IDEAS home Printed from https://ideas.repec.org/p/wbk/wbrwps/9530.html
   My bibliography  Save this paper

Measuring Poverty Rapidly Using Within-Survey Imputations

Author

Listed:
  • Pape,Utz Johann

Abstract

Poverty is an indicator of paramount importance for gauging the socioeconomic well-being of a population. Especially during or after a shock, poverty estimates are invaluable for assessing the severity of the impact and for identifying which parts of the population were most affected. The measurement of consumption-based monetary poverty, however, has traditionally been very time consuming. A household consumption questionnaire usually includes more than 200 items, including food and nonfood items, often requiring more than two hours to administer. This paper proposes a new methodology that combines an innovative questionnaire design with standard imputation techniques. It substantially shortens the time required to administer a household consumption questionnaire to less than 60 minutes by imputing deliberately absent consumption values for items that are not explicitly asked. The proposed methodology makes it possible to derive poverty estimates without compromising the credibility of the resulting estimate, and it performs considerably better than alternative approaches based on reduced consumption aggregates and cross-survey imputations. This new methodology is particularly useful in fragile states given the significant risks associated with lengthy interviews, as well as to rapidly assess the impact of a shock or of a project. It can also be useful to reduce enumerator and respondent fatigue, or to mitigate the problem of high nonresponse rates.

Suggested Citation

  • Pape,Utz Johann, 2021. "Measuring Poverty Rapidly Using Within-Survey Imputations," Policy Research Working Paper Series 9530, The World Bank.
  • Handle: RePEc:wbk:wbrwps:9530
    as

    Download full text from publisher

    File URL: http://documents.worldbank.org/curated/en/900741611846381624/pdf/Measuring-Poverty-Rapidly-Using-Within-Survey-Imputations.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tomoki Fujii & Roy van der Weide, 2020. "Is Predicted Data a Viable Alternative to Real Data?," The World Bank Economic Review, World Bank, vol. 34(2), pages 485-508.
    2. Beegle, Kathleen & De Weerdt, Joachim & Friedman, Jed & Gibson, John, 2012. "Methods of household consumption measurement through surveys: Experimental results from Tanzania," Journal of Development Economics, Elsevier, vol. 98(1), pages 3-18.
    3. Fiedler, John L. & Mwangi, Dena M., 2016. "Improving household consumption and expenditure surveys’ food consumption metrics: Developing a strategic approach to the unfinished agenda:," IFPRI discussion papers 1570, International Food Policy Research Institute (IFPRI).
    4. 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.
    5. 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.
    6. Kathleen Beegle & Luc Christiaensen & Andrew Dabalen & Isis Gaddis, 2016. "Poverty in a Rising Africa," World Bank Publications - Books, The World Bank Group, number 22575.
    7. Baird, Sarah & Hamory, Joan & Miguel, Edward, 2008. "Tracking, Attrition and Data Quality in the Kenyan Life Panel Survey Round 1 (KLPS-1)," Center for International and Development Economics Research, Working Paper Series qt3cw7p1hx, Center for International and Development Economics Research, Institute for Business and Economic Research, UC Berkeley.
    8. Schräpler, Jörg-Peter & Schupp, Jürgen & Wagner, Gert G., 2010. "Changing from PAPI to CAPI: Introducing CAPI in a Longitudinal Study," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 26(2), pages 239-269.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dang, Hai-Anh H & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," IZA Discussion Papers 14631, Institute of Labor Economics (IZA).
    2. 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).
    3. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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).
    3. 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.
    4. Hassine, Nadia Belhaj, 2014. "Economic inequality in the Arab region," Policy Research Working Paper Series 6911, The World Bank.
    5. Pape,Utz Johann & Wollburg,Philip Randolph, 2019. "Estimation of Poverty in Somalia Using Innovative Methodologies," Policy Research Working Paper Series 8735, The World Bank.
    6. Hassine, Nadia Belhaj, 2015. "Economic Inequality in the Arab Region," World Development, Elsevier, vol. 66(C), pages 532-556.
    7. Dang, Hai-Anh H & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," IZA Discussion Papers 14631, Institute of Labor Economics (IZA).
    8. Dean Jolliffe & Espen Beer Prydz, 2016. "Estimating international poverty lines from comparable national thresholds," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 14(2), pages 185-198, June.
    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. 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.
    11. 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.
    12. Sarr, Ibrahima & Dang, Hai-Anh H. & Guzman Gutierrez, Carlos Santiago & Beltramo, Theresa & Verme, Paolo, 2024. "Using Cross-Survey Imputation to Estimate Poverty for Venezuelan Refugees in Colombia," GLO Discussion Paper Series 1534, Global Labor Organization (GLO).
    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. Gaddis,Isis, 2016. "Prices for poverty analysis in Africa," Policy Research Working Paper Series 7652, The World Bank.
    15. 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.
    16. 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).
    17. Nora Lustig & Jon Jellema & Valentina Martinez Pabon, 2023. "Are Budget Neutral Income Floors Fiscally Viable in Sub-Saharan Africa?," Journal of African Economies, Centre for the Study of African Economies, vol. 32(Supplemen), pages 202-227.
    18. repec:lic:licosd:37516 is not listed on IDEAS
    19. Luisa Natali & Marta Moratti, 2012. "Measuring Household Welfare: Short versus long consumption modules," Papers inwopa671, Innocenti Working Papers.
    20. 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.
    21. La-Bhus Fah Jirasavetakul & Christoph Lakner, 2020. "The Distribution of Consumption Expenditure in Sub-Saharan Africa: The Inequality Among All Africans," Journal of African Economies, Centre for the Study of African Economies, vol. 29(1), pages 1-25.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wbk:wbrwps:9530. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Roula I. Yazigi (email available below). General contact details of provider: https://edirc.repec.org/data/dvewbus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.