Father versus mother’s education
Parental education is key determinant that influence children’s schooling decision (De Haan, 2011; Pufall et al., 2016). Educated parents put more emphasis on the education of their children as compared to those parents with low or no education at all (Hill and Duncan, 1987). Educated parents prefer to send their children to full-time school or join schools while working part-time as opposed to those uneducated parents who will let their children to work full-time. (Ravallion and Wodon, 2000). Literature suggests that, that paternal education is more influential than maternal education (Ermisch and Pronzato, 2010; Marks, 2008). We separately include the variable of fathers education and mother education to test for the hypothesis if maternal education has greater effect than paternal on our outcome variable. The result in the Appendix A Table A.4 and A.5 show that the marginal effects on propensity to school enrolment both fathers and mothers education seems to be of similar magnitude. The Fairlie decomposition result in the Appendix A Table A.6 show that mother education contribute higher for ethnic Pahstuns. For the rest of the groups the difference almost remain the same.
Discussion and conclusion
In this chapter, we investigate the differences in school enrolment across ethnic groups in Pakistan and what primary factors account for these differences. The result suggests that there are substantial ethnic disparities in school enrolment in Pakistan. The first part of our result shows that ethnic Pashtuns, Balochs, Sindhis, and Siraykis have much lower enrolment rate, while Mohajirs and Punjabis have comparatively higher enrolment rates.
In the second part, we explored the reasons for these ethnic disparities in enrolment between ethnic majority Punjabis and other ethnic minority groups. The results show that the impact of explanatory variables on child school enrolment varies depending on the ethnic groups. The set of variables included that has the largest coefficients of marginal effects were gender, parental education, and socioeconomic status. However, region and parental education played a considerable role compared to other factors. The results suggest that ethnicity influences school enrolment for children implying that there are historical, cultural and other factors that block these children from their right to have education.
The analysis generates more refined policy implications. For example, enhancing household income or reducing poverty would help increasing school attendance, but it will not work for all ethnic groups living in Pakistan. Our analysis of this study identified that place of residence, and household characteristics, along with unobservable characteristics, are responsible for the disparities in school enrolment. In order to have further progress towards universal enrolment, our analysis proposes a number of possibilities. Conditional cash transfer (Ladhani and Sitter, 2020) and offering transportation to pupils could be one solution since education is free and it is the state’s responsibility to provide the students with vouchers (see for example (Moe, 2004)). The government should provide bus service or any other means of transportation to increase enrolment and reduce dropout rates. The numbers of private schools are mostly established in cities and large population hubs; it could be extended to the marginalised ethnic groups with the help of public-private partnership. Ethnic-based policies aimed at encouraging entrance to school could ensure progress towards achieving universal enrolment. Future research should be directed towards gender gaps in educational outcomes in ethnic groups.
Gender gaps in school enrolment in rural Pakistan
Gender equality has been considered a human right in global policy discussions. Regardless of gender, colour, and race, all humans are born free and equal in dignity and rights. However, the world is still far away from achieving gender equality (Assembly, 1948; Bajaj and Kidwai, 2016). Consequently, the question of gender inequality remains a fundamental challenge for the policymakers due to its considerable effect on human capital formation and economic growth (Duflo, 2012).
The role of educating women on the humanistic, societal, and economic front cannot be overem-phasized. Women play an essential role in building child human capital and boosting economic growth (Beneria and Sen, 1982; Boserup, 2007; Corner, 2008). For details on the wide range of benefits of educating women (see for example, (Janzen, 2008; Pervaiz et al., 2011; Rezai-Rashti and Moghadam, 2011; Shapiro, 2012). However, despite some progress in the last few decades, (Hausmann, 2009; Olivetti and Petrongolo, 2016), gender gaps persist with women lagging behind in majority of life domains including labour market outcomes, access to credit and education (Haus-
mann, 2009; Nordman et al., 2011). Girls have limited educational opportunities to complete 12 years of education due to multiple barriers (Durrani and Halai, 2020). South Asia and Sub-Saharan Africa remain with large gender gaps in the world.
Further, unemployment in Pakistan is much higher than the average unemployment rate in the world (Chaudhary et al., 2014). The percentage of female youth who are outside education and not involved in any economic activity is roughly about 72% in current years (Mani et al., 2020). Pakistan has a huge gender disparity problem. According to the world economic forum, Pakistan ranks 143 out of 144 countries in the gender inequality index (Black, 2016). The percentage of working-age female population who do not seek employment in the labour market due to societal pressure is very high.
As stated in the general introduction, many out of school children of the world reside in Pakistan. An estimated 22.64 million school children between the ages of 5 and 16 are out of school, the majority reported are girls (Stuart and Woodroffe, 2016). In this connection Pakistan education task forum reported that one in ten of the world’s primary school age children out of school reside in Pakistan will never enrol in school. According to (UNICEF) the various barriers for children access to education, sprouting because of, different sets of deep rooted structural inequalities, inadequate budget allocation, and resource distribution along with economic and cultural realities (UNICEF et al., 2017). This compels us to spot those lope holes and propose more realistic and feasible remedies for addressing this issue.
While there has been extensive research on gender gaps in developing countries, to our knowledge, little is known in the context of gender gaps in ethnic groups in Pakistan. The first purpose of this chapter is to assess the gender gaps in different ethnic groups in Pakistan. Reducing gender gaps in education outcomes will reduce poverty, inequality, better employment opportunities, and higher income. Empirically we employ Probit and multilevel regression model. Our result suggests that there exist large gender gaps in school enrolment among and between ethnic groups. We find that gender gaps in school enrolment are wider in ethnic Pashtun, Sindhis, Baloch, and Sirayki children.
The second objective of this chapter is to investigate the gender gaps between ethnic majority group compared to ethnic minority groups. To identify the gender gaps due to observed characteristics empirically, we use the Fairlie decomposition technique. Our results suggest that socioeconomic status, parental education, and the regions explain most of these gaps. The remaining part of this chapter is organised as follows. Section 2 reviews the relevant literature on intersectionality and the gender gap in education. Section 3 briefly describes the database and detailed descriptive statistics. In section 4, we explain the econometric framework adopted for this study. Next, in section 5, we present our results, and finally, section 6 concludes our study with recommendations.
Ethnic diversity is linked with low quality institutions and poorer economic performance (Alesina and Zhuravskaya, 2011; Easterly and Levine, 1997). Higher income gap is observed in such fragmented societies (Perera and Lee, 2013). The literature suggests that ethnic fragmentation is associated with lower school funding and facilities that might effect universal primary education (Churchill et al., 2020; Miguel and Gugerty, 2005). Further, ethnic fragmentation is associated with wider gender gaps through its role in strengthening social and cultural norms that maintain the prevailing gender gaps (Awaworyi Churchill et al., 2019). Gender gaps have been asserted to be deeply rooted in social and cultural norms, reflecting the institutionalise disposition toward gender equality (Hiller, 2014). For instance, certain social norms and religious preferences hinder gender equality. For example, the prevalence of domestic violence, the notion of women staying at home and men as a breadwinner in certain societies reduces her participation in social and economic activities (Ahmed Salim, 2016; Easterly and Levine, 1997; Heintz et al., 2006).
Although, social and cultural norms generally tend to widen gender gaps. However, there is some evidence where social norms promote gender equality. For example, Beaman et al. (2012) show that exposure to female leadership in daily life positively influence girls educational attainment and career aspirations. Also, it reduces male prejudice resulting in more gender equality. Similarly, Kabeer (2016) in her study suggest that partner of working wives raised by working women tends to be more supportive resulting in gender equality.
‘Intersectionality’ derived from feminist theory has been used as a useful lens to view the relationship between social categorisation such as race, ethnicity, gender, and class (Bose, 2012; Collins, 2002). Intersectionality refers to the idea that how intersecting power relations effect social categories across diverse groups, including the individual experiences in daily life. As an analytic tool, intersectionality considers social categories, principally those that involve power or inequality, such as race, ethnicity, class, gender, sexuality, nation and ability, and age-among others- as interrelated and mutually shaping one another. Intersectionality is a method of having knowledge and illustrating the complexities of the world in people and human experiences.
The core insight of intersectionality states that in a given society at a given time, power relations of race, ethnicity, class, and gender are not discrete and mutually exclusive entities. Nevertheless, build on each other and work together, and that, while often invisible, these intersecting power relations affect all aspects of the social world. The term is attributed to Kimberle Crenshaw, an American legal scholar. She explained the plight of African American women and their unique disadvantageous situation in her work (Crenshaw, 1989, 1990). Later, her work drew the attention of researchers and activists to frame multiple forms and layers of discrimination and accentuate it to ‘interlocking systems’ of discrimination (Collins, 2002). The theoretical advancement of the debate on intersectionality led to the critique on the second wave of the feminist movement by accrediting it as a relatively middle class, white-centric movement. It has been argued that it oversimplified the experiences of the disadvantaged women in connection to their social class. Previously intersectionality was intimately linked with gender studies(Fredman, 2005; Lutz et al., 2016; Yuval-Davis, 2006). However, recent years have witnessed the use of intersectionality as conceptual tool in other social science domain such as education (Codiroli Mcmaster and Cook, 2019), health,(Hankivsky, 2011) psychology (Else-Quest and Hyde, 2016), family studies (Few-Demo, 2014) and sociology (Choo and Ferree, 2010).
One of the major aspects that influence children school enrolment in developing countries is gender (Unterhalter, 2014). The south Asian countries, along with Middle Eastern countries, are part of the patriarchy belt where women are less empowered (Caldwell, 1982; Moghadam, 1993). In Pakistan, primarily a male-dominated society, female education has been less of a concern for most families. Male children are given preference over females due to social and cultural norms. The financial mindset about investing in a daughter’s education is often-quoted in a south Asian proverb that, « raising a daughter is watering your neighbour’s garden ». However, in recent times the situation has slightly improved due to the global strain to extend the accessibility of essential education to young girls.
Holmes (2003) investigated the factors helping students in completing their primary level school. She found that female receive less education than males. She argued that girls are unable to complete their primary education because of their economic and socio-cultural constraints. In patrilineal societies in which sons inherit from their fathers, boys are expected to become the future family leaders. Lower values are assigned to girls, who are seen as temporary persons soon to be “given out” in marriage to other families (Colclough et al., 2000). Likewise, Sawada and Lokshin (1999) is of the view that greater opportunity cost of daughter’s education may lead to possible intra-household discrimination against women in terms of education. Pakistan is characterised by among the highest level of gender disparity in education (UNESCO, 2017).
Gender has a strong influence in the rural areas of Pakistan. Being a rural woman minimises the chance of going to school (Aslam, 2007; Lall, 2009; Qureshi and Rarieya, 2007). Similarly, Sawada and Lokshin (2009) estimated that in rural areas of Pakistan, 2.9 Percent of female children’s drop out from the school. The fact that in tribal society, that head of the household has complete dominance over the decisions of the family and his education has a positive impact on the decision of sending girls to the school. Consequently, Qureshi and Rarieya (2007) finds parents unwillingness as a primary reason for not sending their daughters to school due to the large distance from home to school and security threats. Sawada and Lokshin (1999) believes that greater opportunity cost of daughter’s education may lead to possible intra-household discrimination against girls in terms of education. In a study in the Pashtun areas of Pakistan Jamal (2016) found that besides poverty, political apathy, religion and tribal code of conduct restricts women from education. Social norms define women’s role in the family and community—these norms shape parents’ preferences for girls’ education. Parents may have a low expectation of the potential returns from educating their daughters, mainly due to profound entrenched ideas about women’s role in society and labor market opportunities for women. In Pakistan, parents have been found to be less interested in educating daughters because they may leave the family after marriage (Naveed and Arnot, 2019).
Parents’ education is the key determinant that influences children’s schooling decision. Well-educated parents emphasis on their children’s schooling compared to parents with little or no education at all. Moreover, educated parents may be able to help their children with their studies at home, thereby positively influencing children’s schooling outcomes. There is ample evidence that children from educated parents will more often attend school and stay longer (Buchmann and Brakewood, 2000; Colclough et al., 2000; Smits and Ho¸sgör, 2006). Furthermore, the education level of mothers is important for girls schooling (Emerson and Souza, 2007). In a study on primary school children Holmes (2003) found that mothers education is more imperative for girls than fathers’ education, while fathers’ education seemed more imperative for boys than mother’s education. Also, educated parents prefer schooling over child work. Ravallion and Wodon (2000) found that in Bangladesh, educated parents were more interested in sending their children to full-time school or join schools while working part-time as opposed to parents with no education, who will let their children only to work. Connelly and Zheng (2003) found a positive relationship between family incomes, parental education in moulding the family’s choice with respect to the interest in investing in their children’s education. The most exasperating, however not sudden, observation of the study is the prevalence of the impact beginning from parental instruction. It is this generational exchange of human capital that needs more consideration, as it additionally suggests that the lack of education and henceforth the neediness of parents get transmitted to the future generations. Patrinos et al. (2005) study proposes that the impact of parental education exists above and beyond the support of the informed parent’s human capital to family earnings. The education of parents seems to add an additional class enlistment because their level of education permits them to utilise information with respect to the significance of education for their kids. That is, qualified parents know about the advantages of instruction for their children. Also, few studies have suggested that parents age influences the decision of sending their children to school. Older father is less likely to invest in child schooling due to the belief of getting any return from his investment (Chugh, 2004; Thakur and Mukherjee, 2016).
Table of contents :
1 Ethnic disparities in school enrolment in Pakistan
1.2 Literature review
1.3 Regional context, educational system in Pakistan
1.4 Database and descriptive statistics
1.7 Discussion and conclusion
2 Gender gaps in school enrolment in rural Pakistan
2.2 Literature review
2.3 Database and descriptive statistics
2.4 Econometric model
3 School enrolment and learning of children with disabilities
3.1 Introduction and literature review
3.2 Literature review
3.3 Regional context
3.4 Data measurement and research questions
3.5 School enrolment and performance on reading and Maths assessment
3.6 Econometric framework
3.8 Conclusion and discussion
4 Education and women empowerment disparities in Afghanistan
4.2 Literature review
4.3 Afghanistan’s demographic and political background
4.4 Data and descriptive statistics
4.5 Econometric strategy