Employment Diversification and Urban Mobility Disparities: A Multi-scale Analysis of U.S. Core-Based Statistical Areas

Employment Diversification and Urban Mobility Disparities: A Multi-scale Analysis of U.S. Core-Based Statistical Areas | 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 Employment Diversification and Urban Mobility Disparities: A Multi-scale Analysis of U.S. Core-Based Statistical Areas Zeyu Wu, Marta Gonzalez This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8769603/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract The Economic Complexity Index (ECI), a metric traditionally utilized in international trade to correlate high complexity with lower income inequality, is evaluated here at the subnational level to determine if this relationship persists across diverse urban scales. By adapting the ECI to employment distributions across 121 Core-Based Statistical Areas (CBSAs) in five U.S. states—California, New York, New Mexico, Louisiana, and Mississippi—this study integrates Replica mobility data with American Community Survey socioeconomic indicators. The analysis reveals a significant reversal of international trends: CBSAs with the highest economic complexity demonstrate the greatest income inequality (Gini = 0.51, r = 0.42, p < 0.001), despite maintaining superior mobility efficiency through lower VMT per capita and reduced radii of gyration. Utilizing Principal Component Analysis and bootstrap-validated K-means clustering, we categorize regions into four distinct typologies—Prosperous Knowledge Hubs, High-Density Mixed Economies, Rural Resource-Dependent Regions, and Small Industrial Towns—each exhibiting unique trade-offs between complexity, mobility, and equity. This "complexity-inequality paradox" suggests a localized Simpson’s Paradox where skill-biased agglomeration and occupational polarization at the regional scale override the institutional mechanisms typically found at the national level. These findings indicate that employment-based ECI, coupled with high-resolution mobility analytics, provides a scalable diagnostic framework that challenges uniform development strategies in favor of data-driven regional policy. Economic Complexity Index Urban Mobility Income Inequality Simp son’s Paradox Core-Based Statistical Areas Computational Social Science Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 28 Apr, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviewers agreed at journal 11 Mar, 2026 Reviewers invited by journal 11 Mar, 2026 Editor assigned by journal 04 Feb, 2026 Submission checks completed at journal 04 Feb, 2026 First submitted to journal 02 Feb, 2026 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8769603","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588032967,"identity":"9dacef66-6d7e-4734-b3ce-892ea384f59f","order_by":0,"name":"Zeyu Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYBADOQjFRoIWY9K1JDYQrUW+vcdMgrHtcPp2iRwDhg9lhwlrYew5A9aSu3NGjgHjjHNEaGGWyAFq2XY4d8ONHANm3jYitLDJvwFrSTcAaflLjBYeCR6wlgSwFkZitEjwpBVbJP5LN9xw5lnBwZ5z6YS1yLcf3njjwxlreYPjyRsf/CizJqyFgYHDgCEBRAskMBwgRj0QsD+A0PzEahgFo2AUjIIRBwBA9TfIwdaD/gAAAABJRU5ErkJggg==","orcid":"","institution":"New York University","correspondingAuthor":true,"prefix":"","firstName":"Zeyu","middleName":"","lastName":"Wu","suffix":""},{"id":588032968,"identity":"5192e0bb-642b-4396-a8c2-ccaeea25baf7","order_by":1,"name":"Marta Gonzalez","email":"","orcid":"","institution":"University of California, Berkeley","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Gonzalez","suffix":""}],"badges":[],"createdAt":"2026-02-03 00:53:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8769603/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8769603/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102298065,"identity":"8d021ea0-b555-41a7-9acb-832b1ec9bc38","added_by":"auto","created_at":"2026-02-10 10:30:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1306357,"visible":true,"origin":"","legend":"","description":"","filename":"EmploymentDiversificationandUrbanMobilityDisparitiesAMultiScaleAnalysisofUSCoreBasedStatisticalAreas.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8769603/v1_covered_a8151f0c-f239-4815-87c6-8e7c07415fe2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Employment Diversification and Urban Mobility Disparities: A Multi-scale Analysis of U.S. Core-Based Statistical Areas","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"epj-data-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"epds","sideBox":"Learn more about [EPJ Data Science](https://epjdatascience.springeropen.com/)","snPcode":"13688","submissionUrl":"https://submission.springernature.com/new-submission/13688/3","title":"EPJ Data Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Economic Complexity Index, Urban Mobility, Income Inequality, Simp son’s Paradox, Core-Based Statistical Areas, Computational Social Science","lastPublishedDoi":"10.21203/rs.3.rs-8769603/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8769603/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The Economic Complexity Index (ECI), a metric traditionally utilized in international trade to correlate high complexity with lower income inequality, is evaluated here at the subnational level to determine if this relationship persists across diverse urban scales. 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