Disaggregated data for focused development programs

Disaggregated data, or data broken down by age, sex, and income levels, can help governments better target development programs. A series of online seminars by Statistics Canada and the World Bank showed Caribbean countries how to collect and leverage disaggregated data to improve program impacts.

The ongoing pandemic has hugely impacted people across the world, and in so many different ways. Depending on who you are and where you live, the experience can be, to use a cliché, worlds apart! For example, to a young boy living in the city, it could all be about attending school remotely, or not being able to play football with his friends. For him, learning is challenging, his grades are deteriorating, his parents may be out of work. He’s cooped up in a small apartment with his parents, brothers, and sisters. Life is no longer fun.

In contrast, for his grandmother, who still lives in the village with little or no access to the internet, getting information is a challenge. What’s going on with the pandemic? When and where can she get vaccinated? Her daily walks to the market, her weekly gatherings with friends, have all been canceled. For her, life has become lonely. She feels isolated.  

Often, government programs, though well-intended, do not recognize these different experiences. Their one-size-fits-all approach fails to account for and respond to diverse needs. This results in poor targeting, wasted resources, and can even place individuals and groups at greater risk, especially when fighting a life-threatening crisis like COVID-19.

Which is why, to better understand people’s different roles and experiences, countries have been conducting impact assessments of policies based on gender and age.  While approaches to conducting assessments may vary, their effectiveness is heavily dependent on the availability of disaggregated data, or data that is broken down by, to start with, age, sex, or income levels.

The importance of disaggregated data was the focus of a series of seminars that were hosted virtually, between June and December 2021, by Canada’s national statistical office—Statistics Canada— and the World Bank for over 150 participants from Caribbean countries. The objective of the seminar series delivered between June and December 2021 was to share with them Canada’s experience in using disaggregated data to enhance the impact of its programs.

Canada is a pioneer in collecting, analyzing, and using disaggregated data, and thus provides an excellent example of how to use it for more efficient targeting of government programs.  The Canadian government builds on an abundance of disaggregated data collected by Statistics Canada to evaluate the needs of men and women through its Gender-Based Assessment Plus (GBA+) program.

Interestingly, GBA+ goes beyond gender and disaggregates the data even further, breaking it down by race, ethnicity, religion, age, non-binary people, and people with mental or physical disabilities (see figure, below). GBA+’s findings, related programs, and budget measures are presented in the Government’s national budget.

Figure: The intersectionality of the GBA+ approach to assessing the potential impacts of policies, programs, and other initiatives on diverse groups of people

Canada’s GBA+ helps the government assess the impact of its programs across different criteria
Source: Statistics Canada; The Centre for Gender, Diversity, and Inclusion Statistics Hub.

GBA+ helps the government of Canada design better gender-aware policies, including addressing issues like climate change.  When data was disaggregated, it showed, for example, that women are more likely than men to experience the negative impacts of climate change. Canada, therefore, includes women in decision-making in all phases of disaster risk reduction, from preparation and mitigation to response and recovery.

Disaggregated Data is Available

Beyond OECD membership, only a handful of developing and emerging countries have streamlined processes for data collection and disaggregation used for budgeting, including India, Indonesia, Rwanda, and South Africa, among others. Caribbean countries should look to these examples on how data can inform the design of public services. National statistical offices collect disaggregated data as part of national censuses and specialized surveys; other government agencies too, collect administrative data. For example, data by sex and age is collected by health clinics on patients treated for different diseases or by schools on student enrolment rates. However, this type of data is not necessarily fed back to the relevant line ministries and integrated into the review and (re)design of programs and projects. The seminar series showed how this data, which may already be available, could be leveraged to inform and help set goals for government programs.

Encouragingly, some countries in the Caribbean are ready to take determined steps toward designing better gender-aware budget policies. For example, the Government of Grenada has introduced a gender-budgeting framework that consists of a new budget submission template that requires gender analysis of programs and budget allocations based on sex-disaggregated data. Before introducing gender budgeting, the Government clearly articulated how it was going to close gender gaps in around five percent by value of all the services of service delivery ministries. It is expected that this new policy of integrating gender in the design and implementation of budget policies will lead to around 33 percent by value of all the programs of key service delivery ministries showcasing how gender gaps will be addressed.  Saint Vincent and the Grenadines has also started piloting the gender aware approach to the design of budget policies. This includes the review of the extent to which disaggregated data is collected in selected sectors—agriculture and education—and determining how best to use it to design programs that better respond to the needs of men and women, boys and girls.

Statistics Canada conducted the seminars under the Project for the Regional Advancement of Statistics in the Caribbean (PRASC) and the World Bank’s Latin America and the Caribbean Governance team, supported by the Canada-Caribbean Resilience Facility (CRF) under the Global Facility for Disaster Reduction and Recovery (GFDRR), in partnership with the Caribbean Community (CARICOM) Secretariat. Participants were from Antigua and Barbuda, Belize, Dominica, Grenada, Guyana, Jamaica, St. Lucia, St. Vincent and the Grenadines, and Suriname.