We develop a dynamic microsimulation model to project the labor force and economic dependency ratios in the United States from 2022 to 2060, taking population projections and the large inequalities between population groups of different race/ethnicity and gender into account. We contrast policy scenarios and show the potential impact that closing the gaps in education, health, and participation rates between population subgroups can have on increasing the U.S. labor force. Our baseline projections indicate an increase of the labor force of about 27 million people by 2060, which is mainly caused by population growth. The downstream effects of removing disparities in population health and educational attainment on labor force participation can add about 10% (+2.6 million people) to our baseline projections. The potential effects of closing gaps between genders and between minority groups and the non-Hispanic White population, however, are much larger if we assume the equalization of participation rates for individuals with similar characteristics. Closing gender gaps within ethno-racial groups, for instance, can add 9.9 to 14.3 million people to the labor force. Overall, reducing disparities in labor force participation rates has the potential to more than compensate the effects of demographic aging on the economic dependency ratio.
Authors
- Acknowledgements & Disclosure
- The research reported herein was performed pursuant to grant RDR18000003 from the U.S. Social Security Administration (SSA) funded as part of the Retirement and Disability Research Consortium. The opinions and conclusions expressed are solely those of the author(s) and do not represent the opinions or policy of SSA, any agency of the Federal Government, or NBER. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of the contents of this report. Reference herein to any specific commercial product, process or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply endorsement, recommendation or favoring by the United States Government or any agency thereof.
- DOI
- https://doi.org/10.3386/w32590
- Published in
- United States of America
Table of Contents
- Introduction 3
- Background 4
- Method 6
- Results 9
- Baseline 9
- Scenarios 11
- 4.2.1. Scenario description 12
- Scenarios S1 and S1b: Convergence by gender within race/ethnicity subgroups, for given personal characteristics 12
- Scenario S2: Convergence by race/ethnicity, for given for given personal characteristics 13
- Scenario S3: Convergence of education and health status 13
- Scenario S4: combining S2 and S3 13
- 4.2.2. Scenario results 14
- Summary and discussion 18
- Appendix - Tables and Figures 21
- Literature 28
