Women Managers and The Gender-Based Gap in Access to Education: Evidence from Firm-Level Data in Developing Countries

ABSTRACT

A number of studies explore the differences in men's and women's labor market participation rates and wages. Some of these differences have been linked to gender disparities in education access and attainment. The present paper contributes to this literature by analyzing the relationship between the proclivity of a firm having a top woman manager and access to education among women relative to men in the country. The study combines the literature on women's careers in management, which has mostly focused on developed countries, with the development literature that has emphasized the importance of access to education. Using firm-level data for seventy-three developing countries in 2007–10, the study finds strong evidence that countries with a higher proportion of top women managers also have higher enrollment rates for women relative to men in primary, secondary, and tertiary education.

KEYWORDS:

• Gender differences
• education
• development
• employment

JEL Codes:

• J16
• G30

NOTES ON CONTRIBUTORS

Asif Islam is an Economist with the Enterprise Analysis Unit at the World Bank Group. His research experience encompasses gender, private-sector development, government fiscal policy, entrepreneurship, informality, trade, and environment. Asif holds a PhD in Applied Economics from the University of Maryland – College Park.

Mohammad Amin is a Senior Economist with the Enterprise Analysis Unit at the World Bank Group. His current research interest includes work on gender, informality, and international trade. His previous work includes research related to international migration and services trade. Mohammad Amin holds a PhD in Economics from Columbia University.

Notes

1 Some studies in the area show that the benefits of women in positions of powers may be limited in small firms (Andrew M. Penner and Harold J. Toro-Tulla 2010).

2 See for example, Jacob Mincer (1962), Gary Becker (1965), Florence Jaumotte (2003) and Morrison, Raju, and Sinha (2007) for an overview of the more recent literature.

3 Sample size in the regressions varies due to missing data.

4 Enterprise Surveys do not cover the primary sector, mining, and services sectors such as education and health. Data on some of our main variables used in the regressions is missing for the services sectors covered in the survey for some countries.

5 That is, we take the average over 1984 to 1988 values of enrollment ratios for primary, secondary, and tertiary education and then take the average over the three resulting ratios. As mentioned above, for some countries, Enrollment_1986 is computed with data not available for all three education levels. Enrollment levels centered on other years (discussed below) are analogously defined.

6 Note that the Enrollment −1 variable is defined only for those countries for which information is available on all three education levels.

7 The qualitative nature of the results does not change if we include primary and secondary enrollment rates separately in the regressions.

8 We also experimented by using women to men ratio of adult literacy rate (Literacy rate) in place of Enrollment_1986. Results using literacy rates are qualitatively similar to the ones discussed above for Enrollment_1986.

9 To conserve on space, results are shown in Table 3 with no controls and all the controls in place. Results for other specifications shown in Table 2 are qualitatively similar and available on request from the authors. The same holds for results in Table 4.

10 The results are qualitatively similar if we use an interaction term in the regressions between Enrollment_1986 and the dummy for small versus large firms instead of splitting the sample for small and large firms.