Climate Change and Agricultural Productivity in China: Evidence from Parametric and Robust Nonparametric Frontiers

Climate Change and Agricultural Productivity in China: Evidence from Parametric and Robust Nonparametric Frontiers | 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 Climate Change and Agricultural Productivity in China: Evidence from Parametric and Robust Nonparametric Frontiers Chang-Chih Chen, Chuan Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8759428/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 Climate change poses a major challenge to global food security, making it crucial to understand its effects on agricultural productivity. This paper examines how climate affects agricultural total factor productivity (TFP) in China using both parametric panel models and robust nonparametric order‑m frontiers. We find that higher temperatures in hot seasons are associated with lower agricultural TFP, mainly through reduced technical efficiency rather than slower technical change. This negative relationship remains robust after addressing the statistical issues of standard two-stage DEA procedures. The nonparametric conditional frontier analysis further shows that the climate–efficiency relationship is highly nonlinear and exhibits an inverted‑U shape at some temperature levels, suggesting possible benefits from long-term adaptation policies. Our results underscore the importance of targeted interventions aimed at improving technical efficiency to mitigate the adverse impacts of climate change on China’s agricultural productivity. JEL classification: C22, O47, Q54 Climate change Output-oriented effciency Order-m frontier 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-8759428","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595770294,"identity":"2f505c48-2e88-47cf-8fa5-976ac9ad3e06","order_by":0,"name":"Chang-Chih Chen","email":"","orcid":"","institution":"Providence University","correspondingAuthor":false,"prefix":"","firstName":"Chang-Chih","middleName":"","lastName":"Chen","suffix":""},{"id":595770295,"identity":"453f30dd-164c-4675-8062-111e9f2a353f","order_by":1,"name":"Chuan Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYJAC5j8GNqgiEgT18BSkMTCwoWoxIKDlw2EStPDPSH72QMLgvD3//B6zzwUMh+0NDjAfvM3D8CexAYcWiRtp5gYGBrcTZxzjMZ49g+Ews8EBtmRrHgYDnFoMpBPMJBIMbicwALUw8zAcZjM4wGMmDdSSi1tL+jeJAwbn7OWhWngMDvB/I6Alx0yyweAA4waoFgmgLWx4tUjcf1MmzWCQnLjxWFoxM49BuoHkYTZjyzkGxvW4tPD3HN8mzfDHzl7u8OHNzDwV1vZ8x5sf3nhTIWeMQweGO5uBiQHMIFIDENQRr3QUjIJRMApGDAAAGkJJR7JjT8QAAAAASUVORK5CYII=","orcid":"","institution":"Yuan Ze University","correspondingAuthor":true,"prefix":"","firstName":"Chuan","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-02-02 01:39:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8759428/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8759428/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103506617,"identity":"c8686071-f391-46f2-a3a1-240cd4e0bf33","added_by":"auto","created_at":"2026-02-26 13:38:08","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":938388,"visible":true,"origin":"","legend":"","description":"","filename":"paperJWCrevised2026improvedpolishedanonymous24.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8759428/v1_covered_da3cf194-5305-40a5-b232-6c64d0e61951.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Climate Change and Agricultural Productivity in China: Evidence from Parametric and Robust Nonparametric Frontiers","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":"Climate change, Output-oriented effciency, Order-m frontier","lastPublishedDoi":"10.21203/rs.3.rs-8759428/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8759428/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate change poses a major challenge to global food security, making it crucial to understand its effects on agricultural productivity. 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