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The Concept and Empirical Evidence of SWIFT Methodology

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  • World Bank

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  • World Bank, 2022. "The Concept and Empirical Evidence of SWIFT Methodology," World Bank Publications - Reports 38095, The World Bank Group.
    • Handle: RePEc:wbk:wboper:38095
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    1. Yuzhe Liu & Vanathi Gopalakrishnan, 2017. "An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data," Data, MDPI, vol. 2(1), pages 1-15, January.
    2. Ben Leo, Robert Morello, Jonathan Mellon, Tiago Peixoto, and Stephen Davenport, 2015. "Do Mobile Phone Surveys Work in Poor Countries? - Working Paper 398," Working Papers 398, Center for Global Development.
    3. David Stifel & Luc Christiaensen, 2007. "Tracking Poverty Over Time in the Absence of Comparable Consumption Data," The World Bank Economic Review, World Bank, vol. 21(2), pages 317-341, June.
    4. Astrid Mathiassen, 2009. "A model based approach for predicting annual poverty rates without expenditure data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 7(2), pages 117-135, June.
    5. Alessandro Tarozzi & Angus Deaton, 2009. "Using Census and Survey Data to Estimate Poverty and Inequality for Small Areas," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 773-792, November.
    6. Astrid Mathiassen & Bjørn K. Getz Wold, 2021. "Predicting poverty trends by survey-to-survey imputation: the challenge of comparability," Oxford Economic Papers, Oxford University Press, vol. 73(3), pages 1153-1174.
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