258 citations · 345 across the 15 of their papers we have counts for
16 papers
Big Data Privacy in Emerging Market Fintech and Financial Services: A Research Agenda
Joshua E. Blumenstock, Nitin Kohli
The data revolution in low- and middle-income countries is quickly transforming how companies approach emerging markets. As mobile phones and mobile money proliferate, they generat…
Privacy Guarantees for Personal Mobility Data in Humanitarian Response
Nitin Kohli, Emily Aiken, Joshua Blumenstock
Personal mobility data from mobile phones and other sensors are increasingly used to inform policymaking during pandemics, natural disasters, and other humanitarian crises. However…
Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policy
Emily Aiken, Esther Rolf, Joshua Blumenstock
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 governm…
Can Strategic Data Collection Improve the Performance of Poverty Prediction Models?
Satej Soman, Emily Aiken, Esther Rolf +1
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. However, the…
Program Targeting with Machine Learning and Mobile Phone Data: Evidence from an Anti-Poverty Intervention in Afghanistan
Emily Aiken, Guadalupe Bedoya, Joshua Blumenstock +1
Can mobile phone data improve program targeting? By combining rich survey data from a "big push" anti-poverty program in Afghanistan with detailed mobile phone logs from program be…
(Machine) Learning What Policies Value
Daniel Björkegren, Joshua E. Blumenstock, Samsun Knight
When a policy prioritizes one person over another, is it because they benefit more, or because they are preferred? This paper develops a method to uncover the values consistent wit…
Phone Sharing and Cash Transfers in Togo: Quantitative Evidence from Mobile Phone Data
Emily L. Aiken, Viraj Thakur, Joshua E. Blumenstock
Phone sharing is pervasive in many low- and middle-income countries, affecting how millions of people interact with technology and each other. Yet there is very little quantitative…
Micro-Estimates of Wealth for all Low- and Middle-Income Countries
Guanghua Chi, Han Fang, Sourav Chatterjee +1
Many critical policy decisions, from strategic investments to the allocation of humanitarian aid, rely on data about the geographic distribution of wealth and poverty. Yet many pov…
Gamblers Learn from Experience
Joshua E. Blumenstock, Matthew Olckers
Mobile phone-based sports betting has exploded in popularity in many African countries. Commentators worry that low-ability gamblers will not learn from experience, and may rely on…
Manipulation-Proof Machine Learning
Daniel Björkegren, Joshua E. Blumenstock, Samsun Knight
An increasing number of decisions are guided by machine learning algorithms. In many settings, from consumer credit to criminal justice, those decisions are made by applying an est…
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
Esther Rolf, Max Simchowitz, Sarah Dean +4
While real-world decisions involve many competing objectives, algorithmic decisions are often evaluated with a single objective function. In this paper, we study algorithmic polici…
Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty
Muhammad Raza Khan, Joshua E. Blumenstock
With the rapid expansion of mobile phone networks in developing countries, large-scale graph machine learning has gained sudden relevance in the study of global poverty. Recent app…
Determinants of Mobile Money Adoption in Pakistan
Muhammad Raza Khan, Joshua Blumenstock
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. Our results highlight the fac…
Machine Learning Across Cultures: Modeling the Adoption of Financial Services for the Poor
Muhammad Raza Khan, Joshua E. Blumenstock
Recently, mobile operators in many developing economies have launched "Mobile Money" platforms that deliver basic financial services over the mobile phone network. While many belie…
Predicting Student Dropout in Higher Education
Lovenoor Aulck, Nishant Velagapudi, Joshua Blumenstock +1
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. Yet, littl…
Behavioral Modeling for Churn Prediction: Early Indicators and Accurate Predictors of Custom Defection and Loyalty
Muhammad R. Khan, Johua Manoj, Anikate Singh +1
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.…