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How the sharing economy influences American households

By Tingting Nian & Vijay Gurbaxani
Posted on May 04, 2020

In the past decade, the sharing economy has grown into a significant phenomenon, transforming many industries, especially transportation and hospitality. It is based on a peer-to-peer economic model in which people share underutilized assets such as skills, space, cars, tools and other goods.1 The implications of the sharing economy have been subjected to intense scrutiny.

Given the pros and cons, a conclusion on the net effect of the sharing economy is anything but clear. We think it is an issue worth studying with more rigorous data collection and analysis. That is what we do with our TFI research project, in which we examine the effects of the sharing economy on U.S. households.

Uber: a game changing example

Take Uber, the ride-hailing company with a mobile app that helps efficiently match a network of vetted drivers with consumers in need of a taxi ride. Uber offers an affordable and convenient alternative to taxi cabs or public transit. By the end of 2015, over 460,000 U.S. drivers actively partnered with Uber (Hall and Krueger 2018). By July 2019, Uber announced that it had completed 10 billion trips worldwide.

With its scale and size, Uber competes with traditional businesses such as taxi cabs and limousines. This has inevitably brought about heated debate on the costs and benefits of the sharing economy. On the one hand, it creates new financial opportunities for tens of thousands of workers with a low entry barrier; drivers simply need to pass a background check and have a valid driving license. It also offers lower prices and greater convenience for consumers. On the other hand, some critiques suggest that it may displace traditionally secure jobs and threaten the livelihood of traditional taxi drivers (e.g. the price of owning a taxi cab medallion in New York City has dropped from $1 million in 2015 to less than $200,000 in 2019).

Anecdotal evidence suggests that the majority of drivers work part-time, and that the earnings from partnering with Uber (or Lyft) help cover food, housing, medical care and other primary expenses. These earnings can be used to smooth households' income fluctuations to help them get through difficult financial times. Therefore, one impact we expect to see is a reduction in households' chances of building up debts.

“Uber's entry into the market is expected to mostly affect those with irregular or instable income streams”

The impact of the sharing economy

In this research project, we focus on consumers’ credit default rates in particular. We collected and combined various U.S. datasets from multiple sources, for the period between January 2011 and December 2015. These sources included the Federal Judicial Center, the Bureau of Labor Statistics, the US Census Bureau, and major news outlets.

To analyse the causal relationship between the sharing economy platform and the local household financial decisions, we used a difference-in-differences method combined with propensity score matching, exploiting the geographical and temporal variations in Uber's entry. After matching a county in which Uber has started offering services to another county where Uber has not yet started its operation - based on a variety of observed characteristics - we constructed two comparable groups of counties with similar characteristics but with different Uber entry timings into their markets.

By comparing the changes in consumers’ default rates before and after Uber entry between these two groups, we are able to separate out the changes in consumers’ default rates that are attributable to Uber’s entry.

Preliminary results

We discovered that Uber's entry into the market leads to a decline in consumer default rates in a local area, resulting from access to a new and flexible employment opportunity and the enhanced ability to smooth income fluctuations. We also examined the differential effects of Uber’s entry based on income levels, and found that Uber’s entry benefited lower income areas more than higher income ones.

We also found that the effect of Uber’s entry on Chapter 7 personal bankruptcies is greater than that on Chapter 13 personal bankruptcies2, which is consistent with our intuition that Uber’s entry will mostly affect those with irregular or instable income streams. In addition, we do not find any significant changes in the business bankruptcy filings in regions where Uber has started offering services, which further validates the hypothesis that Uber’s operation in a local market is less likely to affect business’ profitability.

We also analysed which factors influenced Uber to enter or avoid a specific U.S. region. So far, we found that three main factors seem to explain what regions Uber enters earlier: regions with 1) a larger population, 2) higher personal income per capita, and 3) lower unemployment rate. These three characteristics are all positively correlated with Uber’s entry probability.

Up next: the economic impact of other sharing economy platforms (think Airbnb)

With the growth in the number and scope of sharing economy platforms, there is a pressing need to identify the costs and societal benefits of these companies. Our current study offers some initial evidence on the impact of Uber’s entry on consumers’ chances of falling into credit defaults. Our next step is to examine the economic impact of some other sharing economy platforms, such as Airbnb.

We will also examine different facets of the societal effects of the sharing economy in our future study, including the impacts of the sharing economy on consumption patterns. Our ultimate goal is to offer policy makers some valuable insights on the economic and societal effects of the sharing economy, which may inform new policy and regulation on the sharing economy.


Tingting Nian is Assistant Professor of Information Systems at the Paul Merage School of Business, University of California. Vijay Gurbaxani is Professor of Information Systems and Computer Science, and Director of the Center for Digital Transformation at the Paul Merage School of Business.

Footnotes

  1. The Economics and Statistics Administration of the U.S. Commerce Department defines the sharing economy, identifying the following four characteristics: 1) use of information technology systems, typically available via web-based platforms such as mobile apps on Internet-enabled devices to facilitate peer-to-peer transactions; 2) use of user-based rating systems for quality control; 3) provision of flexibility for workers in determining their working hours on these matching platforms; and 4) reliance on workers to provide the tools and assets necessary to provide a service (Telles, 2016).
  2. Under Chapter 7, in exchange for discharge of unsecured debts such as credit card debt, installment loans, medical bills, and damage claims, the bankruptcy trustee liquidates all the assets that are not exempt from collection and uses the proceeds to repay creditors. In Chapter 13 bankruptcy, debtors do not give up any assets in bankruptcy, but file a repayment plan with the appointed bankruptcy authority to pay back a portion of their debts from their future earnings.

References

  • Hall, Jonathan V., and Alan B. Krueger. "An analysis of the labor market for Uber’s driver-partners in the United States." ILR Review 71.3 (2018): 705-732.
  • Telles, Rudy. Digital matching firms: A new definition in the" sharing economy" space. US Department of Commerce, Economics and Statistics Administration, Office of the Chief Economist, 2016.