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Estimating Quarterly Poverty Rates Using Labor Force Surveys: A Primer

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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. 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.
  3. 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.
  4. Dang, Hai-Anh & Carletto, Calogero & Gourlay, Sydney & Abanokova, Kseniya, 2024. "Addressing Soil Quality Data Gaps with Imputation: Evidence from Ethiopia and Uganda," GLO Discussion Paper Series 1445, Global Labor Organization (GLO).
  5. 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.
  6. Dang,Hai-Anh H. & Lanjouw,Peter F. & Serajuddin,Umar & Dang,Hai-Anh H. & Lanjouw,Peter F. & Serajuddin,Umar, 2014. "Updating poverty estimates at frequent intervals in the absence of consumption data : methods and illustration with reference to a middle-income country," Policy Research Working Paper Series 7043, The World Bank.
  7. F. Clementi & A. L. Dabalen & V. Molini & F. Schettino, 2017. "When the Centre Cannot Hold: Patterns of Polarization in Nigeria," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(4), pages 608-632, December.
  8. Dang, Hai-Anh H & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," IZA Discussion Papers 14631, Institute of Labor Economics (IZA).
  9. 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.
  10. Verme, Paolo, 2020. "Which Model for Poverty Predictions?," GLO Discussion Paper Series 468, Global Labor Organization (GLO).
  11. 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.
  12. 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.
  13. Pape,Utz Johann & Parisotto,Luca, 2019. "Estimating Poverty in a Fragile Context -- The High Frequency Survey in South Sudan," Policy Research Working Paper Series 8722, The World Bank.
  14. Dang, Hai-Anh H & Kilic, Talip & Abanokova, Kseniya & Carletto, Calogero, 2024. "Imputing Poverty Indicators without Consumption Data: An Exploratory Analysis," IZA Discussion Papers 17136, Institute of Labor Economics (IZA).
  15. 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).
  16. 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.
  17. 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.
  18. 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.
  19. Atamanov, Aziz & Tandon, Sharad & Lopez-Acevedo, Gladys & Vergara Bahena, Mexico Alberto, 2020. "Measuring Monetary Poverty in the Middle East and North Africa (MENA) Region: Data Gaps and Different Options to Address Them," IZA Discussion Papers 13363, Institute of Labor Economics (IZA).
  20. 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).
  21. 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.
  22. Gregorio Izquierdo Llanes & Antonio Salcedo Galiano, 2023. "Why does equivalization matter? An application to the monetary poverty in the sustainable development goals framework," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2575-2589, June.
  23. Sinha Roy,Sutirtha & Van Der Weide,Roy, 2022. "Poverty in India Has Declined over the Last Decade But Not As Much As Previously Thought," Policy Research Working Paper Series 9994, The World Bank.
  24. World Bank, 2016. "Tunisia Poverty Assessment 2015," World Bank Publications - Reports 24410, The World Bank Group.
  25. 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.
  26. Elena Ianchovichina & Lili Mottaghi & Shantayanan Devarajan, "undated". "Middle East and North Africa Economic Monitor, October 2015," World Bank Publications - Reports 22711, The World Bank Group.
  27. Betti, Gianni & Molini, Vasco & Mori, Lorenzo, 2024. "An attempt to correct the underestimation of inequality measures in cross-survey imputation through generalized additive models for location, scale and shape," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
  28. 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.
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