Fundraising appeals to help the world's poor usually focus on compelling causes that tug on our heartstrings, such as sending children to school or feeding them nutritious meals. It is harder to build a compelling case for "improved data collection." Yet, health, education, microfinance and land titling programs all depend on high-quality data to improve the lives of poor people.
The U.N. General Assembly is considering the Sustainable Development Goals, a blueprint to guide its efforts to meet the needs of the world's poorest. Included in those goals, is a call for higher quality data that is broken down in a number of ways such as gender, age, race, and ethnicity. Some leading institutions, like the Copenhagen Consensus Center, have questioned the need for better data and specifically the need for better data broken down by sex claiming "we already have sufficiently available gender disaggregated data," and the cost of any additional data of this kind is "too high relative to any potential benefit." They are wrong on both counts.
In the past, policy makers and development professionals mainly relied on highly aggregated data -- national-level statistics, or averages taken across large groups. But averages across groups often hide gaps in which the needs of some individuals or sub-groups are not being met. For instance, national school enrollment rates may hide the fact that the rates differ markedly for boys and girls, or for rural and urban communities.
While some data broken down by sex are available in the realms of nutrition and schooling, for many topics, gender disaggregated data are simply unavailable. A recent study on women's land ownership for example, found that only one-third of African countries have any data on women's land ownership based on nationally representative or large sample surveys. The lack of data leads to the perpetuation of unfounded claims that are repeatedly referenced and exert profound influence on the agendas of development organizations.
Land is not the only asset for which data are scarce. Many development projects rely on mobile phones to disseminate information on health, agriculture, or business management. But if women lack access to mobile phones, these projects may inadvertently disadvantage them. Currently, the Cherie Blair Foundation estimates that women in low- and middle-income countries are 21 percent less likely than men to own a mobile phone. But this estimate is based on limited information, because there is no systematic data on mobile phone ownership.
One reason that the Copenhagen Consensus does not want to promote the collection of additional gender-disaggregated data is because they believe that it is not possible or cost-effective to identify the owners of assets within households. Yet, the Gender Asset Gap Project, a collaborative research project that my colleagues and I initiated in 2009, has collected individual-level ownership data on the full range of physical and financial assets in Ecuador, Ghana, and the state of Karnataka, India. The data on land, housing, livestock, financial assets, and even mobile phones across all three countries found strikingly different patterns in different countries. For instance, in Ecuador, couples usually own their homes jointly, whereas in Karnataka and Ghana, men own housing. On the other hand, savings accounts are typically individually owned in all three countries. Through our detailed data collection and analysis, we identified key questions that provide critical information with minimal additional cost.
So what should be done? A first step would be to modify studies already being conducted. For example, many household surveys ask about the various parcels of land owned by household members. Adding one simple question, "Who owns the parcel?" provides information on whether the land is owned individually by a man or woman, or jointly by the couple. Asking whose name is on the title (or registration deed) provides further information about legal rights. Numerous studies have found instances where couples claim to own property jointly, but the title lists only the husband's name. The wife may then have no legal rights over the property. The cost of adding these questions to existing surveys is minimal but the potential benefit is significant.
To be sure, understanding all of the nuances of asset ownership would require more than one or two questions in a household survey. It requires understanding of the legal frameworks and how the laws are implemented. Family law, including laws regarding marital property and inheritance, affect patterns of property ownership. Additional questions could identify who within the household has the right to sell or mortgage the property and who decides what crops to grow. But the few additional questions would provide an important basis for monitoring women's asset ownership.
When it comes to improving the lives of the world's poor, data collection may not be as sexy of a focus as improving access to clean water or more nutritious food. But better data is essential to monitoring progress and ultimately maximizing impact. It is critical that the General Assembly adopt the recommendation for better data at the individual level so that countries and develop organizations are better equipped to tackle the problems of poverty in a meaningful way. If we don't truly understand what is happening at the individual level, we have little hope of solving the problems.