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Introducing SWIFT: Real-time poverty monitoring using machine learning

The World Bank developed the Survey of Well-Being via Instant and Frequent Tracking (SWIFT) in 2014 to speed up and streamline poverty and inequality monitoring. It applies machine-learning techniques to the latest available household survey data to generate high-frequency poverty estimates that are comparable with official statistics.
World Bank Frequent Tracking Real Time Poverty Monitoring Southern Malawi Frequent Monitoring System

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Monitoring Social and Economic Impacts of COVID-19 on Refugees in Uganda: Results from the High-Frequency Phone Survey First round (October/November 2020) - Uganda

Monitoring Social and Economic Impacts of COVID-19 on Refugees in Uganda: Results from the High-Frequency Phone Survey First round (October/November 2020) Format โœ“ The employment rate among refugees was low, reaching 43 percent in October/November 2020. This was significantly lower than the employment rate among Ugandans which reached 90 percent in September/October 2020. Refugees in Kampala had the lowest employment rate (27 percent). โœ“ The sector and type of employment among refugees diff...
Nahr An Nil Access To Services South West West Nile Frequent Tracking Economic Shocks

Data-driven tools can support decision-making and improve implementation – especially in crises like COVID-19

Data-driven tools can support decision-making and improve implementation โ€“ especially in crises like COVID-19 Following major shocks due to conflict, natural disasters, or even pandemics such as COVID-19, this kind of data collection can be impossibleโ€”or too slow to be useful. Governments and development organizations can sometimes find themselves in a catch-22, with well-designed interventions being most needed in the very places where timely data are impossible to collect. To improve our...
Saint Lucia United States Saint Lucians Municipal Performance Program World Bank Rapid Response Phone Surveys

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