Abstract
The widespread adoption of mobile devices that record the communications, social relations, and movements of billions of individuals in great detail presents unique opportunities for the study of social structures and human dynamics at very large scales. This is particularly the case for developing countries where social and economic data can be hard to obtain and is often too sparse for real-time analytics. Here we leverage mobile call log data from Côte d’Ivoire to analyze the relations between its nation-wide communications network and the socio-economic dynamics of its regional economies. We introduce the CallRank indicator to quantify the relative importance of an area on the basis of call records, and show that a region’s ratio of in- and out-going calls can predict its income level. We detect a communication divide between rich and poor regions of Côte d’Ivoire, which corresponds to existing socio-economic data. Our results demonstrate the potential of mobile communication data to monitor the economic development and social dynamics of low-income developing countries in the absence of extensive econometric and social data. Our work may support efforts to stimulate sustainable economic development and to reduce poverty and inequality.
Highlights
Accurate and timely information is a necessary condition for the implementation of policies that fosters socio-economic development
4 Discussion We analyze the mobile phone call logs and human mobility traces from a large-scale mobile dataset collected in Côte d’Ivoire with the aim to further understand the country’s economic development
We found that CallRank informs us about the importance of regions, and the relative frequency of initiating calls to other areas consistently correlates with local economic statistics like low poverty rate and high annual income
Summary
Accurate and timely information is a necessary condition for the implementation of policies that fosters socio-economic development. Governments and private organizations invest significant resources in the construction of socio-economic indicators that are frequently derived from resource-intensive surveys and economic reports. The U.S Department of Labor records unemployment insurance claims on a weekly basis to monitor changes in labor market conditions. The University of Michigan and Thomson Reuters publish U.S Consumer Confidence index every month obtained from extensive consumer surveys. Gallup reports the daily U.S Economic Confidence index, which is derived from comprehensive and large-scale economic surveys. The coverage of these indicators is significant from a temporal perspective, and in spatial terms: the
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