Estimating Inequality of Opportunity in Ghana Across Cohorts: A Machine Learning Approach

Estimating Inequality of Opportunity in Ghana Across Cohorts: A Machine Learning Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Estimating Inequality of Opportunity in Ghana Across Cohorts: A Machine Learning Approach Vito De Sandi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7630180/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In the last decades, the inequality of opportunity has captured more and more of the attention of researchers and policymakers. While extensive theoretical and empirical work has been carried out in this field, only a small fraction has been conducted in developing countries, particularly in Africa, due to a lack of data. The paper presents new estimates of inequality of opportunity in Ghana across cohorts, showing the pattern of such measures over time and generations. The current approaches to estimating inequality of opportunity are often hindered by the ad-hoc model selection, which can lead researchers to either overestimate or underestimate the actual amount of inequality of opportunity. Hence, we implement a machine learning approach (Regression Tree and Forests) that is able to overcome the discretionary factors in the model and circumstances selection. We have shown that IOp follows an increasing pattern for the middle generation and then decreases for the last generation; hence, the generations born in more recent cohorts experience more equality in terms of opportunity than the older ones. The trend seems to follow the political events that affect the country: the more instability there is, the higher the Iop. We record the effect of the education policies (which opened up women’s enrollment) on the mother’s education as one of the main drivers of the inequality of opportunity for the last cohort. Geography and ethnicity matter considerably, and they seem to matter less and less than in the past. Inequality of Opportunity Regression Tress Forests Ghana Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7630180","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":515930932,"identity":"ef4a6f4f-910b-4fac-99d5-2ceead9bd750","order_by":0,"name":"Vito De Sandi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYDACZiDmAbMSGw58AFJs7AS1MMO1NB6cAdLCTIw1EC0JzId5YPbiAwbH+Q8+eFNRJ2/Ontxw2ObXNnk+ZgbGDx9z8Gg5zMxsOOfMYcOdPQ8bDuf23TZsY2Zglpy5DbcWyWZmNmnetgOMG24kArX03GYEamFj5iWo5V+dPViLZc9te4Ja+JlBWhqYE8FaGH7cTiRGi7HhnGOHkzecedhwsLfhdnIbM2MzXr+w8R98+OBNTZ3thuPpjz/8+HPbdn5788EPH/FoQQWMbWCygVj1IPCHFMWjYBSMglEwUgAAkdZTMU2Br9IAAAAASUVORK5CYII=","orcid":"","institution":"Luxembourg Institute of Socio Economic Research","correspondingAuthor":true,"prefix":"","firstName":"Vito","middleName":"","lastName":"De Sandi","suffix":""}],"badges":[],"createdAt":"2025-09-16 12:07:30","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7630180/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7630180/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91497526,"identity":"50fdccf6-56a7-4c9a-be6a-80e63e33d389","added_by":"auto","created_at":"2025-09-17 06:39:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1045341,"visible":true,"origin":"","legend":"","description":"","filename":"Chapter14.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7630180/v1_covered_d0e411e8-8beb-49f5-8a8c-6a8b1c60c211.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eEstimating Inequality of Opportunity in Ghana Across Cohorts: A Machine Learning Approach\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Luxembourg Institute of Socio-Economic Research","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Inequality of Opportunity, Regression Tress, Forests, Ghana","lastPublishedDoi":"10.21203/rs.3.rs-7630180/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7630180/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the last decades, the inequality of opportunity has captured more and more of the attention of researchers and policymakers. 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The trend seems to follow the political events that affect the country: the more instability there is, the higher the Iop. We record the effect of the education policies (which opened up women’s enrollment) on the mother’s education as one of the main drivers of the inequality of opportunity for the last cohort. 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