The Impact of the Gig-Economy on Financial Hardship Among Low-Income Families

Problem Definition: New work arrangements coordinated by gig-economy platforms offer workers discretion over their work schedules at the expense of traditional worker protections. We empirically measure the impact of expanding access to gigs on worker welfare, with a focus on low-income families. Academic/Practical Relevance: Understanding the welfare implication of access to gigs informs workers considering working gigs and regulators empowered to protect them. Additionally, firms who rely on this working arrangement may find themselves exposed to increased worker turnover and regulatory intervention if gigs negatively impact worker welfare. Methodology: We analyze a novel data set documenting the financial health of a sample of low-income families. We are interested in the likelihood that a family experiences hardship, meaning they fail to pay their bills on time. We leverage the sequential launch of Uber's UberX service across locations to identify the impact of the associated increase in access to gigs on hardship via a difference-in-differences design. The granularity of our data allows exploration of possible mechanisms for our results. Results: We find that UberX increases hardship among the low-income population, primarily by decreasing overall take-home pay (i.e. annual income less expenses). This is despite a corresponding reduction in income volatility, generally a boon to low-income families who have insufficient savings to weather unexpected dips in earnings. Managerial Implications: These results caution that gigs can be harmful to the most vulnerable members of society, bolstering the position of Uber drivers suing for employee status and governments seeking to regulate the gig economy. Our analysis of mechanisms driving this result offers guidance for effective mechanisms for improving worker financial health in the presence of gigs. Further, we find that gigs offer potential benefits to the low-income population through reduction in income volatility.