Policies, strategies and programmes require access to high-quality and timely information to tackle extreme poverty and to monitor progress towards achieving the Sustainable Development Goals (SDGs). However, this information is not always available, is available at high cost, or only at the overall national level (i.e. not at lower levels, such as in regions or municipalities). Traditional approaches to poverty measurement rely on household surveys or census data, which are costly and therefore collected infrequently, leading to gaps in data. New sources of data – including remote sensing data, data from the data exhaust, online data, crowd-sourced data, and mobile phone survey data – and novel statistical techniques can start to fill this gap and to enhance the toolkit of approaches available for measuring and investigating extreme poverty.
This Research Insight summarises the findings of a longer review produced by the Data and Evidence to end Extreme Poverty (DEEP) research programme to explore how innovation in data collection, data processing, and data analysis might provide solutions to ‘pinch points’ in policymaking and policy management for poverty reduction.
Available at: https://doi.org/10.55158/DEEPWPR1
