Skill-biased Technical Change and Intergenerational Education Mobility

preprint OA: closed CC-BY-4.0
📄 Open PDF Full text JSON View at publisher
AI-generated summary by claude@2026-07, 2026-07-17

This study develops a model showing skill-biased technological change can improve intergenerational education mobility by incentivizing parental investment in children's education, and finds empirical support using US commuting zone data.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

AI-generated deep summary by claude@2026-07, 2026-07-17 · read from full text

This paper studies how skill-biased technical change (SBTC) affects intergenerational education mobility, using an overlapping generations model where households invest in children’s education to produce skilled outcomes. Technology is modeled to generate both pecuniary benefits (a higher skill premium) and non-pecuniary benefits (improved life skills), while also constraining low-income investment by increasing inequality; the author finds a critical range of technology levels where SBTC shocks raise investments for both high- and low-income households, improving absolute and relative education mobility, with larger relative gains for initially lower-investing low-income families. Empirically, the author links commuting-zone college attendance by children’s parents’ income rank (Chetty et al., 2014) to a constructed local SBTC proxy based on STEM-worker shares, instrumented with a Bartik-type IV, and reports 2SLS results showing improved college attendance in higher-technology commuting zones, particularly for lower-ranked households. The main caveat explicitly stated is that the work is a preprint that has not been peer reviewed by a journal. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

This paper analyzes the impact of skill-biased technological change (SBTC) on intergenerational education mobility. I set up an SBTC model with an overlapping generations framework, where heterogeneously-skilled households invest in their children's education to make them skilled. Technology incentivizes these investments by creating both pecuniary (higher skill-premium) and non-pecuniary (improved life skills) benefits; it constrains investments among low-income households by increasing inequality. I show there is a critical technology range within which SBTC shocks can increase investments by both high-income and low-income households, improving absolute education mobility. Moreover, the relative increase in transfers can be larger for the low-income group who initially have lower investment levels, which can help their children catch-up. I test the predictions of the model using data from Chetty et al. (2014) which show how college attendance rates of children in U.S. commuting zones (CZs) are linked to the rank of their families in the national income distribution. A technology measure is constructed for each CZ using its share of STEM workers, which I instrument using a Bartik-type IV to deal with endogeneity concerns. From 2SLS estimations, I find that college attendance rates of children from households in the same income rank improve if households are located in higher technology CZs, with the improvement being larger among lower-ranked households. Thus, SBTC is found to improve both absolute and relative intergenerational education mobility. JEL Codes: J24, J31, J62, I24, O33
Full text 10,617 characters · extracted from preprint-html · click to expand
Skill-biased Technical Change and Intergenerational Education Mobility | 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 Skill-biased Technical Change and Intergenerational Education Mobility Imran Aziz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2219954/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 This paper analyzes the impact of skill-biased technological change (SBTC) on intergenerational education mobility. I set up an SBTC model with an overlapping generations framework, where heterogeneously-skilled households invest in their children's education to make them skilled. Technology incentivizes these investments by creating both pecuniary (higher skill-premium) and non-pecuniary (improved life skills) benefits; it constrains investments among low-income households by increasing inequality. I show there is a critical technology range within which SBTC shocks can increase investments by both high-income and low-income households, improving absolute education mobility. Moreover, the relative increase in transfers can be larger for the low-income group who initially have lower investment levels, which can help their children catch-up. I test the predictions of the model using data from Chetty et al. (2014) which show how college attendance rates of children in U.S. commuting zones (CZs) are linked to the rank of their families in the national income distribution. A technology measure is constructed for each CZ using its share of STEM workers, which I instrument using a Bartik-type IV to deal with endogeneity concerns. From 2SLS estimations, I find that college attendance rates of children from households in the same income rank improve if households are located in higher technology CZs, with the improvement being larger among lower-ranked households. Thus, SBTC is found to improve both absolute and relative intergenerational education mobility. JEL Codes: J24, J31, J62, I24, O33 Education Attainment Intergenerational Mobility Skill-biased Technical Change Full Text Additional Declarations No competing interests reported. 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. 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-2219954","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":154984527,"identity":"f7109004-0ed8-425e-ac73-5a4c24677840","order_by":0,"name":"Imran Aziz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYBACNiA+wFABJHmAjAcFRGs5A9WSYECsVYxtEC0MRGnhYz/+8ODPeYflzHvOGAJtsUlsYD/8AL/DeBISDkhuO2wsc7bHAKglLbGBJw2/XWwMCQcOGG47nDiDny0BqOVwYoMEAwEt/A8bDiTOgWv5D9TC/gG/FolkhgMHG4BaeJsPALUcAGrhIWCLxDOGgw3H0o0leA6DtCQbt/Hk4I8d+f70xx9/1FjLSfAkNn/4UGEn289+fANeLVDQjGQvMeqBoI5IdaNgFIyCUTAiAQDe1UlDL1xXDwAAAABJRU5ErkJggg==","orcid":"","institution":"Yorkville University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Imran","middleName":"","lastName":"Aziz","suffix":""}],"badges":[],"createdAt":"2022-10-31 02:59:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2219954/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2219954/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":32773377,"identity":"bf08d3d4-186d-4763-8fde-e839b142ee50","added_by":"auto","created_at":"2023-02-10 20:14:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":420865,"visible":true,"origin":"","legend":"","description":"","filename":"SBTCandIMJEIOct2022.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2219954/v1_covered.pdf"},{"id":29608693,"identity":"adf04a08-30dd-4943-9767-2fa1638ae01c","added_by":"auto","created_at":"2022-11-28 19:29:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":410307,"visible":true,"origin":"","legend":"","description":"","filename":"SBTCandIMJEIOct2022.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2219954/v1/8fc2dfae563fa99ae09bb282.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Skill-biased Technical Change and Intergenerational Education Mobility","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"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":"Education Attainment, Intergenerational Mobility, Skill-biased Technical Change","lastPublishedDoi":"10.21203/rs.3.rs-2219954/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2219954/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper analyzes the impact of skill-biased technological change (SBTC) on intergenerational education mobility. I set up an SBTC model with an overlapping generations framework, where heterogeneously-skilled households invest in their children's education to make them skilled. Technology incentivizes these investments by creating both pecuniary (higher skill-premium) and non-pecuniary (improved life skills) benefits; it constrains investments among low-income households by increasing inequality. I show there is a critical technology range within which SBTC shocks can increase investments by both high-income and low-income households, improving absolute education mobility. Moreover, the relative increase in transfers can be larger for the low-income group who initially have lower investment levels, which can help their children catch-up. I test the predictions of the model using data from Chetty et al. (2014) which show how college attendance rates of children in U.S. commuting zones (CZs) are linked to the rank of their families in the national income distribution. A technology measure is constructed for each CZ using its share of STEM workers, which I instrument using a Bartik-type IV to deal with endogeneity concerns. From 2SLS estimations, I find that college attendance rates of children from households in the same income rank improve if households are located in higher technology CZs, with the improvement being larger among lower-ranked households. Thus, SBTC is found to improve both absolute and relative intergenerational education mobility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJEL Codes: \u003c/strong\u003eJ24, J31, J62, I24, O33\u003c/p\u003e","manuscriptTitle":"Skill-biased Technical Change and Intergenerational Education Mobility","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-28 19:28:57","doi":"10.21203/rs.3.rs-2219954/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"90f79ce6-16b0-46e5-94fe-cba2290727bd","owner":[],"postedDate":"November 28th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-03-10T07:14:10+00:00","versionOfRecord":[],"versionCreatedAt":"2022-11-28 19:28:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2219954","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2219954","identity":"rs-2219954","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-06-05T02:00:03.366016+00:00
License: CC-BY-4.0