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(Machine) Learning What Policies Value
When a policy prioritizes one person over another, is it because they benefit more, or because they are preferred?
Micro-Estimates of Wealth for all Low- and Middle-Income Countries
Many critical policy decisions, from strategic investments to the allocation of humanitarian aid, rely on data about the geographic distribution of wealth and poverty.
Gamblers Learn from Experience
Using data on financial transactions for over 50 000 Kenyan smartphone users, we find that gamblers do learn from experience.
Manipulation-Proof Machine Learning
An increasing number of decisions are guided by machine learning algorithms.
Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty
We show that this method outperforms state-of-the-art semi-supervised learning algorithms on three different prediction tasks using mobile phone datasets from three different developing countries.
Machine Learning Across Cultures: Modeling the Adoption of Financial Services for the Poor
Recently, mobile operators in many developing economies have launched "Mobile Money" platforms that deliver basic financial services over the mobile phone network.
