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Volatility of Education Aid and Female Education

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Advances in Cross-Section Data Methods in Applied Economic Research (ICOAE 2019)

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Abstract

Positive contributions of females to economic growth cannot be denied and they can contribute more effectively to economic development if they get a better education. Thus, it is essential to explore the different ways of enhancing female education and reducing the gender gap. Such actions can be even more crucial in low-income countries where the need for higher economic growth is more pressing. The important point for these countries is that the scope and quality of education are highly dependent on foreign aid on education. This paper empirically investigates the link between schooling of female students and the volatility of foreign aid on education to better understand the impact of aid on female education and the ways of improving it. The results show that the share of female students increases with declining volatility of foreign aid in low-income countries. Another interesting finding is that the volatility of education aid also affects total students, but this effect is relatively weak when compared to female students only. The dataset covers the years 2002–2016 and 27 low-income countries from Africa and Asia.

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Notes

  1. 1.

    For a review of empirical evidence on the positive effect of human capital on development, and methodological issues in assessing that link, see Stevens and Weale (2004), Hanushek and Woessmann (2012), and Glewwe et al. (2014).

  2. 2.

    See Data Appendix for details on variables.

  3. 3.

    It should be noted that, in addition to annual data, both cross-section regressions and regressions with 5-year averages are also considered. Cross-section analysis including country averages could not capture the negative effect of the volatility of education foreign aid on education outcomes. This finding indicates that the time dimension is important to capture the link between the volatility of education aid and education outcomes. Given that the time period is short due to the limited availability of the detailed classification of foreign aid from the data sources, a sufficient number of observations could not be obtained with 5-year averages for robust panel regressions. Thus, these two results are not reported in this paper.

  4. 4.

    A report by International Labor Organization (2018) finds that globally women continue to be paid approximately 20 percent less than men.

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Correspondence to Nihal Bayraktar .

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Data Appendix—Variable Definitions and Sources

Data Appendix—Variable Definitions and Sources

(Note Definitions are copied from the data sources)

  • Number of female and male students in secondary education: Secondary education, female and male pupils: Secondary education male and female pupils are the total number of pupils enrolled at secondary level in public and private schools. Source: World Bank’s World Development Indicators (WDI); African Development Indicators (ADI).

  • School enrollment, secondary, female (% net): Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers. Source: Data from WDI and ADI

  • Number of students in secondary education in % of population: Number of students in secondary education divided by total population from WDI

  • Education aid (gross disbursements): Education, total (gross disbursements) in current US dollars. Source: OECD’s Creditor Reporting System (CRS)

  • Education aid (in % of GDP): Education aid (gross disbursements) divided by GDP from WDI (in %)

  • Volatility of education aid (in % of GDP): Rolling standard deviation of education aid in percent of GDP over 3-year overlapping sub-periods

  • Mortality rate, under-five (per 1000 live births): Under-five mortality rate is the probability per 1000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year. Source: World Bank’s WDI

  • Pupils/teachers ratio (in %): Pupil-teacher ratio, secondary: Secondary school pupil-teacher ratio is the average number of pupils per teacher in secondary school. Source: World Bank’s WDI and ADI

  • GDPPC (in constant 2010 dollars): GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2010 US dollars. Source: World Bank’s WDI

  • Urban population (% of total): Urban population refers to people living in urban areas as defined by national statistical offices. The data are collected and smoothed by United Nations Population Division. Source: World Bank’s WDI

  • Life expectancy: Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. Source: World Bank’s WDI

  • Public education spending (in % of GDP): Government expenditure on education, total (% of GDP): General government expenditure on education (current, capital and transfers) is expressed as a percentage of GDP. It includes expenditure funded by transfers from international sources to government. General government usually refers to local, regional and central governments. Source: Authors’ calculation with data from the World Bank’s WDI and ADI.

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Bayraktar, N. (2020). Volatility of Education Aid and Female Education. In: Tsounis, N., Vlachvei, A. (eds) Advances in Cross-Section Data Methods in Applied Economic Research. ICOAE 2019. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-38253-7_2

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