Guest blog post from Sarah Hughes, Senior Fellow at Mathematica
Sub-Saharan Africa is home to more than half of all people living in extreme poverty in the world. Alongside poverty, the 48 countries that make up the region include multiple languages, low literacy rates and hard-to-reach areas. Other challenges include limited communications infrastructure, nomadic and displaced populations, and conflict zones. These circumstances create obstacles for those trying to collect accurate data, a basic requirement for implementing sound public policy. In fact, a number of countries have not carried out censuses in many years, a situation that researchers at the World Bankdescribe as “data deprivation.” Without census data, governments and development agencies can’t know the population or its needs, and policymakers have difficulty tailoring assistance to the people who need it most.
As I noted recently in a chapter I authored in Advances in Comparative Survey Methodology, evaluators working in the region must understand the challenges to collecting accurate data so they can adapt their data collection approaches to the varied and often difficult contexts they will encounter.
Many researchers and data collection teams in the region are not formally trained in survey methodology, and advanced statistical training for managing surveys and data quality is rare. One consequence is that local data collection teams might not realize the errors introduced into the data by poorly worded or translated questions or by poorly trained interviewers. I work to address this knowledge gap by providing survey methods and fieldwork training in all my evaluations and projects. For example, I recently have been training data collectors in Benin for an independent evaluation of an electrification project funded by the Millennium Challenge Corporation, a U.S. global development agency.
Beyond training, the rapid penetration and adoption of mobile devices and the expansion of communication networks in sub-Saharan Africa hold great promise for helping researchers and policymakers reach populations in remote areas to understand their needs.
First, telephone surveys are far less costly than face-to-face interviewing, so more frequent or larger, more representative data collections might be possible as phone ownership spreads. Even less expensive are text message or SMS surveys that permit data collection over mobile phones, enabling respondents to indicate their responses by pushing the numbers or letters on the phone. But SMS surveys, though effective for gathering information for some populations, are not effective for others, such as those with limited literacy or for people who don’t have access to a phone. Mathematica has partnered with FinMark Trust and Insight2Impact to develop a new statistical model that we hope will enable us to adjust for under coverage of some populations answering SMS and telephone surveys in developing countries.
Even though in-person surveys are still the most common type in sub-Saharan Africa, the decrease in the cost of tablets in recent years combined with easy-to-use survey questionnaire software such as SurveyBe are helping researchers and local data collection entities design and execute their own high quality surveys at a much lower cost. Survey designers use the software to reduce data-entry errors and guide interviewers through the questionnaire. The use of GPS and satellite tools that come with tablets also help researchers estimate and sample populations, improve data quality, and confirm survey-collected data such as crop production.
I’m very excited that technology is helping policymakers, researchers, and development agencies reach more people in sub-Saharan Africa. This is a region whose development is a lifelong interest of mine. First, as a Peace Corps volunteer helping farmers learn new agricultural and gardening techniques in Mauritania, and today as an international development researcher for Mathematica.
At Mathematica, we’re dedicated to improving public well-being and reimagining the way the world gathers and uses data, and I believe improving survey data in Africa is a step toward helping African governments, international donors, and investors make better informed evidence-based decisions to improve the lives of Africans and, through our global connectedness, of all populations. These decisions can take the form of public policies and investments to expand electrification, provide access to education, or improve health outcomes. Better technology-based approaches to survey data collection such as using mobile phones, tablets, and computer-assisted questionnaire programs, combined with appropriate survey training, create an opportunity to better serve citizens everywhere.
