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Using Big Data to transform the poverty conversation: a Small Area Estimation approach

Social protection programs and appropriate policy are impactful drivers of poverty reduction but they need up-to-date, comprehensive and accurate data in order to effectively tackle the causes of poverty. Here we talk about advanced statistical techniques using Big Data to generate granular poverty estimates at a much lower cost and more frequently than ever before, enabling more dynamic conversations to help end extreme poverty.

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Utilising first order dominance methodology to evaluate Multidimensional Poverty in Mozambique

Multidimensional Poverty Index- A Progress Review from India by NITI Aayog

Most of the world’s extreme poor live in middle income countries – but not for long

IIn the early 1990s, there was a near complete overlap between poor people and poor countries, with more than 9 out of 10 of the world’s extreme poor living in low-income countries at the time. This picture changed over the following two decades, in part driven by the movement in and out of the low-income group of populous countries like China and India where most of the extreme poor lived.