Reducing the gender pay gap: Could more women in STEM be the answer?

Amanda photo

This essay was written by Amanda Summers and is the winning education entry in the 2019 Critical Writing Prize. Amanda, a student at the University of Derby was nominated by her lecturer, Jennifer Marshall.


The gender pay gap is a measure of the difference between the median wages earned by men and by women (OECD, 2018c). Despite policies initiated by various governments to reduce gender inequality the gender pay gap remains a persistent problem worldwide. Indeed, recent data (Figure 1) shows that median wages earned by men outstrip those earned by women in every country in the OECD (OECD, 2018c).

figure 1

Figure 1: Gender wage gap (Total, % of male median wage, 2016 or latest available) for countries in the OECD. Source: OECD (2018c).

Notably, the UK has a gender pay gap above the OECD average and it is one of the highest in Western Europe. Prime Minister Theresa May has described this as one of “the burning injustices which mar our society” (May, 2018) and has committed the UK government to reducing gender pay inequality (Conservative Party, 2017). In this report I will examine the role of education in reducing the gender pay gap. Particularly, I will look at the gender pay gap of graduates in the UK, and how this is influenced by the degree subject choices of women. I will also examine evidence from Malaysia, a country which has successfully encouraged more women to study science, technology, engineering and maths (STEM) (Tienxhi, 2017), and will discuss the effect of this on gender pay inequality.

The gender pay gap and the role of education

In almost all OECD countries, including the UK, the number of women enrolling in higher education exceeds that of men (OECD, 2018b). However, as previously highlighted, this does not translate into long term economic advantage for women. A recent analysis of the UK Longitudinal Education Outcomes (LEO) data by the Department for Education revealed that just one year after graduation male earnings exceeded female earnings by 9%, with the gap widening to 30% ten years after graduation (Department for Education, 2018). It should be noted that the data is not longitudinal in the strictest sense, as it does not follow a single cohort of students as their careers progress. Nevertheless, the study shows that a gender pay gap for graduates exists one, three, five and ten years after graduation across different cohorts (Table 1).

Table 1: Median earnings by gender, one, three and five and ten years after graduation. Source: Department for Education (2018).

Years after graduation Median Earnings (£) Difference

(% female earnings)

Female Male

(2013/14 cohort)

18,300 19,900 9%

(2011/12 cohort)

21,800 24,200 11%

(2009/10 cohort)

24,500 27,800 13%

(2004/05 cohort)

27,100 35,100 30%


It has been argued that part of the reason for this gap can be found in differences in the subject areas that men and women choose to study at university; women are generally over-represented in the arts, social sciences and humanities but underrepresented in the STEM subjects (Machin and Puhani, 2003; Grove, Hussey and Jetter, 2011; Davies et al., 2013). Since STEM degrees tend to lead to more financially lucrative careers, it is believed that this difference feeds into the gender pay gap (Machin and Puhani, 2003; Chevalier, 2007; Grove, Hussey and Jetter, 2011; Davies et al., 2013).

In the UK, the underrepresentation of women in STEM subjects is confirmed by an analysis of higher education statistics (Figure 2). Recent data shows that male students outnumber female students in every STEM subject apart from those associated with life sciences. Furthermore, female students outnumber male students in almost all subjects associated with the social sciences, humanities and the arts (HESA, 2018).

figure 2

Figure 2: Relative numbers of students by gender in each subject area for 2016/2017. Source: HESA, (2018)

Further data from the LEO survey shows that, ten years after graduation, those who studied medicine, economics, mathematics, engineering and technology, and architecture, building and planning, were able to achieve the highest graduate earnings (Department for Education, 2018). Of these five areas four were either pure STEM subjects or included a significant STEM component and all were male-dominated fields (HESA, 2018). Conversely, the lowest earnings were achieved by graduates of the creative arts, agriculture, education, psychology and mass communication (Department for Education, 2018). Of these five areas only psychology is a STEM subject and all are female dominated fields (HESA, 2018).

These findings have been used to suggest that policy makers need to consider the influence of the educational choices of men and women – particularly with regard to STEM subjects – when considering how to promote gender equality in earnings (Machin and Puhani, 2003; Davies et al., 2013). Such authors have supported this argument through use of the economic theory of human capital.

Human capital theory

Human capital theory asserts that a worker’s earnings are directly related to their human capital investments in the labour market and education. According to this model, a worker who makes greater investments in factors such as work experience or education and training should expect to attain higher wages than those with lower levels of investment (Becker, 1962; Blinder, 1973). Proponents of the theory suggest that this helps to explain the gender pay gap. Firstly, it has been noted that women tend to make lower investments in the labour market, as they are more likely to experience interruptions to their careers or work part time (Goldin and Katz, 2008; Bertrand, Goldin and Katz, 2010). Furthermore, as previously highlighted, they make different investments in their education – by studying different subjects. Factoring these variables into an individual’s stock in human capital, leads to the argument that men enjoy greater economic benefits because of these differing choices (Blinder, 1973; Oaxaca, 1973). However, along with this explained gap in earnings, economists note that there may be an additional, unexplained gap that cannot be attributed to one of these factors. This further gap, they suggest, represents discrimination (Blinder, 1973; Oaxaca, 1973). Thus, the explained gap plus the unexplained gap represents the gender pay gap (Figure 3).

figure 3

Figure 3: A schematic representation of the gender pay gap.


Consequently, human capital theory has been used as a framework to consider how the degree subject choices of men and women effect their earnings (Machin and Puhani, 2003; Chevalier, 2007; Grove, Hussey and Jetter, 2011; Davies et al., 2013). Commentators argue that as men make investments in subjects which provide a greater financial return, they maximise their expected wages. Whereas women are more likely to make investments in subjects that will lead to lower rates of pay (Machin and Puhani, 2003; Chevalier, 2007; Davies et al., 2013). This approach, however, has weaknesses; by making a distinction between the explained and unexplained gap, proponents of human capital theory have failed to understand that the factors contributing to the explained gap may themselves be subject to discrimination (England, Allison and Wu, 2007; Lips, 2013). For example, due to an unequal division of childcare responsibilities, women may be more likely to make investments in areas of the labour market that accommodate them at the cost of lower pay (Dias, Joyce and Parodi, 2018). This issue was recognised by economist Ronald Oaxaca who noted that one of the limitations of human capital theory is that “it does not take into account the feedback from labour market discrimination on the male-female differences in the selected individual characteristics” (Oaxaca 1973, p.708). Encouraging more women into STEM fields may not, therefore, be a straightforward solution in helping rectify the gender pay gap. To examine this further I will consider the experience of Malaysia and discuss the consequences of government policies that have been deliberately structured to encourage more women into STEM fields.

More women in STEM: The experience of Malaysia

Since the late 1960s successive Malaysian governments have pursued a range of interventionist policies aimed at fostering industrialisation and economic growth (Osman and Shahiri, 2014). Consequently, Malaysia has moved from being a low-income agriculturally dependent economy to being “one of the most rapidly developing economies in the world” (The World Bank 2007, p.8). Government investment in education, higher education and particularly in STEM education has been a key factor in this transformation (Ministry of Education Malaysia, 2016; Wan, 2018). As part of this drive for economic development the role of Malaysian women has been vital. Prior to its economic transformation female participation in the workforce was low, just 37.2% in 1970 (Nagaraj et al., 2014). With industrialisation, however, women’s labour came to be viewed as an underutilised resource and thus, successive governments initiated policies to harness it (Elias, 2011). In 1989 the Malaysian government formulated its national policy for women, with the aim of engaging women in the economic development of the nation (Economic Planning Unit Malaysia, 1991; Nagaraj et al., 2014). This was built upon in the 1990s, through a recognition of the economic role of women, in the Sixth Malaysia plan (Economic Planning Unit Malaysia, 1991; Nagaraj et al., 2014). More recently the Ministry of Education has outlined its strategy for encouraging women into STEM fields (Ministry of Education Malaysia, 2016). Such strategies have led to an increase in female participation in the workplace, rising to 51% in 2017 (World Bank, 2017), and with it women’s participation in higher education has also flourished.

An analysis of higher education statistics shows that in 1980 women accounted for 38.5% of the tertiary student population in Malaysia. By the year 2000 the proportion of women in higher education marginally surpassed the number of men and by the year 2015 this gap had grown such that the proportion of women in tertiary education exceeded 55% (World Bank, 2018). The data shows that these figures compare similarly with changes to the student population in the UK (Table 2).

Table 2: Percentage of students in tertiary education who are female (%) Source: (World Bank, 2018)

1980 1990 2000 2010 2015
United Kingdom 36.5 47.6 53.9 56.6 56.1
Malaysia 38.5 51 55.2


However, whilst participation rates may be similar, data shows that the degree subject choices of women in both countries differ. In recent decades the Malaysian government has encouraged participation in STEM subjects across the student population and has targeted female students through a variety of initiatives. For example, the highest attaining secondary school pupils, most of whom happen to be girls, are now automatically placed onto a STEM focussed curriculum (Ministry of Education Malaysia, 2016). Consequently, higher education statistics from 2013 show that, in contrast to the UK, the number of female students outnumbered the number of male students in all STEM subjects except for engineering (Table 3). However, even in engineering women still constituted 36.5% of the student population compared with just 17.5% for engineering and technology (combined) in the UK for 2017 (HESA, 2018).

Table 3: Students enrolled in Malaysian public universities by field of study 2013. Source: Ministry of Education 2014 (Cited by Wan, 2018 p.224).

Field of study Total enrolled Female enrolled % Female (vs. % male)
Science and Mathematics 48,591 33,479 68.9
Information technology and communications 30,586 16,276 53.2
Engineering 87,247 31,866 36.5
Manufacturing, processing and technology 18,259 10,582 66.3

The expansion of higher education, a focus on the education of women, and the promotion of STEM subjects appear to have done much to reduce gender inequalities in the Malaysian labour market. For example, as noted above, female participation in the workplace has grown significantly. Furthermore, government statistics show that in recent years Malaysia has been able to achieve a low gender pay gap, especially when compared with economies such as the UK (Figure 4). The extent to which Malaysian statistics can be compared to OECD calculations of the gender pay gap in the UK may be limited due to differing collection methods. Nevertheless, commentators suggest that this data shows that strategies to encourage women into STEM fields have reduced gender pay inequality in Malaysia (Strauss, 2018).


Figure 4: Gender pay gap in the UK and Malaysia 2012-2017. Source: (Department of Statistics Malaysia, 2013, 2014, 2015, 2016, 2017; OECD, 2018c).

However, these figures may fail to give a full account of the Malaysian experience. The following data shows that whilst for younger women the pay gap is low – indeed on average women in the 25-40 age range earn more than men – for older women the gap is much greater (Figure 5). This suggests that whilst younger women are able to capitalise on their investment in education, this advantage begins to reduce once women reach their mid-thirties and is completely eradicated and even reversed later in their careers.

Gender graph
Figure 5: Gender pay gap in Malaysia by age group, 2013-2017. Source: (Department of Statistics Malaysia, 2013, 2014, 2015, 2016, 2017).

It has been argued that this is mostly due to the persistence of traditional gender roles in Malaysia, with women often undertaking caring roles in addition to employment. Goy and Johnes (2011) suggest that this factor along with a lack of affordable childcare and a dearth of company policies on flexible working has resulted in women being less likely to take on senior positions later in their careers. Therefore, the Malaysian example shows us that whilst female investments in STEM education may promote an initial reduction in the gender pay gap, this reduction may be short-lived if women operate within a system which prevents them from making long-term investments in the workplace. These assertions have been supported by other authors who also note that once they have children women in Malaysia are much more likely to leave the labour force completely (Elias, 2011). The Malaysian government recognises these problems and is seeking to remedy them through a range of policies such as encouraging flexible working practices and improving accessibility to childcare (Economic Planning Unit Malaysia, 2015).

When comparing the Malaysian experience to the situation in the UK it should be noted that levels of female participation in the workforce are much greater in the UK (World Bank, 2017). Consequently, a simple comparison of the gender pay gap does not demonstrate how Malaysian women are more likely to be completely absent from the workforce and thus unaccounted for in gender pay statistics. Therefore, a comparison of data between Malaysia and the UK is limited. However, when considering UK policy, and the extent to which the gender pay gap may be reduced by encouraging more women into STEM fields, the Malaysian experience serves as an interesting example.

Consequences for policy in the UK

The Malaysian example would indicate that encouraging more women to study STEM subjects does not automatically translate into long term economic advantage for women. Indeed, it demonstrates that despite achieving better educational outcomes, pay and opportunities for women are constrained by a system which limits their capacity to make equal human capital investments in the workplace. Commentators have suggested that women in the UK face similar barriers. For example in the UK it has been noted that an unequal division of childcare responsibilities often results in women moving away from jobs that provide higher wages and towards jobs that provide other benefits such as flexibility (Dias, Joyce and Parodi, 2018). Furthermore, it has been argued that within the context of male-dominated STEM industries such as engineering, IT or construction that these challenges are even more profound. Research in these sectors indicates that inflexible working practices are common and career breaks are viewed negatively. Consequently women are often side-lined into lower status jobs later in their careers (Watts, 2009; Herman, 2015; Kirton and Robertson, 2018). These assertions are supported by data from the LEO survey which shows that ten years after graduation female STEM graduates in the UK earn 15-23% less than their male counterparts (Table 4).

Table 4: Gender wage differentials for STEM graduates ten years after graduation. Source: (Department for Education, 2018)

Male wages 10 years after graduation (£). Female wages 10 years after graduation (£). Female wages as a % of male wages
Biological Sciences 33,000 28,000 85
Physical Sciences 35,600 28,800 81
Mathematical Sciences 43,900 35,700 81
Computer Science 35,700 27,800 78
Engineering and Technology 41,000 31,500 77

Nevertheless, it could be argued that encouraging a higher proportion of women into STEM fields may help to promote cultural change within these sectors, which could in turn reduce the gender pay gap. However, it has been suggested that when women enter male-dominated industries in significant numbers that this leads to a reduction in rates of pay (Cain Miller, 2016). Evidence to support this shows that when women move into a sector, the perceived status of jobs in that field reduces. Consequently, men within that sector negotiate new roles, which become higher status and better paid than the roles now fulfilled by women (Lips, 2013; Goldin, 2014). Examples of this can be found in longitudinal studies in the US (England et al. 2007) and Europe (Murphy and Oesch, 2014).

Taken together, the evidence suggests that encouraging women into male-dominated STEM fields may not be sufficient to bridge the gender pay gap. When looking at examples of other countries in the OECD which have succeeded in reducing their gender pay gap, none of them have achieved this through an integration of women into STEM fields. For example, Belgium has seen one of the most dramatic reductions in its gender pay gap moving from 13.6% in 2000 to 4.7% in 2015 (OECD, 2018a). This has been achieved mostly through strategies which seek to negate structural inequalities in the working environment. For example, collective bargaining has been strengthened, meaning that gains made apply equally to both men and women, and gender-pay-gap reporting has been made mandatory (Stone, 2018). Other countries with lower gender pay gaps have instituted a range of policies aimed at tackling structural gender inequalities such as improvements to pay transparency (Norway; Collinson, 2016), mandatory paternity leave (Sweden; Jackson, 2015), and mandatory employer certification of pay parity (Iceland; Henley, 2018). It is interesting to note that in these countries the emphasis has been on tackling structural inequalities in the workplace rather than targeting individual investments in education and the labour market.


Following an analysis of data from both the UK and Malaysia and a review of the academic work in the area, I would suggest that human capital theory only provides us with a limited understanding of the gender pay gap and how it can be tackled through changes to education policy. Commentators who use this theory as a framework fail to acknowledge that changes in individual investments do not take place within the context of a gender-neutral environment. As previously discussed, individual investments are subject to the constraints of the system in which they are made and these constraints may not be the same for everybody. Therefore, as has been seen in Malaysia, encouraging women into STEM education may reap short term benefits regarding gender pay equality but long term benefits may only be possible with structural changes to the employment system.

There are, of course, other reasons why it could be desirable to encourage more women into STEM fields. Since the year 2000 the government has shown concern over the UK’s ability to improve productivity within an increasingly technical global economy (National Audit Office, 2018). Within this context the National Audit Office highlighted the need to encourage more women into STEM education as it argued that women represent “a pool of potential STEM-skilled people that is currently being lost to the economy” (National Audit Office 2018, P.26). Therefore, encouraging more women into STEM could be regarded as an important step towards ensuring future economic prosperity. However, for women to enjoy an equal stake in this prosperity it will be necessary for the government to tackle systemic constraints on the ability of women to invest in the workplace on equal terms with men.


Becker, G. S. (1962) ‘Investment in Human Capital: A Theoretical Analysis’, The Journal of Political Economy, 70(5), pp. 9–49. doi: 10.1086/258724.

Bertrand, M., Goldin, C. and Katz, L. F. (2010) ‘Dynamics of the gender gap for young professionals in the financial and corporate sectors’, American Economic Journal: Applied Economics, 2(3), pp. 228–255. doi: 10.1257/app.2.3.228.

Blinder, A. S. (1973) ‘Wage Discrimination: Reduced Form and Structural Estimates’, The Journal of Human Resources, 8(4), p. 436. doi: 10.2307/144855.

Cain Miller, C. (2016) ‘As women take over a male dominated field, the pay drops’, New York Times, 18 March. Available at: (Accessed: 21 May 2018).

Chevalier, A. (2007) ‘Education, occupation and career expectations: Determinants of the gender pay gap for UK graduates’, Oxford Bulletin of Economics and Statistics, 69(6), pp. 819–842. doi: 10.1111/j.1468-0084.2007.00483.x.

Collinson, P. (2016) ‘Norway, the country where you can see everyone’s tax returns’, The Guardian, 11 April. Available at: (Accessed: 24 July 2018).

Conservative Party (2017) Forward, Together Our Plan for a Stronger Britain and a Prosperous Future, The Conservative and Unionist Manifesto. Available at: (Accessed: 9 July 2018).

Davies, P. et al. (2013) ‘Labour market motivation and undergraduates’ choice of degree subject’, British Educational Research Journal, 39(2), pp. 361–382. doi: 10.1080/01411926.2011.646239.

Department for Education (2018) Graduate outcomes (LEO): Employment and earnings outcomes of higher education graduates by subject studied and graduate characteristics. Available at: (Accessed: 9 July 2018).

Department of Statistics Malaysia (2013) Salary and Wages Survey Report, 2013. Available at: (Accessed: 18 July 2018).

Department of Statistics Malaysia (2014) Salary and Wages Survey Report 2014. Available at: (Accessed: 18 July 2018).

Department of Statistics Malaysia (2015) Salary and Wages Survey Report, 2015. Available at: (Accessed: 18 July 2018).

Department of Statistics Malaysia (2016) Salary and Wages Survey Report, 2016. Available at: (Accessed: 18 July 2018).

Department of Statistics Malaysia (2017) Salary and Wages Survey Report, 2017. Available at: (Accessed: 18 July 2018).

Dias, M. C., Joyce, R. and Parodi, F. (2018) Wage Progression and the Gender Wage Gap: The Causal Impact of Hours of Work, IFS Briefing Note BN223. Available at: (Accessed: 24 July 2018).

Economic Planning Unit Malaysia (1991) ‘Women in Development’, in Sixth Malaysia Plan, 1991 – 1995. Putrajaya: Economic Planning Unit Malaysia, pp. 413–427. Available at: (Accessed: 17 July 2018).

Economic Planning Unit Malaysia (2015) ‘Enhancing inclusiveness towards an equitable society’, in Eleventh Malaysia Plan, 2016 – 2020. Putrajaya: Economic Planning Unit Malaysia, p. 3/1-3/36. Available at: (Accessed: 17 July 2018).

Elias, J. (2011) ‘The gender politics of economic competitiveness in Malaysia’s transition to a knowledge economy’, Pacific Review, 24(5), pp. 529–552. doi: 10.1080/09512748.2011.596564.

England, P., Allison, P. and Wu, Y. (2007) ‘Does bad pay cause occupations to feminize, Does feminization reduce pay, and How can we tell with longitudinal data?’, Social Science Research, 36(3), pp. 1237–1256. doi: 10.1016/j.ssresearch.2006.08.003.

Goldin, C. (2014) ‘A Pollution Theory of Discrimination: Male and Female Differences in Occupations and Earnings’, in Platt Boustan, L., Frydman, C., and Margo, R. A. (eds) Human Capital in History : The American Record. Chicago: University of Chicago Press, pp. 313–348. Available at:

Goldin, C. and Katz, L. F. (2008) ‘Transitions: Career and family life cycles of the educational elite’, American Economic Review, 98(2), pp. 363–369. doi: 10.1257/aer.98.2.363.

Goy, S. C. and Johnes, G. (2011) ‘Occupational Segregation in the Malaysian Labor Market: Evidence on the L Index’, The Singapore Economic Review, 56(03), pp. 397–421. doi: 10.1142/S0217590811004341.

Grove, W. A., Hussey, A. and Jetter, M. (2011) ‘The gender pay gap beyond human capital: Heterogeneity in noncognitive skills and in labor market tastes’, Journal of Human Resources, 46(4), pp. 827–874.

Henley, J. (2018) ‘“Equality won’t happen by itself”: How Iceland got tough on gender pay gap’, The Guardian, 20 February. Available at: (Accessed: 24 July 2018).

Herman, C. (2015) ‘Rebooting and Rerouting: Women’s Articulations of Frayed Careers in Science, Engineering and Technology Professions’, Gender, Work and Organization, 22(4), pp. 324–338. doi: 10.1111/gwao.12088.

HESA (2018) What do HE students study? Available at: (Accessed: 2 June 2018).

Jackson, G. (2015) Force men to take paternity leave. It will make the world a better place, The Guardian. Available at: (Accessed: 24 July 2015).

Kirton, G. and Robertson, M. (2018) ‘Sustaining and advancing IT careers: Women’s experiences in a UK-based IT company’, Journal of Strategic Information Systems, 27(2), pp. 157–169. doi: 10.1016/j.jsis.2018.01.001.

Lips, H. M. (2013) ‘The Gender Pay Gap: Challenging the Rationalizations. Perceived Equity, Discrimination, and the Limits of Human Capital Models’, Sex Roles, 68(3–4), pp. 169–185. doi: 10.1007/s11199-012-0165-z.

Machin, S. and Puhani, P. A. (2003) ‘Subject of degree and the gender wage differential: Evidence from the UK and Germany’, Economics Letters, 79(3), pp. 393–400. doi: 10.1016/S0165-1765(03)00027-2.

May, T. (2018) ‘We must make the gender pay gap a thing of the past’, Daily Telegraph, 3 April. Available at: (Accessed: 9 July 2018).

Ministry of Education Malaysia (2016) Sharing Malaysian Experience in Participation of Girls in Stem. Available at: (Accessed: 27 June 2018).

Murphy, E. and Oesch, D. (2014) ‘The feminization of occupations and wage change: a panel analyis of Britain, Germany and Switzerland’. doi: 10.1093/sf/sov099.

Nagaraj, S. et al. (2014) ‘Gender imbalance in educational attainment and labour market dynamics: Evidence from Malaysia’, Malaysian Journal of Economic Studies, 51(SPEC. ISSUE), pp. 127–145.

National Audit Office (2018) Delivering STEM (science, technology, engineering and mathematics) skills for the economy. Available at: (Accessed: 25 July 2018).

Oaxaca, R. (1973) ‘Male–female wage differentials in urban labor markets’, International Economic Review, 14(3), pp. 693–709.

OECD (2018a) Employment: Gender wage gap. Available at: (Accessed: 24 July 2018).

OECD (2018b) Enrolment rate (indicator). Available at: (Accessed: 2 July 2018).

OECD (2018c) Gender wage gap (indicator). Available at: (Accessed: 2 July 2018).

Osman, Z. and Shahiri, H. (2014) ‘Ethnic and Gender Inequality in Employment during the New Economic Policy’, Institutions and Economies, 6(1), pp. 57–72.

Stone, J. (2018) ‘How Belgium is defeating the gender pay gap’, The Independent, 5 April. Available at: (Accessed: 24 July 2018).

Strauss, K. (2018) ‘The Countries With The Best And Worst Gender Pay Gap Expectations–And How The U.S. Stacks Up’, Forbes, 22 January. Available at: (Accessed: 22 July 2018).

Tienxhi, J. Y. (2017) ‘The Gender Gap in Malaysian Public Universities: Examining The ’Lost Boys’ ’, Journal of International and Comparative Education, 6(1), pp. 1–16. doi: 10.14425/JICE.2017.6.1.0116.

Wan, C. Da (2018) ‘Student enrolment in Malaysian higher education: is there gender disparity and what can we learn from the disparity?’, Compare, 48(2), pp. 244–261. doi: 10.1080/03057925.2017.1306435.

Watts, J. H. (2009) ‘“Allowed into a man’s world” meanings of work-life balance: Perspectives of women civil engineers as “minority” workers in construction’, Gender, Work and Organization, 16(1), pp. 37–57. doi: 10.1111/j.1468-0432.2007.00352.x.

World Bank (2007) Malaysia and the knowledge economy: Building a world class higher education system. Available at: (Accessed: 17 July 2018).

World Bank (2017) Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate). Available at: (Accessed: 22 July 2018).

World Bank (2018) Percentage of students in tertiary education who are female (%). Available at: (Accessed: 17 July 2018).

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s