Inequalities in education

Abstract: School effects are a well-known explanation in the explanation of the intergeneration transmission of inequality in the sociological literature. Research has focus almost exclusively in their impact in early stages of the school careers including primary and lower secondary education. Little is known about the importance of the college attended in tertiary education. For almost the first time, evidence from the TEDS-M survey allows studying the impact of the clustering of future teachers still enrolled in university programs in their knowledge of mathematics. Using a multilevel modeling strategy we study ‘school effects’ for the outcomes of students in Spain and the US attending concurrent programs. Both countries have important similarities that ease the comparison and differ in essential aspects that help to expect softer school effects in the first of these two countries (diversification of tertiary education institutions in the US and a weak certification of the quality of the future teacher education programs in Spain). Our results confirm that while in Spain the college attended can determine up to only a 2% of the knowledge in mathematics, in the US schools matter far more (21%).

This paper tries to study the gender differences in educational status of unmarried youth in India and to find out the role of education and gender on process of growing up using the data from “Youth in India: Situation and Needs 2006-2007”. Bi-variate and multi-variate techniques are used to find out the level of literacy among youth, reasons for not attending the school, gender differences in dropping out in school and percent distribution of type of school in various states and sex. Result shows that one fifth youth in Bihar are illiterate against only 1 percent in selected southern states. Main reason for non- attendance of schools in Bihar are economic. Majority of the youth are attending government schools. Maximum number of youth discusses about their school performance with father is relatively more than with mother. A huge gender gap is visible in discussion of growing up issues with parents. When more than 70 percent girls discuss it with mother, it is rather negligible by young boys. The multinomial logistic regression analysis shows that good communication with father is found to be significantly higher among male compared to females and also highly significant with the higher level of education. Less communication with father shows similar result.

In 2002, the Hong Kong Secondary School Places Allocation System made an important policy shift. The old strategy which allocated boys and girls separately was replaced by a new strategy which allocated boys and girls together. Using the TIMSS (Trends in International Mathematics and Science Study) data and a DDD (difference-in difference- in differences) approach, this paper investigates the influence of the change of SSPA system on the within-school gender gaps in mathematics and science literacy. This research will have both essential theoretical and policy implications. Regarding of theoretical implication, we can contribute new evidences to the existing theoretical controversy on the gender differences in cognitive development. Regarding of policy implication, we can offer practical suggestions to the policy of secondary school allocation, and also provide valuable reference for the ongoing educational reform in Mainland China and other areas.

In 2002, the Hong Kong Secondary School Places Allocation (SSPA) System made an important policy shift. The old strategy which allocates boys and girls separately was replaced by a new strategy that allocates boys and girls together. Using the HKPISA data, this paper investigates the within-school gender gaps in reading, mathematics and science literacy before and after the change of the SSPA system. Although girls consistently perform better in reading and perform worse in mathematics and science, surprisingly, we found that the within-school gender gaps in mathematics and science significantly increased instead of decreased as expected after the educational reform. Why a policy aimed to reduce gender inequality actually created greater gender gap? There’re two competing theories that can explain this puzzle. In order to examine these two alternative theories, we further use TIMSS2007 and PISA2009 data to focus on a certain cohort, and look into their cognitive gender difference at 8th grade and 10th grade.

The paper aims to analyze the employment and related aspects of engineering graduates in Delhi, India using the data collected from the final year engineering graduates studying in different types of institutions (central government/state government/private) and courses of study (traditional/IT related courses) in Delhi. The survey covers 1178 students in the academic year 2009-10. Different issues/questions dealt in the paper include: first, what are the factors determining the employment probabilities of engineering graduates? Second, does the offered earning of engineering graduates vary according to their socio-economic, academic and current educational background? Third, the crude rates of return to engineering education is estimated to evaluate labour market value of taking four years of engineering education in the instead of entering into the job market after completing senior secondary level of education. A few major policy implications are also drawn from the several results presented. Econometric tools used in the analysis include logistic regression (in case of the dependent variable is binary) and OLS technique (where the dependent variable is continuous). The explanatory variables included in the analyses are broadly categorised as individual characteristics, household factors and students' academic background.

A vast sociological and psychological literature has showed that children from intact and non intact families have different scholastic and behavioural outcomes. This may be due to the different parental investment both in term of money and in term of time spent with the children.
In this paper we investigate whether living with both parents affects the time devoted by children in more formative activities such as reading and studying and in less formative activities such as watching tv or playing video-games with respect to children living with a singlemother. As explanatory variable we consider also the input in terms of time children spend with their parents in doing _human capital accumulating_ activities.
We use data from the Italian Time Use Survey for the year 2008 that contains a detailed time diary for all family members above the age of three.
We concentrate our analysis on children between 5 and 14 year old and we find that having a single mother reduces the time children devote to readying and studying and this effect turns out to be driven by poor single mothers and low educated single mothers, and the time devoted to less formative activities is higher for children with poor or lower educated single mothers.

Levels of educational attainment are the main component of human capital that is used in many models, mostly related to economics. However a large majority of data on education suffer from severe flows, hampering any trend and regression analysis on levels of educational attainment. We show in this paper how picking the right data and adjusting it so that it becomes consistent across ages and countries can be a real hassle. This exercise was done in the framework of Wittgenstein Centre for Demography and Global Human Capital new round of population projections by levels of educational attainment from 2000 to 2060 and the reconstruction of the same data back to 1960. Both exercises require base-year data on population disaggregated by levels of educational attainment by age and sex. These were gathered for 170 countries for six education categories between 2000 and 2011.

Education has emerged as the most important demographic indicators influencing human development. Despite the various affirmative action by the Central and State Government inequality of educational opportunities is a reality that is persisting in India for generations. Using data from 64thround of National Sample Survey (2007-08) we have examined the education inequality among social groups in EAG states of India. Concentration index (CI) gives the education inequality among social groups and binary logistic regression gives the association between social status and education enrollment. Results shows that there is lowest inequality in enrollment in elementary education and highest inequality in graduation and above.Social gradient in education inequality is highest for the secondary and higher education followed by elementary education. Surprisingly, by social group inequality of enrollment in graduation and above education is lowest than higher secondary and lower education. This might be due average low level of graduation and above enrollment in all EAG states. Hence, government policy should be focused to first, reducing educational inequality in enrollment in secondary and higher secondary education; second, to increase average enrollment in graduation and above education.

In 1997 the government of Uganda introduced the policy of Universal Primary Education – UPE whose aim was to improve on school enrollment. Equal opportunity and access to education is a central theme in the political agenda of government of Uganda, indeed universal access to primary education is MDG Goal II, which governments world over are striving to achieve. Research has not established whether inequalities in access to education still exist a decade after UPE was introduced in the country. Using data from the Uganda National Household Survey 2009/2010, this paper attempts to examine this issue. A total of 12,424 children of ages 6-17 years are selected for study. An index of dissimilarity and a binary logistic regression are fitted to the data, adjusted for a number of social and demographic characteristics. The findings suggest that 81% of the children were currently attending school. Gender disparities in enrollment were not significant in the regression model. However, substantial and significant differences were observed for the various regions of the country, among the poor, and household size. Although not all factors affecting current enrollment among children were analyzed, the discourse in this paper suggests need for intervention to address enrollment inequalities.

Present paper is an attempt to understand the patterns of inequality in attaining higher education, and specifically how these patterns differs from different socioeconomic groups as well as across the states in India. Analysis has been done using the Indian Human Development Survey, 2005. Findings show that in different socioeconomic standing, quite significant differences were found in the attainment of higher education. Women in younger ages were more educated as compared to their counterparts. Women residing in urban areas and belonging to better-off families were having higher levels of education. States like Rajasthan, Bihar, Uttar Pradesh and Madhya Pradesh are more disadvantaged in regards to education of women as these states are having poor socioeconomic background. However, in states like Kerala, Assam, Karnataka, Tamil Nadu, Maharashtra and Punjab, a better picture is visible in terms of higher education. But overall, as level of education increases the proportion of women receiving it decreases, which clearly depicts the inequalities in receiving higher education. In India, very few women got the opportunity to complete their bachelor’s or master’s degree. Thus, there is an urgent need to formulate appropriate policy measures which can benefit women who are equally responsible for building the nation’s future.