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Costing household surveys for monitoring progress toward ending extreme poverty and boosting shared prosperity

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  • Kilic,Talip
  • Serajuddin,Umar
  • Uematsu,Hiroki
  • Yoshida,Nobuo
  • Kilic,Talip
  • Serajuddin,Umar
  • Uematsu,Hiroki
  • Yoshida,Nobuo

Abstract

On October 15, 2015, World Bank Group President Jim Yong Kim announced the World Bank Group?s commitment to support the 78 poorest countries to implement a multi-topic household survey every three years between 2016 and 2030, for monitoring progress toward ending extreme poverty and boosting shared prosperity. This paper estimates the resource requirements to achieve the objectives of implementing 390 surveys across 78 International Development Association countries from 2016 to 2030, and providing direct technical assistance to the national statistical offices on all facets of survey design, implementation, and dissemination toward timely production of quality household survey data. The approach to the costing exercise is unique, as it makes use of detailed data on actual survey implementation and technical assistance costs from a group of countries, unlike previous attempts at costing household survey data gaps. The required total budget, in accordance with the survey design features recommended by the World Bank Household Survey Strategy, is estimated at US$945 million for the period of 2016-2030. Of this, US$692 million is projected to cover the survey implementation costs across 78 countries, and US$253 million is projected to cover the costs of direct technical assistance to be provided to the national statistical offices.

Suggested Citation

  • Kilic,Talip & Serajuddin,Umar & Uematsu,Hiroki & Yoshida,Nobuo & Kilic,Talip & Serajuddin,Umar & Uematsu,Hiroki & Yoshida,Nobuo, 2017. "Costing household surveys for monitoring progress toward ending extreme poverty and boosting shared prosperity," Policy Research Working Paper Series 7951, The World Bank.
  • Handle: RePEc:wbk:wbrwps:7951
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. M. Enenkel & M. E. Brown & J. V. Vogt & J. L. McCarty & A. Reid Bell & D. Guha-Sapir & W. Dorigo & K. Vasilaky & M. Svoboda & R. Bonifacio & M. Anderson & C. Funk & D. Osgood & C. Hain & P. Vinck, 2020. "Why predict climate hazards if we need to understand impacts? Putting humans back into the drought equation," Climatic Change, Springer, vol. 162(3), pages 1161-1176, October.
    3. Thi Huong Trinh & Dharani Dhar Burra & Michel Simioni & Stef de Haan & Tuyen Thi Thanh Huynh & Tung Van Huynh & Andrew D. Jones, 2019. "Supermarkets and their impacts on the relationship between food acquisition patterns and socio-economic and demographic characteristics of households: empirical evidence from Vietnam," Post-Print hal-02790424, HAL.
    4. Huong Thi Trinh & Burra D. Dhar & Michel Simioni & Stef de Haan & Tuyen Thi Thanh Huynh & Tung V. Huynh & Andrew D. Jones, 2020. "Supermarkets and household food acquisition patterns in Vietnam in relation to population demographics and socioeconomic strata: insights from public data," Post-Print hal-02624928, HAL.
    5. Dang,Hai-Anh H. & Pullinger,John James & Serajuddin,Umar & Stacy,Brian William, 2021. "Statistical Performance Indicators and Index : A New Tool to Measure Country Statistical Capacity," Policy Research Working Paper Series 9570, The World Bank.
    6. Gourlay, Sydney & Kilic, Talip & Martuscelli, Antonio & Wollburg, Philip & Zezza, Alberto, 2021. "Viewpoint: High-frequency phone surveys on COVID-19: Good practices, open questions," Food Policy, Elsevier, vol. 105(C).
    7. 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.
    8. Thomas Pave Sohnesen & Peter Fisker & David Malmgren‐Hansen, 2022. "Using Satellite Data to Guide Urban Poverty Reduction," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(S2), pages 282-294, December.
    9. Fisker,Peter Simonsen & Gallego-Ayala,Jordi Jose & Malmgren Hansen,David & Pave Sohnesen,Thomas & Murrugarra,Edmundo, 2022. "Guiding Social Protection Targeting Through Satellite Data in São Tomé and Príncipe," Social Protection Discussion Papers and Notes 177340, The World Bank.
    10. 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.
    11. Van Der Weide,Roy & Blankespoor,Brian & Elbers,Chris T.M. & Lanjouw,Peter F., 2022. "How Accurate Is a Poverty Map Based on Remote Sensing Data ? An Application to Malawi," Policy Research Working Paper Series 10171, The World Bank.

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