Predicting poverty and wealth from mobile phone metadata

Accurate and timely estimates of population characteristics are a critical input to social and economic research and policy. In industrialized economies, novel sources of data are enabling new approaches to demographic profiling, but in developing countries, fewer sources of big data exist. We show...

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Bibliographic Details
Published in:Science (American Association for the Advancement of Science) Vol. 350; no. 6264; p. 1073
Main Authors: Blumenstock, Joshua, Cadamuro, Gabriel, On, Robert
Format: Journal Article
Language:English
Published: United States 27.11.2015
Subjects:
Cell Phone - statistics & numerical data
Censuses
Developing Countries - statistics & numerical data
Family Characteristics
Humans
Poverty - statistics & numerical data
Rwanda
Social Class
ISSN:1095-9203, 1095-9203
Online Access:Get more information
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Summary:Accurate and timely estimates of population characteristics are a critical input to social and economic research and policy. In industrialized economies, novel sources of data are enabling new approaches to demographic profiling, but in developing countries, fewer sources of big data exist. We show that an individual's past history of mobile phone use can be used to infer his or her socioeconomic status. Furthermore, we demonstrate that the predicted attributes of millions of individuals can, in turn, accurately reconstruct the distribution of wealth of an entire nation or to infer the asset distribution of microregions composed of just a few households. In resource-constrained environments where censuses and household surveys are rare, this approach creates an option for gathering localized and timely information at a fraction of the cost of traditional methods.
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ISSN:1095-9203
1095-9203
DOI:10.1126/science.aac4420