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The provision of high-quality education and health care to all of the population is considered a core element of public policy in most countries. In India, the government is active in both education and health but the private sector also plays an important role, notably for heath, and to a lesser extent in education. At present, the quality and qua...
Citations
... There are numerous references in the literature to results that link household wealth and quality of schooling (Checchi, 2006;Glewwe and Kremer, 2006;Figlio et al., 2016). Studies such as those of Desai and Kulkarni (2008) and Asadullah et al. (2009) show that despite significant growth in school enrolment in India (Dougherty and Herd, 2008), the widening of wealth inequality that has been observed over the course of the last two decades may have had an effect on the academic performance of poorer children along the lines that we describe in this article. Aspects of school quality such as teacher-pupil ratio (Case and Deaton, 1999) and teacher quality (Rothstein, 2010;Rivkin and Schiman, 2015) could also be contributing to the performance gap between children from poorer and wealthier households-partly because allocation into high-quality schools is influenced by family socioeconomic background. ...
We use data from the Young Lives longitudinal survey to analyse the effect of socioeconomic conditions and gender on the educational performance of young children in India. In particular, we use data for standardised scores on two cognitive tests: the Peabody Picture Vocabulary Test (PPVT) and a maths test. Our results show that there are significant gender differences in the way that household wealth affects the educational performance of children. Specifically, boys born into wealthier households perform significantly better in maths than those from worse‐off economic backgrounds. The effect of wealth on the PPVT is stronger for girls than it is for boys. The results are robust across a range of specifications. The effect of household wealth on performance differed between the genders, even when we focused our analysis on the bottom 10% and top 10% of the performance distribution. One possible explanation for these differences is parental aspirations. We tested this hypothesis and found that boys from wealthier households with higher parental educational aspirations are positively and significantly associated with higher maths scores. Further analysis showed that the moderating role of parents’ educational aspirations was more pronounced at the top of the test score distribution, an indication that more able children are associated with wealthier and more ambitious parents.
... Pakistan is world's sixth most populous country comprising of around 207.7 million inhabitants living in 32.2 million households. The negative impacts of growing population are reversible only through human capital formation (Sarwar et al. 2013) because of its direct link with earning ability of the poor on one side (Yamauchi 2010;Johnson and Li 2010) and improvement in living standards of people in a country on the other side (Dougherty and Herd 2008). But an important element in the promotion of human capital is educational capital (Guichard and Larre 2006;Afzal et al. 2011), which not only fasters economic growth in a country (Jehan 2000) but also reduces poverty (Afzal et al. 2011;Montenegro and Patrinos 2014). ...
This paper is aimed at to ascertain the relationship between education of head of the households and their financial vulnerability using data comprising of 17,031 households obtained from Household Integrated Economic Survey 2015–2016 in Pakistan. We have compiled three measures of financial vulnerability at household level i.e. financial margins excluding and including the rental payments and Financial Vulnerability Index (FVI). According to the results, proportion of financially vulnerable households in both measures of financial margin declines along with increase in level of education of the head of households and stands at 66% and 77% for no formal education of the head, 56% and 70% for primary, 42% and 61% for secondary, 27% and 44% for higher secondary, 14% and 32% for graduate and 13% and 24% for post graduate levels of education. FVI results indicate that out of 2504 highly vulnerable households i.e. falling in the bottom 10% of the distribution, 63.8% were those with no formal education of their heads followed by 19.3% with primary, 14.3% with secondary and 1.9% with higher secondary level of education. Further, various levels of education and individual characteristics such as marital status, gender, region, province and employment status of the heads, have been emerged as significant determinants of financial vulnerability in all three estimated measures along with household’s income, consumption, savings and rental payments. Findings of the study calls for greater human capital investment both by households and the government of Pakistan in order to stabilize the financial conditions of the households at micro level, which in turn can promote stability and resilience at macro level.
... There has been a significant increase in educational attainment in India in the 50 years since the formation of the union in the middle of the twentieth century (Dougherty and Herd 2008;Kingdon 2007). Adult literacy rate rose from 18% of the population in the history of dispossession of land rights, occupational segregation in low-status jobs and other forms of restrictions in social life. ...
There has been significant progress in educational attainment in India since its independence. Yet the achievements are low in comparison to countries in similar stages of development. The situation is worse among groups who have a history of exclusion. Children from these groups have lower enrollment and higher dropout rates than national averages. Yet some of them are able to overcome these limitations and show academic resilience. Using data from the Indian Human Development Survey (2005), we study the role of the different child, household, and school-level factors associated with academic resilience among these children. Further, to understand the mechanism through which group membership affects resilience we also study the indirect effect of group membership mediated through those factors. We find that the protective factors vary across the different disadvantaged groups. The main effect of group membership is through structural factors like poverty and maternal education. Yet, the child level and household level factors play an important role in most cases. Schools fail to play the expected role of being the source of resilience among those who face the strongest burden of structural factors. For some, the schools are the main site where they experience most of the adversities of group memberships. The results highlight the need for educational policy, which addresses the importance of schools as drivers and determinants of academic resilience.
... According to Sarwar, et al., (2013) human capital formation is the only way to reverse the negative impacts of growing population for a developing country like Pakistan because it directly improve earning ability of the poor (Son, 2010;Yamauchi, 2010). Human capital is also a fundamental factor for the improvement of living standards of people in a country (Dougherty & Herd, 2008). But, a fundamental challenge in fostering human capital formation lies in promoting the educational capital (Guichard & Larre, 2006). ...
The objective of this paper is to analyze the gender earning gaps existing in urban areas of Pakistan using data from a household survey. The earning functions have been estimated separately for males and females using Ordinary Least Squares (OLS) as well as quantile regressions including education, literacy, experience, employment related variables such as type of industry and occupation and age as explanatory variables. The earning gaps between males and females have also been analyzed using the Blinder-Oaxaca decomposition method. Results suggest higher mean earnings for males as compared to females but higher incremental returns to investment in human capital for females at all levels of education. Further, higher returns to schooling have also been noted in bottom part of the income distribution i.e. 5th& 25th quantiles for workers of both sexes as compared to those present in the top of the distribution i.e. 75th& 95th quantiles at all educational levels. Education, industry of employment and occupations has been emerged as the main determinants of income gap between male and female workers in urban Pakistan.
... The program is funded by the central government, with the support of some international organizations. The budget of SSA program for 2002-2006 was equal to 0.3 percent of GDP of the country (Dougherty and Herd, 2008). ...
... For example, the government-funded "Mid-day meals" program provides subsidized food in schools. Furthermore, in 2006 the government passed a law prohibiting children 14 years and younger to engage in low paid work instead of attending school (Dougherty and Herd, 2008). ...
Purpose
The goal of this article is to conduct macro‐level analysis of human capital (HC) development strategies, pursued by four countries commonly referred to as BRICs (Brazil, Russia, India, and China).
Design/methodology/approach
This analysis is based on comparisons of macro indices of human capital and innovativeness of the economy and a review of related academic literature and government publications.
Findings
The study results suggest that in terms of present human capital capacity Russia and Brazil are ahead of China and India. However, during the last decade the governments of the latter two countries have initiated impressive national programs of HC development, which include significant investment and targeted government regulation in such areas as primary and secondary education, vocational education and training, and higher education, especially in science and technology fields. Russia and Brazil have targeted programs in some of the above areas, but lack comprehensive long‐term strategies, covering all the above areas and coordinating effort of various agencies and constituencies.
Research limitations/implications
It is recommended to expand the scope of analysis to include other fast growing developing economies (e.g. Mexico, Indonesia, and Turkey).
Originality/value
The article provides, for the first time, a comparison of human capital development indices and strategies of the four largest developing economies. The original feature of the article is a combination of the analysis of macro‐level indices with an in‐depth analysis of policy documents and academic literature.
... Overall enrollment of children in all stages of education in India has improved over the years. Such increase in school participation has been also associated with a significant jump in the literacy rate which rose from 18% in 1951 to 65% in 2001 (Dougherty & Herd, 2008). The growth in enrollment has taken place amidst the introduction of various centrally sponsored educational interventions. ...
... Andhra Pradesh also hosts one of the largest Anganwadi systems in India, which brought children from poor households into schools. While in some states such initiatives have led to significant growth in school enrollment, large disparities in educational achievement across Indian states remain -about two-thirds of the children who do not attend school are in five of the poorest states: Bihar, Uttar Pradesh, West Bengal, Madhya Pradesh, and Rajasthan (Dougherty & Herd, 2008). ...
This paper documents the extent of inequality of educational opportunity in India spanning the period 1983-2004 using National Sample Survey (NSS) data. We build on recent developments in the literature that has operationalized concepts in the inequality of opportunity theory (including Roemer's) and construct three indices of inequality of educational opportunity using data on an adult sample. Irrespective of the index used, the state of Kerala stands out as the least unequal in terms of educational opportunities. However, even after excluding Kerala, significant inter-state divergence remains amongst the remaining states. Transition matrix analysis confirms substantial inter-temporal mobility in inequality of opportunity across Indian states. Rajasthan and Gujarat in the West and Uttar Pradesh and Bihar in the Centre experienced large-scale fall in the ranking of inequality of opportunities. However, despite being poor, Eastern states of West Bengal and Orissa made significant progress in reducing inequality of opportunity. At a region level, Southern, North-eastern and Eastern regions on average experienced upward mobility (i.e. decline in inequality of opportunity) whilst the Central region experienced downward mobility. We conclude by examining the link between progress towards equality of opportunity and poverty reduction, growth and a selection of pro-poor policies.
... Overall enrollment of children in all stages of education in India has improved over the years. Such increase in school participation has been also associated with a significant jump in the literacy rate which rose from 18% in 1951 to 65% in 2001 (Dougherty & Herd, 2008). The growth in enrollment has taken place amidst the introduction of various centrally sponsored educational interventions. ...
... Andhra Pradesh also hosts one of the largest Anganwadi systems in India, which brought children from poor households into schools. While in some states such initiatives have led to significant growth in school enrollment, large disparities in educational achievement across Indian states remain -about two-thirds of the children who do not attend school are in five of the poorest states: Bihar, Uttar Pradesh, West Bengal, Madhya Pradesh, and Rajasthan (Dougherty & Herd, 2008). ...
... De la Fuente and Jimeno [6] show a framework that combine the discounting method with the wage estimation and other premium in the labour market, taking into account the worker training and the worker education. It becomes interesting the number of factors that have been combined in order to construct comprehensive measures of benefits flow and costs of education. ...
... The opportunity cost of schooling, ie, future earnings and experience in the labour market due to the greater number of years of schooling and The direct cost of schooling, mainly tuition and other costs incurred during the enrollment agent. Other assumptions that De la Fuente and Jimeno [6] in their approach and to consider whether to apply to our case, are: ...
... On De la Fuente and Jimeno [6] proposal, and in the context of our country, it should be noted that the labour market in the software industry, is not evident that a person ends their tertiary education or university before entering the job market. Quite the opposite, and this becomes a threat to the students that many times or are severely delayed in her career, or drop out, staying in a level in which only the increase in their experience and hours worked, can make his salary and other conditions related to work become better. ...
In this paper, the human-capital is presented in relationship with the educational system and, also, with the labour market and the software enterprises needs. The problem is analyzed in several other countries so that to can compare it with our particular local situation. It is discussed an approach focusing on measuring the human-capital. Suggestions are proposed to sustain and improve the human-capital in the software industry cluster. Finally, the conclusions are presented, in particular, those that highlight the necessity of a transversal strategic plan in order to improve the human-capital in the high-school, tertiary and university level as well as in the software industry area, in Argentina. 1. WHAT DO WE UNDERSTAND BY HUMAN-CAPITAL? There are several definitions about human-capital. The one we choose in this paper is: Intangible capital's expression that include population's knowledge and population's intellectual abilities, especially of the worker population, which have been acquired by educative and qualification's processes, which make possible the supply of capacities and services for a company or institution. The human-capital has an important role in the economic growth process and individuals possibilities in the labour market are joined with the educative level they have reached (1). In the human-capital theory (2), schooling is seen as an investment decision. One assume that individuals continue in the educative circuit until the point in which the present value of the expected benefits of the additional schooling are equal to it's direct or indirect costs (for example, tuitions, future incomes). One assume that education increases people's productivity and that workers with better education are, then, those who can get higher salaries, under the hypothesis that the work market is perfect and that the work is paid to it's marginal value. The celerity in the creation, dissemination and access to the knowledge has caused the sensible shorten of intervals between knowledge generation and the practical applications of such intellectual creations, which hit sensible in individuals life. Another evident phenomenon is the fast growth and development of computer science technology, which aids in an essential way to the verification of the phenomenon previously enunciated. Finally, the diminution in the communications costs brings a change at the economic activity disposition. In particular, intangible products such as education, investigation and software can surpass certain tangible products. That's why the promotion and investment in innovation as well as in higher education become very important resources for the economic growth of a country. In particular, in the software industry of our country, high levels education developments, with a theoretical and practical preparation to the higher level students, as well as to the active professionals or to those that could be reincorporated to the labour market, become a key need.
The Indian higher education system is said to be the world's third largest. There is evidence of inequalities of educational opportunities. In this article, we compare between two states in India-Karnataka and West Bengal. We observe that the status of education in Karnataka is higher than West Bengal as there are many private university and colleges in Karnataka compared to West Bengal.
This study examines the relationship of public sector social safety nets, social protection and quality of life in Pakistan. Both social safety net and social protection programs are aimed at either helping out the needy, the poor and deprived segments of society to maintain a designated standard of living or to protect them from shocks arising due to global and domestic political, financial and economic fluctuations and thus improves the quality of life of people. Benazir Income Support Program (BISP), being the country's premier safety net program, has more than five million families as its beneficiaries. The government expenditure on social protection has generally been around 1% of the GDP during the 2000s. Further, the quality of life; measured through per capita income, literacy rate, life expectancy at birth and infant mortality rate, has been emerged as having a positive relationship with both social safety nets and social protection programs.
