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dc.titleEstimating and Forecasting Income Poverty and Inequality in Haiti Using Satellite Imagery and Mobile Phone Data
dc.contributor.authorPokhriyal, Neeti
dc.contributor.authorZambrano, Omar
dc.contributor.authorLinares, Jennifer
dc.contributor.authorHernández, Hugo
dc.contributor.orgunitCountry Office in Haiti
dc.coverageHaiti
dc.date.available2020-06-30T00:00:00
dc.date.issue2020-06-30T00:00:00
dc.description.abstractReporting poverty and other social indicators on a regular basis is a challenge in several developing countries due to the high costs associated with collecting household survey data. The present report adds to the poverty literature on Haiti by disaggregating 2012 household survey data on income poverty, income inequality, and standard of living deprivations at the commune level using a Machine Learning framework. The resulting estimates where then used to validate the values of these indicators for 2014, which were estimated using features extracted from aerial imagery and anonymized call detailed records. In addition, satellite imagery was used to forecast these indicators for 2019. Our general findings can be summarized as follows: a) One out of four Haitians living in poverty reside in 10 specific communes in the Artibonite, Ouest, Nord-Ouest and Nord departments, b) Communes in the Ouest department tend to consistently perform better than the rest of the communes; c) Nord-Ouest communes increasingly became poorer and more deprived in 2019 relative to 2014, when the worst-performing communes were mainly located in Nord-Est and Centre; and d) some communes in the Sud Department became more deprived in 2019 relative 2014. Our results provide evidence that there is a need of incorporating a territorial perspective to all growth strategies considered by Haitian policymakers. Further, in the context of the COVID-19 pandemic, our results can prove useful when prioritizing the areas where social interventions should be focused.
dc.format.extent44
dc.identifier.doihttp://dx.doi.org/10.18235/0002466
dc.identifier.urlhttps://publications.iadb.org/publications/english/document/Estimating-and-Forecasting-Income-Poverty-and-Inequality-in-Haiti-Using-Satellite-Imagery-and-Mobile-Phone-Data.pdf
dc.identifier.urlhttps://publications.iadb.org/publications/french/document/Estimation-et-prevision-de-la-pauvrete-et-des-inegalites-de-revenus-en-Haiti-en-utilisant-limagerie-satellite-et-les-donnees-du-telephone-mobile.pdf
dc.language.isoen
dc.mediumAdobe PDF
dc.publisherInter-American Development Bank
dc.subjectMobile Phone System
dc.subjectMachine Learning
dc.subjectSocial Innovation
dc.subjectBig Data
dc.subjectEquality
dc.subjectPoverty
dc.subjectIncome Equality
dc.subjectHousehold Survey
dc.subjectPoverty Rate
dc.subjectSocial Indicator
dc.subject.jelcodeO31 - Innovation and Invention: Processes and Incentives
dc.subject.jelcodeI38 - Government Policy • Provision and Effects of Welfare Programs
dc.subject.jelcodeO54 - Latin America • Caribbean
dc.subject.jelcodeO35 - Social Innovation
dc.subject.jelcodeI32 - Measurement and Analysis of Poverty
dc.subject.keywordsbig data;machine learning;Economic Development;Social innovation;Caribbean;Haiti;income inequality;satellite imagery;poverty maps;measurementand analysis of poverty;geographic information systems
dc.typeMonographs
idb.identifier.pubnumberIDB-MG-00824
idb.operationHA-T1256
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