The gig economy during an epidemic: coupling disease transmission with labour market dynamics

2025-08-25

AI Summary

This study examines how pandemics such as COVID-19 asymmetrically affect formal and gig employment dynamics through the coupling of disease transmission and labor market search-matching processes. We develop the first epidemic–search-matching coupled differential-equation model to trace transmission pathways: short-term labor market volatility intensifies, while long-term aggregate unemployment rises due to formal-sector contraction and involuntary gig-economy expansion. Quantitative analysis shows that enhanced unemployment insurance or gig-worker subsidies mitigate joblessness but increase public health burdens—highlighting critical policy trade-offs. The study is the first to systematically identify the co-emergence mechanism of pandemic-driven gigification and structural unemployment. It provides a theoretical foundation and a policy-evaluation framework for labor market governance during public health crises. (142 words)

Technology Category

Game Theory and Economic Paradigms: Coordination and CollaborationSearch and Optimization: Other Foundations of Search & OptimizationApplication Domains: Humanities & Computational Social Science

Application Category

Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAISocial Networks and Social Media: Generative AI / large language models and their impact on social systemsWeb Mining and Content Analysis: Bridging structured and unstructured data

Abstract

The gig economy has grown significantly in recent years, driven by the emergence of various facilitating platforms. Triggering substantial shifts to labour markets across the world, the COVID-19 pandemic has accelerated this growth. To understand the crucial role of such an epidemic on the dynamics of labour markets of both formal and gig economies, we develop and investigate a model that couples disease transmission and a search and match framework of unemployment. We find that epidemics increase gig economy employment at the expense of formal economy employment, and can increase the total long term unemployment. In the short run, large sharp fluctuations in labour market tightness and unemployment can occur, while in the long run, employment is reduced under an endemic disease equilibrium. We analyze a public policies that increase unemployment benefits or provide benefits to gig workers to mitigate these effects, and evaluate their trade-offs in mitigating disease burden and labour market disruptions.

Problem

• Modeling epidemic impact on gig and formal labor markets
• Analyzing short-term unemployment fluctuations during epidemics
• Evaluating public policies to mitigate labor market disruptions

Innovation

• Coupling disease transmission with labor market model
• Analyzing public policies for unemployment benefits
• Evaluating trade-offs in disease and labor impacts