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Regression-based Imputation for Poverty Measurement in Data Scarce Settings

Author

Listed:
  • Hai-Anh Dang

    (World Bank)

  • Peter Lanjouw

    (Vrije Unversiteit, Amsterdam)

Abstract

Measuring poverty trends and dynamics are important inputs in the formulation and design of poverty reduction policies. The empirical underpinnings of such exercises are often constrained by the absence of suitable data. We provide a broad, generalist, overview of regression-based imputation methods that have seen widespread application to estimate poverty outcomes in data-scarce environments. In particular, we review two imputation methods employed in tracking poverty over time and estimating poverty dynamics. We also discuss new areas that promise of further research.

Suggested Citation

  • Hai-Anh Dang & Peter Lanjouw, 2022. "Regression-based Imputation for Poverty Measurement in Data Scarce Settings," Working Papers 611, ECINEQ, Society for the Study of Economic Inequality.
    • Handle: RePEc:inq:inqwps:ecineq2022-611
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    File URL: http://www.ecineq.org/milano/WP/ECINEQ2022-611.pdf
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    References listed on IDEAS

    as
    1. Hai-Anh Dang & Toan L.D. Huynh & Manh-Hung Nguyen, 2023. "Does the COVID-19 pandemic disproportionately affect the poor? Evidence from a six-country survey," Journal of Economics and Development, Emerald Group Publishing Limited, vol. 26(1), pages 2-18, December.
    2. Pape,Utz Johann, 2021. "Measuring Poverty Rapidly Using Within-Survey Imputations," Policy Research Working Paper Series 9530, The World Bank.
    3. 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.
    4. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
    5. Dang,Hai-Anh H. & Lanjouw,Peter F., 2013. "Measuring poverty dynamics with synthetic panels based on cross-sections," Policy Research Working Paper Series 6504, The World Bank.
    6. Dang, Hai-Anh H. & Serajuddin, Umar, 2020. "Tracking the sustainable development goals: Emerging measurement challenges and further reflections," World Development, Elsevier, vol. 127(C).
    7. Tarozzi, Alessandro, 2007. "Calculating Comparable Statistics From Incomparable Surveys, With an Application to Poverty in India," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 314-336, July.
    8. Altındağ, Onur & O'Connell, Stephen D. & Şaşmaz, Aytuğ & Balcıoğlu, Zeynep & Cadoni, Paola & Jerneck, Matilda & Foong, Aimee Kunze, 2021. "Targeting humanitarian aid using administrative data: Model design and validation," Journal of Development Economics, Elsevier, vol. 148(C).
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    10. 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.
    11. Jean Olson Lanjouw & Peter Lanjouw, 2001. "How to Compare Apples And Oranges: Poverty Measurement Based on Different Definitions of Consumption," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 47(1), pages 25-42, March.
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    13. Luc Christiaensen & Peter Lanjouw & Jill Luoto & David Stifel, 2012. "Small area estimation-based prediction methods to track poverty: validation and applications," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 10(2), pages 267-297, June.
    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. 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.
    16. Ravallion, Martin, 2016. "The Economics of Poverty: History, Measurement, and Policy," OUP Catalogue, Oxford University Press, number 9780190212773.
    17. Angus Deaton and Jean Drèze & Jean Drèze, 2002. "Poverty and Inequality in India: A Reexamination," Working papers 107, Centre for Development Economics, Delhi School of Economics.
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    19. 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.
    20. 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.
    21. Yoko Kijima & Lanjouw, Peter, 2003. "Poverty in India during the1990s - a regional perspective," Policy Research Working Paper Series 3141, The World Bank.
    22. 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.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    poverty; imputation; consumption; wealth index; synthetic panels; household survey;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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