Policy Design and Efficiency of R&D Subsidy

Policy Design and Efficiency of R&D Subsidy | 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Download PDF Research Article Policy Design and Efficiency of R&D Subsidy Wenhan Liu, Shu Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4700305/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Optimizing the allocation of innovation resources and strengthening the importance of innovation are the main engines of modern growth. Research and development (R&D) subsidy policy is an essential means to guide enterprises to increase R&D investment, enhance the efficiency of fiscal subsidy funds, and leverage higher-level corporate R&D investment at the core of policy design. This study uses data on applications for and acceptance of R&D subsidy projects and provides the first comparative analysis of the policy’s effects and fund-use efficiency between the resource-leaning (increased subsidy rate) and inclusive (increased number of funded enterprises) models of R&D subsidies. This study constructs a theoretical model based on the actual process of R&D subsidies, which includes three stages: enterprises’ subsidy application choices, government review decisions, and enterprises’ R&D behavior. It estimates the model parameters based on enterprise-level data regarding R&D subsidy applications and granted subsidy amounts. The empirical results demonstrate that the rules of current R&D subsidies reflect government preferences and selection of subsidy recipients. In this context, one unit of R&D subsidy can engender an increase of 4.51 units in corporate R&D investment and an enhancement of 0.98 units in net social benefits. Simultaneously, resource-leaning subsidies tend to attract leading enterprises, whereas inclusive subsidies may induce adverse selection, with the former exhibiting a higher fiscal expenditure efficiency. The conclusions of this research offer empirical support for the scientific formulation and optimization of R&D subsidy systems under various policy objectives, underscoring the complexity of designing measures that balance effectiveness with efficiency. By shedding light on the differentiated impacts of resource learning and inclusive subsidy designs, this study contributes valuable insights into the nuanced relationship between policy design and intended outcomes in the context of innovation-driven development. JEL Classification: H29; L59; O31 R&D Subsidy Policy Design Process of R&D subsidy Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions 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-4700305","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":336495008,"identity":"f70e20a4-bd5a-46f0-a1fe-063bd097de76","order_by":0,"name":"Wenhan Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYBACfv7m4z8+GNjIyTMcPkCcFskZxxIkZ1SkGRs2HksgTovBgRwDaZ4zhxIbDp8xINJlBw4YGPC2HUhsbDvz8cYbBjs53QYCOhibGxISJNvuGLfznN1sOYch2djsAAEtzEBrDhi2PZNtnHF2mzQPw4HEbYS0sDEkNjYkth1mbLj/5hlxWngYkoEWnTms2HDgDBtxWiQkjrExNoACueGYseUcAyL8Yn++/xvzH0hUPrzxpsJOjqAWVCt5iI0aJC2k6hgFo2AUjIIRAQCEyUyTKhmhuAAAAABJRU5ErkJggg==","orcid":"","institution":"Chengdu University","correspondingAuthor":true,"prefix":"","firstName":"Wenhan","middleName":"","lastName":"Liu","suffix":""},{"id":336495009,"identity":"6ed3544a-d215-4911-ae8f-17776e417b2e","order_by":1,"name":"Shu Xu","email":"","orcid":"","institution":"Southwestern University of Finance and Economics","correspondingAuthor":false,"prefix":"","firstName":"Shu","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-07-07 13:03:29","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4700305/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-4700305/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62299156,"identity":"664e45d6-22bb-41b1-913f-fdcdc9a6fa70","added_by":"auto","created_at":"2024-08-12 16:18:37","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":544422,"visible":true,"origin":"","legend":"","description":"","filename":"PolicyDesignandEfficiencyofRDSubsidy.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4700305/v2_covered_219f6926-1fbf-45c8-9502-ea2a01bd535a.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"Policy Design and Efficiency of R\u0026amp;D Subsidy","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":true,"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":"R\u0026D Subsidy, Policy Design, Process of R\u0026D subsidy","lastPublishedDoi":"10.21203/rs.3.rs-4700305/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4700305/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOptimizing the allocation of innovation resources and strengthening the importance of innovation are the main engines of modern growth. Research and development (R\u0026amp;D) subsidy policy is an essential means to guide enterprises to increase R\u0026amp;D investment, enhance the efficiency of fiscal subsidy funds, and leverage higher-level corporate R\u0026amp;D investment at the core of policy design. This study uses data on applications for and acceptance of R\u0026amp;D subsidy projects and provides the first comparative analysis of the policy’s effects and fund-use efficiency between the resource-leaning (increased subsidy rate) and inclusive (increased number of funded enterprises) models of R\u0026amp;D subsidies. This study constructs a theoretical model based on the actual process of R\u0026amp;D subsidies, which includes three stages: enterprises’ subsidy application choices, government review decisions, and enterprises’ R\u0026amp;D behavior. It estimates the model parameters based on enterprise-level data regarding R\u0026amp;D subsidy applications and granted subsidy amounts. The empirical results demonstrate that the rules of current R\u0026amp;D subsidies reflect government preferences and selection of subsidy recipients. In this context, one unit of R\u0026amp;D subsidy can engender an increase of 4.51 units in corporate R\u0026amp;D investment and an enhancement of 0.98 units in net social benefits. Simultaneously, resource-leaning subsidies tend to attract leading enterprises, whereas inclusive subsidies may induce adverse selection, with the former exhibiting a higher fiscal expenditure efficiency. The conclusions of this research offer empirical support for the scientific formulation and optimization of R\u0026amp;D subsidy systems under various policy objectives, underscoring the complexity of designing measures that balance effectiveness with efficiency. 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