- Top charities
Published: November 2010
In reviewing the evidence for education programs, we observe that:
If you're committed to the cause of education, we recommend that you investigate the following questions for any charity you are considering:
Our top-ranked developing-world education charity is Pratham. Pratham has, in the past, shown a commitment to rigorous evaluation of its programming. This commitment does not by itself answer all the questions above, but to us it implies an organizational commitment to learning about what works and holding itself accountable. This charity has been closely involved with some of the studies discussed below1 and has completed a number of projects that have been evaluated by the Poverty Action Lab at M.I.T.2
We have not identified any other charities in this area with compelling evidence of impact or answers to the other key questions above.
Here we review available information about programs seeking to improve school-based education in the developing world. We rely mostly on a literature review (Glewwe and Kremer 2006) on the subject.3
Based on our review of the evidence, we believe that:
Many charities focus on building schools and/or providing scholarships to offset private school fees (which are common in the developing world4). Charities we considered that focus primarily on these activities include:
A major concern with programs like these is that they may accomplish little if the schools are of low quality, and available research implies that the quality of schooling in the developing world is often extremely poor (well beyond what is considered "poor" in the U.S.)
Research on school building is slightly encouraging, but relatively sparse and confined to a few specific places and times. In order to have confidence in a charity focused on school building, we would need a solid understanding of the communities in which the schools are being built (in particular, who is likely to staff them and what quality controls will be in place - see above).
Studies from Bangladesh and Pakistan show mixed results of scholarships on school enrollment/completion (the Pakistan study concludes success for urban areas and failure for rural areas; the Bangladesh study concludes the program was successful in raising enrollment rates). They do not examine impact beyond enrollment/attendance and may not be correctly identifying the effect of the scholarship programs, as opposed to other changes taking place at the same time.18 A merit scholarship program (discussed below) was found to have encouraging effects.
As with school building, we would need substantial information about a community and school system to feel confident that a scholarship program is improving educational outcomes for students.
Another concern regarding scholarships is that they may lead to increased class sizes, which could degrade the quality of education (see "Improving teacher:pupil ratios" below).
Some charities attempt to improve the quality of schools, or even in some cases to run their own schools in the developing world.
There is little strong evidence regarding what sorts of programs have been successful in the past (in terms of raising graduation, test scores, and/or later life outcomes). As with U.S. education, many studies have significant flaws due to selection bias and other concerns.19 Here we summarize the results from stronger studies of improving developing-world schooling. Many apparently logical programs, including provision of textbooks/supplies, have had mixed or no effects.
The very limited existing evidence implies that providing school supplies is not, by itself, key to improving school quality.
Some programs seek to hire more teachers in order to lower class sizes. Past examinations of this approach have found positive effects on enrollment/completion and mixed effects on test scores.
Impact on literacy/numeracy as measured by test scores was not examined. 28
A rigorous evaluation of a "pay-for-performance" program in Kenya found discouraging results implying that it mostly led to "teaching to the test." Schools were randomly selected to participate in the program, which "offered teachers prizes based on their schools' average scores on district-wide exams" (while penalizing them for dropouts). The program led to improved test scores in the short term, but the largest improvements were on the most memorization-dependent tests, and no lasting improvement was discernible a year after the program ended. It appeared that teachers responded to the program largely by conducting outside-of-school test prep sessions.29
Randomized evaluations have found encouraging effects for four programs that appear to us to be relatively rare among charities. Two of these programs are focused on health/nutrition rather than pedagogy.
All of the studies discussed above focus on very short-term impacts on results such as school attendance, completion, and test scores. However, a major question of ours is whether, when, where and how children in developing countries ultimately benefit from the skills taught in school.
We would guess that education is often highly beneficial, partly based on our informal observations and discussions. However, we have little to go on in checking this view or in assessing under what circumstances/in what ways education is most beneficial.
Higher-education enrollment rates in South Asia and Africa are extremely low (under 10% for the regions as a whole, and possibly lower for the areas most likely to be focused on by charities),36 and a recent review states that there is inadequate "empirical knowledge of what is happening within universities and to the students who spend a considerable part of their prime years there."37 As for the usefulness of a pre-university degree, we have seen little empirical evidence and would guess that it depends heavily on the specifics of the region.
A large number of studies have linked education levels to earnings levels in the developing world, but nearly all of them suffer from serious selection bias issues, since those who complete more years of education are likely to have many advantages over those who don't (for example, higher socioeconomic status and more favorable locations). Three relatively recent papers on this topic note this problem with past research, while attempting to draw more valid conclusions about the connection between education and earnings; we find all three problematic, but even if one accepted their conclusions at face value, they show mixed results in a limited number of regions.
We find this analysis to have similar problems to the study cited directly above.
"Nongovernmental organizations in developing countries may be very well placed to conduct randomized evaluations. Unlike governments, NGOs are not expected to serve entire populations. Also unlike governments, financial and administrative constraints often lead NGOs to phase in programs over time, and randomization will often be the fairest way to of determining the phase-in order. In contrast to developed countries, where NGOs typically do not have sufficient resources to conduct large programs that could serve as a model for public policy, this is not the case in developing countries. Since many NGOs exist and they frequently seek out new projects, NGOs willing to conduct randomized evaluations can often be found. ...
A second example is the collaboration between the Indian NGO Pratham and researchers from the Massachusetts Institute of Technology that led to the evaluations of the remedial education (Banerjee 2000) and computer-assisted learning programs (Banerjee 2004). However, while NGOs are well placed to conduct randomized evaluations, expecting them to finance the research is less reasonable, as the results are global public goods. ... In the case of the Indian educational programs, Pratham found a corporate sponsor, India's second-largest bank, ICICI Bank, which was keenly interested in evaluating the impact of the program and helped finance part of the evaluation." Glewwe and Kremer 2006, Pg 53.
J-PAL, "Pratham." Two other J-PAL partners, ICS Africa (J-PAL, "International Child Support (ICS) Africa") and Seva Mandir (J-PAL, "Seva Mandir") have also had some education projects reviewed by J-PAL. Donors should note that these organizations have a broader scope than Pratham, implementing projects including health, economic empowerment and other activities.
This paper criticizes the "retrospective study" methodology (Pgs 14-17), and favors the "natural experiment/randomized trial" methodology (Pgs 17-18). In general, we address all the studies it includes in the latter category, with the exception of three studies that were done on data from Israel (country-wide) in the 1990s; we don't feel that Israel is appropriately included in the "developing-world" category we focus on.
"This low spending on primary and (to a lesser extent) secondary education in developing countries often implies that households bear much of the cost of that education. Thus parents, rather than the school or ministry of education, are responsible for providing many basic school inputs such as textbooks, chairs, and even the school building itself. Some of these costs are the collective responsibility of parents, but some are passed on to parents through official or unofficial school fees or by requiring parents to purchase uniforms and textbooks for their children. Data on such costs are not available for many countries, but a few examples are worth considering, although it is worth bearing in mind that they may not be representative. In Jamaica, government expenditures per primary school student are US$221 while private expenditures are $178 (Planning Institute of Jamaica, 1992). In the Philippines, the analogous figures are $110 and $309 (Asian Development Bank, 1999), and for Vietnam they are $23 and $14 (World Bank, 1997b). These figures include private school costs." Glewwe and Kremer 2006, Pg 9.
One Kid One World, "Homepage."
Orphans of Rwanda, "Homepage."
Root Foundation, "Homepage."
"The quality of schooling in developing countries is often very low. Grade repetition and leaving school at an early age are common, teachers are often absent from classrooms, and many children learn much less than the learning objectives set in the official curriculum (Lockheed and Verspoor, 1991; Harbison and Hanushek, 1992; Hanushek, 1995; Glewwe, 1999). Visitors from developed countries are often shocked at the conditions in many (but not all) schools in developing countries. Many schools lack the most basic equipment and school supplies—textbooks, blackboards, desks, benches, and sometimes even classrooms (in which case classes meet outside and are cancelled when it rains). In rural areas of Vietnam's Northern Uplands region in 1998, 39 percent of primary school classrooms did not have blackboards. In India in 1987, more than 8 percent of schools did not have a building in which to meet (World Bank, 1997). Teacher quality and availability is also a common problem. In rural areas of Northeast Brazil in the early 1980s, 60 percent of primary school teachers had not even completed primary education (Harbison and Hanushek, 1992). Shortages of teachers and school buildings can result in double shifts (which shorten the school day for individual pupils) or very large class sizes. In Vietnam, more than 90 percent of children in rural areas attend schools with two or more shifts, resulting in an average class time of only 3 hours and 10 minutes per day (Glewwe, 2004). In districts with low literacy rates in the Indian State of Tamil Nadu, the average class size in primary school was 78 students (World Bank, 1997). Teachers often have weak incentives and little supervision, and their absenteeism runs high. Chaudhury et al. (forthcoming) reports that when enumerators made surprise visits to primary schools in six developing countries, on average (across these countries) about 19 percent of teachers were absent. Beyond absence, many “present” teachers were found to not be actually teaching; for example, in India one quarter of government primary school teachers were absent from school, but only about half of the teachers were actually teaching in their classrooms when enumerators arrived at the schools." Glewwe and Kremer 2006, Pg 2.
"A team of researchers who visited schools in India (PROBE Team, 1999) found some teachers who kept schools closed or nonfunctional for weeks or months at a time, drunken teachers, and a headmaster who expected the students to perform domestic chores and babysit. Sexual abuse of female students by teachers is a problem in several countries. To the extent that teachers do have incentives, these incentives are often focused on exam scores. Teachers often instruct by rote, sometimes copying from textbooks onto the blackboard and having students copy from the blackboard onto notebooks or slates. In many countries, teachers offer, and pressure parents to pay for, “extra lessons” after school or on weekends to prepare students for important examinations (Bray, 1999). In such situations, increased teaching effort at school could reduce the demand for extra lessons, and thus teacher income." Glewwe and Kremer 2006, Pg 10.
"Another unusual characteristic of many developing countries is that students are taught in a language that is not their mother tongue. This primarily reflects the fact that almost all developing countries were once colonies of developed countries, and their school systems still embody many elements of the systems developed under colonial rule. Many Sub-Saharan African countries use English or French as their national language, and most of India's 1 billion inhabits are not native speakers of either of the two official national languages (Hindi and English). Given the heterogeneity in educational background, school quality, and language within many developing countries, designing a single curriculum appropriate for all students is difficult for any country. Yet most developing countries have a single centrally set curriculum, often geared to the needs of relatively elite students, which leaves many other students behind. This contributes to the poor performance of a significant percentage of students on national examinations and to high dropout and repetition rates. For example, in Tanzania between 1997 and 2001, only 22 percent of the students who attempted were able to pass the primary education final examination, and only 28 percent of those who attempted passed the certificate of secondary education exam (Tanzania Media Monitoring, 2002)." Glewwe and Kremer 2006, Pg 10.
"A retrospective study in Ghana by Glewwe and Jacoby (1994) presents evidence on the impact of distance and school quality on the years of schooling of individuals aged 11 to 20, using data collected in 1988-89 on household, school, and teacher characteristics. To estimate the impact of school characteristics and other factors on years of schooling attained, an ordered probit specification was used that allows for right censoring. According to the study findings, years of schooling was reasonably responsive to school quality. The estimates indicate that years of completed schooling could increase by 2 to 2.5 years by raising average teacher experience (from 2 years to 10 years), repairing leaking roofs, reducing travel time (from 2 hours to a few minutes), or providing blackboards to schools without them. Since repairing roofs and providing blackboards is much less expensive than building new schools, these results suggest that repairing classrooms in Ghana is a more cost-effective means of increasing the quantity of schooling than building new schools to reduce travel time.
Although the results from the Ghana study appear plausible, the estimates could be biased for a number of reasons. The data had 18 school and teacher variables, but schools can differ in many more ways, which raises the problem of omitted variable bias. Measurement error in these variables is also a potential problem, either because the assumption that they change little over time is false or because errors were made in collecting the data. Finally, no attempt was made to avoid bias due to endogenous program placement.
In a retrospective study in Tanzania, Bommier and Lambert (2000) found that distance to school had a significantly negative effect on years of schooling, while the quality of Swahili teaching had a positive effect. However, the authors note some problems with measurement error in these variables. For example, many households reported implausible distances to the nearest primary schools, sometimes more than 100 kilometers. Moreover, since school characteristics were averaged over responses given by households, there could be systematic bias. For example, parents may 'justify' a decision to allow a child to drop out of school by claiming that the local school was of low quality (in the Ghana study school quality variables were collected from schools, not households). Finally, given that there are only four school quality variables, there are serious concerns of omitted variable bias." Glewwe and Kremer 2006, Pgs 21-22.
"Between 1973–1974 and 1978–1979, 61,807 new schools were constructed (Table 1, panel B), at a cost of over 500 million 1990 U.S. dollars (1.5 percent of the Indonesian GDP in 1973). This represented more than one school per 500 children aged 5 to 14 in 1971, which reportedly makes INPRES the fastest primary school construction program ever undertaken in the world (World Bank, 1990)." Duflo 2001, Pg 797.
Full methodology laid out in Duflo 2001, Pgs 797-799.
"The identiï¬cation assumption should not be taken for granted: The pattern of increase in education could vary systematically across regions. In particular, there could be mean reversion. However, an implication of the identiï¬cation assumption can be tested because individuals aged 12 or older in 1974 were not exposed to the program. The increase in education between cohorts in this age-group should not differ systematically across regions. In Table 3, panel B, I present this control experiment. I consider a cohort aged 18 to 24 in 1974 and a cohort aged 12 to 17 in 1974. The estimated differences in differences are very close to 0. These results provide some suggestive evidence that the differences in differences are not driven by inappropriate identiï¬cation assumptions, although they are imprecisely estimated." Duflo 2001, Pgs 798-799.
"An individual young enough, born in a high program region, received on average 0.12 more years of education, and the logarithm of his wage in 1995 was 0.026 higher. These differences in differences are not significantly different from 0." Duflo 2001, Pg 798.
"Research on girls' scholarship programs is limited but suggests that scholarships can have major impacts on girls' enrollment rates. Research on a small fellowship program in Pakistan that subsidized girls' primary education in private schools was shown to be successful in urban areas but a failure in rural areas (Kim, Alderman, and Orazem, 1999; Alderman, Kim, and Orazem, 2003). A national scholarship program for girls in rural Bangladesh increased girls' enrollment rates even after controlling for other measurable influences (World Bank, 2001b). Because with economic development enrollment of girls usually rises (and the gender gap between boys' and girls' enrollments narrows), it is potentially very problematic to draw conclusions from before and after comparisons of girls' enrollment rates. This difficulty highlights the need for randomized evaluations of such programs." Glewwe and Kremer 2006, Pg 28.
See Glewwe and Kremer 2006, Pgs 29-34 for an overview.
"Glewwe, Kremer, and Sylvie Moulin (2003) find no evidence that provision of official Kenyan government textbooks increased scores for the typical student. However, they do find evidence that textbooks led to higher test scores for the subset of students who scored well on a pretest. The authors note that English, the medium of instruction in Kenyan schools and the language in which textbooks were written, was the third language for most pupils, and cite evidence that many pupils had difficulty reading the books. As discussed further below, there is reason to think that the Kenyan curriculum is not appropriate for the typical student in rural areas." Glewwe and Kremer 2006, Pg 38. This appears in a section entitled "Randomized evaluations."
"Given the results with textbooks, the NGO tried providing an alternative input, flip charts that presumably were more accessible to weak pupils." Kremer 2003, Pg 5.
"A third Kenyan study, not discussed above, is Glewwe and others (2004). It examined flip charts: large poster-sized charts with instructional material that can be mounted on walls or placed on easels. This intervention, which was not examined in Section IV because it did not evaluate the impact of flip charts on any indicators of the quantity of schooling, covered 178 primary schools, half of them randomly selected to receive flip charts covering science, mathematics, geography, and health. Despite a large sample size and 2 years of follow-up data, the estimated impact of flip charts on student test scores is very close to zero and completely insignificant. In contrast, several conventional OLS estimates, which may suffer from many of the problems described in subsection III.B, show impacts as large as 0.2 standard deviations, 5 to 10 times larger than the estimates based on randomized trials." Glewwe and Kremer 2006, Pg 38. (The study itself confirms that were chosen at random.)
"Jamison and others (1981) conducted a randomized trial in Nicaragua in which 48 first-grade classrooms received radio mathematics instruction, 20 received mathematics workbooks, and 20 served as a comparison group. After 1 year, on mathematics tests the radio students scored more than one standard deviation higher, and the workbook students about a third of a standard deviation higher, than students in the control group. Both differences were highly statistically significant." Glewwe and Kremer 2006, Pg 37.
"Kremer and others (2002) conducted a randomized trial in rural Kenya to evaluate a program in which a nongovernmental organization (NGO), Internationaal Christelijk Steunfonds Africa (ICS), provided uniforms and textbooks and built classrooms for 7 schools randomly selected from a pool of 14 poorly performing schools. Dropout rates fell considerably in the 7 schools selected for participation, and after 5 years pupils in those schools had completed about 15 percent more years of schooling. In addition, many students from nearby schools transferred into program schools, raising class size by 50 percent. This suggests that students and parents were willing to trade off much larger class sizes for the benefit of free uniforms, textbooks, and improved classrooms. The authors argue that the main reason for the increase in years of schooling is most likely the financial benefit of free uniforms. A randomized trial of textbook provision in Kenya, discussed in the next subsection, showed almost no impact of textbooks on the quantity of schooling, and while the new classroom construction may have had an impact, the first new classrooms were not built until the second year of the program, while dropout rates fell dramatically in the first year. Anticipation of later classroom construction may have influenced these results, but the authors doubt it, because effects were present for students in the upper grades who would have finished school by the time the classrooms were built." Glewwe and Kremer 2006, Pg 24.
"The program schools attracted a large influx of pupils from neighboring schools, increasing average class size by 8.9 students." Glewwe and Kremer 2006, Pg 47.
Glewwe and Kremer 2006, Pg 27.
"Banerjee and others (2000) used a randomized evaluation to examine the impact of a program in India that attempted to raise school quality by hiring additional teachers, especially female teachers. An Indian NGO, Seva Mandir, runs nonformal schools that teach basic numeracy and literacy skills to children who do not attend formal schools and, in the medium term, attempts to “mainstream” these children into the regular school system. These schools are plagued by high teacher and child absenteeism, so the NGO decided to evaluate the impact of hiring a second teacher (where possible, a woman) in the hope of increasing the number of days the school was open, increasing student attendance, improving performance through individualized attention to students, and making school more attractive to girls. The program reduced the number of days a school was closed (one-teacher schools were closed 44 percent of the time, whereas two-teacher schools were closed 39 percent of the time), and girls' attendance increased by 50 percent. However, the program had no significant effect on the attendance of boys." Glewwe and Kremer 2006, Pg 27.
"Glewwe, Ilias and Kremer (2004) do this, examining a randomized evaluation of the impact of a teacher incentives program in Kenya on both teacher behavior and test scores. They consider a model in which teachers can invest both in efforts to promote long-run learning and in short-run manipulation of test scores. Data were collected on many types of teacher effort—attendance, homework assignment, pedagogical techniques, and holding extra exam-preparation sessions—and on scores after the end of the program. The teacher incentive program in Kenya offered teachers prizes based on their schools' average scores on district-wide exams. The program penalized teachers for dropouts by assigning low scores to students who did not take the exam. During the two years the program was in place, student scores increased significantly in treatment schools (0.14 standard deviations above the control group). However, analysis of the Kenyan data suggests that this improvement did not necessarily occur through the channels intended. Teacher attendance and student dropout and repetition rates did not improve, and no changes were found in either homework assignment or pedagogy. Instead, teachers were more likely to conduct test-preparation sessions outside of normal class hours. Data from the year after the program ended show no lasting test score gains, which suggests that the teachers' effort was concentrated in improving short-run outcomes, rather than stimulating long-run learning. The test-score effect was strongest for subject tests on geography, history, and Christian religion, arguably the subjects involving the most memorization. Also consistent with this hypothesis, the program had no impact on dropout rates, but exam participation rose (presumably because teachers wanted to avoid penalties for no-shows at exams)." Glewwe and Kremer 2006, Pg 44.
"Finally, Banerjee and others (2004) recently conducted a randomized evaluation of a computer-assisted learning program in India and found much more positive results than those from the computer-assisted learning program in Israel (Angrist and Lavy, 2002). The idea of using computers in schools seems particularly promising in areas where both the number of qualified teachers and the quality of employed teachers is notoriously poor. The Indian CAL program took advantage of a donation by the state government of four computers to each municipal primary school in Vadodara and gave each child in the fourth standard 2 hours of shared computer time to play educational games that reinforced mathematical concepts (ranging from standard 1 to standard 3 levels). The program was found to be quite effective, with average mathematics score increases of 0.36 standard deviations in the first year and 0.51 standard deviations in the second year. The program was equally effective across student ability levels." Glewwe and Kremer 2006, Pg 39. See Banerjee et al. 2005, Pg 12 for details of the study.
"This paper presents the evaluation of the program Computers for Education. The program aims to integrate computers, donated by the private sector, into the teaching of language in public schools. The authors conduct a two-year randomized evaluation of the program using a sample of 97 schools and 5,201 children. Overall, the program seems to have had little effect on students' test scores and other outcomes. These results are consistent across grade levels, subjects, and gender. The main reason for these results seems to be the failure to incorporate the computers into the educational process. Although the program increased the number of computers in the treatment schools and provided training to the teachers on how to use the computers in their classrooms, surveys of both teachers and students suggest that teachers did not incorporate the computers into their curriculum." Barrera-Osorio and Linden 2009, abstract.
"Vermeersch and Kremer (2004) conducted a randomized evaluation of the impact of school meals on participation in Kenyan preschools, and found that school participation was 30 percent greater in the 25 Kenyan preschools where a free breakfast was introduced than in the 25 comparison schools. There was some evidence the provision of meals cut into instruction time. In schools where the teacher was relatively well trained prior to the program, the meals program led to higher test scores (0.4 of a standard deviation) on academic tests. There were no effects on tests of general cognitive skills, implying the school meals program did not improve children's nutritional status and that the academic test score increases were likely due to more time spent in school." Glewwe and Kremer 2006, Pg 25.
"Kremer, Miguel, and Thornton (2004) conducted a randomized evaluation of the Girl's Scholarship Program (GSP), introduced in rural Kenya in late 2001 to enhance girls' education. Out of a set of 128 schools, half were randomly chosen as schools eligible for the program. The program consisted of a merit-based scholarship awarded to girls in two districts of Western Kenya who scored in the top 15 percent on tests administered by the Kenyan government. One portion of the scholarship was paid directly to the school for school fees, the other portion to the family for school supplies and uniforms. Girls eligible for the scholarship had significantly higher school attendance rates (as well as significantly higher test scores, average gains of 0.12-0.19 standard deviations). Schools offering the scholarship also had significantly higher teacher attendance after the program was introduced, and there is evidence of positive program externalities on boys (who were ineligible for the awards) as well as on girls with low pre-test scores (who were unlikely to win awards)." Glewwe and Kremer 2006, Pg 28.
"A remedial education program in urban India, focused on improving the learning environment in public schools, appears to have increased test scores at a low cost. Banerjee and others (2004) conducted a randomized evaluation of a 2-year remedial education program in Mumbai and Vadodara, India. The remedial education program is run by a collaboration between a local NGO and the Indian government, and hires (at a yearly cost of only US$5 per child) young women from the community to teach basic literacy and numeracy skills to children who reach grade 3 or 4 without mastery of some basic competencies. On average, the program increased test scores by 0.14 standard deviations in the first year and 0.28 in the second year. The gains were largest for children at the bottom of the distribution, which is unusual for educational programs. Results were similar in both grade levels and in two different cities. The authors note that this program would be several times more cost-effective than hiring new teachers." Glewwe and Kremer 2006, Pg 38.
Miguel and Kremer 2004.
Kapur and Crowley 2008, Pg 6. The figure given is the "gross enrollment ratio," which is the "total enrollment at a given educational level, regardless of age, divided by the population of the age group that typically corresponds to that level of education. The specification of age groups varies by country."
Kapur and Crowley 2008, Pg 4.
Behrman, Ross, and Sabot 2002, abstract.
"The earnings function estimates indicate that increasing quantity and improving quality, by raising cognitive achievement, yield a payoff in the form of higher wages." Behrman, Ross, and Sabot 2002, Pg 4.
"Economists often examine the relationship between years of schooling and income, yet more can be learned from examining the direct relationship between income and cognitive skills. First, positive correlation of cognitive skills with earnings, after conditioning on years of schooling, degrees obtained, and measures of innate ability, casts doubt on other interpretations of the correlation between income and education, such as claims that such correlation reflects only "sheepskin" effects, individuals' innate ability, or learned acquiescent behavior (Samuel Bowles and Herbert Gintis, 1976). (Sheepskin effects are increases in income solely due to possession of a diploma or other certificate, as distinct from any effect of skills acquired from the education that the diploma or certificate represents.)
Despite these potential benefits, there has been little research in both developed and developing countries on the relationship between cognitive skills and income. The main obstacle is the paucity of data sets that include both the incomes and the cognitive skills of adults, although the situation has improved in recent years. This section examines the evidence from developing countries on the impact of cognitive skills on incomes, both wage income and income from self-employment activities." Glewwe 2002, Pg 466.
Glewwe 2002, Pgs 468-469.
"The first is by Dean Jolliffe (1998), who estimates the impact of mathematics and reading skills on the agricultural, nonagricultural, and total income of 1388 Ghanaian households. He finds that cognitive skills raise nonfarm income and total income, but not farm income. This suggests low returns to numeracy and literacy in agricultural activities in Ghana, which induces households with relatively high skills to move out of farming and into non-farm activities.
Jolliffe's paper is quite innovative; perhaps the main criticism is what it did not examine. It never used the Raven's test data to see whether they have any explanatory power beyond that provided by cognitive skills and years of schooling. Also, it does not investigate whether schooling becomes insignificant when skills variables are added. Finally, it does not examine whether agricultural productivity per hour of work, rather than total income, was affected by cognitive skills, since the absence of an impact on total agricultural income may reflect decreased time spent in that activity. (Similarly, part of the positive impact of skills on non-farm income may reflect more hours in that activity.)
The only other study of the impact of cognitive skills on self-employment income is that of Wim Vijverberg (1999), who examined the same data used by Glewwe and Jolliffe. The author examined 1074 household enterprises in Ghana. Unlike the studies on wages and on total household income, he finds only weak evidence that schooling, measured either by years of school attendance or by cognitive skills, affects income from such enterprises. In fact, the impact of cognitive skills is often weaker than that of years of education. Yet there is one point of agreement with the wage studies: innate ability as measured by the Raven's test has no significant impact on income from nonfarm self-employment activities. Vijverberg concludes that impact of education on non- farm self-employment income is complex and probably varies by the type of business.
Vijverberg's analysis has no serious flaws, but unlike Jolliffe he does little to account for sample selection bias." Glewwe 2002, Pgs 470-471.
"A large body of literature investigates the impact of schooling infrastructure on schooling, as well as the returns to education in developing countries [see George Psacharopoulos (1994) and John Strauss and Duncan Thomas (1995) for surveys]. Estimated returns to education are, in general, larger in developing countries than in industrialized countries. However, most of the existing studies are based on simple correlations between years of education and wages. Family and community background are important determinants of both schooling and labor market outcomes in developing countries, and the bias inestimates that treat an individual's education level as exogenous could be important." Duflo 2001, Pg 795.