Innovation and Bank Capital Adequacy: An Empirical Assessment across European Economies

Innovation and Bank Capital Adequacy: An Empirical Assessment across European Economies | 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 Innovation and Bank Capital Adequacy: An Empirical Assessment across European Economies Massimo Arnone, Alberto Costantiello, Carlo Drago, Angelo Leogrande This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7497736/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 explores the connection between innovation dynamics and the Bank Capital to Asset Ratio (CAR) in the context of 39 European nations from 2018 to 2025. With a multidimensional panel data approach that incorporates a combination of static and dynamic panel models and machine learning algorithms—specifically Decision Tree Regression—the study conducts a data-oriented analysis of the impact of various types of innovation on the resilience of the banking sector. The study differentiates innovation inputs (e.g., trademark applications, innovator share), outputs (e.g., new-to-marketing and new-to-firm product sales), and productivity factors and factors permitting a finely grained comprehension of innovation inputs and financial consequences. Cluster analysis is applied to classify countries into innovation performance groups and is followed by regression and variable importance calculations. The study identifies that process innovations executed by small and medium enterprises (SMEs) are positively linked with CAR and that information is associated with greater financial stability, whereas innovation outputs and productivity indicators at times relate inversely and register corresponding financial stress in the face of innovation-driven transitions. Further, pre-stage innovation inputs may raise banks' uncertainty and register systematic risk escalation. The model of a Decision Tree also reveals the sales of innovative products and labor productivity to be the most robust determinants of CAR with varied directional impacts between them. These results document the innovation-finance nexus complexity and refute the supposition that innovation equally strengthens economic prudence. The study contributes new knowledge to the literature through the combination of the assessment of financial prudency with the type of innovation and provides clear policy directions for the synchronization of innovation strategies with macroprudency aims across the European region. JEL CODES: G21, O31, C38, O52, E44. Innovation Bank Capital Financial Stability Decision Tree Regression Europe 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. We do this by developing innovative software and high quality services for the global research community. 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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-7497736","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":507930354,"identity":"dcfed6a8-86f1-47b2-86e6-13e277b01934","order_by":0,"name":"Massimo Arnone","email":"","orcid":"","institution":"University of Catania","correspondingAuthor":false,"prefix":"","firstName":"Massimo","middleName":"","lastName":"Arnone","suffix":""},{"id":507930355,"identity":"df146b80-e752-43fd-8589-fbc8f27e4fc8","order_by":1,"name":"Alberto Costantiello","email":"","orcid":"","institution":"LUM University Giuseppe Degennaro","correspondingAuthor":false,"prefix":"","firstName":"Alberto","middleName":"","lastName":"Costantiello","suffix":""},{"id":507930356,"identity":"a92ade6a-455b-4db9-b08a-508e5a43ed33","order_by":2,"name":"Carlo Drago","email":"","orcid":"","institution":"Unicusano University","correspondingAuthor":false,"prefix":"","firstName":"Carlo","middleName":"","lastName":"Drago","suffix":""},{"id":507930357,"identity":"716eda22-067b-4827-b40d-a0f2bb8d5293","order_by":3,"name":"Angelo Leogrande","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYBACPijN2AAiH4AI9mYQWwKnFjYULQkJQILnIFgLTj1YtEgkgtm4tbA3H35dUXNHtp+B+ZlE4g+bfH7Jh21SNxgs6nBq4TmWZnnm2DPjmQ1sZhIJCWmWM2cntknn4HOYRI6ZYQPb4cQNB3jYgFoOGxjcJqRF/g1Qy7/DifthWuxvHiRkC4/xw8Y2oC0MMFskGAlo4UlLY2zsO2w84zCbsUVCWpqBxJnEZuscAwnJBhxa+NkPH/7Y8O2wbH9788MbH2xsDPjbDx+8nVNRx4/LFrDbwBQziqABHg1AtR/wSo+CUTAKRsEoAABg1U/Q4kxZZwAAAABJRU5ErkJggg==","orcid":"","institution":"Lum University Giuseppe Degennaro","correspondingAuthor":true,"prefix":"","firstName":"Angelo","middleName":"","lastName":"Leogrande","suffix":""}],"badges":[],"createdAt":"2025-08-31 00:48:23","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-7497736/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7497736/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90480464,"identity":"71b27d3b-882a-46f8-957c-75b44e03eb9f","added_by":"auto","created_at":"2025-09-03 07:59:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":624346,"visible":true,"origin":"","legend":"","description":"","filename":"InnovationandBankCapitalAdequacy.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7497736/v1_covered_1c06715b-8bb3-48d6-979c-9caf0b824189.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eInnovation and Bank Capital Adequacy: An Empirical Assessment across European Economies\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Innovation, Bank Capital, Financial Stability, Decision Tree Regression, Europe","lastPublishedDoi":"10.21203/rs.3.rs-7497736/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7497736/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper explores the connection between innovation dynamics and the Bank Capital to Asset Ratio (CAR) in the context of 39 European nations from 2018 to 2025. With a multidimensional panel data approach that incorporates a combination of static and dynamic panel models and machine learning algorithms—specifically Decision Tree Regression—the study conducts a data-oriented analysis of the impact of various types of innovation on the resilience of the banking sector. The study differentiates innovation inputs (e.g., trademark applications, innovator share), outputs (e.g., new-to-marketing and new-to-firm product sales), and productivity factors and factors permitting a finely grained comprehension of innovation inputs and financial consequences. Cluster analysis is applied to classify countries into innovation performance groups and is followed by regression and variable importance calculations. 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