adopts a low-cost policy and solution-oriented perspective and identifies recurring adjustment strategies, i.e., reduction of hours instead of layoffs, sectoral adjustment to low-entry-barrier services, the increase in contingent and gig employment, and gradual geographical mobility during recovery periods, as a solution to stabilizing employment during recessions. The recent slowdowns of the labor market caused by inflation, as well as the COVID-19 shock and post-pandemic restructuring, demonstrate the ability of flexible work and fast skill adjustments to divert scarring in the labor market. Based on these findings, the paper suggests scalable interventions, including short-term work support, micro-credential reskilling, adaptive scheduling, and data-light early warning systems, to policymakers and employers. The findings suggest that the greater capacity to make work more flexible at the micro-behavioral level in advance of future recessions can more effectively support labor resilience than inclusive employment stabilization via broad fiscal stimulus, which can be viewed as a practical way to achieve sustainable and inclusive employment stabilization.