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Indicators of wealth , economic diversity and segregation in Côte d’Ivoire using Mobile Phone datasets. Thoralf Gutierrez UCLouvain Gautier Krings Real Impact, UCLouvain Vincent D Blondel UCLouvain. Côte d’Ivoire. Few reliable statistics on the state of the population
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Indicators of wealth, economic diversity and segregationin Côte d’Ivoire using Mobile Phone datasets Thoralf GutierrezUCLouvain Gautier KringsReal Impact, UCLouvain Vincent D BlondelUCLouvain
Côte d’Ivoire Few reliable statistics on the state of the population Civil war that ended two years ago and changed the face of the country
Mobile Phone Datasets • Mobility variables • Where people live • Consumption variables • How people buy airtime credit • Social variables • How people are connected to each other
Mobile Phone Datasets • Mobility variables • Where people live • Consumption variables • How people buy airtime credit • Social variables • How people are connected to each other
Where do people live ? Where are they the most active between 5pm and 5am (at night) ? When they are expected to be at home
Repartition of users Korhogo 1 500 000 150 000 15 000 1 500 Bouaké Daloa Yamoussoukro Gagnoa Abidjan San Pédro
Mobile Phone Datasets • Mobility variables • Where people live • Consumption variables • How people buy airtime credit • Social variables • How people are connected to each other
How do people buy airtime credit ? • Côte d’Ivoire is dominantly prepaid • Do people have a stable behavior ?Do they tend to buy chunks of credit of the same amount ? • 80 % of people have a CV under 60% where is the standard deviation of a person’s top-ups where is the average of a person’s top-ups
Different top-up patterns 1 1 1 1 10 1 1 1 1 1 1
Different top-up patterns Higher household income 10 Averagetop-up size Lower household income 1 1 1 1 1 1 1 1 1 1 Top-up frequency
Average of top-up behavior 0.53 USD 0.73 USD 1.02 USD 1.44 USD
0.53 USD 0.73 USD 1.02 USD 1.44 USD
Coefficient of Variation of top-up behavior 33.8 % 92.3 % 205.5 % 457.3 %
Mobile Phone Datasets • Mobility variables • Where people live • Consumption variables • How people buy airtime credit • Social variables • How people are connected to each other
Constructing the social graph • Enough communications • Reciprocity • Not especially in developing countries … They are connected if …
Coefficient of Variation of top-up behaviorwithin communities 24.9 % 38.5 % 52.1 % 65.8 %
Coefficient of Variation of top-up behavior 33.8 % 92.3 % 205.5 % 457.3 %
Coefficient of Variation of top-up behaviorwithin communities 24.9 % 38.5 % 52.1 % 65.8 %
Mobile Phone Datasets • Mobility variables • Localization of the population within the country • Consumption variables • Estimating wealth, mapping it and its diversity • Social variables • Estimating segregation