« Back to Results

The Gig Economy

Paper Session

Saturday, Jan. 7, 2023 8:00 AM - 10:00 AM (CST)

Hilton Riverside, Grand Salon C Sec 13 & 16
Hosted By: American Economic Association
  • Chair: Ron Jarmin, U.S. Census Bureau

Joining the Gig Workforce: A (Potentially) One-Way Trip with An Expensive Return Ticket

Kristina Sargent
,
Middlebury College
Jessie (Jue) Wang 
,
RAND Corporation

Abstract

We propose a dynamic search and matching model to explore the labor market implications of a booming gig economy. The economy has conventional and gig sectors, with workers searching in both. Some workers never consider gig employment, and others do under certain conditions. Workers are allowed to work in both sectors at the same time if they prefer. Workers match with gig positions with probability one but face more frictions in gaining employment in the conventional sector afterward. As a result, gig work plays an important role as an alternative to collecting unemployment insurance benefits for workers, and the gig sector absorbs labor market slack from the conventional sector. We show that the barriers to return to the conventional market from the gig sector led to an increased proportion of gig workers over time. By comparing the implications of the model under various levels of exposure to the gig economy, we explore the nature of the sector and the opportunities and consequences that come with it. The benchmark model provides insights into the rise of the gig economy, highlighting its impact on low-wage workers and the segmentation of the labor markets. Counterfactual exercises reveal the sensitivity of the sector to labor market conditions and policy interventions.

The Labor Supply of Gig Jobs and the Response to a Minimum Wage Increase

Kathryn Edwards
,
RAND Corporation
Hilary Wething
,
Pennsylvania State University

Abstract

The majority of workers who participate in the gig economy have a primary job. This paper examines the prevalence and pattern of holding a gig job over a 25-year period: how frequently the gig jobs are held, tenure of gig jobs, how much of total earnings is derived from gig work, and the demographics and economic status of workers most likely to hold them. We then examine numerous state and federal minimum wages increases to determine to what extent higher earnings on a primary, or employer-based job, reduces the incidence of gig work.

New Gig Work or Changes in Reporting? Understanding Self-Employment Trends in Tax Data

Andrew Garin
,
University of Illinois-Urbana-Champaign
Emilie Jackson
,
Michigan State University
Dmitri Koustas
,
University of Chicago

Abstract

Rising self-employment rates in U.S. tax data that are absent in survey data have led to speculation that tax records capture a rise in new "gig" work that surveys miss. Drawing on the universe of IRS tax returns, we show that trends in firm-reported payments to "gig" and other contract workers do not explain the rise in self-employment reported to the IRS; rather, that increase is driven by self-reported earnings of individuals in the EITC phase-in range. We isolate pure reporting responses from real labor supply responses by examining births of workers' first children around an end-of-year cutoff for credit eligibility that creates exogenous variation in tax rates at the end of the tax year after labor supply decisions are already sunk. We find that exposing workers with sunk labor supply to negative marginal tax rates results in large increases in their propensity to self-report self-employment - only a small minority of which leads to bunching at kink-points. Consistent with pure strategic reporting behavior, we find no impact on reporting among taxpayers with no incentive to report additional income and no effects on firm-reported payments of any kind. Moreover, we find these reporting responses have grown over time as knowledge of tax incentives has become widespread. Quantitatively, our results suggest that as much as 59 percent of the growth in self-employment rates, and all counter-cyclicality, can be attributed to changes in reporting behavior that are independent of changes in the nature of work. Our findings suggest caution is warranted before deferring to administrative data over survey data when measuring labor market trends.

Reconciling Administrative Data Sources on Self-Employment Activity: A Growing Gap Between Schedule C and SE Filers 

Katharine Abraham
,
University of Maryland
John Haltiwanger
,
University of Maryland
Claire Hou
,
Congressional Budget Office
Kristin   Sandusky
,
U.S. Census Bureau
James Spletzer
,
U.S. Census Bureau

Abstract

Recent research has emphasized the differences between administrative and survey data on the growth of self-employment activity. Household survey data exhibit little if any growth in the self-employment share of employment in the post 2000 period. In contrast, administrative data exhibit a pronounced increase. Ongoing research has explored alternative explanations of this growing gap ranging from growth in the gig economy involving changes in the nature of self-employment to changes in the incentives for households to report self-employment income. In this paper, we consider a second puzzle. Since 2013 there has been a growing gap in self-employment trends across two key administrative data sources: Schedule SE and Schedule C. Schedule C must be filed for any sole proprietorship with positive gross receipts even if net earnings (taking into account expenses) is small or negative. In contrast, a Schedule SE is required only if the Schedule SE net income is at least $433. These differences in filing requirements yielded about a half a percentage point gap in the self-employment rate measured using Schedule C vs Schedule SE during the 2008-13 period. That gap more than tripled to about a 1.5 percentage point gap by 2018. This increase is accounted for by substantial increases in the self-employment rate based on Schedule C filings from 2013-18 while the self-employment rate using Schedule SE was flat over this period. We document and explore the reasons for this increasing gap. Our findings are important for understanding the extent of growth in the gig economy. For example, we find that NAICS industry 4853 (Taxi and Limousine Services), the industry in which self-employed individuals working with online ridesharing platforms will report their incomes, dominates the increase in Schedule C filings over this period, but not all of these individuals are required to file a Schedule SE. 

Discussant(s)
James Spletzer
,
U.S. Census Bureau
Jesse Rothstein
,
University of California-Los Angeles
JEL Classifications
  • J2 - Demand and Supply of Labor
  • J4 - Particular Labor Markets