Publication:
Predicting Income Distributions from Almost Nothing

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dc.contributor.authorMahler, Daniel Gerszon
dc.contributor.authorSchoch, Marta
dc.contributor.authorLakner, Christoph
dc.contributor.authorNguyen, Minh
dc.contributor.authorMontes, Jose
dc.date.accessioned2025-01-13T22:47:14Z
dc.date.available2025-01-13T22:47:14Z
dc.date.issued2025-01-13
dc.description.abstractThis paper develops a method to predict comparable income and consumption distributions for all countries in the world from a simple regression with a handful of country-level variables. To fit the model, the analysis uses more than 2,000 distributions from household surveys covering 168 countries from the World Bank’s Poverty and Inequality Platform. More than 1,000 economic, demographic, and remote sensing predictors from multiple databases are used to test the models. A model is selected that balances out-of-sample accuracy, simplicity, and the share of countries for which the method can be applied. The paper finds that a simple model relying on gross domestic product per capita, under-5 mortality rate, life expectancy, and rural population share gives almost the same accuracy as a complex machine learning model using 1,000 indicators jointly. The method allows for easy distributional analysis in countries with extreme data deprivation where survey data are unavailable or severely outdated, several of which are likely among the poorest countries in the world.en
dc.identifierhttp://documents.worldbank.org/curated/en/099601001132518556/IDU1882a78c419c7914d98199f71043cd8419e26
dc.identifier.doi10.1596/1813-9450-11034
dc.identifier.urihttps://hdl.handle.net/10986/42676
dc.languageEnglish
dc.language.isoen_US
dc.publisherWashington, DC: World Bank
dc.relation.ispartofseriesPolicy Research Working Paper; 11034
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/igo/
dc.subjectINCOME
dc.subjectCONSUMPTION
dc.subjectDATA DEPRIVATION
dc.subjectMACHINE LEARNING
dc.subjectPOVERTY
dc.subjectMEASUREMENT
dc.titlePredicting Income Distributions from Almost Nothingen
dc.typeWorking Paper
dspace.entity.typePublication
okr.date.disclosure2025-01-13
okr.date.doiregistration2025-04-14T11:57:35.489053Z
okr.date.lastmodified2025-01-13T00:00:00Zen
okr.doctypePolicy Research Working Paper
okr.doctypePublications & Research
okr.docurlhttp://documents.worldbank.org/curated/en/099601001132518556/IDU1882a78c419c7914d98199f71043cd8419e26
okr.guid099601001132518556
okr.identifier.docmidIDU-882a78c4-9c79-4d98-99f7-043cd8419e26
okr.identifier.doi10.1596/1813-9450-11034
okr.identifier.externaldocumentum34445442
okr.identifier.internaldocumentum34445442
okr.identifier.reportWPS11034
okr.import.id6327
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/099601001132518556/pdf/IDU1882a78c419c7914d98199f71043cd8419e26.pdfen
okr.region.geographicalWorld
okr.topicMacroeconomics and Economic Growth::Econometrics
okr.topicMacroeconomics and Economic Growth::Economic Modeling and Statistics
okr.topicMacroeconomics and Economic Growth::Income
okr.topicPoverty Reduction::Poverty Assessment
okr.topicPoverty Reduction::Poverty Monitoring & Analysis
okr.topicMacroeconomics and Economic Growth::Economic Development
okr.unitDevelopment Indicators and Data (DECID)
okr.unitEFI-SAR-POV-Poverty and Equity (ESAPV)
relation.isAuthorOfPublication3360909a-fdcc-580a-9567-25d105453578
relation.isAuthorOfPublicationfe09a17f-1d05-5a36-808c-daa18418e7bb
relation.isAuthorOfPublication.latestForDiscovery3360909a-fdcc-580a-9567-25d105453578
relation.isSeriesOfPublication26e071dc-b0bf-409c-b982-df2970295c87
relation.isSeriesOfPublication.latestForDiscovery26e071dc-b0bf-409c-b982-df2970295c87
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