A person's history of phone communication can be used to infer aspects of his or her socioeconomic status, a new study suggests. The study, focused in Rwanda, reveals how cell phone metrics can be a source of "big data" in resource-constrained regions. Collecting data on basic economics quantities, such as wealth and income, is challenging in developing countries, making reliable quantitative data scarce; in much of Africa, for instance, national statistics on economic production may be off by as much as 50%, previous research suggests. Yet insights into the geographic distribution of poverty and wealth are critical for policymakers and others. Here, Joshua Blumenstock and colleagues sought to develop a new approach to measuring how poverty and wealth are distributed in developing countries. The researchers took advantage of the ubiquity of mobile phones in Rwanda, and the fact that mobile phone data captures information about the structure of a person's social network, his patterns of travel, his histories of data use and expenditure, and more. By combining data about individual cell phone users' calls from an anonymized call database containing billions of interactions with information from a follow-up phone survey on basic welfare indicators involving more than 850 respondents, Blumenstock et al. developed a model that maps poverty and wealth of individual phone users at very high resolution (greater than that achieved with satellites). They used the model to predict wealth throughout Rwanda, showing that their predictions agreed with detailed, boots-on-the-ground surveys of the Rwandan population.
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Journal
Science