Education programmes do not appear to be linked to emigration decisions

One of the strategic goals of Cambodia's educational policy 2014-18 is to ensure equitable access to education. Programmes such as scholarships and school meal programmes, distribution of textbooks and Take-Home Ration programmes⁴ aim to increase school enrolment rates, especially by poor and vulnerable children. The provision of textbooks aims to provide students with textbooks for all subjects from grades 1 to 12. Scholarships, school meal programmes and Take-Home Rations contribute to Cambodia's educational policies as well as to the National Social Protection Strategy for the Poor and vulnerable. The aim is to provide cash and in-kind (food) assistance to poor students to enable them to attend school. However, achieving wide coverage of scholarship and school feeding programmes remains a challenge. For example, a shortfall of funds for the Take-Home Ration programme has meant that not all poor areas are covered.

The IPPMD household survey included questions on both in-kind and cash-based programmes targeting primary and secondary schooling (Figure 5.3). Households were asked if any members had benefited from any of the specified programmes in the five years prior to the survey.

Overall, 29% of the surveyed households had benefited from an education support programme of some kind. The most common support was the distribution of school textbooks (23% of households), while 11% of households benefited from school meal programmes. very few households benefited from scholarships, which is the only cash-based programme in the survey. Descriptive statistics also suggest that households with at least one emigrant were more likely to have benefitted from an education programme (Figure 5.3). In other words, households not benefiting from education programmes are less likely to have a member abroad. This could suggest that households use the financial support from education programmes to finance emigration. To investigate this further it is necessary to control for other factors, such as household wealth, size and number of dependent children, which might influence the decision to emigrate. This was done using a regression analysis summarised in Box 5.3.

The regression results show only a weak link between education programmes and emigration decisions. Although there is a positive relationship between benefitting from an education programme and receiving remittances (column 3), the relationship is no longer significant when including a control for having an emigrant (column 4). The results do not show any statistically significant association between benefiting from an education programme and intentions to emigrate. The weak link between education policies and emigration decisions may be explained by the nature of the programmes. The education policies in Cambodia are to a large extent distribution programmes - for example school textbooks and school meals - rather than cash-based. As discussed, cash-based programmes may have a stronger effect on migration decisions as they decrease the incentives to emigrate to finance education. However, there was no significant link between cash-based scholarship programmes and migration outcomes. This is potentially partly explained by the low coverage of such programmes (Figure 5.3) as few households benefited from scholarship programmes.

Box 5.3. The links between education policies and migration

To estimate the impact of education support programmes on the decision to emigrate, the following probit equation was applied:

Prob(mighh) = во + Ptedu _ policy _ш + Ycontrols_ш +Sr + е_ш (4)

where mig_hh represents household migration status, being a binary variable for the household either having at least one member planning to emigrate in the future (specification 1), having at least one emigrant who left in the five years prior to the survey (specification 2), or receiving remittances (specification 3 and 4). edu_policy_hh is the variable of interest and represents a binary variable indicating if the household

Figure 5.3. Households with emigrants are more likely to have benefited from an education programme

Share of households benefiting from an education policy (%), by having an emigrant or not

Source: Authors’ own work based on IPPMD data.

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Box 5.3. The links between education policies and migration (cont.)

benefited from an education policy in the five years prior to the study (results presented in the upper part of the table). It takes on a value of “1” if the household has benefited from an education policy programme and “0” otherwise. Cash-based programmes (scholarships for primary and secondary education) are also analysed separately (results presented in the lower part of the table). edu_policy_hh is the variable of interest and represents a binary variable indicating if the household benefited from any education policy in the five years prior to the study. It takes on a value of “1” if the household had benefited from an education support programme and “0” if not. controls_hh are a set of observed individual and household characteristics influencing the outcome.³ S_r represents regional fixed effects and s_hh is the randomly distributed error term.

Table 5.4. The links between education programmes and migration dimensions are weak

Note: Statistical significance is indicated as follows: ***: 99%, **: 95%, *: 90. Standard errors are in parentheses and robust to heteroskedasticity. The sample is restricted to emigrant households with a member who emigrated abroad in the past five years in order to capture the timing of the migration decision and the policy intervention. Analysis was also performed on a sub-sample of households with children in school age (6-20 years), which did not affect the results.

a. The control variables include household size, household dependency ratio (defined as the number of children and elderly in the household as a share of members in working age), the mean education level of adults in the household, the number of young children (aged 6-14) and the number of youth (aged 15-17) in the household, a binary variable for urban location, and an asset index aiming to capture household wealth.