At DEEP, we aim to help uncover new data, ideas, and solutions to support the change that is needed to end extreme poverty. Soon you will be able to search our Resource Centre for our latest insights, including publications and other materials.
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You are seeing pre-filtered results for Drivers and patterns of extreme poverty.
There are 13 search results using the selected filters.
This research paper explores the extent to which information extracted from satellite images can help predict the distribution of extreme urban poverty in Ethiopia, Tanzania, and Mozambique.
Latest paper from India analysing the poverty data available and applying statistical methods to create synthetic data.
Looking into the country dynamics of Tanzania where economic growth did not mean less poverty.
Poverty dynamics in Myanmar in light of last decade's social, political, and global changes.
In-depth look at how Covid-19 and other global and regional factors alter the picture of poverty in Mozambique.
Poverty transitions in Ethiopia and related impacts explored in our latest paper.
Describing a recently developed approach for constructing synthetic panels from cross-section data
Methods and tools notes about Synthetic panel estimation
A paper exploring the suite of different data sources that can be used for measuring and investigating poverty, including new data sources and statistical techniques.
A research insight summarising a longer review exploring how innovation in data collection, data processing, and data analysis, might provide solutions to ‘pinch points’ in policymaking and management
Annexe to the paper 'How can new technology support better measurement of extreme poverty?' covering methods for producing high-resolution and high-frequency poverty estimates.
As part of the inception phase of DEEP we have undertaken a selective review of what works to reduce extreme poverty in five countries.