Poverty mapping in the age of machine learning
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DOI: 10.1016/j.jdeveco.2024.103377
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- Karl Majeske & Terri Lynch-Caris & Janet Brelin-Fornari, 2010. "Quantifying R2 bias in the presence of measurement error," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(4), pages 667-677.
- 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).
- 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.
- Nikos Tzavidis & Li‐Chun Zhang & Angela Luna & Timo Schmid & Natalia Rojas‐Perilla, 2018. "From start to finish: a framework for the production of small area official statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 927-979, October.
- 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.
- Engstrom,Ryan & Hersh,Jonathan Samuel & Newhouse,David Locke & Engstrom,Ryan & Hersh,Jonathan Samuel & Newhouse,David Locke, 2017. "Poverty from space : using high-resolution satellite imagery for estimating economic well-being," Policy Research Working Paper Series 8284, The World Bank.
- Hentschel, Jesko & Lanjouw, Jean Olson & Lanjouw, Peter & Poggi, Javier, 1998. "Combining census and survey data to study spatial dimensions of poverty," Policy Research Working Paper Series 1928, The World Bank.
- Corral Rodas,Paul Andres & Kastelic,Kristen Himelein & Mcgee,Kevin Robert & Molina,Isabel, 2021. "A Map of the Poor or a Poor Map ?," Policy Research Working Paper Series 9620, The World Bank.
- 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.
- Elbers, Chris & Tomoki Fujii & Lanjouw, Peter & Ozler, Berk & Yin, Wesley, 2004. "Poverty alleviation through geographic targeting : how much does disaggregation help?," Policy Research Working Paper Series 3419, The World Bank.
- Jonathan Hersh & Ryan Engstrom & Michael Mann, 2021. "Open data for algorithms: mapping poverty in Belize using open satellite derived features and machine learning," Information Technology for Development, Taylor & Francis Journals, vol. 27(2), pages 263-292, April.
- 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, April.
- 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.
- Athey, Susan & Imbens, Guido W., 2019.
"Machine Learning Methods Economists Should Know About,"
Research Papers
3776, Stanford University, Graduate School of Business.
- Susan Athey & Guido Imbens, 2019. "Machine Learning Methods Economists Should Know About," Papers 1903.10075, arXiv.org.
- 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.
- Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
- Simon Lange & Utz Johann Pape & Peter Pütz, 2022.
"Small Area Estimation of Poverty Under Structural Change,"
Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(S2), pages 264-281, December.
- Lange,Simon & Pape,Utz Johann & Putz,Peter, 2018. "Small area estimation of poverty under structural change," Policy Research Working Paper Series 8472, The World Bank.
- Torabi, Mahmoud & Rao, J.N.K., 2014. "On small area estimation under a sub-area level model," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 36-55.
- Paul Corral & Alexandru Cojocaru & Sandra Segovia & Isabel Molina, 2022. "Guidelines to Small Area Estimation for Poverty Mapping," World Bank Publications - Reports 37728, The World Bank Group.
- 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.
- Guanghua Chi & Han Fang & Sourav Chatterjee & Joshua E. Blumenstock, 2021. "Micro-Estimates of Wealth for all Low- and Middle-Income Countries," Papers 2104.07761, arXiv.org.
- Paul Corral & Kristen Himelein & Kevin McGee & Isabel Molina, 2021. "A Map of the Poor or a Poor Map?," Mathematics, MDPI, vol. 9(21), pages 1-40, November.
- 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.
- 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.
- Grosh, M.E. & Munoz, J., 1996. "A Manual for Planning and Implementing the Living Standards Measurement Study Survey," Papers 126, World Bank - Living Standards Measurement.
- Susan Athey & Guido W. Imbens, 2019. "Machine Learning Methods That Economists Should Know About," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 685-725, August.
- Molina, Isabel, 2019. "Desagregación de datos en encuestas de hogares: metodologías de estimación en áreas pequeñas," Estudios Estadísticos 44214, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
- Emily Aiken & Suzanne Bellue & Dean Karlan & Chris Udry & Joshua E. Blumenstock, 2022. "Machine learning and phone data can improve targeting of humanitarian aid," Nature, Nature, vol. 603(7903), pages 864-870, March.
- Seitz,William Hutchins, 2019. "Where They Live : District-Level Measures of Poverty, Average Consumption, and the Middle Class in Central Asia," Policy Research Working Paper Series 8940, The World Bank.
- Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
- Ola Hall & Francis Dompae & Ibrahim Wahab & Fred Mawunyo Dzanku, 2023. "A review of machine learning and satellite imagery for poverty prediction: Implications for development research and applications," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(7), pages 1753-1768, October.
- 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.
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More about this item
Keywords
Small-area estimation; Poverty mapping; Machine learning; Satellite imagery;All these keywords.
JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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