IDEAS home Printed from https://ideas.repec.org/p/wbk/wbgpmt/15.html
   My bibliography  Save this paper

March 2021 PovcalNet Update: What's New

Author

Listed:
  • 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. Edochie
  • Dean M. Jolliffe
  • Christoph Lakner
  • Daniel Gerszon Mahler
  • Jose Montes
  • Laura Liliana Moreno Herrera
  • Rose Mungai
  • David Locke Newhouse
  • Minh C. Nguyen
  • Diana M. Sanchez Castro
  • Marta Schoch
  • Dhiraj Sharma
  • Kenneth Simler
  • Rob Swinkel
  • Shinya Takamatsu
  • Ikuko Uochi
  • Martha C. Viveros Mendoza
  • Nishant Yonzan
  • Nobuo Yoshida
  • Haoyu Wu

Abstract

The March 2021 update to PovcalNet involves several changes to the data underlying the global poverty estimates. Some welfare aggregates have been changed for improved harmonization, and the CPI, national accounts, and population input data have been updated. This document explains these changes in detail and the reasoning behind them. In addition to the changes listed here, a large number of new country-years have been added, resulting in a total number of surveys of more than 1,900. Moreover, this update includes important revisions to the historical survey data and for the first time, poverty estimates based on imputed consumption data.

Suggested Citation

  • 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.
  • Handle: RePEc:wbk:wbgpmt:15
    as

    Download full text from publisher

    File URL: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/654971615585402030/march-2021-povcalnet-update-what-s-new
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. World Bank, 2020. "Poverty and Shared Prosperity 2020," World Bank Publications - Books, The World Bank Group, number 34496.
    3. 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.
    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. 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.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Dang, Hai-Anh H & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," IZA Discussion Papers 14631, Institute of Labor Economics (IZA).
    6. 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.
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. 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.
    12. World Bank, 2016. "Tunisia Poverty Assessment 2015," World Bank Publications - Reports 24410, The World Bank Group.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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).
    18. 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.
    19. 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.
    20. 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.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:wbgpmt:15. 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.