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New Research Sheds Light on How U.S. Labor Market is Evolving

Although the American labor market is evolving, a scarcity of data has often made it difficult to know exactly what is going on and what to make of it. Having a better understanding of how the nature of work is changing would help individuals prepare for their role in it. It would also help policymakers pass appropriate laws that promote competition, protect workers, and encourage investment in both human and physical capital.

One of the leading academics in this field has been Alan Krueger, former chairman of President Obama’s Council of Economic Advisers. Dr. Krueger has coauthored two recent studies that provide policymakers with a better understanding of how labor markets are evolving on both the macro and micro levels.

Our understanding of macro changes to the labor market is limited by the fact that, because of funding limitations, the Bureau of Labor Statistics (BLS) last conducted its Contingent Worker Survey, which gathers data on people who have contingent and alternative work arrangements, in 2005. In a recent paper, Lawrence Katz, a Harvard economist, and Dr. Krueger included a version of this survey in the RAND American Life Panel, thereby updating the data to November 2015. The survey contains several interesting findings.

First, the percentage of workers undertaking alternative work arrangements (defined to include temporary help, on-call, contract, and independent contractor work) increased from 10.1 percent of the total U.S. workforce in 2005 to 15.8 percent in 2015. Independent contractors also rose from 6.9 percent in 2005 to 8.4 percent in 2015. Although independent contracting continues to be the largest category of alternative work, the other categories have more than doubled, rising from 3.2 to 7.3 percent of the workforce. The largest increase was for contract firms, which rose from 0.6 percent to 3.1 percent of the workforce. The finding of a rise in self-employment contradicts data from the BLS Current Population Survey, which shows a decline over the last two decades. The authors speculate this may be due to a growth in self-employment in secondary jobs as well as under reporting of self-employment for main jobs. The contradictory data suggest that we need to know more about how workers earn and report income earned outside traditional employment.

Second, despite all of the attention they have been getting, Internet job matching platforms such as Uber and TaskRabbit are still used by only a small fraction of the workforce. Katz and Krueger estimate that workers who provide either goods or services through online intermediaries make up only 0.5 percent of the workforce. In the survey, about twice that number of workers selling goods or services reported that they still rely on offline intermediaries to find customers. So Internet platforms selling both goods and services still have a way to go even when considering just those workers who already sell directly to consumers.

Third, the increase in alternative work arrangements does not just affect low-income workers. In fact the incidence of alternative work is greater among workers with higher wages. This is largely due to independent contractors. High-paid workers, like business consultants, editors, graphic artists, and others are also more likely to have their work contracted out than those on the lower end. However, independent contracting has recently grown faster among low-income workers. Temporary help and on-call jobs are more prevalent among low-income workers.

Finally, the authors point out that the increase in alternative work arrangements exceeds the net employment growth in the U.S. economy since 2005. The authors speculate that an increase in workers’ demand for flexible work hours, combined with technological changes that make it easier to monitor alternative work arrangements, may have driven much of the change. In particular, broadband Internet access, coupled with an array of new apps (like video telephony, cloud computing, and the like) make it much easier to work remotely, whether as a contractor or regular employee.

On the micro level, a paper by economist Judd Cramer and Dr. Krueger looks at how Uber was able to disrupt the traditional taxi business. The short answer is that Uber’s drivers are much more efficient while working, both in terms of hours and miles driven. This in turn allows them to make more money, even if they charge less than taxis for individual fares.

Uber’s use of the Internet to interact with both drivers and passengers creates a large volume of electronic data, which the authors were able to analyze. Unfortunately, they were only able to get roughly equivalent data for taxi cabs in five cities: Boston, Los Angeles, New York, San Francisco, and Seattle. The authors looked at both the percentage of time that drivers spent with a rider in their car and the percentage of total miles driven with a rider in the car. By both measures, Uber drivers tended to be 30 to 50 percent more efficient than taxi cabs.

The authors attribute this difference to four factors. First, Uber’s Internet platform does a better job of matching drivers to riders. One can frequently see this when going to an airport or hotel where there are often extremely long lines of cabs sitting waiting, sometimes for over an hour, to get a fare. Second, Uber operates at a larger scale than most taxi companies, enabling it to shorten the distance that a driver has to go in order to find a rider. Third, many taxi regulations artificially restrict where cabs can operate. Finally, the flexibility Uber gives drivers and its surge pricing allow it to match supply to demand more closely than cab companies. These factors also explain why Uber riders generally have shorter waits before a car comes.

U.S. labor markets will continue to evolve. In most instances, this evolution will benefit companies, workers, and consumers. As long as markets remain competitive, the ready availability of alternatives will ensure that no party can be taken advantage of. But in order for public policy to respond wisely to these changes, accurate analysis of data will continue to be crucial.  This means among other things reversing funding cuts to the BLS.

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