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Estimation of Poverty Transition Matrices with Noisy Data

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  • Nayoung Lee
  • Geert Ridder
  • John Strauss

Abstract

This paper investigates potential measurement error biases in estimated poverty transition matrices. Transition matrices based on survey expenditure data has been compared to transition matrices based on measurement-error-free simulated expenditure. The simulation model uses estimates that correct for measurement error in expenditure. This dynamic model needs error-free initial conditions that can not be derived from these estimates. [Working Paper No. 270]
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  • Nayoung Lee & Geert Ridder & John Strauss, 2017. "Estimation of Poverty Transition Matrices with Noisy Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 37-55, January.
    • Handle: RePEc:wly:japmet:v:32:y:2017:i:1:p:37-55
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    Cited by:

    1. Francesco Devicienti & Valentina Gualtieri & Mariacristina Rossi, 2014. "The Persistence Of Income Poverty And Lifestyle Deprivation: Evidence From Italy," Bulletin of Economic Research, Wiley Blackwell, vol. 66(3), pages 246-278, July.
    2. John Gibson & Omoniyi Alimi, 2020. "Measuring poverty with noisy and corrected estimates of annual consumption: Evidence from Nigeria," African Development Review, African Development Bank, vol. 32(1), pages 96-107, March.
    3. Hai‐Anh H. Dang & Peter F. Lanjouw, 2023. "Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross Sections," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 599-622, June.
    4. Janz, Teresa & Augsburg, Britta & Gassmann, Franziska & Nimeh, Zina, 2023. "Leaving no one behind: Urban poverty traps in Sub-Saharan Africa," World Development, Elsevier, vol. 172(C).
    5. Simone Schotte & Rocco Zizzamia & Murray Leibbrandt, 2022. "Snakes and ladders and loaded dice: Poverty dynamics and inequality in South Africa between 2008 and 2017," South African Journal of Economics, Economic Society of South Africa, vol. 90(2), pages 214-242, June.
    6. Nayoung Lee & Geert Ridder & John Strauss, 2017. "Estimation of Poverty Transition Matrices with Noisy Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 37-55, January.
    7. Dang,Hai-Anh H. & Lanjouw,Peter F. & Swinkels,Robertus A & Dang,Hai-Anh H. & Lanjouw,Peter F. & Swinkels,Robertus A, 2014. "Who remained in poverty, who moved up, and who fell down ? an investigation of poverty dynamics in Senegal in the late 2000s," Policy Research Working Paper Series 7141, The World Bank.
    8. Guglielmo D'Amico & Riccardo De Blasis & Philippe Regnault, 2020. "Confidence sets for dynamic poverty indexes," Papers 2006.06595, arXiv.org.
    9. Lilik Sugiharti & Miguel Angel Esquivias & Mohd Shahidan Shaari & Ari Dwi Jayanti & Abdul Rahim Ridzuan, 2023. "Indonesia’s poverty puzzle: Chronic vs. transient poverty dynamics," Cogent Economics & Finance, Taylor & Francis Journals, vol. 11(2), pages 2267927-226, October.
    10. Rishi Kumar, 2022. "Household poverty dynamics in tribal Madhya Pradesh, India: A case study of 54 villages," Poverty & Public Policy, John Wiley & Sons, vol. 14(2), pages 184-203, June.
    11. Luis Beccaria & Roxana Maurizio & Ana Fernández & Paula Monsalvo & Mariana Álvarez, 2013. "Urban poverty and labor market dynamics in five Latin American countries: 2003–2008," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(4), pages 555-580, December.
    12. Dang, Hai-Anh & Lanjouw, Peter & Luoto, Jill & McKenzie, David, 2014. "Using repeated cross-sections to explore movements into and out of poverty," Journal of Development Economics, Elsevier, vol. 107(C), pages 112-128.
    13. 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.
    14. Guglielmo D’Amico & Philippe Regnault, 2018. "Dynamic Measurement of Poverty: Modeling and Estimation," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(2), pages 305-340, November.
    15. Alessio Fusco & Philippe Van Kerm, 2023. "Measuring poverty persistence," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 18, pages 192-200, Edward Elgar Publishing.
    16. Robert Schoen, 2020. "Dynamic Multistate Models With Constant Cross-Product Ratios: Applications to Poverty Status," Demography, Springer;Population Association of America (PAA), vol. 57(2), pages 779-797, April.
    17. Garza-Rodriguez, Jorge & Fernández-Ramos, Jennifer & Garcia-Guerra, Ana K. & Morales-Ramirez, Gabriela, 2015. "The dynamics of poverty in Mexico: A multinomial logistic regression analysis," MPRA Paper 77743, University Library of Munich, Germany.
    18. Jennifer Fernández-Ramos & Ana K. Garcia-Guerra & Jorge Garza-Rodriguez & Gabriela Morales-Ramirez, 2016. "The dynamics of poverty transitions in Mexico," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 43(11), pages 1082-1095, November.
    19. Hillebrecht, Michael & Klonner, Stefan & Pacere, Noraogo A., 2023. "The dynamics of poverty targeting," Journal of Development Economics, Elsevier, vol. 161(C).
    20. Rocco Zizzamia & Simone Schotte & Murray Leibbrandt & Vimal Ranchhod, 2016. "Vulnerability and the Middle Class in South Africa," SALDRU Working Papers 188, Southern Africa Labour and Development Research Unit, University of Cape Town.

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