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Fridays Academy: Education, Poverty Reduction and Economic Growth II

Ignacio Hernandez's picture

Like every Friday, from Raj Nallari and Breda Griffith's lecture notes on Economic Policies for Poverty Reduction.

 

Education, Growth and Poverty Reduction

One of the major contributions to the new economic growth literature has been the recognition that human capital is critical in explaining growth differences across countries, with human capital in turn relying on a strong education system. Education directly benefits the individual and has positive spin-off effects for society in terms of increased productivity, higher rates of innovation and invention, and adaptation of new technologies.  However, the focus on ‘school attainment’ has generated criticism in recent years. Researchers note that while school attainment may be correlated with economic growth, this does not suggest a causal relationship.  Moreover, the relationship is sensitive to alternative estimates of school attainment and the underlying assumptions. 

 

A broader measure of human capital that recognizes its development impact is the quality of schooling.  Hanushek and Kimko (2000) gathered international test scores on mathematics and science knowledge from 1960 and formed these into a composite measure of ‘school quality’ and related this to differences in cross-country growth rates.  Also included in the model were the level of income, quantity of schooling, and population growth.  All of the variables helped in explaining differences in growth rates and the quality of schooling variable proved highly significant. One standard deviation difference in test performance was related to one percentage point difference in annual per capita GDP growth rates (Hanushek, 2005).  Moreover, test scores as a measure of school quality are strongly linked to an individual’s earnings and productivity—the higher the test scores, the higher the earning advantage.  Although the research has come predominantly from the developed countries, it appears to hold for developing economies also (Hanushek, 2005).

 

However, human capital in many developing economies starts from a very low base and it faces many challenges, both in terms of quantity and quality.  Its importance for economic growth and poverty reduction is critical and this has been recognized in the global initiatives aimed at improving access and quality, e.g. the UPE Initiative (that aims for universal primary education for all by 2015) and the education goal in the MDGs as well as the Fast Track Initiative endorsed by the World Bank.

 

In terms of quantity, there are a number of reasons why school attainment remains of interest.  Although overall education rates have increased, they hide disparities with regard to family income, gender and geographic location.  Furthermore, the rates are often exaggerated due to the high incidence of repeat students. 

 

Net Primary Enrollment Ratios

chart 

                              Source: Cohen and Bloom (2005)

 

Exhibit above examines net primary enrollment rates.  The net enrollment rate (NER) is the ratio of the number of children in the official primary school age group enrolled in primary education to the population of the primary school age group.  The NER for developed countries was 96 percent in 2002 compared to 83 percent for developing economies. Among the developing regions, Sub-Saharan Africa had the lowest NER, just 63 percent compared to 96 percent for Latin America and the Caribbean. The exhibit shows, however, that the NER has increased the most between 1998 and 2002 in Sub-Saharan Africa and South and West Asia reflecting increasing school attendance. 

 

A less strict standard than the NER is the gross enrollment rate (GER), which captures the ratio of the number of children enrolled in primary education, regardless of age, to the population of the age group that corresponds to the nationally-defined ages for primary schooling.

 

GER for Africa, various years

GER

Source:   Compiled from Fredriksen, 2005

 

The GER for Africa has increased remarkably since the 1990s—from 73 percent in 1992 to 83 percent in 2000 and 91 percent in 2002, with partial data for more recent years confirming a continued increase. However, given the grade repetition rate of 20 percent, the Africa region needs a GER of 120 percent to enroll all children of primary school age (Fredriksen, 2005).

 

Other advances in school enrollment noted by Cohen and Bloom (2005) are the increase in literacy among developing countries, from 25 to 75 percent in the 20th century and the increase in the average years of schooling from 2.1 to 4.4 years.  Furthermore, the number of students enrolled in secondary school increased from 50 million to 500 million over the past 50 years.

 

Although overall education rates have increased in developing countries, they still remain far short of what is needed.  Furthermore, enrollment in developing countries does not mean attendance and attendance is not necessarily an iron cast predictor of receiving an education, never mind a high quality education. Standardized test scores show a huge disparity between children from industrialized countries and those from developing countries.  The global commitment to achieve UPE as outlined in the MDGs and even broader education goals agreed at Dakar for 2015 is a response to the unacceptable situation in which[1]:

  1. Over 100 million primary school-age children are out of school; 

  2. Roughly 380 million children are not enrolled in school (28 percent of the age group, typically 6);

  3. Roughly 280 million children are absent from secondary school;

  4. Of school-age children who enter primary school in developing countries, more than one in four drops out before attaining literacy;

  5. Less than one-third of children in Africa and South Asia can read and write.

  6. One-in-five children in primary school repeat grade in Africa;

  7. 150 million children in school are likely to drop out before completing primary school;

  8. More than half of all girls in Africa never enroll in school;



[1] Sources for these data are: 2,3,4,6 Cohen and Bloom (2005) and 1,5,7,8 Sperling and Balu (2005).