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Small area estimation-based prediction methods to track poverty : validation and applications

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Cited by:

  1. Talip Kilic & Thomas Pave Sohnesen, 2019. "Same Question But Different Answer: Experimental Evidence on Questionnaire Design's Impact on Poverty Measured by Proxies," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(1), pages 144-165, March.
  2. Diana K. L. Ngo & Luc Christiaensen, 2019. "The Performance Of A Consumption Augmented Asset Index In Ranking Households And Identifying The Poor," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(4), pages 804-833, December.
  3. Betti,Gianni & Molini,Vasco & Mori,Lorenzo, 2022. "New Algorithm to Estimate Inequality Measures in Cross-Survey Imputation : An Attemptto Correct the Underestimation of Extreme Values," Policy Research Working Paper Series 10013, The World Bank.
  4. Alfani, Federica & Dabalen, Andrew & Fisker, Peter & Molini, Vasco, 2015. "Can we measure resilience ? a proposed method and evidence from countries in the Sahel," Policy Research Working Paper Series 7170, The World Bank.
  5. Aziza Usmanova & Ahmed Aziz & Dilshodjon Rakhmonov & Walid Osamy, 2022. "Utilities of Artificial Intelligence in Poverty Prediction: A Review," Sustainability, MDPI, vol. 14(21), pages 1-39, October.
  6. World Bank, "undated". "Africa's Pulse, April 2013 : An Analysis of Issues Shaping Africa's Economic Future," World Bank Publications - Reports 20238, The World Bank Group.
  7. Mohamed Douidich & Abdeljaouad Ezzrari & Roy Van der Weide & Paolo Verme, 2016. "Estimating Quarterly Poverty Rates Using Labor Force Surveys: A Primer," The World Bank Economic Review, World Bank, vol. 30(3), pages 475-500.
  8. Lain,Jonathan William & Schoch,Marta & Vishwanath,Tara, 2022. "Estimating a Poverty Trend for Nigeria between 2009 and 2019," Policy Research Working Paper Series 9974, The World Bank.
  9. Pape,Utz Johann, 2021. "Measuring Poverty Rapidly Using Within-Survey Imputations," Policy Research Working Paper Series 9530, The World Bank.
  10. Thomas Pave Sohnesen & Niels Stender, 2017. "Is Random Forest a Superior Methodology for Predicting Poverty? An Empirical Assessment," Poverty & Public Policy, John Wiley & Sons, vol. 9(1), pages 118-133, March.
  11. Rodrigo LOVATON DAVILA & Aine Seitz MCCARTHY & Dorothy GONDWE & Phatta KIRDRUAND & Uttan SHARMA, 2022. "Water, Walls, and Bicycles: Wealth Index Composition Using Census Microdata," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 88(1), pages 79-120, March.
  12. Ahmed, Faizuddin & Dorji, Cheku & Takamatsu, Shinya & Yoshida, Nobuo, 2014. "Hybrid survey to improve the reliability of poverty statistics in a cost-effective manner," Policy Research Working Paper Series 6909, The World Bank.
  13. Diana Chiliquinga & Gaurav Datt, 2016. "Changing Betas or Changing X’s? Evolution of Income and Poverty in Ecuador, 2001-12," Monash Economics Working Papers 14-16, Monash University, Department of Economics.
  14. Dang,Hai-Anh H. & Kilic,Talip & Carletto,Calogero & Abanokova,Kseniya, 2021. "Poverty Imputation in Contexts without Consumption Data : A Revisit with Further Refinements," Policy Research Working Paper Series 9838, The World Bank.
  15. Hai-Anh H. Dang & Paolo Verme, 2023. "Estimating poverty for refugees in data-scarce contexts: an application of cross-survey imputation," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 653-679, April.
  16. World Bank, 2015. "Tanzania Poverty Assessment," World Bank Publications - Reports 21871, The World Bank Group.
  17. Hai‐Anh Dang & Dean Jolliffe & Calogero Carletto, 2019. "Data Gaps, Data Incomparability, And Data Imputation: A Review Of Poverty Measurement Methods For Data‐Scarce Environments," Journal of Economic Surveys, Wiley Blackwell, vol. 33(3), pages 757-797, July.
  18. Dang, Hai-Anh & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," IZA Discussion Papers 14631, Institute of Labor Economics (IZA).
  19. World Bank, "undated". "Africa's Pulse, October 2013 : An Analysis of Issues Shaping Africa's Economic Future," World Bank Publications - Reports 20237, The World Bank Group.
  20. Li, Qing & Yu, Shuai & Échevin, Damien & Fan, Min, 2022. "Is poverty predictable with machine learning? A study of DHS data from Kyrgyzstan," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
  21. Hassine, Nadia Belhaj, 2015. "Economic Inequality in the Arab Region," World Development, Elsevier, vol. 66(C), pages 532-556.
  22. Hai-Anh H. Dang & Peter F. Lanjouw & Umar Serajuddin, 2017. "Updating poverty estimates in the absence of regular and comparable consumption data: methods and illustration with reference to a middle-income country," Oxford Economic Papers, Oxford University Press, vol. 69(4), pages 939-962.
  23. Abate, Gashaw T. & de Brauw, Alan & Hirvonen, Kalle & Wolle, Abdulazize, 2023. "Measuring consumption over the phone: Evidence from a survey experiment in urban Ethiopia," Journal of Development Economics, Elsevier, vol. 161(C).
  24. Hai-Anh H. Dang & Peter F. Lanjouw, 2023. "Regression-based imputation for poverty measurement in data-scarce settings," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 13, pages 141-150, Edward Elgar Publishing.
  25. Anh Thu Quang Pham & Pundarik Mukhopadhaya & Ha Vu, 2020. "Targeting Administrative Regions for Multidimensional Poverty Alleviation: A Study on Vietnam," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(1), pages 143-189, July.
  26. Hai‐Anh H. Dang, 2021. "To impute or not to impute, and how? A review of poverty‐estimation methods in the absence of consumption data," Development Policy Review, Overseas Development Institute, vol. 39(6), pages 1008-1030, November.
  27. Javier Sierra & Victoria Muriel-Patino & Fernando Rodríguez-López, 2024. "A comprehensive framework for understanding microfinance performance evaluation methods," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
  28. Skoufias, Emmanuel & Diamond, Alexis & Vinha, Katja & Gill, Michael & Dellepiane, Miguel Rebolledo, 2020. "Estimating poverty rates in subnational populations of interest: An assessment of the Simple Poverty Scorecard," World Development, Elsevier, vol. 129(C).
  29. Floyd Mwansa, 2023. "Measuring Distribution of Wealth in Zambia Using Census Micro Data: An Application of Principal Component Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 13(3), pages 126-140, May.
  30. Ligon, Ethan & Christiaensen, Luc & Sohnesen, Thomas P, 2020. "Should Consumption Sub-Aggregates be Used to Measure Poverty?," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9b9929jh, Department of Agricultural & Resource Economics, UC Berkeley.
  31. Newhouse, D. & Shivakumaran, S. & Takamatsu, S. & Yoshida, N., 2014. "How survey-to-survey imputation can fail," Policy Research Working Paper Series 6961, The World Bank.
  32. Carlo Azzarri & Elizabeth Cross, 2016. "Improved Spatially Disaggregated Livestock Measures for Uganda," The Review of Regional Studies, Southern Regional Science Association, vol. 46(1), pages 37-73, Winter.
  33. Hassine, Nadia Belhaj, 2014. "Economic inequality in the Arab region," Policy Research Working Paper Series 6911, The World Bank.
  34. Lisa Daniels & Nicholas Minot, 2021. "Do remote areas benefit from economic growth? Evidence from Uganda," Journal of International Development, John Wiley & Sons, Ltd., vol. 33(3), pages 545-568, April.
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