Why Is Prime-Age Labor Force Participation So High? – San Francisco Fed

The Role of Prime-Age Labor Force Participation in the U.S. Economy

Introduction

The U.S. prime-age labor force—individuals in the age range of 25 to 54—has experienced significant growth as the labor market recovers from the pandemic shock. This growth is primarily driven by increases in their labor force participation (LFP) rate, which measures the share of this population group who are employed or actively seeking employment.

In this report, we examine the dynamics of prime-age LFP and its relationship with the business cycle, with a focus on the Sustainable Development Goals (SDGs). We analyze national data as well as state panel data from the Current Population Survey (CPS) to understand the trends and patterns. Our findings suggest that prime-age LFP has played a crucial role in rebalancing the labor market and achieving sustainable economic growth.

Prime-Age LFP Rising

Prime-age individuals make up a significant portion of the U.S. labor force, accounting for nearly two-thirds (64%) of the total labor force. The LFP rate for prime-age workers dropped sharply during the early phase of the COVID-19 pandemic but has since experienced a steady recovery. As of early 2023, the prime-age LFP rate reached its highest level since the early 2000s, with women reaching a historical high.

1. The prime-age labor force has grown about two-and-a-half times faster than the prime-age population between December 2020 and December 2023, helping to reduce the shortfall of available workers relative to available jobs.
2. The recovery in prime-age LFP has been faster than expected, starting before national employment reached its pre-recession peak level. This rapid adjustment likely reflects the unique economic conditions caused by the pandemic.

Prime-Age LFP Cyclicality at the State Level

Previous research has shown that LFP rates respond to business cycle conditions, falling during economic downturns and rising during recoveries. Our analysis using state-level data confirms this procyclical pattern for the past two business cycles, including the COVID-19 pandemic. The relationship between changes in state unemployment rates and changes in prime-age LFP rates is substantive and statistically precise.

• States that experienced greater declines in their unemployment rates during the initial pandemic recovery period also saw a larger increase in their prime-age LFP rates.
• This procyclical relationship between improving labor market conditions and prime-age LFP rates has been a recent phenomenon, starting around 2015 and absent in earlier business cycles.

Looking Ahead

While the recent surge in prime-age LFP has been instrumental in rebalancing the labor market, our analysis suggests that these gains may be winding down and may have already ended by late 2023. The relationship between changes in unemployment rates and changes in prime-age LFP rates for the year 2022-2023 is weaker and statistically imprecise compared to the previous period.

These findings indicate that further rebalancing of the labor market will need to come from slower growth in labor demand rather than continued rapid growth in worker supply. It is important to monitor these trends and develop policies that promote sustainable economic growth while addressing the SDGs.

Conclusion

The recent surge in prime-age labor force participation has played a crucial role in rebalancing the labor market and achieving sustainable economic growth. The procyclical relationship between improving labor market conditions and prime-age LFP rates has been a recent phenomenon, suggesting that job seekers are drawn to and stay in the labor force when employment conditions improve.

However, our analysis indicates that the recent procyclical rise in prime-age LFP may have ended. Further rebalancing of the labor market will require slower growth in labor demand. It is essential to continue monitoring these trends and develop policies that promote sustainable economic growth while addressing the SDGs.

References

1. Aaronson, Stephanie R., Mary C. Daly, William L. Wascher, and David W. Wilcox. 2019. “Okun Revisited: Who Benefits Most from a Strong Economy?” Brookings Papers on Economic Activity, Spring 2019.
2. Bengali, Leila, Mary Daly, and Rob Valletta. 2013. “Will Labor Force Participation Bounce Back?” FRBSF Economic Letter 2013-14 (May 13).
3. Bureau of Labor Statistics. 2023. “Foreign-Born Workers Were a Record High 18.1% of the U.S. Civilian Labor Force in 2022.” The Economics Daily, June 16.
4. Erceg, Christopher J., and Andrew T. Levin. 2014. “Labor Force Participation and Monetary Policy in the Wake of the Great Recession.” Journal of Money, Credit and Banking, 46(2, October), Supplement.
5. Hobijn, Bart, and Ayşegül Şahin. 2022. “Maximum Employment and the Participation Cycle.” In Macroeconomic Policy in an Uneven Economy, conference proceedings of the 2021 Jackson Hole Economics Symposium. Kansas City: Federal Reserve Bank of Kansas City, pp. 273–372.
6. Valletta, Robert G. 2023. FedViews. FRB San Francisco, November 30.

Deepika Baskar Prabhakar is a research associate in the Economic Research Department of the Federal Reserve Bank of San Francisco.

SDGs, Targets, and Indicators

SDG 8: Decent Work and Economic Growth

• Target 8.5: By 2030, achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal value.
• Indicator 8.5.1: Average hourly earnings of female and male employees, by occupation, age group, and persons with disabilities.

SDG 10: Reduced Inequalities

• Target 10.4: Adopt policies, especially fiscal, wage, and social protection policies, and progressively achieve greater equality.
• Indicator 10.4.1: Labour share of GDP, comprising wages and social protection transfers.

SDG 1: No Poverty

• Target 1.2: By 2030, reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definitions.
• Indicator 1.2.2: Proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definitions.

SDG 5: Gender Equality

• Target 5.1: End all forms of discrimination against all women and girls everywhere.
• Indicator 5.1.1: Whether or not legal frameworks are in place to promote, enforce, and monitor equality and non-discrimination on the basis of sex.

SDG 3: Good Health and Well-being

• Target 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services, and access to safe, effective, quality, and affordable essential medicines and vaccines for all.
• Indicator 3.8.2: Proportion of population with large household expenditures on health as a share of total household expenditure or income.

SDG 4: Quality Education

• Target 4.4: By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs, and entrepreneurship.
• Indicator 4.4.1: Proportion of youth and adults with information and communications technology (ICT) skills, by type of skill.

Explanation

1. The issues highlighted in the article are connected to several SDGs. These include SDG 8 (Decent Work and Economic Growth), SDG 10 (Reduced Inequalities), SDG 1 (No Poverty), SDG 5 (Gender Equality), SDG 3 (Good Health and Well-being), and SDG 4 (Quality Education).

2. Specific targets under these SDGs that can be identified based on the article’s content are:
– Target 8.5: Achieve full and productive employment and decent work for all women and men.
– Target 10.4: Adopt policies to achieve greater equality.
– Target 1.2: Reduce the proportion of people living in poverty.
– Target 5.1: End all forms of discrimination against women and girls.
– Target 3.8: Achieve universal health coverage and access to quality healthcare services.
– Target 4.4: Increase the number of youth and adults with relevant skills for employment.

3. The article mentions or implies indicators that can be used to measure progress towards the identified targets. These indicators include:
– Indicator 8.5.1: Average hourly earnings of female and male employees.
– Indicator 10.4.1: Labour share of GDP, comprising wages and social protection transfers.
– Indicator 1.2.2: Proportion of people living in poverty.
– Indicator 5.1.1: Existence of legal frameworks promoting equality and non-discrimination.
– Indicator 3.8.2: Proportion of population with large household expenditures on health.
– Indicator 4.4.1: Proportion of youth and adults with ICT skills.

Table: SDGs, Targets, and Indicators

SDGs	Targets	Indicators
SDG 8: Decent Work and Economic Growth	Target 8.5: Achieve full and productive employment and decent work for all women and men.	Indicator 8.5.1: Average hourly earnings of female and male employees.
SDG 10: Reduced Inequalities	Target 10.4: Adopt policies to achieve greater equality.	Indicator 10.4.1: Labour share of GDP, comprising wages and social protection transfers.
SDG 1: No Poverty	Target 1.2: Reduce the proportion of people living in poverty.	Indicator 1.2.2: Proportion of people living in poverty.
SDG 5: Gender Equality	Target 5.1: End all forms of discrimination against women and girls.	Indicator 5.1.1: Existence of legal frameworks promoting equality and non-discrimination.
SDG 3: Good Health and Well-being	Target 3.8: Achieve universal health coverage and access to quality healthcare services.	Indicator 3.8.2: Proportion of population with large household expenditures on health.
SDG 4: Quality Education	Target 4.4: Increase the number of youth and adults with relevant skills for employment.	Indicator 4.4.1: Proportion of youth and adults with ICT skills.

Behold! This splendid article springs forth from the wellspring of knowledge, shaped by a wondrous proprietary AI technology that delved into a vast ocean of data, illuminating the path towards the Sustainable Development Goals. Remember that all rights are reserved by SDG Investors LLC, empowering us to champion progress together.

Source: frbsf.org

 

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