Copyright Page
© 2022 International Monetary Fund
WP/22/42
IMF Working Paper
Asia and Pacific Department
Are Low-Skill Women Being Left Behind? Labor Market Evidence from the UK
Prepared by Era Dabla-Norris, Carlo Pizzinelli, and Jay Rappaport1
Authorized for distribution by Era Dabla-Norris
February 2022
IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
ABSTRACT: Labor markets in the UK have been characterized by markedly widening wage inequality for low-skill (non-college) women, a trend that predates the pandemic. We examine the contribution of job polarization to this trend by estimating age, period, and cohort effects for the likelihood of employment in different occupations and the wages earned therein over 2001–2019. For recent generations of women, cohort effects indicate a higher likelihood of employment in low-paying manual jobs relative to high-paying abstract jobs. However, cohort effects also underpin falling wages for post-1980 cohorts across all occupations. We find that falling returns to labor rather than job polarization has been a key driver of rising inter-age wage inequality among low-skill females. Wage-level cohort effects underpin a nearly 10 percent fall in expected lifetime earnings for low-skill women born in 1990 relative to those born in 1970.
| JEL Classification Numbers: | J21, J24, J31 |
| Keywords: | Job polarization, Occupational choice, Life-cycle, Cohorts, Inter-generational inequality |
| Author’s E-Mail Address: | edablanorris@imf.org; cpizzinelli@imf.org; jaywrappaport@gmail.com |
| JEL Classification Numbers: | J21, J24, J31 |
| Keywords: | Job polarization, Occupational choice, Life-cycle, Cohorts, Inter-generational inequality |
| Author’s E-Mail Address: | edablanorris@imf.org; cpizzinelli@imf.org; jaywrappaport@gmail.com |
Contents
1 Introduction
2 Relation to the literature
3 The data
4 Occupational shifts by cohorts
5 Empirical strategy
6 Results for employment propensities and wages
7 Decomposition exercises
8 Possible drivers of cohort effects
9 Conclusion
A Additional Tables and Figures
A.1 Sensitivity analysis of baseline regression
B Data appendix
B.1 Occupational categorization measures
B.2 Alternative occupational categorization
C Alternative estimation approaches
C.1 Discussion of alternative estimation approaches of age, period, and cohort effects
C.2 Results
We thank Cristian Alonso, Vitor Gaspar, Klaus Hellwig, Rachel Ngai, Myrto Oikonomou, and participants in various IMF seminars for their comments.