What Can Internationally Comparable Quantitative Data Tell Us about How Gender Norms Are Changing?

"Which types of data can tell us about changes in people's attitudes and practices when it comes to gender?"

This research and practice note outlines how standardised national surveys, opinion data, and administrative data from developing countries, collected at regular intervals, can reveal information about how gender norms affect adolescent girls, as well as whether prevailing norms are changing. It is part of the Overseas Development Institute (ODI)'s Knowledge to Action Resource Series 2015, which was funded by the Department for International Development (DFID). This series emerged from the 4-year programme Transforming the Lives of Adolescent Girls, which involved fieldwork in Ethiopia, Uganda, Nepal, and Viet Nam.

As explained here, developing country governments regularly collect nationally representative data relevant to gender norms in the form of three major household surveys: the Multiple Indicator Cluster Survey (MICS); the Demographic and Health Survey (DHS); and the Living Standards Measurement Study (LSMS). There are various text boxes within the resource exploring these survey, such as Box 4: How MICS, DHS and LSMS data can give a fuller picture of how gender norms affect adolescent girls in Nepal - "Here, we set out data on Nepal from rounds of MICS, DHS and LSMS, using a selection of indicators relevant to gender norms and adolescent girls. This illustrates not just that the type of data available on gender norms and adolescent girls varies over different periods of time, but also that data from different sources can complement each other to give a much fuller picture. (The data have been collected from country reports for each survey rather than direct analysis of the data sets.)" Because most countries collect data every few years, indicators from these surveys can provide useful insights for development policymakers and practitioners about how gender norms are changing.

This note describes the main data available to help identify how gender norms are changing in a given country or context. It looks at the usefulness of data from three main sources: the regular household surveys already mentioned; opinion or perception surveys; and administrative data collected by governments at different levels (such as region, district, zone, or village). These types of surveys are particularly useful for:

• Understanding trends in gender norms: Large-scale household surveys include questionnaires designed for women, posing questions to girls from the age of 15 up. The data generated can reveal the situation of adolescent girls at a given point in time (year of the most recent survey) or over time (for countries where two or more rounds of data are available). This makes it possible to see any change (or lack of change) for relevant indicators during that period.
• Exploring links between attitudes, practices, and social and demographic characteristics: In addition to enabling simple trend analysis of indicators, analysing the different background characteristics of the households and/or individuals interviewed helps determine correlations between norm indicators and socioeconomic characteristics - for example, household members' level of education, their religion, ethnicity, language, location, and economic status. This can answer questions such as, in a given country, which geographic localities (regions and urban/rural populations) are more likely to have seen changes in early marriage over time? And are certain discriminatory gender norms more entrenched among some ethnic groups?
• Revealing insights into programme or policy effectiveness: Although most household survey data are not linked to any specific intervention, changes over time can be explored in light of policy or programmes that might have contributed to such changes. If the policies and programmes are introduced at the national level and at sufficient scale, they can trigger changes that can be picked up by subsequent rounds of national survey data.
• Making comparisons across countries and regions: Data sets from standardised surveys (such as the DHS, MICS, and LSMS) in different countries allow for comparisons of indicators across countries and/or regions. When comparing two or more countries, it is worth checking how the questions have been translated - both in terms of language and cultural understanding - to ensure that responses are indeed comparable.

The note explains that there are, however, some constraints in using these data to analyse changing gender norms that affect adolescent girls. The vast majority of relevant survey data examine either attitudes or practices and, while these are useful proxies for indicators of norms, they are not the same as norms. Data on people's perceptions of norms are typically collected via small-scale studies and are not available in internationally comparable data sets. Other weaknesses include the following:

• Data on attitudes to gender equality are mostly framed broadly and captured from adults rather than asking girls for their views; this said, the data capture gender norms in the broader environment in which girls are growing up. Some data on prevailing norms and practices do relate directly to girls' lives - for example, data on education enrolment, adolescent pregnancy, and/or female genital mutilation/cutting (FGM/C).
• The standardised and large-scale nature of the MICS, DHS, and LSMS means that local differences in norms and practices could be missed or misrepresented. For example, when child marriages formally take place but the girl does not go to live with her husband until she is some years older (e.g., during mid-adolescence), data on the age of marriage can be inaccurate.
• Despite training and guidance for interviewers and survey designers, it is possible that respondents will not always give truthful answers to questions on very sensitive matters such as domestic violence, child marriage, and harmful traditional practices.
• Survey or administrative data may not be available for the most marginalised groups and communities - for example, people living in very remote or conflict-affected areas - and thus give an incomplete picture of whether gender norms are changing, and how.

With a comprehensive list of links to the surveys outlined and related literature, this note provides an insight into how internationally comparable quantitative data can be used effectively by policymakers, development practitioners, and evaluators.