Although machine learning models using mobile phone data can make poverty targeting faster and more cost-effective, traditional survey-based methods remain more accurate. The optimal approach therefore depends on striking the right balance between co...

In settings where reliable data on poverty is difficult to come by, non-traditional data sources such as mobile phone metadata has the potential to fill data gaps. New research on a cash transfer programme in Togo reveals that mobile phone data enabl...

New research uses mobile phone transaction data to shed light on the nature of religious adherence in Afghanistan, revealing that religiously motivated insurgent violence reduces religiosity while climate-induced income shocks increase religiosity.

The Mobile Salary Payment (MSP) reform in Afghanistan was an ambitious effort to build administrative capacity in one of the world’s most fragile states. Evidence on its impacts sheds light on what helps to improve state performance, and how fragilit...