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Updating poverty estimates at frequent intervals in the absence of consumption data : methods and illustration with reference to a middle-income country

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Cited by:

  1. Hai-Anh H. Dang & Peter F. Lanjouw, 2018. "Poverty Dynamics in India between 2004 and 2012: Insights from Longitudinal Analysis Using Synthetic Panel Data," Economic Development and Cultural Change, University of Chicago Press, vol. 67(1), pages 131-170.
  2. Cuesta, Jose & Chagalj, Cristian, 2019. "Measuring poverty with administrative data in data deprived contexts: The case of Nicaragua," Economics Letters, Elsevier, vol. 183(C), pages 1-1.
  3. Federica Alfani & Fabio Clementi & Michele Fabiani & Vasco Molini & Enzo Valentini, 2023. "Once NEET, always NEET? A synthetic panel approach to analyze the Moroccan labor market," Review of Development Economics, Wiley Blackwell, vol. 27(4), pages 2401-2437, November.
  4. Gianni Betti & Vasco Molini & Dan Pavelesku, 2023. "Using poverty maps to improve the design of household surveys: the evidence from Tunisia," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1641-1657, December.
  5. Theresa Beltramo & Hai-Anh Dang & Ibrahima Sarr & Paolo Verme, 2024. "Estimating poverty among refugee populations: a cross-survey imputation exercise for Chad," Oxford Development Studies, Taylor & Francis Journals, vol. 52(1), pages 94-113, January.
  6. Shinya Takamatsu & Nobuo Yoshida & Rakesh Ramasubbaiah & Freeha Fatima, 2021. "Rapid Consumption Method and Poverty and Inequality Estimation in South Sudan Revisited," World Bank Publications - Reports 36540, The World Bank Group.
  7. Dang,Hai-Anh H., 2018. "To impute or not to impute ? a review of alternative poverty estimation methods in the context of unavailable consumption data," Policy Research Working Paper Series 8403, The World Bank.
  8. Jose Cuesta & Gabriel Lara Ibarra, 2017. "Comparing Cross-Survey Micro Imputation and Macro Projection Techniques: Poverty in Post Revolution Tunisia," Journal of Income Distribution, Ad libros publications inc., vol. 25(1), pages 1-30, March.
  9. Sarr, Ibrahima & Dang, Hai-Anh H & Gutierrez, Carlos Santiago Guzman & Beltramo, Theresa & Verme, Paolo, 2024. "Using Cross-Survey Imputation to Estimate Poverty for Venezuelan Refugees in Colombia," IZA Discussion Papers 17036, Institute of Labor Economics (IZA).
  10. Hai-Anh H. Dang, 2019. "To impute or not to impute, and how? A review of alternative poverty estimation methods in the context of unavailable consumption data," Working Papers 507, ECINEQ, Society for the Study of Economic Inequality.
  11. Dang, Hai-Anh H. & Serajuddin, Umar, 2020. "Tracking the sustainable development goals: Emerging measurement challenges and further reflections," World Development, Elsevier, vol. 127(C).
  12. Salvucci, Vincenzo & Tarp, Finn, 2024. "Crises, prices, and poverty – An analysis based on the Mozambican household budget surveys 1996/97–2019/20," Food Policy, Elsevier, vol. 125(C).
  13. Dang,Hai-Anh H. & Verme,Paolo, 2019. "Estimating Poverty for Refugee Populations : Can Cross-Survey Imputation Methods Substitute for Data Scarcity ?," Policy Research Working Paper Series 9076, The World Bank.
  14. 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.
  15. Dang, Hai-Anh H & Kilic, Talip & Hlasny, Vladimir & Abanokova, Kseniya & Carletto, Calogero, 2024. "Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost: Evidence from a Randomized Survey Experiment," IZA Discussion Papers 16792, Institute of Labor Economics (IZA).
  16. Shinya Takamatsu & Nobuo Yoshida & Aphichoke Kotikula, 2022. "Rapid Consumption Method and Poverty and Inequality Estimation in Somalia Revisited," Global Poverty Monitoring Technical Note Series 19, The World Bank.
  17. Peter Edward & Andy Sumner, 2015. "New estimates of global poverty and inequality: How much difference do price data," Working Papers 365, ECINEQ, Society for the Study of Economic Inequality.
  18. 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.
  19. Hai‐Anh H. Dang & Talip Kilic & Kseniya Abanokova & Calogero Carletto, 2025. "Poverty Imputation in Contexts Without Consumption Data: A Revisit With Further Refinements," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 71(1), February.
  20. 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.
  21. Eri Nakamura & Kimitaka Nishitani & Fumitoshi Mizutani, 2023. "Do Consumers Really Pay for SDGs? Re-Evaluating Consumer Behaviour Using Surveys in the USA, Germany, and Japan," CESifo Economic Studies, CESifo Group, vol. 69(3), pages 158-176.
  22. 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.
  23. Dang, Hai-Anh H & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," IZA Discussion Papers 14631, Institute of Labor Economics (IZA).
  24. Tanida Arayavechkit & Aziz Atamanov & Karen Y. Barreto Herrera & Nadia Belhaj Hassine Belghith & R. Andres Castaneda Aguilar & Tony H. M. J. Fujs & Reno Dewina & Carolina Diaz-Bonilla & Ifeanyi N. Edo, 2021. "March 2021 PovcalNet Update: What's New," Global Poverty Monitoring Technical Note Series 15, The World Bank.
  25. Caroline Krafft & Ragui Assaad & Hanan Nazier & Racha Ramadan & Atiyeh Vahidmanesh & Sami Zouari, 2019. "Estimating poverty and inequality in the absence of consumption data: an application to the Middle East and North Africa," Middle East Development Journal, Taylor & Francis Journals, vol. 11(1), pages 1-29, January.
  26. World Bank, 2016. "Tunisia Poverty Assessment 2015," World Bank Publications - Reports 24410, The World Bank Group.
  27. 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.
  28. 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.
  29. Newhouse,David Locke & Vyas,Pallavi, 2019. "Estimating Poverty in India without Expenditure Data : A Survey-to-Survey Imputation Approach," Policy Research Working Paper Series 8878, The World Bank.
  30. Jose Cuesta & Gabriel Lara Ibarra, 2018. "Comparing Cross-Survey Micro Imputation and Macro Projection Techniques: Poverty in Post Revolution Tunisia," Journal of Income Distribution, Ad libros publications inc., vol. 25(1), pages 1-30, March.
  31. 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.
  32. Shinya Takamatsu & Nobuo Yoshida & Rakesh Ramasubbaiah & Freeha Fatima, 2021. "Rapid Consumption Method and Poverty and Inequality Estimation in South Sudan revisited," Global Poverty Monitoring Technical Note Series 18, The World Bank.
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