Household survey data: How do we measure progress towards SDG 4 – Part 2

By Silvia Montoya, Director, UIS, and Manos Antoninis, Director, GEM Report

Historically, data to monitor progress in education have come from education institutions and ministries based on records (see our previous blog on administrative data). However, the increasing availability of household and other surveys over the past 30 years means that they have become a complementary (and, in a few cases, as in the case of equity, almost exclusive) source of data on education indicators that needs to be accommodated by national education statistics systems.

What information do household surveys contribute?

Household surveys collect information from members of households about various aspects of their lives. They collect data on school attendance, literacy, and education spending, among other pieces of information. Two major cross-national household surveys, DHS and MICS, tend to take place every 5 years and cover areas such as child development to ICT skills. Labour force surveys provide information on adult education. School surveys can generate data on school health and nutrition.

One of the major benefits of using data from household surveys is that they can be broken down by individual and household characteristics, such as socioeconomic background (e.g. sex, ethnicity, disability, and income or wealth). The WIDE database on inequalities in education shows just how useful such data can be for visualizing education gaps and for informing policy responses.

If nationally representative, household surveys can also collect information that administrative data cannot, such as self-reported skills and training taking place outside of the educational system. The more regular and comparable they are, the richer they are as a source for monitoring SDG 4, providing trends over time. This is proved by the extent to which survey data feeds into the indicators published by the UIS.

SDG 4 indicators that may be derived using household survey data, by provider

Six challenges to using household surveys and potential solutions

There are challenges to using household surveys more consistently, however, which can be reduced to six core areas. The lack of harmonization means that their findings may not be comparable to those from other countries. Comparability can also be challenged by different reference periods or incomplete coverage of education providers. The quality of the background information that enables some of the data to be broken down by factors such as wealth, migration and disability, is sometimes insufficient.  In addition, many countries do not make their data accessible, limiting cross-country analysis. In addition, outcomes, notably those related to literacy and learning, are conceptualized differently across surveys, some relying on self-reporting and others on direct measures, while they may be administered to different population groups. Similarly, while household surveys provide critical information on household spending, respondents may be reticent to share financial information. Surveys also differ in the types of expenses they capture.

Solutions

Against the challenges, there are, thankfully, solutions, many of which will be tabled at the first ever Conference on Education Data and Statistics being convened by UNESCO on 7-9 February in Paris. To maximize the potential of surveys, the Conference will present the need for a comprehensive strategy for all actors that involves collaboration, capacity building, and standardization. Within this strategy, there are responsibilities and roles at the global and national levels.

At global level

We should:

  • Raise awareness among policymakers, researchers, and the public of the opportunities that surveys offer for generating education statistics and advocate for:
    • the importance of high-quality survey-based data for evidence-based decision-making; and
    • the need for continued financial and technical support for household surveys in education.
  • Develop a household survey data repository with the collaboration of member states, ensuring accessibility while maintaining data security and privacy.

At national level

In their national household survey programs, countries should strive to establish standardized, modular survey instruments. They should ensure covering all major national education programs and foster more dialogue between their national statistical office, the education ministry and any technical partner developing survey questionnaires. They should, for instance:

  • Ensure that the questions on education programs are aligned with the International Standard Classification of Education (ISCED).
  • Ensure that survey questions related to education attendance are clearly aligned with specific school years and the reference periods for SDG 4 indicators. Record more information to calculate children’s age precisely at the beginning of the school year.
  • Develop standardized definitions and measures for socioeconomic factors like household wealth, migration, and disability to enhance comparability across surveys, referring to international existing guidelines such as the Washington Group on disability questions.
  • Integrate simple enumerator-assessed literacy tests alongside self-assessed measures. Expand such assessments to all youth and adults, not just those below a certain level of educational attainment.
  • Ensure that questions on types of education expenditure follow global guidelines for comparability – and link education expenditure to individual students within households for more precise data.

Countries should also develop guidelines for data collection and processing to ensure consistency and comparability of education indicators.

Lastly, countries are encouraged to share survey microdata for public use.

In conclusion, household surveys offer valuable insights into education indicators, but their effective implementation and utilization face numerous challenges. Addressing these challenges is essential to ensure reliable and meaningful data for monitoring progress towards SDG 4.

 

Read the first blog in the series:

Administrative data: How do we measure progress towards SDG 4 – Part 1

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