ESG Drivers of Financial Development: A Multimethod Analysis of Domestic Credit to the Private Sector

preprint OA: closed
Full text JSON View at publisher

Abstract

Abstract This paper investigates the influence of environmental, social, and governance (ESG) factors on financial development, using Domestic Credit to the Private Sector by Banks (DCB) as the core indicator of credit market development. To effectively market the research within the broader literature on finance and ESG issues, the authors employ an approach combining econometric analysis, K-Nearest Neighbors (KNN), cluster analysis, and network analysis. By analyzing the impact through the estimation of the model parameters through the impact of instrumental variable estimation on the model parameters (using Two-Stage Least Squares (IV), Random Effects (IV), and First-Differenced (IV) methods), the study confirms that access to clean fuels and natural resource depletion impact the model margins significantly. However, across all the models used in the analysis, the impact of access to clean energy is positive. By analyzing the significance of the issue using the KNN model throughout the research process on the impact of ESG on credit market dynamics across countries, the research demonstrates that the issue is significant. By performing hierarchical cluster analysis on the significance of the research by considering the significance of the issue in its contribution to the impact on credit market dynamics in countries, in terms of climate stress issues being core in influencing the dynamics of credit in countries, through network analysis mapping performed by carrying out research on the topic. JEL Codes: G21, Q56, O16, C38, E44.
Full text 11,600 characters · extracted from preprint-html · click to expand
ESG Drivers of Financial Development: A Multimethod Analysis of Domestic Credit to the Private Sector | 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 ESG Drivers of Financial Development: A Multimethod Analysis of Domestic Credit to the Private Sector 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-8225300/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 investigates the influence of environmental, social, and governance (ESG) factors on financial development, using Domestic Credit to the Private Sector by Banks (DCB) as the core indicator of credit market development. To effectively market the research within the broader literature on finance and ESG issues, the authors employ an approach combining econometric analysis, K-Nearest Neighbors (KNN), cluster analysis, and network analysis. By analyzing the impact through the estimation of the model parameters through the impact of instrumental variable estimation on the model parameters (using Two-Stage Least Squares (IV), Random Effects (IV), and First-Differenced (IV) methods), the study confirms that access to clean fuels and natural resource depletion impact the model margins significantly. However, across all the models used in the analysis, the impact of access to clean energy is positive. By analyzing the significance of the issue using the KNN model throughout the research process on the impact of ESG on credit market dynamics across countries, the research demonstrates that the issue is significant. By performing hierarchical cluster analysis on the significance of the research by considering the significance of the issue in its contribution to the impact on credit market dynamics in countries, in terms of climate stress issues being core in influencing the dynamics of credit in countries, through network analysis mapping performed by carrying out research on the topic. JEL Codes: G21, Q56, O16, C38, E44. Macroeconomics Microeconomics ESG Financial Development Domestic Credit Sustainability Environmental Indicators 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. 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-8225300","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":551961986,"identity":"34bf6a91-187e-4e82-9997-2dd3c5efc1b8","order_by":0,"name":"Massimo Arnone","email":"","orcid":"","institution":"University of Catania","correspondingAuthor":false,"prefix":"","firstName":"Massimo","middleName":"","lastName":"Arnone","suffix":""},{"id":551961987,"identity":"1db242d4-6b06-4f50-be31-4ca1f8e77bdf","order_by":1,"name":"Alberto Costantiello","email":"","orcid":"","institution":"LUM University Giuseppe Degennaro","correspondingAuthor":false,"prefix":"","firstName":"Alberto","middleName":"","lastName":"Costantiello","suffix":""},{"id":551961988,"identity":"51b106a9-d24e-4f5c-840e-b5b6290e9d74","order_by":2,"name":"Carlo Drago","email":"","orcid":"","institution":"Unicusano University","correspondingAuthor":false,"prefix":"","firstName":"Carlo","middleName":"","lastName":"Drago","suffix":""},{"id":551961989,"identity":"d9828d02-e553-4575-a922-4676e2288537","order_by":3,"name":"Angelo Leogrande","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYBACA/nDBz//MDhcZ9/A/Eya8Z9NvX17D5s0D0NdfQMuLRJsydI8FY+TDRjYzKQZDNISN/CcYZOewyDBg9MWCR4zZp4znxM3MPCIAbUcTtwgkcMm/YeQFt42sBY2iBbJN2zSOfi0yPeYMf9su524H6ql3l46h4AWoC3WD4FaYLbUGBCjRdrw33m4ljQDyTOgECOgRbLtONz7yUARQlqAgczbdjzZgJnN2BgSyDnMxjwGuLXYzwdGJW8bMCrbmx8+/mFgk7i//fzDxzwVdTi1IAAzqu2ENYyCUTAKRsEowA0AAPZQRqtcYAUAAAAASUVORK5CYII=","orcid":"","institution":"LUM University Giuseppe Degennaro","correspondingAuthor":true,"prefix":"","firstName":"Angelo","middleName":"","lastName":"Leogrande","suffix":""}],"badges":[],"createdAt":"2025-11-27 23:37:14","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-8225300/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8225300/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97370136,"identity":"c87f7882-fe4d-4045-9dcd-35dd0df024d0","added_by":"auto","created_at":"2025-12-03 16:26:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1644502,"visible":true,"origin":"","legend":"","description":"","filename":"28112025ESGDriversofFinancialDevelopment.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8225300/v1_covered_b3bccce7-f078-44fa-8734-efcea066bc20.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eESG Drivers of Financial Development: A Multimethod Analysis of Domestic Credit to the Private Sector\u003c/strong\u003e\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":"ESG, Financial Development, Domestic Credit, Sustainability, Environmental Indicators","lastPublishedDoi":"10.21203/rs.3.rs-8225300/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8225300/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper investigates the influence of environmental, social, and governance (ESG) factors on financial development, using Domestic Credit to the Private Sector by Banks (DCB) as the core indicator of credit market development. To effectively market the research within the broader literature on finance and ESG issues, the authors employ an approach combining econometric analysis, K-Nearest Neighbors (KNN), cluster analysis, and network analysis. By analyzing the impact through the estimation of the model parameters through the impact of instrumental variable estimation on the model parameters (using Two-Stage Least Squares (IV), Random Effects (IV), and First-Differenced (IV) methods), the study confirms that access to clean fuels and natural resource depletion impact the model margins significantly. However, across all the models used in the analysis, the impact of access to clean energy is positive. By analyzing the significance of the issue using the KNN model throughout the research process on the impact of ESG on credit market dynamics across countries, the research demonstrates that the issue is significant. By performing hierarchical cluster analysis on the significance of the research by considering the significance of the issue in its contribution to the impact on credit market dynamics in countries, in terms of climate stress issues being core in influencing the dynamics of credit in countries, through network analysis mapping performed by carrying out research on the topic.\u003c/p\u003e\n\u003cp\u003eJEL Codes: G21, Q56, O16, C38, E44.\u003c/p\u003e","manuscriptTitle":"ESG Drivers of Financial Development: A Multimethod Analysis of Domestic Credit to the Private Sector","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-03 04:42:58","doi":"10.21203/rs.3.rs-8225300/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":"8bd783af-4ef0-42e0-823a-b1317eec47b0","owner":[],"postedDate":"December 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58737244,"name":"Macroeconomics"},{"id":58737245,"name":"Microeconomics"}],"tags":[],"updatedAt":"2025-12-03T04:42:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-03 04:42:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8225300","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8225300","identity":"rs-8225300","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","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. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00