Gender pay gaps and moving up the ladder at work

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Lots of data and diagnostics from middle and low income countries establish a range of gender gaps in labor outcomes – among them lower force participation for women and segregation in work in terms of formality, occupation, and sector). And many studies look at the ranges of causes of these gaps, and the interventions that might shrink them (Buvinic and O’Donnell review published two months ago is among the latest summaries of the evidence). Adding to what we know about gender gaps at work, in their study of wages in garment factories in Bangladesh, Menzel and Woodruff unpack the path of wage gaps. In a setting where men and women start at the same pay-grade when they enter these jobs, Menzel and Woodruff explore what underlies a pay gap that grows to 8 percent on average.

 

Two aspects to their work drew my attention. To be sure, in most low-income countries, there are not many large factory employers (in this study there are on average over 2,000 employees per factory). Of course, we need to continue to study income gaps for men and women in the dominant forms of work -- smallholder farming or non-farm household enterprises. But at the same time, there is a lively discussion about the scope for growing manufacturing (that is labor intensive) as a development pathway for countries. To quote the authors, “Export manufacturing is viewed as one of the few development strategies that has been successful in generating sustained economic growth.” And there is a growing body of research on what these opportunities mean for women especially to which this paper adds. Research shows that garment jobs specifically can, among other outcomes, give women a greater say in household decision-making, increase women’s savings, delay marriage and childbearing, and increase education outcomes for girls (that these job prospects motivate parents to send girls to school for longer). On the other hand, such jobs may come with greater risks, including health or sexual harassment, not to mention other risks like factory fires or collapse (notable those in 2012 and 2013 in Bangladesh). NB: I am not citing any specific papers – you can find some references in Menzel and Woodruff’s paper.

 

My second interest in this paper was their use of administrative HR data from 70 export-oriented garment manufacturers – rather than the more typical household/worker survey in low-income contexts. They use monthly payroll records for shop-floor workers, with a median factory having 11 consecutive months of data. They combine these admin data with surveys of workers to decompose the pathway of wage gaps between wage growth within factories and that from moving across factories. The admin data is not without its challenges. The sex of the worker has to be inferred from names. In some factories, worker IDs are sometimes recycled when one worker leaves or new IDs are assigned when a worker is promoted. And those promoted to supervisor drop from the data (which could be incorrectly interpreted as leaving the factory). They augment the admin data with skills assessment data (to control for productivity) and a survey of workers (for a subset of grade levels and factories – taking advantage of another project on-going, which made me curious about that other work…). The survey of workers is used to examine how much of wage gap growth stems from movements between factories, which they can’t asses using just the admin data. How they use the data and the various caveats are explained in the paper.

 

As mentioned above, they find a 8 percent earnings gap between men and women (monthly base pay is near $70 at the time of the data for a 6 day work week). Controlling for grade (five grades ranging from entry-level helper to highly skilled operators), the gender gap in earnings falls below 2 percent. They describe the wage gap in these factories as a “grade gap”. Men in the admin data are twice as likely to be in the highest grade position than women, and the reverse is true for the lowest grade jobs. Controlling for average absenteeism or overtime hours of workers does not change these results. But skills differences do explain up to half of the gender gap.

 

The growth of wage gaps between men and women start early in their factory careers because men move more quickly out of entry-level positions. The wage growth for men is split between internal promotion and moving to another factory for a promotion. At later stages of workers’ careers, when almost all wage growth is within factory, wage growth rates do not differ between women and men.

 

Is the grade gap driven by a skills gap? Partly. After controlling for skills the, gender gap in internal promotion rates drops in half (of note, only one of the four skills measures is statistically significant at predicting promotion). In terms of training opportunities for workers, the survey data does not reveal a gap between men and women.

 

Is the grade gap driven by marriage, children, or domestic roles? Not so much. Among women, wage levels, wage growth, and the rate of movement between factories do not differ among married female workers, those with children, and those who are unmarried or childless women. On the other hand, marriage seems to boost men’s outcomes (as found in high income countries): married men have higher wage growth and rates of movements across factories than unmarried men.

 

Combined, Menzel and Woodruff posit that their results point to either a higher cost of investing in skills for women than men or lower expected returns to skills. While they don’t address the former, for the latter they do find that women have lower returns at least for one of their skills measure, which also is the one most associated with promotions in factories. Added to this is the fact they note that women have largely been excluded from high level positions in these factories which might lead to less investment in skills by women.

 

There is a lot of good stuff in this paper … so it is disappointing to read this last sentence: “the data point to higher levels of ambition by men as the main cause of the wage gap in this specific context.” And likewise the last sentence of the abstract which states that the gaps “appear to arise mainly from career concerns.” Is this really a problem of women not “leaning in”? I think their work is far from showing that lower ambition or career concerns of women is the main cause of earnings gaps (driven by promotion gaps). There are other potential explanations. Not least is the quite open bias towards female workers among employers in the region which is readily expressed: firm managers in Bangladesh are not shy about stating that hiring women is constrained because women will “disrupt the working environment”.

Authors

Kathleen Beegle

Lead Economist with the World Bank Gender Group

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