Closing Occupational Gender Gaps
The Global Gender Gap Index holds more than a decade of time series data on the evolution of the global gender gap. At an indicator level, three of the Index’s data points, in particular, put into context the current stagnation of progress towards closing the economic gender gap. First, global labour force participation has been in decline globally for both men and women—but this decline has been particularly accentuated for women. Second, in absolute terms, earned incomes of both men and women have been increasing, but this upward trend has been steeper for men than for women, suggesting that the growth in prosperity is not equitably distributed along gender lines. Third, women’s share among senior positions both in the public sector and in business is not trending towards equal representation, standing at less than half way towards parity. Currently, only 22% of individuals holding senior managerial positions are women (see Figure 12).
These trends observed by the Global Gender Gap Index over the past years point to a continued under-use of the ever-increasing numbers of educated women (see Figure 13 below). While much of this imbalance is explained by the discrepancy in caregiving and unpaid work, institutional and policy inertia, outdated organizational structures and discrimination, one additional explanatory factor is the skills differentials in the types of degrees women and men seek out in their education. Do these choices prepare women adequately for prospering in the labour market to the same extent as their male counterparts? In exploring this question, a number of recent studies—and controversies—have focused on the question of potential behavioural and cognitive differences between men and women. However, rigorous research has cast doubt on interpreting such differences as ‘natural’ or ‘hard-wired’. For example, analysis points to wide variation in mathematical skills outcomes across both individuals and economies and to the strong influence of socio-cultural factors in producing gender-based skills differentials.32 In particular, in a wide range of economies, a variety of social circumstances limit girls’ and women’s access to technology and therefore their ability to gain proficiency in its use. These range from lower participation in the labour market—and therefore less opportunities to learn on the job—to lower access to technology in the home.33 Finally, there is evidence that, when women do have the relevant mathematical and technology skills, unconscious biases can influence their peers’ recognition of their capabilities.34
Given these contributing factors, instances of occupational gender imbalances reflect, on the one hand, the societal expectations and role models that contribute to educational and field of study choices young girls and boys make when they embark upon acquiring foundational competencies and, on the other hand, women and men’s career planning trajectories as well as the dynamics of hiring imbalances across industries. As students transition from education to work—and into occupations with distinctive cultures, skill sets, languages, practices and values—the availability or otherwise of opportunities for learning on the job enhances or inhibits women and men’s opportunities to further develop the relevant skills for success in their industry.35
As shown in Figure 14 (below), globally, women that are employed are more likely to be educated to an intermediate (secondary) or advanced (tertiary) level. Although gender does not statistically affect the overall diversity of educational fields studied, there are notable imbalances in the specific fields of study in which men and women tend to specialize. In particular, on average, men tend to be underrepresented in the Education as well as Health and Welfare fields, whereas women, on average, tend to be underrepresented in the Engineering, Manufacturing and Construction as well as Information, Communication and Technology fields (see Figure 14 on page 32). However, such field of study imbalances are nevertheless insufficient in size to fully account for the gender gaps observed in particular industries that strongly rely on hiring talent from certain specific fields of study.
To further explore this issue, the World Economic Forum’s analysis, conducted as one part of a broader research partnership with LinkedIn, illustrates the discrepancy between the overall gender distributions of particular fields of study among all LinkedIn members compared to the typical gender distributions of LinkedIn members with those fields of study actually employed in a variety of industries (see Figure 15 below). If we take the example of computer science graduates, industries which already exhibit stronger gender parity, such as Corporate Services, draw a larger-than-average proportion of the female talent pool, while industries which exhibit weaker gender parity, such as Manufacturing, draw a smaller-than-average proportion of the female talent pool. While, on average, women make up 23% of all LinkedIn members with computer science degrees, among LinkedIn members working in Corporate Services they make up 32% of computer science degree holders in the industry. By contrast, in Manufacturing they make up only 16%.
These trends suggest a two-pronged approach for advancing progress towards closing economic gender gaps. First, at the level of foundational education, there is a need to re-balance degree specialization choices. Second, within the workplace, there is a need to avoid further exacerbating occupational imbalances through gender-biased hiring and workplace practices that lead to a low rate of female applicants and a high rate of exit among female talent in certain industries. For example, across European Union countries, only 20% of women aged 30 and over who hold ICT-related degrees decide to stay in the technology industry,36 with research on women’s motives for leaving STEM jobs pointing to the effects of workplace culture.37
Existing research on national-level gender-based wage distributions has also pointed to a tendency towards lower pay for occupations that have historically developed as predominantly female. For example, in US-specific longitudinal research on wage effects, gender-based differences in occupational wage gaps persisted throughout increases in women’s educational participation and labour market exposure.38 Put another way, these studies have found that when women enter a profession in large numbers, the pay-related benefits of participating in the profession depreciate.39 Accordingly, in such situations, fair returns to skills and the availability of deeper talent pools are undermined by existing cultural biases. Further, at either end of the pay spectrum, the industries historically most affected by occupational gender imbalances—the education, care, non-profit and the emerging technology sectors—are losing out. In fact, there is ample evidence that recognizing and better remunerating work in the care economy could produce significant benefits to economies, societies and individuals.40 Similarly, the technology sector is already experiencing significant talent bottlenecks.
The World Economic Forum’s research partnership with LinkedIn provides innovative data and a unique view of progress towards gender parity achieved in various industries to date. Our analysis reveals the growth of female industry talent pools over the past decade as well as industries’ propensity to hire women—at both entry and senior leadership levels (positions at director level and above)—and the hiring biases that may be implied by examining gender gaps represented in the data.41
Based on an analysis of LinkedIn membership from more than 100 countries and 12 selected industries,42 over the past decade, the proportion of female hiring has increased across all selected industries—as has the tendency to hire women into senior leadership positions. Nevertheless, female leadership representation remains below 50% in all industries, often significantly so, and every industry exhibits a leadership gender gap. Over the past 10 years all industries have seen increases in the female share of their potential talent pool. However, across industries such as Manufacturing as well as Energy and Mining, modest gains in hiring do not match current untapped opportunities. The largest gaps are found in the STEM fields: Software and IT Services, Manufacturing and Energy and Mining. While industries such as Energy and Mining have seen comparatively little progress, others—such as Software and IT Services—have made significant progress from a low base.
In Healthcare, Education, Non-profits, Legal, Public Administration and Media and Communications the proportion of women in the industry stands at or exceeds 50%. Of these sectors, Healthcare, Education and Non-profits employ more women than men, exhibiting a reverse gender gap. However, that reverse gender gap does not equate to parity when it comes to hiring women into leadership positions. Among these sectors, the only one currently trending towards full parity is Non-profits. Whereas over the past 10 years, Public Administration has seen strong growth in the hiring of women (+4.1%), the Education sector has stagnated at the 40% leadership hiring mark.
We illustrate the talent profiles by gender for a range of key industries in Figures 16 and 17, below, to highlight opportunities for further developing the talent pipeline across industries. For example, more men embarking on education-related fields of study could help re-balance occupational gender gaps in the Education sector. Similarly, across most industries, gender parity could be advanced by including more women with Business, Administration and Law degrees. While a lack of parity in Engineering and ICT-related degrees contributes to the gender gap across all industries (even in Non-profits, men with ICT-specializations outnumber women), these gaps appear in somewhat different quantities, suggesting a need for a more nuanced discussion on gender gaps in STEM.
Comparing hiring trends to the presence of preferred talent for that industry highlights that talent shortages are unlikely to be the only factor holding back progress in low-parity industries. Although some divergences in graduates’ field of study specializations account for a portion of this variation, overall, the divergence in fields of study between men and women is more limited than the dispersion that is evident in industries that exhibit low gender parity. Furthermore, the World Economic Forum’s research collaboration with LinkedIn has shown a strong correlation between industries with strong female representation in leadership and hiring for women, furthering the hypothesis that talent shortages are far from the only factor holding back progress in low-parity industries.
Despite a large and growing number of businesses taking proactive company-level action to address occupational gender imbalances, progression and leadership gaps, unconscious biases and systemic efforts focused on driving change at the industry or country level through public-private collaboration remain scarce. Analyses of local barriers to female economic participation across industries, constructive dialogue, shared objectives and unified action are rare in many countries, and a scarcity of cross-industry collaboration denies companies the benefits of shared learning and opportunities to pursue common goals and initiatives.
To help bridge this gap, the World Economic Forum and its constituents launched a public-private collaboration model that has been successful in accelerating progress on a number of these dimensions in seven countries to date. From 2012–2014, pilot task forces in Mexico, Japan, Turkey and South Korea convened public and private sector leaders with the capacity to bring more women into the economy, catalysing new collaboration and action at the national level. Current task forces in Chile, Argentina and Panama have also proven successful in building knowledge on the practices that advance female economic participation, providing a platform for public-private dialogue and sparking engagement and collaboration on gender issues. The World Economic Forum is exploring options to scale this model in collaboration with multilateral development agencies, national governments, businesses and civil society organizations wishing to use the model to accelerate country-level change on gender parity, particularly in light of the broader flux in labour markets.43