IDEAS home Printed from https://ideas.repec.org/p/wbk/wbrwps/9259.html
   My bibliography  Save this paper

Measuring Monetary Poverty in the Middle East and North Africa (MENA) Region : Data Gaps and Different Options to Address Them

Author

Listed:
  • Atamanov,Aziz
  • Tandon,Sharad Alan
  • Lopez-Acevedo,Gladys C.
  • Vergara Bahena,Mexico Alberto

Abstract

This paper identifies gaps in availability, access, and quality of household budget surveys in the Middle East and North Africa region used to measure monetary poverty and evaluates ways to fill these information gaps. Despite improving public access to household budget surveys, the availability and timeliness of welfare data in the Middle East and North Africa region is poor compared to the rest of the world. Closing the data gap requires collection of more HBS data in more countries and improving access to data where it exists. However, when collection of consumption data is not possible, a variety of other second-best strategies can be employed. Using imputation methods can help to measure monetary poverty. Constructing non-monetary poverty and asset indexes from less robust surveys, using non-traditional surveys such as phone surveys, and "big data" -- administrative records, social networks and communications data, and geospatial data -- can help substitute for, or complement data from existing traditional survey data.

Suggested Citation

  • Atamanov,Aziz & Tandon,Sharad Alan & Lopez-Acevedo,Gladys C. & Vergara Bahena,Mexico Alberto, 2020. "Measuring Monetary Poverty in the Middle East and North Africa (MENA) Region : Data Gaps and Different Options to Address Them," Policy Research Working Paper Series 9259, The World Bank.
    • Handle: RePEc:wbk:wbrwps:9259
    as

    Download full text from publisher

    File URL: http://documents.worldbank.org/curated/en/114681590710969392/pdf/Measuring-Monetary-Poverty-in-the-Middle-East-and-North-Africa-MENA-Region-Data-Gaps-and-Different-Options-to-Address-Them.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Atamanov,Aziz & Wieser,Christina & Uematsu,Hiroki & Yoshida,Nobuo & Nguyen,Minh Cong & Azevedo,Joao Pedro Wagner De & Dewina,Reno, 2016. "Robustness of shared prosperity estimates : how different methodological choices matter," Policy Research Working Paper Series 7611, The World Bank.
    2. Raj Chetty & John N. Friedman & Nathaniel Hilger & Emmanuel Saez & Diane Whitmore Schanzenbach & Danny Yagan, 2011. "How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project Star," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(4), pages 1593-1660.
    3. Francisco H. G. Ferreira & Shaohua Chen & Andrew Dabalen & Yuri Dikhanov & Nada Hamadeh & Dean Jolliffe & Ambar Narayan & Espen Beer Prydz & Ana Revenga & Prem Sangraula & Umar Serajuddin & Nobuo Yosh, 2016. "A global count of the extreme poor in 2012: data issues, methodology and initial results," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 14(2), pages 141-172, June.
    4. Celhay, Pablo & Meyer, Bruce D. & Mittag, Nikolas, 2021. "Errors in Reporting and Imputation of Government Benefits and Their Implications," IZA Discussion Papers 14396, Institute of Labor Economics (IZA).
    5. 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.
    6. Deon Filmer & Kinnon Scott, 2012. "Assessing Asset Indices," Demography, Springer;Population Association of America (PAA), vol. 49(1), pages 359-392, February.
    7. Serajuddin,Umar & Uematsu,Hiroki & Wieser,Christina & Yoshida,Nobuo & Dabalen,Andrew L., 2015. "Data deprivation : another deprivation to end," Policy Research Working Paper Series 7252, The World Bank.
    8. Bruce Meyer & Robert Goerge, 2011. "Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation," Working Papers 11-14, Center for Economic Studies, U.S. Census Bureau.
    9. Kenneth Harttgen & Stephan Klasen & Sebastian Vollmer, 2013. "An African Growth Miracle? Or: What do Asset Indices Tell Us About Trends in Economic Performance?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59, pages 37-61, October.
    10. Dave Donaldson & Adam Storeygard, 2016. "The View from Above: Applications of Satellite Data in Economics," Journal of Economic Perspectives, American Economic Association, vol. 30(4), pages 171-198, Fall.
    11. Santos, María Emma, 2019. "Non-monetary indicators to monitor SDG targets 1.2 and 1.4: standards, availability, comparability and quality," Estudios Estadísticos 44452, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    12. Jose Cuesta & Gabriel Lara Ibarra, 2017. "Comparing Cross-Survey Micro Imputation and Macro Projection Techniques: Poverty in Post Revolution Tunisia," Journal of Income Distribution, Ad libros publications inc., vol. 25(1), pages 1-30, March.
    13. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    14. Aziz Atamanov & Dean M. Jolliffe & Christoph Lakner & Espen Beer Prydz, 2018. "Purchasing Power Parities Used in Global Poverty Measurement," Global Poverty Monitoring Technical Note Series 5, The World Bank.
    15. Johannes Hoogeveen & Utz Pape, 2020. "Data Collection in Fragile States," World Bank Publications - Books, The World Bank Group, number 32576, April.
    16. 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.
    17. Croke, Kevin & Dabalen, Andrew & Demombynes, Gabriel & Giugale, Marcelo & Hoogeveen, Johannes, 2012. "Collecting high frequency panel data in Africa using mobile phone interviews," Policy Research Working Paper Series 6097, The World Bank.
    18. Meyer, Bruce D. & Mittag, Nikolas & Goerge, Robert M., 2018. "Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation," IZA Discussion Papers 11776, Institute of Labor Economics (IZA).
    19. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7), pages 476-487.
    20. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    21. Anna Aizer & Shari Eli & Joseph Ferrie & Adriana Lleras-Muney, 2016. "The Long-Run Impact of Cash Transfers to Poor Families," American Economic Review, American Economic Association, vol. 106(4), pages 935-971, April.
    22. Anna, Petrenko, 2016. "Мaркування готової продукції як складова частина інформаційного забезпечення маркетингової діяльності підприємств овочепродуктового підкомплексу," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 2(01), March.
    23. 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.
    24. Johannes Hoogeveen & Andrew Dabalen & Elvis Mushi & Alvin Etang & Youdi Schipper & Johannes von Engelhardt, 2016. "Mobile Phone Panel Surveys in Developing Countries," World Bank Publications - Books, The World Bank Group, number 24595, April.
    25. Toomet,Ott & Blumenstock,Joshua Evan & Scherer,Thomas & Herskowitz,Sylvan Rene & Ghani,Tarek F. & Kapstein,Ethan B., 2018. "Insecurity and industrial organization : evidence from Afghanistan," Policy Research Working Paper Series 8301, The World Bank.
    26. World Bank, 2018. "Poverty and Shared Prosperity 2018 [Rapport 2018 sur la pauvreté et la prospérité partagée]," World Bank Publications - Books, The World Bank Group, number 30418, April.
    27. Katharine G. Abraham & Sara E. Helms & Stanley Presser, 2008. "How Social Processes Distort Measurement: The Impact of Survey Nonresponse on Estimates of Volunteer Work," NBER Working Papers 14076, National Bureau of Economic Research, Inc.
    28. World Bank, 2017. "Monitoring Global Poverty," World Bank Publications - Books, The World Bank Group, number 25141, April.
    29. Nethra Palaniswamy & Aziz Atamanov, 2018. "West Bank and Gaza Poverty and Shared Prosperity Diagnostic 2011-2017," World Bank Publications - Reports 30405, The World Bank Group.
    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. Robertson, Raymond & Vergara Bahena, Mexico Alberto & Lopez-Acevedo, Gladys, 2022. "Is International Trade Always Beneficial to Labor Markets? A Case Study from Egypt," IZA Discussion Papers 15626, Institute of Labor Economics (IZA).
    2. Ekhator-Mobayode,Uche Eseosa & Hoogeveen,Johannes G., 2021. "Microdata Collection and Openness in the Middle East and North Africa (MENA) : Introducing the MENAMicrodata Access Indicator," Policy Research Working Paper Series 9892, The World Bank.
    3. Vladimir Hlasny & Paolo Verme, 2022. "On the ‘Arab Inequality Puzzle’: A Comment," Development and Change, International Institute of Social Studies, vol. 53(2), pages 448-458, March.
    4. Robertson,Raymond & Vergara Bahena,Mexico Alberto & Kokas,Deeksha & Lopez-Acevedo,Gladys C., 2021. "International Trade and Labor Markets : Evidence from the Arab Republic of Egypt," Policy Research Working Paper Series 9668, The World Bank.
    5. Paul Makdissi & Walid Marrouch & Myra Yazbeck, 2025. "Monitoring Poverty in a Data‐Deprived Environment: The Case of Lebanon," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 71(1), February.
    6. Mohamad A. Khaled & Paul Makdissi & D.S. Prasada Rao & Myra Yazbeck, 2023. "A unidimensional representation of multidimensional inequality, with an application to the Arab region," Discussion Papers Series 659, School of Economics, University of Queensland, Australia.

    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. 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. 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 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. 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. 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.
    6. van der Weide, Roy & Blankespoor, Brian & Elbers, Chris & Lanjouw, Peter, 2024. "How accurate is a poverty map based on remote sensing data? An application to Malawi," Journal of Development Economics, Elsevier, vol. 171(C).
    7. Dang, Hai-Anh H & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," IZA Discussion Papers 14631, Institute of Labor Economics (IZA).
    8. Winters, P. & Kafle, K. & Benfica, R., 2018. "IFAD RESEARCH SERIES 21 - Does relative deprivation induce migration? Evidence from sub-Saharan Africa," IFAD Research Series 280070, International Fund for Agricultural Development (IFAD).
    9. Dang, Hai-Anh H. & Serajuddin, Umar, 2020. "Tracking the sustainable development goals: Emerging measurement challenges and further reflections," World Development, Elsevier, vol. 127(C).
    10. Dutta, Indranil & Nogales, Ricardo & Yalonetzky, Gaston, 2021. "Endogenous weights and multidimensional poverty: A cautionary tale," Journal of Development Economics, Elsevier, vol. 151(C).
    11. Andrea Brandolini & John Micklewright, 2020. "Tony Atkinson’s new book, Measuring Poverty Around the World. Some further reflections," Working Papers 518, ECINEQ, Society for the Study of Economic Inequality.
    12. Marion Dovis & Patricia Augier & Clémentine Sadania, 2021. "Labor Market Shocks and Youths’ Time Allocation in Egypt: Where Does Women’s Empowerment Come In?," Economic Development and Cultural Change, University of Chicago Press, vol. 69(4), pages 1501-1540.
    13. Mausumi Mahapatro & Deborah Johnston, 2020. "Imperfection Measures and the Production of Poverty: A Case Study of the Use of the Asset Index in Bangladesh," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(2), pages 513-531, November.
    14. Hilary Hoynes & Diane Whitmore Schanzenbach & Douglas Almond, 2016. "Long-Run Impacts of Childhood Access to the Safety Net," American Economic Review, American Economic Association, vol. 106(4), pages 903-934, April.
    15. 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.
    16. Guanghua Chi & Han Fang & Sourav Chatterjee & Joshua E. Blumenstock, 2022. "Microestimates of wealth for all low- and middle-income countries," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(3), pages 2113658119-, January.
    17. Colleen Heflin & Michah W. Rothbart & Mattie Mackenzie-Liu, 2022. "Below the Tip of the Iceberg: Examining Early Childhood Participation in SNAP and TANF from Birth to Age Six," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(2), pages 729-755, April.
    18. Anna Bruederle & Roland Hodler, 2018. "Nighttime lights as a proxy for human development at the local level," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-22, September.
    19. 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.
    20. Kafle, Kashi & Jolliffe, Dean & Winter-Nelson, Alex, 2018. "Do different types of assets have differential effects on child education? Evidence from Tanzania," World Development, Elsevier, vol. 109(C), pages 14-28.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

    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:wbrwps:9259. 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.