Data crunching: the story behind economic indicators and enrolment rates in Indonesia
In Indonesia, Seefar is interested in promoting social equality and mobility among disadvantaged and marginalized groups. The first step to action is understanding how social mobility is influenced by education and the economy. We have analyzed macro-level statistics available on Indonesia to discern trends and establish whether economic welfare and school enrollment in Indonesia are linked. We want to test the hypothesis that better economic welfare corresponds to higher school enrollment rates.
Gross domestic product (GDP) is a common indicator used to gauge economic progress. A higher GDP implies more value in the economy and higher spending on goods and services. Therefore, we have used the GDP as an indicator of economic welfare in each province across the country.
The GDP by province varies from IDR 13,000,000 per capita in Nusa Tengara Timur to almost 175,000,000 per capita in Jakarta. The three provinces with the highest GDP per capita, and thus the most economically wealthiest provinces, are Jakarta, Kalimantan Timur and Riau.
What about school enrollment for Indonesian children?
We looked at enrollment data by four age categories:
- 7 to 12 years old
- 13 to 15 years old
- 16 to 18 years old
- 19 to 24 years old
The percentage of children or youth enrolled in school differs by age category.
- From 7 to 12 years old, the percentage of children enrolled in school varies from 81% (Papua) to 100% (Aceh, Yogyakarta, Bengkulu).
- From 13 to 15 years old, the percentage of children enrolled in school varies from 78% (Papua) to 100% (Yogyakarta).
- From 16 to 18 years old, the percentage of youth enrolled in school varies from 62% (Papua) to 87% (Yogyakarta).
- From 19 to 24 years old, the percentage of youth enrolled in school varies from 13% (Bengka Belitung islands) to 49% (Yogyakarta).
Is there a correlation between school enrollment and GDP per capita? Do provinces with a stronger economic welfare have higher enrollment rates?
In general, we see that as children and youth grow older, their level of enrollment decreases. However, there is no direct correlation between the GDP per capita in a given province with the percentage of children enrolled in school.
What trends are discernable if we only look at children from the 30 percent lowest welfare class of households? We would expect that if the overall Gross Domestic Product per capita of a province is high, the households at the bottom 30 percent would be wealthier than households in provinces with lower GDPs (unless the level of socio-economic inequality is particularly high). Is it the case that the number of children enrolled from households with the lowest welfare increases as GDP per capita increases?
The ratio of children enrolled from 30 percent of the poorest households does not increase with an increasing GDP per capita.
Going a step further, we examined whether wealthier provinces (i.e. those with higher GDP per capita), had more school facilities. We wanted to see if there is a link between GDP per capita and the number of villages in a province that have school facilities.
Our analysis and visualization shows that education facilities become few and far between in villages as the level of education increases. Villages are far less likely to have high school facilities than they are primary school facilities. Nonetheless, there is no direct relationship between the number school facilities a village has and the GDP per capita.
In conclusion, our starting hypothesis that better economic welfare would correspond with higher school enrollment rates in provinces is not supported by available data. What this tells us is that economic growth does not necessarily translate into school enrollment and the number of educational facilities. The enrollment of children and youth is thus more likely to be explained by other independent variables or a combination of variables. These could include intergenerational social mobility, accessibility, demographics, opportunity costs of time spent at school, unemployment of adults and local policies aimed at increasing the global level of education. Household income could be another explanation.
On our final dashboard, we compare the ratio of all children living in a given province who are enrolled in school with the ratio of children from households with the lowest welfare enrolled in school. We see that whatever the age category, the ratio of children enrolled in school who come from households with a lower welfare status is always lower than the ratio of all children enrolled in school living in a given province.
Despite the absence of a direct link between GDP per capita and enrolment, there are interesting regional disparities to examine. Information is available by province to explore. Let us know what you think, and what other data you think we should analyse!