By Adam Jones

The Bureau of Labor Statistics (BLS) and Virginia Employment Commission convened a Data Users Conference on February 22, 2017 to discuss new data tools and employment concepts. The Federal Reserve Bank of Richmond hosted the conference, and participants ranged from small social service providers to the Bank’s President, Jeffrey Lacker. On the importance of this conference, BLS Regional Commissioner Sheila Watkins said, “Having access to timely and objective data is more important than ever in understanding our changing economy and making informed business and policy decisions”. The post will discuss structural changes in the labor force and the changing nature of employment in the United States, as well as novel data concepts and tools to analyze and track these trends.

What Does the Data Show?

Employment metrics, specifically the Labor Force Participation Rate (LFPR), can identify symptoms of structural changes in the economy and can provide insight into their underlying causes. LFPR is a simple metric that looks at the percentage of the population that is or is willing to work. The BLS defines the LFPR as, “This measure is the number of people in the labor force as a percentage of the civilian noninstitutional population 16 years old and over. In other words, it is the percentage of the population that is either working or actively seeking work.”[1]

Dr. Michael Horrigan, BLS Associate Commissioner, focused specifically on LFPR and why it has steadily declined since 2000. His first argument is the aging Baby Boomer population. The figure below shows the gradual movement of the Baby Boomer generation through the workforce, culminating in their exit that started in 2009 and is ongoing.

As the Baby Boomer generation exits the labor force, the numerator of the LFPR formula decreases, leading to a smaller participation rate. These changes are considered structural, and as a study by the Federal Reserve Bank of Cleveland points out, “Most prominently, the on-going aging of the baby-boom generation into ages with traditionally lower attachment to the labor force can, by itself account for nearly half of the decline”.[2]

Horrigan then brought up the dramatic decline of youth participation in the workforce, and specifically points out the role school enrollment plays in said decline. With the figures below, he pointed out how the 16-19 year-old population sees a significant rise in school enrollment, with a correlated decline in labor force participation.

Horrigan noted that economists disagree on the empirical causes of such structural shifts. Based on personal experiences and conversations with my peers, I would posit that compulsory high school enrollment and a shift in the cultural importance of attending college are most likely the culprits.

Finally, Horrigan noted that changes in gender dynamics and labor participation are the final explanation of the decline in labor force participation. The BLS has introduced new surveys and data tools to take a deeper look into this important economic transformation.

The Changing Nature of Work

 The conference then pivoted to an in-depth look at the changing nature of work by exploring contingent workers and the “Gig” economy. The BLS defines a contingent worker as, “persons who do not expect their jobs to last or who reported that their jobs are temporary”.[3] One of the main goals of this conference was to explain the methodology behind the BLS’s Contingent Worker Survey (CWS), which included a variety of technical definitions differentiating alternative employment arrangements. These include independent contractors, on-call workers, temporary help agency workers, and workers provided by contract firms.

The main purpose of this section was to discuss changes to the CWS that will be released in May 2017. There were two main changes to this survey: changes to the wording of the 2005 survey, and the addition of questions to address new types of alterative work arrangements. These additional questions focus largely on how the internet and mobile networks have changed the landscape of employment in America. Although, the gig economy is by nature hard to measure, even with a more sophisticated CWS. The labor experience of the gig economy is particularly of interest to BLS and their data users. Hour flexibility, the freedom of not having a boss, and frictional unemployment all play major roles in the demographic profile of the gig economy.

Pay for Success

The Bureau of Labor Statistics and the Virginia Employment Commission provide crucial data for the implementation of Pay for Success (PFS) contracts. For example, PFS projects can provide services for low-income workers in the gig economy, such as transitional job training for those trying to re-enter the labor force or to increase workforce development programs.

Northern Virginia’s SkillSource Group, Inc. is currently developing a PFS project under the direction of Third Sector Capital Partners. Third Sector, a grantee of the Social Innovation Fund’s Pay for Success program, chose SkillSource to be part of a cohort of municipalities across the country that are exploring PFS projects that will utilize the Workforce Innovation and Opportunity Act (WIOA) Youth Program and WIOA pay-for-performance authorities. The project will serve youths aging out of foster care or who have been involved in the juvenile justice system with the goal of improving their education, employment, and criminal justice outcomes.

With the new tools provided by the BLS and CWS, SkillSource and other youth workforce development service providers can analyze the efficacy of arrangements that place youths in temporary employment positions while finishing school or going through job training. With the evolving landscape of employment programs, WIOA service providers should start to look at how contingent jobs can supplement and complement current services. The balance between temporary work and sustainable educational attainment can also start to fill in the lagging demographics of the declining LFPR. Overall, the new tools provided by the BLS can be leveraged to improve workforce development services while increasing the labor force participation rate.

Adam Jones is a Third Year at the University of Virginia studying Economics and Computer Science, and Fellow in the University of Virginia Pay for Success Lab. 

Sources

[1] U.S. Bureau of Labor Statistics. (2015, October 8). How the government measures unemployment. Retrieved from https://www.bls.gov/cps/cps_htgm.htm#definitions

[2] Aaronson, S., Cajner, T., Fallick, B., Galbis-Reig, F., Smith, C., & Wascher, W. (2014). Labor force participation: Recent developments and future prospects (Brookings Papers on Economic Activity, Rep.). Washington, DC: Brookings Institution.

[3] U.S. Bureau of Labor Statistics. (n.d.). Labor force characteristics. Retrieved February 8, 2017, from https://www.bls.gov/cps/lfcharacteristics.htm#contingent