IDEAS home Printed from https://ideas.repec.org/p/wbk/wbrwps/10171.html
   My bibliography  Save this paper

How Accurate Is a Poverty Map Based on Remote Sensing Data ? An Application to Malawi

Author

Listed:
  • Van Der Weide,Roy
  • Blankespoor,Brian
  • Elbers,Chris T.M.
  • Lanjouw,Peter F.

Abstract

This paper assesses the reliability of poverty maps derived from remote-sensing data. Employingdata for Malawi, it first obtains small area estimates of poverty by combining the Malawi household expenditure surveyfrom 2010/11 with unit record population census data from 2008. It then ignores the population census data and obtainsa second poverty map for Malawi by combining the survey data with predictors of poverty derived from remote sensing data.This allows for a clean comparison between the two poverty maps. The findings are encouraging - although thatassessment depends somewhat on the evaluation criteria employed. The two approaches reveal the same patterns in thegeography of poverty. However, there are instances where the two approaches obtain markedly different estimates ofpoverty. Poverty maps obtained using remote sensing data may do well when the decision maker is interested in comparisonsof poverty between assemblies of areas, yet may be less reliable when the focus is on estimates for specific small areas.

Suggested Citation

  • 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.
    • Handle: RePEc:wbk:wbrwps:10171
    as

    Download full text from publisher

    File URL: http://documents.worldbank.org/curated/en/099419209132236954/pdf/IDU0fcecbbc004dd3041cc088360d1c57c5ffe04.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    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. Bluhm, Richard & Krause, Melanie, 2022. "Top lights: Bright cities and their contribution to economic development," Journal of Development Economics, Elsevier, vol. 157(C).
    3. Michler, Jeffrey D. & Josephson, Anna & Kilic, Talip & Murray, Siobhan, 2022. "Privacy protection, measurement error, and the integration of remote sensing and socioeconomic survey data," Journal of Development Economics, Elsevier, vol. 158(C).
    4. Harold Alderman & Miriam Babita & Gabriel Demombynes & Nthabiseng Makhatha & Berk Özler, 2002. "How Low Can You Go? Combining Census and Survey Data for Mapping Poverty in South Africa," Journal of African Economies, Centre for the Study of African Economies, vol. 11(2), pages 169-200, June.
    5. 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.
    6. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    7. John Gibson, 2021. "Better Night Lights Data, For Longer," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 770-791, June.
    8. Van Der Weide,Roy & Rijkers,Bob & Blankespoor,Brian & Abrahams,Alexei Sisulu, 2018. "Obstacles on the road to Palestinian economic growth," Policy Research Working Paper Series 8385, The World Bank.
    9. Deon Filmer & Kinnon Scott, 2012. "Assessing Asset Indices," Demography, Springer;Population Association of America (PAA), vol. 49(1), pages 359-392, February.
    10. Baird, Sarah & McIntosh, Craig & Özler, Berk, 2013. "The regressive demands of demand-driven development," Journal of Public Economics, Elsevier, vol. 106(C), pages 27-41.
    11. Ryan Engstrom & Jonathan Hersh & David Newhouse, 2022. "Poverty from Space: Using High Resolution Satellite Imagery for Estimating Economic Well-being," The World Bank Economic Review, World Bank, vol. 36(2), pages 382-412.
    12. repec:lic:licosd:41920 is not listed on IDEAS
    13. Elbers, Chris & Lanjouw, Peter & Leite, Phillippe George, 2008. "Brazil within Brazil : testing the poverty map methodology in Minas Gerais," Policy Research Working Paper Series 4513, The World Bank.
    14. Hertel, Thomas & Burke, Marshall & Lobell, David, 2010. "The Poverty Implications of Climate-Induced Crop Yield Changes by 2030," GTAP Working Papers 3196, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
    15. van der Weide, Roy, 2014. "GLS estimation and empirical bayes prediction for linear mixed models with Heteroskedasticity and sampling weights : a background study for the POVMAP project," Policy Research Working Paper Series 7028, The World Bank.
    16. Gibson, John & Olivia, Susan & Boe-Gibson, Geua & Li, Chao, 2021. "Which night lights data should we use in economics, and where?," Journal of Development Economics, Elsevier, vol. 149(C).
    17. Bonggeun Kim & John Gibson & Geua Boe‐Gibson, 2024. "Measurement errors in popular night lights data may bias estimated impacts of economic sanctions: Evidence from closing the Kaesong Industrial Zone," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 375-389, January.
    18. John Gibson & Susan Olivia & Geua Boe‐Gibson, 2020. "Night Lights In Economics: Sources And Uses," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 955-980, December.
    19. 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.
    20. Elbers, Chris & Lanjouw, Jean O. & Lanjouw, Peter, 2002. "Micro-level estimation of welfare," Policy Research Working Paper Series 2911, The World Bank.
    21. Garcia Rojas, Diana C. & Appelt, Jonas L. & Epprecht, Michael & Kounnavong, Sengchanh & Elbers, Chris & Lanjouw, Peter F. & van Vliet, Jasper, 2024. "Interactions between sustainable development goals at the district level in Lao PDR," World Development, Elsevier, vol. 178(C).
    22. 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.
    23. Elbers, Chris & Fujii, Tomoki & Lanjouw, Peter & Ozler, Berk & Yin, Wesley, 2007. "Poverty alleviation through geographic targeting: How much does disaggregation help?," Journal of Development Economics, Elsevier, vol. 83(1), pages 198-213, May.
    24. Martin Ravallion, 2018. "Inequality and Globalization: A Review Essay," Journal of Economic Literature, American Economic Association, vol. 56(2), pages 620-642, June.
    25. Nathan Nunn & Diego Puga, 2012. "Ruggedness: The Blessing of Bad Geography in Africa," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 20-36, February.
    26. Cuong Nhu Nguyen & Ilan Noy, 2020. "Measuring the impact of insurance on urban earthquake recovery using nightlights [Simple diagnostic tests for spatial dependence]," Journal of Economic Geography, Oxford University Press, vol. 20(3), pages 857-877.
    27. Tara Bedi & Aline Coudouel & Kenneth Simler, 2007. "More Than a Pretty Picture : Using Poverty Maps to Design Better Policies and Interventions," World Bank Publications - Books, The World Bank Group, number 6800.
    28. 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.
    29. Matthijs van Veelen & Roy van der Weide, 2008. "A Note on Different Approaches to Index Number Theory," American Economic Review, American Economic Association, vol. 98(4), pages 1722-1730, September.
    30. Isabella S. Smythe & Joshua E. Blumenstock, 2022. "Geographic microtargeting of social assistance with high-resolution poverty maps," Decision Analysis, INFORMS, vol. 119(32), pages 2120025119-, August.
    31. Corral Rodas,Paul Andres & Molina,Isabel & Nguyen,Minh Cong, 2020. "Pull Your Small Area Estimates up by the Bootstraps," Policy Research Working Paper Series 9256, The World Bank.
    32. Newhouse,David Locke & Merfeld,Joshua David & Ramakrishnan,Anusha Pudugramam & Swartz,Tom & Lahiri,Partha, 2022. "Small Area Estimation of Monetary Poverty in Mexico Using Satellite Imagery and Machine Learning," Policy Research Working Paper Series 10175, The World Bank.
    33. Benjamin Marx & Thomas M. Stoker & Tavneet Suri, 2019. "There Is No Free House: Ethnic Patronage in a Kenyan Slum," American Economic Journal: Applied Economics, American Economic Association, vol. 11(4), pages 36-70, October.
    34. Demombynes, Gabriel & Ozler, Berk, 2005. "Crime and local inequality in South Africa," Journal of Development Economics, Elsevier, vol. 76(2), pages 265-292, April.
    35. 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.
    36. Winsemius, Hessel C. & Jongman, Brenden & Veldkamp, Ted I.E. & Hallegatte, Stephane & Bangalore, Mook & Ward, Philip J., 2018. "Disaster risk, climate change, and poverty: assessing the global exposure of poor people to floods and droughts," Environment and Development Economics, Cambridge University Press, vol. 23(3), pages 328-348, June.
    37. Isabella S. Smythe & Joshua E. Blumenstock, 2022. "Geographic microtargeting of social assistance with high-resolution poverty maps," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(32), pages 2120025119-, August.
    38. Roberts,Mark & Blankespoor,Brian & Deuskar,Chandan & Stewart,Benjamin P., 2017. "Urbanization and development : is Latin America and the Caribbean different from the rest of the world?," Policy Research Working Paper Series 8019, The World Bank.
    39. Kathleen P. Bell & Nancy E. Bockstael, 2000. "Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Microlevel Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 72-82, February.
    40. Olivia, Susan & Gibson, John & Rozelle, Scott & Huang, Jikun & Deng, Xiangzheng, 2011. "Mapping poverty in rural China: how much does the environment matter?," Environment and Development Economics, Cambridge University Press, vol. 16(2), pages 129-153, April.
    41. Hertel, Thomas & Burke, Marshall & Lobell, David, 2010. "The Poverty Implications of Climate-Induced Crop Yield Changes by 2030," GTAP Working Papers 3196, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
    42. Monica Pratesi & Nicola Salvati, 2008. "Small area estimation: the EBLUP estimator based on spatially correlated random area effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(1), pages 113-141, February.
    43. Elbers, Chris & van der Weide, Roy, 2014. "Estimation of normal mixtures in a nested error model with an application to small area estimation of poverty and inequality," Policy Research Working Paper Series 6962, The World Bank.
    44. Watmough, Gary R. & Atkinson, Peter M. & Saikia, Arupjyoti & Hutton, Craig W., 2016. "Understanding the Evidence Base for Poverty–Environment Relationships using Remotely Sensed Satellite Data: An Example from Assam, India," World Development, Elsevier, vol. 78(C), pages 188-203.
    45. Tomoki Fujii, 2010. "Micro-Level Estimation of Child Undernutrition Indicators in Cambodia," The World Bank Economic Review, World Bank, vol. 24(3), pages 520-553, December.
    46. Xiaoxuan Zhang & John Gibson & Xiangzheng Deng, 2023. "Remotely too equal: Popular DMSP night‐time lights data understate spatial inequality," Regional Science Policy & Practice, Wiley Blackwell, vol. 15(9), pages 2106-2125, December.
    47. Samuel Bazzi, 2017. "Wealth Heterogeneity and the Income Elasticity of Migration," American Economic Journal: Applied Economics, American Economic Association, vol. 9(2), pages 219-255, April.
    48. John Gibson & Trinh Le & Bonggeun Kim, 2017. "Prices, Engel Curves, and Time-Space Deflation: Impacts on Poverty and Inequality in Vietnam," The World Bank Economic Review, World Bank, vol. 31(2), pages 504-530.
    49. 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.
    50. Lee, Kamwoo & Braithwaite, Jeanine, 2022. "High-resolution poverty maps in Sub-Saharan Africa," World Development, Elsevier, vol. 159(C).
    51. Hentschel, Jesko, et al, 2000. "Combining Census and Survey Data to Trace the Spatial Dimensions of Poverty: A Case Study of Ecuador," The World Bank Economic Review, World Bank, vol. 14(1), pages 147-165, January.
    52. Christopher Yeh & Anthony Perez & Anne Driscoll & George Azzari & Zhongyi Tang & David Lobell & Stefano Ermon & Marshall Burke, 2020. "Using publicly available satellite imagery and deep learning to understand economic well-being in Africa," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    53. Tarozzi, Alessandro, 2011. "Can census data alone signal heterogeneity in the estimation of poverty maps?," Journal of Development Economics, Elsevier, vol. 95(2), pages 170-185, July.
    54. William Nordhaus & Xi Chen, 2015. "A sharper image? Estimates of the precision of nighttime lights as a proxy for economic statistics," Journal of Economic Geography, Oxford University Press, vol. 15(1), pages 217-246.
    55. Maxim Pinkovskiy & Xavier Sala-i-Martin, 2016. "Lights, Camera … Income! Illuminating the National Accounts-Household Surveys Debate," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 579-631.
    56. Araujo, M. Caridad & Ferreira, Francisco H.G. & Lanjouw, Peter & Özler, Berk, 2008. "Local inequality and project choice: Theory and evidence from Ecuador," Journal of Public Economics, Elsevier, vol. 92(5-6), pages 1022-1046, June.
    57. Keola, Souknilanh & Andersson, Magnus & Hall, Ola, 2015. "Monitoring Economic Development from Space: Using Nighttime Light and Land Cover Data to Measure Economic Growth," World Development, Elsevier, vol. 66(C), pages 322-334.
    58. Benjamin Crost & Joseph Felter & Patrick Johnston, 2014. "Aid under Fire: Development Projects and Civil Conflict," American Economic Review, American Economic Association, vol. 104(6), pages 1833-1856, June.
    59. Luis R. Martínez, 2022. "How Much Should We Trust the Dictator’s GDP Growth Estimates?," Journal of Political Economy, University of Chicago Press, vol. 130(10), pages 2731-2769.
    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. John Gibson & Susan Olivia & Geua Boe‐Gibson, 2020. "Night Lights In Economics: Sources And Uses," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 955-980, December.
    2. Jesse Naidoo, 2009. "Finite-Sample Bias and Inconsistency in the Estimation of Poverty Maps," SALDRU Working Papers 36, Southern Africa Labour and Development Research Unit, University of Cape Town.
    3. Shapiro, Daniel & Oh, Chang Hoon & Zhang, Peng, 2023. "Nighttime lights data and their implications for IB research," Journal of International Management, Elsevier, vol. 29(5).
    4. Felbermayr, Gabriel & Gröschl, Jasmin & Sanders, Mark & Schippers, Vincent & Steinwachs, Thomas, 2022. "The economic impact of weather anomalies," World Development, Elsevier, vol. 151(C).
    5. Omoniyi Alimi & Geua Boe-Gibson & John Gibson, 2022. "Noisy Night Lights Data: Effects on Research Findings for Developing Countries," Working Papers in Economics 22/12, University of Waikato.
    6. GIBSON, John & ZHANG, Xiaoxuan & PARK, Albert & YI, Jiang & XI, Li, 2024. "Remotely measuring rural economic activity and poverty : Do we just need better sensors?," CEI Working Paper Series 2023-08, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    7. Jesson A. Pagaduan, 2022. "Do higher‐quality nighttime lights and net primary productivity predict subnational GDP in developing countries? Evidence from the Philippines," Asian Economic Journal, East Asian Economic Association, vol. 36(3), pages 288-317, September.
    8. Tanner Regan & Giorgio Chiovelli & Stelios Michalopoulos & Elias Papaioannou, 2023. "Illuminating Africa?," Working Papers 2023-11, The George Washington University, Institute for International Economic Policy.
    9. Masaki,Takaaki & Newhouse,David Locke & Silwal,Ani Rudra & Bedada,Adane & Engstrom,Ryan, 2020. "Small Area Estimation of Non-Monetary Poverty with Geospatial Data," Policy Research Working Paper Series 9383, The World Bank.
    10. Dickinson, Jeffrey, 2020. "Planes, Trains, and Automobiles: What Drives Human-Made Light?," MPRA Paper 103504, University Library of Munich, Germany.
    11. Gibson, John & Olivia, Susan & Boe-Gibson, Geua & Li, Chao, 2021. "Which night lights data should we use in economics, and where?," Journal of Development Economics, Elsevier, vol. 149(C).
    12. Felbermayr, Gabriel & Gröschl, Jasmin & Sanders, Mark & Schippers, Vincent & Steinwachs, Thomas, 2018. "Shedding Light on the Spatial Diffusion of Disasters," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181556, Verein für Socialpolitik / German Economic Association.
    13. Linsenmeier, Manuel, 2021. "Temperature variability and long-run economic development," LSE Research Online Documents on Economics 110499, London School of Economics and Political Science, LSE Library.
    14. repec:ags:aaea22:335528 is not listed on IDEAS
    15. McSharry, Patrick & Mawejje, Joseph, 2024. "Estimating urban GDP growth using nighttime lights and machine learning techniques in data poor environments: The case of South Sudan," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    16. Bonggeun Kim & John Gibson & Geua Boe‐Gibson, 2024. "Measurement errors in popular night lights data may bias estimated impacts of economic sanctions: Evidence from closing the Kaesong Industrial Zone," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 375-389, January.
    17. Patrick Lehnert & Michael Niederberger & Uschi Backes-Gellner & Eric Bettinger, 2020. "Proxying Economic Activity with Daytime Satellite Imagery: Filling Data Gaps Across Time and Space," Economics of Education Working Paper Series 0165, University of Zurich, Department of Business Administration (IBW), revised Sep 2022.
    18. Diep Hoang Phan, 2023. "Lights and GDP relationship: What does the computer tell us?," Empirical Economics, Springer, vol. 65(3), pages 1215-1252, September.
    19. Thomas Steinwachs, 2019. "Geography Matters: Spatial Dimensions of Trade, Migration and Growth," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 81, May.
    20. John Gibson & Bonggeun Kim & Geua Boe-Gibson, 2022. "How effective are sanctions on North Korea? Popular DMSP night-lights data may bias evaluations due to blurring and poor low-light detection," Working Papers in Economics 22/06, University of Waikato, revised 14 Nov 2022.
    21. Tomoki Fujii, 2013. "Geographic decomposition of inequality in health and wealth: evidence from Cambodia," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(3), pages 373-392, September.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies
    • Y91 - Miscellaneous Categories - - Other - - - Pictures and Maps

    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:10171. 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.