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Found 8 papers, 1 papers with code
Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policy
Poverty maps derived from satellite imagery are increasingly used to inform high-stakes policy decisions, such as the allocation of humanitarian aid and the distribution of government resources.
Can Strategic Data Collection Improve the Performance of Poverty Prediction Models?
Machine learning-based estimates of poverty and wealth are increasingly being used to guide the targeting of humanitarian aid and the allocation of social assistance.
Program Targeting with Machine Learning and Mobile Phone Data: Evidence from an Anti-Poverty Intervention in Afghanistan
Can mobile phone data improve program targeting?
Instant Loans Can Lift Subjective Well-Being: A Randomized Evaluation of Digital Credit in Nigeria
Digital loans have exploded in popularity across low and middle income countries, providing short term, high interest credit via mobile phones.
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
Our theoretical results characterize the optimal strategies in this class, bound the Pareto errors due to inaccuracies in the scores, and show an equivalence between optimal strategies and a rich class of fairness-constrained profit-maximizing policies.
Determinants of Mobile Money Adoption in Pakistan
In this work, we analyze the problem of adoption of mobile money in Pakistan by using the call detail records of a major telecom company as our input.
Predicting Student Dropout in Higher Education
Each year, roughly 30% of first-year students at US baccalaureate institutions do not return for their second year and over $9 billion is spent educating these students.
Behavioral Modeling for Churn Prediction: Early Indicators and Accurate Predictors of Custom Defection and Loyalty
Churn prediction, or the task of identifying customers who are likely to discontinue use of a service, is an important and lucrative concern of firms in many different industries.
