Other Explanatory Variables

Hansen and Tarp (2001) argue that aid effectiveness is highly sensitive to model

specification, for which reason other factors found to affect Net Enrolment Rates in the development education literature are tested in bivariate regressions in order to inform the specification of the final multivariate model.

The inclusion of public education expenditure is a standard feature of education

production functions, although research on its impact is somewhat inconclusive. Bergh and Fink (2006) argue that increased public spending on basic education allows a greater

proportion of the population to complete primary and secondary education; whilst Rajkumar and Swaroop (2008) offer evidence that the effect of government spending on education may be positively correlated with the quality of governance. However, RECOUP research on the impact of public expenditure on educational outcomes conducted in Pakistan by Malik and Naveed (2012) demonstrates the difficulties of establishing conclusive causal links between public spending and primary NERs. Likewise, Dreher, Nunnenkamp et al. (2008) conclude from their findings that domestic spending on

education has virtually no effect on education outcomes. Al-Samarrai (2003), exploring the relationship between public education spending and education outcomes at the primary school level in developing countries from a cross-country perspective before concentrating on three African case studies – Botswana, Malawi and Uganda – finds the link between resources and education outcomes to be weak, arguing that increased resources are unlikely to be sufficient for achieving international education goals.

In the present study, average domestic expenditure on education as a percentage of GDP across the 61 countries is found to have ranged from 5.2 per cent in the period 1970-74 to

percentage of recipient GDP marginally contracted, per capita expenditure increased significantly, particularly in the period 2000 onwards. The reasons for this may be three-fold. First, the Monterrey Consensus (refer to United Nations 2002) and the MDGs ask that countries play a much greater role in financing education. Second, in recent years, aid has increasingly been channelled to recipients in the form of general or sector budget support - spent through government structures - swelling public expenditure on education.

Third, the spread of multi-party politics following the end of the Cold War has been linked to greater public spending on education. Empirical research conducted by Stasavage (2005) demonstrates that the consequent increases in levels of democracy are associated with greater spending on primary schooling. Per capita domestic spending on education is found to be significant [0.140 (0.100)] at the 10 per cent level in the bivariate regression run for the group of 61 developing countries.

Pupil-teacher ratios are a frequently considered characteristic of education systems; with a questioning of why reduced class size has been shown to increase education outcomes in developed countries (Krueger and Whitmore 2002), whilst the effect of the pupil-teacher ratio is consistently found insignificant in low-income countries (Banerjee, Cole et al. 2007;

Duflo, Dupas et al. 2007). Duflo, Dupas et al. (2007) argue that the insignificant effect of smaller class sizes in poorer countries to be the result of weak governance reducing the impact of additional education expenditure. Michaelowa and Weber (2006) find a high pupil-teacher-ratio to exert a significant and negative effect on completion, which they argue may reflect reduced demand for education and earlier drop-out in the case of crowded classrooms. They suggest that parents’ perception is clearly that crowded

classrooms are problematic and that demand is affected by such perceptions independently of whether these perceptions are justified or not. This point of view is upheld by research on the impact of Free Primary Education in Kenya which saw primary school enrolment increase from 5.9 million in 2002 to 7.2 million in 2003 (MOEST 2004), exerting

considerable pressure on the physical and human resources of Kenyan schools with pupil-teacher ratios rising rapidly from 1:40 to 1: 60 (Majanga, Nasongo et al. 2011; Ngware, Oketch et al. 2011). Large class sizes are shown to have led to deteriorating educational quality and eroding initial gains and are an issue of great concern to many Kenyan teachers (Oketch, Mutisya et al. 2010; Majanga, Nasongo et al. 2011; Ngware, Oketch et al. 2011).

In the bivariate analysis run here, the average teacher to pupil ratio was observed to drop steadily over time from 1:48 in the period 1970-74 to 1:36 in the period 2010-13. The relationship between pupil-teacher ratio and net primary enrolment is shown to be a highly significant predictor of enrolment [-1.434 (0.000)].

The size of the school population is deemed to be reflective of the relative demand for education. This variable is included with the purpose of holding constant the degree of strain that the composition of the national population places on the education system. A number of countries have well-established education systems that offer near universal primary coverage and are close to doing so at secondary level. A steady decline in the size of the school-age populations has meant that investments in education have grown. As a result, the challenge does not necessarily lie in responding to growing demand for education but problems of teacher supply as related to shortages of specialised teachers, either in terms of subject matter or the ability to work with children with special needs.

There are other countries where school-age populations continue to grow steadily and universal primary or basic education has yet to be attained. A greater school-age population may place pressure on the education system for example in terms of the supply or

deployment of teachers to meet demand. The availability of resources becomes critical - where countries have abolished primary school fees there has been an influx of millions of new pupils, often without the necessary resources in place (UNESCO Institute for

Statistics 2006). Countries with a greater percentage of the population aged less than 15 have the potential for more students to be enrolled in education and a smaller percentage of adults to provide and pay for schooling. Gupta, Verhoeven et al. (1999) report that the share of the population under 15 exerts a strong influence on enrolment. Michaelowa and Weber (2006) also find that a relatively high share of youth significantly increases the difficulties in reaching high completion rates. Whilst absolute numbers of school-age children in the 61 countries analysed in the present study have continued to rise across the country grouping, the fraction of the population that is youth (<15 years) has dropped marginally over time from an average of 44 per cent in the period 1970-74 to 34 per cent in the period 2010-13. There is found to be a highly significant negative correlation between the percentage of the population aged less than 15 and primary net enrolment [-2.795 (0.000)] suggesting that population pressure is an important determinant of enrolment in education. That the correlation is negative indicates that a rise in the youth population places considerable strain on national education systems.

The extent of urbanisation is also supposed to effect enrolment rates, although the evidence for this is mixed with Dreher, Nunnenkamp et al. (2008) finding the variable to be insignificant, whilst Fafchamps and Wahba (2006) find that in the case of Nepal,

school – an issue associated with rural areas (Huisman and Smits 2009). Distance to school is most likely to be problematic for girls, in part as a result of parents’ concern for their daughters’ safety, which is particularly a hurdle once girls reach puberty. Glick and Sahn (2006) find distance to have a strong negative impact on the demand for education in Madagascar and Colclough, Rose et al. (2000) find the same in the cases of Ethiopia and Guinea. Jakupec and Meier (2015) contend that in order for socio-economic disadvantages to be equalized, adequate funding of education and training systems for rural regions must be realised. The percentage of the population living in urban areas is found to be highly significant in the bivariate analysis, having a positive and substantial effect on primary enrolment rates [1.378 (0.000)].

GDP per capita is frequently employed as a proxy for household poverty (Mingat and Tan 1998; Gupta, Verhoeven et al. 1999; Baldacci, Clements et al. 2004) and is argued to reflect demand for schooling. The Education Policy and Data Center (2008) find, across four studies of growth in access to education, inequality in enrolment to be the product of disparity in pupil income; in almost all cases, the poorer the pupils, the smaller the enrolment rates. Two specifications of GDP per capita - one of which adjusts for

purchasing power parity (PPP) – which is expected to reflect demand for education, were run in the bivariate analysis with interesting results. Both measures were found to be significant. In this case, the more intuitive measure of GDP per capita adjusted for purchasing power parity [0.011 (0.000)] is found to be preferable for inclusion in the final model.

The bivariate analysis presented above provides a rich understanding of the correlations between the explanatory variables and the dependent variable of primary net enrolment and may be used to guide the selection of explanatory variables for inclusion in the multivariate model. It shows that once the issue of the potential for endogeneity has been addressed, all explanatory covariates (with the exception of domestic expenditure on education) were found to be statistically significant. Education aid was significant at the 5 per cent level whilst all others were significant at the 1 per cent level (Table 5). Domestic education expenditure was found to be significant at the 10 per cent level in the bivariate analysis. Whilst not significant at the usual levels of acceptable significance (<0.05), given the research’s concern with financial inputs and the interest in the effect of public

education expenditure in the development education literature, the usual acceptable level of significance was broadened to allow for inclusion of this variable in the multivariate

analysis.

Table 5: Explanatory Variable Selection for Multivariate Analysis

Variables Bivariate Results Conclusion

Education aid (per capita) Significant Include

Public expenditure on education (per capita) Significant (10%) Include

Pupil teacher ratio Significant Include

Percentage of youth under 15 years Significant Include

Share of population in urban areas Significant Include

GDP per capita adjusted for PPP Significant Include

Sources: OECD CRS (2015) and World Bank (2015a)

NB: ‘Significant’ indicates a p-value <0.05 (5%) unless otherwise stated