Understanding Income Volatility and the Role of the Online Platform Economy

Even as the U.S. economy continues to create thousands of jobs each month, there are insufficient data to examine the income volatility workers are experiencing on a regular basis. We know that individuals experience high levels of income and spending volatility. Yet, we need to more clearly understand the root causes of this volatility in order to arm decision makers with the data to better inform policy interventions that successfully address this pervasive issue. What variations in income do individuals experience month-to-month? Who is being impacted the most by changes in their earnings? What are they doing to supplement or substitute these shifts in income? And, how heavily are they relying on new ways to work to mitigate this volatility?

The newest report from the JPMorgan Chase Institute, "Paychecks, Paydays, and the Online Platform Economy: Big Data on Income Volatility," answers these questions by analyzing an anonymized sample of 1 million Chase customers in an effort to determine the key sources of income volatility and provide the most in-depth look to date into the size and growth of the Online Platform Economy.

By examining consumers" take home pay, the Institute explores their level of income volatility and, for the first time, looks at the growing usage of online platforms, such as Uber, Etsy and Airbnb, as a potential resource to mitigate fluctuations in income.

How Paychecks and Paydays Contribute to Income Volatility

Building on our first report, Weathering Volatility, we found that income volatility is a present and real phenomenon for individuals across the income spectrum:

Finding One: Income volatility, prevalent across the board, was most marked among the young, those in the bottom income quintile, and those living in the West.

Finding Two: Median-income individuals experienced nearly $500 in labor income fluctuations across months, with spikes in earnings larger but less frequent than dips. For median-income individuals, this volatility translated into an average $475 change, including changes greater than $903 one quarter of the time.

Finding Three: Most of the month-to-month volatility in take-home pay (86 percent) came from variation in pay within distinct jobs. Within-job volatility in earnings stems primarily from: variation in paycheck amounts (72%) and pay frequency (28%):

• Variation in paycheck amounts: Sixty-one percent of individuals experienced an end-of-year pay spike some time between December and March that resulted in a 30 percent increase in pay; and 61 percent of individuals experienced other idiosyncratic fluctuations in income from their job that resulted in absolute changes in labor income of approximately 27 percent in a positive or negative direction.
• Changes in pay frequencies: Eighty percent of individuals experience the "five-Friday effect".
  • Fifty-five percent of individuals had a job that pays every two weeks and they experienced a 26 percent increase in pay in months with three paychecks.
  • Twenty-five percent of individuals had a job that pays weekly; they experienced a 14 percent increase in pay in months with five paychecks.

Finding Four: Almost four in 10 individuals experienced a job transition in a given year, contributing 14 percent of the month-to-month volatility in labor income.

A new way to earn: the Online Platform Economy

When it comes to managing persistent levels of income volatility, a subset of the population is turning to the Online Platform Economy. The ease and quickness with which a person can earn through these platforms are making it a viable tool for substituting and supplementing their income.

The Institute analyzed anonymized data from more than 260,000 participants who earned income from one of 30 distinct platforms within the Online Platform Economy from October 2012 to September 2015. We distinguished the Online Platform Economy into two distinct segments: labor platforms, such as Uber and TaskRabbit, which allow individuals to perform discrete tasks or projects as well as capital platforms, such as eBay or Airbnb, which allow individuals to rent assets or sell goods peer-to-peer.

Here's what we learned about this new way to work:

Finding Five: Although 1 percent of adults earned income from the Online Platform Economy in a given month, more than 4 percent participated over the three-year period.

• The monthly participation rate increased 10-fold over the three year-period, and the cumulative participation rate increased 47-fold over the three years. In any given month, 0.4 percent of adults (40 percent of all platform participants) received earnings from labor platforms and 0.6 percent of adults (62 percent of all platform participants) received income from capital platforms. Thus, a total of 2.5 million adults are participating in the Online Platform Economy in the U.S.
• Among all participants over the three years, 21 percent participated in labor platforms, 78 percent participated in capital platforms, and 2 percent participated in both.
• Yet, after the first month of platform participation, participation is quite sporadic. For labor platforms, individuals earned money in only 56 percent of subsequent months; for capital platforms, the number drops to 32 percent.
• Most individuals only earn from one platform, though those who use labor platforms are more likely (14%) to use multiple platforms, than capital platform participants (just 1 percent use multiple platforms).

Finding Six: The Online Platform Economy was a secondary source of income, and participants did not increase their reliance on platform earnings over time.

• Average monthly earnings were $533 for labor platforms, representing 33 percent of participants" total monthly income. For capital platforms, average earnings were $314, representing 20 percent of total monthly income.
• Reliance on platform earnings remained stable over time in terms of both the fractions of months that participants are active and the fraction of total income earned on platforms in active months.
  • As of September 2015, 25 percent of labor platform participants relied on platform income for more than 75 percent of their total income; for capital platforms, only 17 percent of participants relied on platform income for more than 75 percent of total income.

Finding Seven: Earnings from labor platforms offset dips in non-platform income, but earnings from capital platforms only supplemented non-platform income.

• In aggregate, labor platform earnings appeared to largely substitute for a 14 percent shortfall in non-platform income in months with platform earnings. In months with platform earnings, it contributed an additional 15 percent of income, increasing total income by less than 1 percent.
• Capital platform earnings tended to supplement rather than substitute for other income. Non-platform earnings tended to be less than 1 percent lower in months with platform earnings, and capital platform earnings contributed another 7 percent, raising income by 7 percent.

With this report, we can begin to build a deeper understanding of our labor market, how it's changing and how those changes are affecting individuals" income. With timely, relevant data, smarter policy decisions can be made that keep pace with changes to our economy and the types of jobs being created. This is the mission of the JPMorgan Chase Institute. We will continue to tap into our unprecedented data set to dig into the turmoil in our labor market and provide decision makers with the facts and analyses to increase economic opportunity by reducing income volatility.

Diana Farrell is the founding President and Chief Executive Officer of the JPMorgan Chase Institute. Previously, Diana was the Global Head of the McKinsey Center for Government and the McKinsey Global Institute. She served in the White House as Deputy Director of the National Economic Council and Deputy Assistant to the President on Economic Policy.