The Power of Data for Women and Girls

Article | 2 October 2017

Household-level poverty and development data often masks key inequalities between men and women, particularly when it comes to the control of resources and assets. A new effort is underway to take a closer look.

Data is what drives resources toward development. Policy makers decide where to invest in infrastructure, education and other important aspects of people’s lives by examining data related to poverty and quality of life. This data often drills down to the household level and specifically looks at differences between homes headed by a male or a female.

Increasingly, researchers are finding that this level of data masks deeper inequalities within households, particularly when it comes to women’s ability to equally obtain and control assets and resources.

Data shows generally that women’s control of things such as land, property, and businesses – as well as better nutrition and education for their children, lower rates of domestic violence, and greater equity in household decision making – benefit society as a whole.

The problem is there is very little data that exposes this mismatch in economic power between men and women in the same household. Conventional surveys tend to ignore women in male-headed homes, as well as men in homes where a woman is in charge. These types of surveys also gloss over the reality that women and men often experience poverty in very different ways within the same household, often linked to access to assets.

Although there are a number of initiatives to collect asset data at the level of the individual, there’s a huge challenge in the effort to standardize questionnaire design, sampling and methodology. Without a degree of standardization, comparing data becomes impossible. Building the capacity of national statistical offices to carry out this level of data collection is another challenge.

One global initiative to address these issues is the Evidence and Data for Global Equality project (EDGE). It’s a joint venture by the UN Statistics Division and UN Women to integrate gender issues into official statistics for better, evidence-based policies. EDGE has established an online gender data portal to share existing statistics on education, health, and employment.

“To accelerate the collection of internationally comparable gender indicators, the EDGE project is working with partner agencies and pilot countries to develop methodological guidelines on asset ownership and entrepreneurship,” said Andrew Smith, a statistician with the UN Department of Economic and Social Affairs.

The survey methodology developed by EDGE has been piloted in seven countries. The Asian Development Bank provided technical and financial support for gendered surveys on assets in Georgia, Mongolia and the Philippines. The Georgia and Mongolia surveys (sample of 3,160 and 3,008 households, respectively) are nationally representative, while the Philippines survey (sample of 1,536 households) is representative for the province of Cavite only.

ADB provided technical and financial support for gendered surveys on assets in Georgia, Mongolia and the Philippines. The three-country survey shows clearly that men are more likely to be owners of assets than women.
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The three-country survey shows clearly that men are more likely to be owners of assets than women. The gender gap is highest in Mongolia for most assets and lowest in Cavite, Philippines. Focusing on immovable property, men in Mongolia are twice as likely as women to own their dwellings, four times as likely to own land, and a little more than one-and-a-half times as likely to own other real estate.

The real value of the EDGE pilot surveys is that they demonstrate that with standardized methods and guidelines, such data collection is feasible and practical. Moreover, valid data comparisons can be made between countries and regions as similar survey techniques were deployed.

The United Nations Statistics Division, a partner in the pilot data project, believes that although challenging, with minimal adaptation these guidelines can be applied across diverse economic and social contexts.

The pilot surveys taught those involved important lessons that will help improve the data collection process. “One needs a basket of indicators, such as the proportion of men and women who own different types of assets, and how assets are acquired and used to undertake a comprehensive gender analysis of asset ownership,” said ADB Statistician Kaushal Joshi.

There’s a new realization that generating social and economic data separated by sex tells a more complete and nuanced story about income and ownership at the micro level. While the lack of comparable national-level data on men and women’s asset ownership remains a serious constraint in shaping policy that promotes gender equality, that is clearly changing.

As 2030 approaches, the need for economic and social statistical evidence by sex will become more critical as the world focuses on progress on gender-related Sustainable Development Goals.