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Why we need more sex-disaggregated social protection data and what we’re doing to get there

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A World Bank supported cash transfer program in Madagascar.
A World Bank supported cash transfer program in Madagascar. Photo: Mohammad Al-Arief/The World Bank.

The COVID-19 pandemic has hit women particularly hard, exacerbating existing gender gaps. Not only are women disproportionally represented in the worst affected industries such as retail, food services and hospitality, but many were forced out of the labor market due to increased caregiving responsibilities. Beyond labor market impacts, the pandemic has also undermined progress on other dimensions of gender equality—data suggest that gender-based violence has increased, while gains towards closing gaps in human capital may be eroding. This is concerning since we know that gender equality is smart economics: greater gender equality can enhance economic productivity and accelerate the recovery.

Social protection has been at the core of the policy response to the pandemic. Countries have planned or implemented more than 3,000 measures to help people cope with the effects of lockdowns and job losses. While we know that men and women don’t have equal access to these schemes, in most places sex-disaggregated data are not available to understand differences in access to and impact of these measures on men and women, girls and boys. Sex-disaggregated data are key to understanding and addressing an uneven economic recovery. 

To date, our main tool for tracking the size and distributional performance of social protection and labor interventions has been the Atlas of Social Protection: Indicators of Resilience and Equity (ASPIRE) — the World Bank’s main compilation of indicators generated on the basis of administrative program-level data and nationally representative household surveys. The ASPIRE database serves as a tool to benchmark the performance of social protection programs across countries and time periods. It is also one of the sources to monitor progress towards Sustainable Development Goal 1: ‘end poverty in all forms everywhere’; specifically Target 1.3: ‘Implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerable.’

Limitations of current data tracking social protection and labor interventions

However, when it comes to sex-disaggregated indicators, ASPIRE faces two limitations. First, many national statistical offices only collect social protection information at the household level. This means that all household members are tagged as recipients of the program and/or the same amount of transfers is reported for all members alike. In those cases, disaggregating data by sex, or by any demographic characteristic, is not possible since the direct beneficiary of the program within the household cannot be established. (Of course, in the real world, individuals in a household are likely to share resources, thus all household members are considered direct and indirect beneficiaries).

Out of the 125 countries covered in the ASPIRE database, only 34 collect the receipt of social protection benefits at the individual level; most of these are in Latin America and the Caribbean. An additional 52 countries collect this information at both individual and household levels, while 39 countries collect all social protection variables only at the household level. (Note that most OECD countries collect social protection data for individual recipients, but most of them are not part of the ASPIRE database). 

Availability of individual vs. household-level social protection information in household surveys included in the ASPIRE database

type of datamap
Source: Author's calculations

Second, even when social protection data is collected for the individual recipient, ASPIRE’s data processing methodology is not set up to produce sex-disaggregated indicators. Given the different levels of data reporting across countries, producing indicators at the individual level for global benchmarking, including regional and income group averages, is difficult. For this reason, ASPIRE aggregates data at the common denominator—which is the household level—to generate indicators that are comparable across countries. However, the ASPIRE team has already embarked on a significant effort to start generating sex-disaggregated indicators for the subset of countries where the data allow it.

Improvements to help capture individual-level and sex-disaggregated social protection data

Collecting individual-level social protection data is important to allow for a richer analysis of programs targeted to individuals (e.g. pensions, unemployment insurance, school feeding).  However, many programs are intended for the household as a whole by design. In those cases, household surveys will collect information on the receipt of the benefit at the household level. When individual identification of the beneficiary is not possible, whether because the program information is reported for the household or due to inaccuracies in individual reporting, an analysis of the consumption patterns of the various household members can discern disaggregated impacts of the transfers. 

ASPIRE’s efforts to generate sex-disaggregated data concentrate not only on household survey data but also on program administrative data. First, ASPIRE is reengineering its household data process to automate the generation of sex-disaggregated indicators for those program variables that capture information for direct beneficiaries. This will enable a wide range of analyses that will help decision-makers understand the gender impacts of social protection interventions. Second, ASPIRE has developed a new administrative data collection tool that captures important program parameters such as the sex of the recipient, the provision of and participation in complementary measures, or whether digital payments are used to pay benefits. This will help us learn about ‘cash plus’ measures and access to digital payments by men and women.

These improvements in ASPIRE’s data collection and processing are a first step towards tracking and understanding the sex-differentiated impacts of social protection more systematically.  Given the fiscal pressures resulting from the COVID-19 pandemic, we need better data to design social protection schemes for optimal impact. We also need government partners, across the world, to continue collecting, producing and making available individual-level and sex-disaggregated social protection data when pertinent in household surveys and administrative records.

For additional country-level sex-disaggregated data and gender statistics, please visit the World Bank Gender Data Portal.


Alessandra Heinemann

Senior Social Protection Specialist and Gender Lead

Vikesh Mahboobani Martinez

Consultant, Social Protection and Jobs Global Practice, World Bank

Claudia Rodríguez Alas

Senior Social Protection Specialist at the World Bank

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