IDEAS home Printed from https://ideas.repec.org/p/wbk/wboper/38095.html
   My bibliography  Save this paper

The Concept and Empirical Evidence of SWIFT Methodology

Author

Listed:
  • World Bank

Abstract

No abstract is available for this item.

Suggested Citation

  • World Bank, 2022. "The Concept and Empirical Evidence of SWIFT Methodology," World Bank Publications - Reports 38095, The World Bank Group.
    • Handle: RePEc:wbk:wboper:38095
    as

    Download full text from publisher

    File URL: https://openknowledge.worldbank.org/bitstreams/2939b66e-6631-5d65-bc2d-05301c79d226/download
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuzhe Liu & Vanathi Gopalakrishnan, 2017. "An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data," Data, MDPI, vol. 2(1), pages 1-15, January.
    2. Ben Leo, Robert Morello, Jonathan Mellon, Tiago Peixoto, and Stephen Davenport, 2015. "Do Mobile Phone Surveys Work in Poor Countries? - Working Paper 398," Working Papers 398, Center for Global Development.
    3. David Stifel & Luc Christiaensen, 2007. "Tracking Poverty Over Time in the Absence of Comparable Consumption Data," The World Bank Economic Review, World Bank, vol. 21(2), pages 317-341, June.
    4. Astrid Mathiassen, 2009. "A model based approach for predicting annual poverty rates without expenditure data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 7(2), pages 117-135, June.
    5. Alessandro Tarozzi & Angus Deaton, 2009. "Using Census and Survey Data to Estimate Poverty and Inequality for Small Areas," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 773-792, November.
    6. 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.
    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 & 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.
    2. Ibrahima Sarr & Hai-Anh H. Dang & Carlos Santiago Guzman Gutierrez & Theresa Beltramo & Paolo Verme, 2025. "Using Cross-Survey Imputation to Estimate Poverty for Venezuelan Refugees in Colombia," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 177(1), pages 207-251, March.
    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. Hai-Anh H. Dang & Talip Kilic & Ksenia Abanokova & Gero Carletto, 2024. "Imputing Poverty Indicators without Consumption Data : An Exploratory Analysis," Policy Research Working Paper Series 10867, The World Bank.
    5. 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.
    6. 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.
    7. 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.
    8. Dang, Hai-Anh H & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," IZA Discussion Papers 14631, Institute of Labor Economics (IZA).
    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. Caroline Krafft & Ragui Assaad & Hanan Nazier & Racha Ramadan & Atiyeh Vahidmanesh & Sami Zouari, 2019. "Estimating poverty and inequality in the absence of consumption data: an application to the Middle East and North Africa," Middle East Development Journal, Taylor & Francis Journals, vol. 11(1), pages 1-29, January.
    11. World Bank, 2016. "Tunisia Poverty Assessment 2015," World Bank Publications - Reports 24410, The World Bank Group.
    12. 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.
    13. Hai-Anh H. Dang, 2019. "To impute or not to impute, and how? A review of alternative poverty estimation methods in the context of unavailable consumption data," Working Papers 507, ECINEQ, Society for the Study of Economic Inequality.
    14. Echevin, Damien, 2011. "Vulnerability and livelihoods before and after the Haiti earthquake," Policy Research Working Paper Series 5850, The World Bank.
    15. Jarrad Farris & Catherine Larochelle & Jeffrey Alwang & George W. Norton & Caleb King, 2017. "Poverty analysis using small area estimation: an application to conservation agriculture in Uganda," Agricultural Economics, International Association of Agricultural Economists, vol. 48(6), pages 671-681, November.
    16. Channing Arndt & Azhar M. Hussain & Vincenzo Salvucci & Finn Tarp & Lars Peter Østerdal, 2016. "Poverty Mapping Based on First‐Order Dominance with an Example from Mozambique," Journal of International Development, John Wiley & Sons, Ltd., vol. 28(1), pages 3-21, January.
    17. Janina Isabel Steinert & Lucie Dale Cluver & G. J. Melendez-Torres & Sebastian Vollmer, 2018. "One Size Fits All? The Validity of a Composite Poverty Index Across Urban and Rural Households in South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(1), pages 51-72, February.
    18. Ndashimye, Felix & Hebie, Oumarou & Tjaden, Jasper, 2021. "Effectiveness of WhatsApp for measuring migration in follow-up phone surveys - Lessons from a mode experiment in two low-income countries during COVID contact restrictions," OSF Preprints khd32, Center for Open Science.
    19. Maria Plotnikova, 2020. "Explaining Spatial Patterns Of Incapacity Benefit Claimant Rolls," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 14(2), pages 35-48, DECEMBER.
    20. Takaaki Masaki & David Newhouse & Ani Rudra Silwal & Adane Bedada & Ryan Engstrom, 2020. "Small Area Estimation of Non-Monetary Poverty with Geospatial Data," World Bank Publications - Reports 34469, The World Bank Group.

    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:wboper:38095. 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: Tal Ayalon (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.