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Using Big Data and machine learning to locate the poor in Nigeria


Using Big Data and machine learning to locate the poor in Nigeria
According to the 2018/19 Nigeria Living Standards Survey (NLSS), just 1.6% of Nigerians lived in a household that was enrolled in the National Social Safety Net Project (NASSP), the country’s flagship social protection program. As is the case in other countries, those Nigerians newly impoverished by the COVID-19 crisis are likely to be different from the existing poor: they are more urban, more likely to live in southern Nigeria, and more dependent on service sector incomes. This evolving profile of the poor is reflected in current efforts to expand social protection in Nigeria, including the Rapid Response Register for the COVID-19 Cash Transfer Project, which is being guided by the mapping exercise described below. ....

United States , National Social Safety Net Project , University Of California , National Social Safety Nets Coordinating Office , Nigeria Living Standards Survey , Health Survey , Living Standards Survey , Rapid Response Register , Transfer Project , Big Data , South West , Poverty Action , Geographic Micro Targeting , Social Assistance , High Resolution Poverty , ஒன்றுபட்டது மாநிலங்களில் , தேசிய சமூக பாதுகாப்பு நிகர ப்ராஜெக்ட் , பல்கலைக்கழகம் ஆஃப் கலிஃபோர்னியா , தேசிய சமூக பாதுகாப்பு வலைகள் ஒருங்கிணைத்தல் அலுவலகம் , நைஜீரியா வாழும் தரநிலைகள் கணக்கெடுப்பு , ஆரோக்கியம் கணக்கெடுப்பு , வாழும் தரநிலைகள் கணக்கெடுப்பு , விரைவான பதில் பதிவு , பரிமாற்றம் ப்ராஜெக்ட் , பெரியது தகவல்கள் , தெற்கு மேற்கு ,