New Household Survey Data from DHS and MICS

The Education Policy and Data Center (EPDC) has just updated its database with education indicators from recent rounds of household surveys from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). The updates mean data is now available at epdc.org for the following countries and years: India 2015 (DHS), Senegal 2015 (DHS), Ethiopia 2016 (DHS), Armenia 2016 (DHS), and Paraguay 2016 (MICS).

EPDC's database includes data from over 220 large-scale household surveys from countries and territories world-wide. The microdata from these surveys are available to researchers online, but, to increase accessiblity of the data, EPDC prepares and shares the education-related data on its website, with the mission to inform and facilitate education policy-making and research efforts around the world.

The DHS program is funded by the U.S. Agency for International Development (USAID) and is a comprehensive, household survey on human development indicators including but not limited to health, socio-economic status, women's empowerment, and education. The standard DHS surveys have large sample sizes, usually ranging between 5,000 and 30,000 households, and are nationally-representative. Typically, the head of the household is asked questions about education attainment (highest level achieved) and as well as attendance of household members. Additionally, women and men aged 15 and older answer questions about their literacy skills. MICS, funded by UNICEF, is another source of nationally-representative household-level data. MICS offers similar sets of education questions, allowing us to share similar indicators from both sources. Furthermore, MICS often asks about two years of attendance information that we use to calculate indicators of education efficiency, such as repetition rates. More information on EPDC's extraction process can be found here.

Among the indicators EPDC calculates are gross attendance rates (GAR), net attendance rates (NAR), and the percentage of children that are out of school. GAR is the total number of students attending each level regardless of age, expressed as a percentage of the official population for that school level. It is possible for GAR to be above 100%, indicating that there are children who are outside official ages for a school level but still attend. The NAR is the percentage of the official school-age population for a school level that does not attend school at that level, e.g., the percentage of those who are of primary school ages who attend primary school. Out of school rates show the percentage of school-age pupils who are not attending school at the official level for their age group or at a higher level. The following figures show the GAR, NAR, and percent of out of school children for the five surveys recently added to the EPDC database. You may toggle full screen options in the lower-right-hand corner, and zoom options in the top-right corner of each individual graph. The drop-down menu will allow you to visualize a subset of countries.

The above graphs illustrate the disparity between attendance rates at different schools levels within countries, evident in both GAR and NAR. Ethiopia, for instance, has high attendance rates in primary school, but attendance drops off significantly in lower secondary school and again in upper secondary school. There are also notable between-country disparities. Armenia, a country with relatively higher per capita income, has the highest attendance rates at all levels of the five surveys, though attendance rates do decline at the upper secondary school level. These relationships are also reflected in estimates on out-of-school children. The percentage of children out of school rises from primary to secondary school and, again, Armenia, followed by Paraguay, has lower percentages across each education level than other countries.

Turning to inequalities within countries, the following figures show GAR, NAR, and the percentage of children out of school at the secondary level broken down by wealth status (measured as quintiles of an index calculated by DHS and MICS through factor analysis of household assets). We see a drastic difference in school participation between rich and poor households in some countries. In Senegal, for example, we see that only 13% of children from the poorest households attend school compared to 60% from the richest households. However, in Armenia (again, a relatively richer country), there is less inequality in school participation between rich and poor.

The extracted education indicators are available to download as csv or xls files and can be found in the data section of EPDC's website. Searches can also be saved for later use on the website, and can be visualized using our data visualization tool.

EPDC updates its database with the latest household survey data regularly. To stay updated on the databases’ available resources and new features, follow EPDC on Twitter @FHI360EPDC .