n one study, DEEP researchers used advanced statistical techniques to predict the distribution of extreme urban poverty in Tanzania. By using household surveys and satellite imagery, we highlighted the limitations of using surveys alone and found that the poorest neighbourhoods tend to be far from city centres. The research has been cited and discussed at a range of African conferences and meetings, and in the UK. Our work to identify who is living in poverty in Tanzania has also touched on conflict, climate change, social protection and multidimensional poverty. 

Innovative use of AI has helped DEEP researchers explore the drivers of poverty and how these might change over time. We found fluctuations in poverty in different regions and in rural areas, with persistent poverty among farm workers and households led by people with lower levels of education. These findings have been discussed at multiple high-level conferences. We’re also producing a visual overview of poverty evidence in Tanzania to identify gaps and inform research priorities. 

Our wide-ranging studies on addressing poverty in Tanzania have explored energy efficiency, decarbonisation, gender norms, disability, food security in urban areas, social protection and asset transfers. Another study is looking at the economic benefits of providing information via mobile phones. We’re also providing statistical training to a range of government bodies. And we’re working with the President’s Office to provide evidence for the country’s Vision 2050 plan to build an inclusive economy and reduce poverty.