Adaptive food price forecasts enhance public information during rapid economic changes

Adaptive food price forecasts enhance public information during rapid economic changes | 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 Article Adaptive food price forecasts enhance public information during rapid economic changes Matthew MacLachlan, Michael Adjemian, Xiaoli Etienne, Megan Sweitzer, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4345029/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The advent of COVID-19 ended an era of stable US retail food prices that followed the world food price crisis of 2010-2012. Pandemic-related disruptions, avian influenza outbreaks, and the Russia-Ukraine war drove 2022 food-at-home inflation to its highest rate since 1974 (11.4%). In 2023, US Department of Agriculture (USDA) economists responded to these changes by updating food price forecasts with statistical learning protocols to select time-series models and prediction intervals to convey their uncertainty. We characterise the public good provided by these "adaptive" inflation forecasts and enhance them by continuously selecting exogenous variables, improving their precision and explanatory power. The all-items-less-food-and-energy ("core") index helps predict food prices until 2017; then, the money supply, wholesale-food prices, and food service wages help generate optimal forecasts. The strong relationships between food prices and other prices and the money supply indicate the sensitivity of food markets to macroeconomic forces and government policy choices. Scientific community and society/Social sciences/Economics Scientific community and society/Social sciences/Government Scientific community and society/Business and industry/Industry Scientific community and society/Agriculture Scientific community and society/Social sciences/Decision making Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Under Review 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-4345029","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":313790828,"identity":"a47787b5-7629-4036-ab5f-43798c5d693b","order_by":0,"name":"Matthew MacLachlan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYFCCA+y/f1TYQNgPCkAChLUwSDOcSYOwEwyI0sLAIM3YcpgELbqNpxOMCxvOy/NLnz34AKhFju9GAn4tZgfObkieueO24cy+vGQDoBZjSWK0HOA9czvB4AyPmQRQS+IGIrRsbOBtOwfSYv4DqKWeGC2bmXnbDoBtAXk/wYAILdsYZ5xJNpzZw2MMdJiE4cwzDwhouXF2G8OHCjt5fh4eww8fKmzk+Y4TsIVB4gAql4ByEOBvIELRKBgFo2AUjGwAAHMPS7GETcTkAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-1044-9827","institution":"Cornell University","correspondingAuthor":true,"prefix":"","firstName":"Matthew","middleName":"","lastName":"MacLachlan","suffix":""},{"id":313790829,"identity":"38b47246-69c4-46bb-95c9-7898eddd0e59","order_by":1,"name":"Michael Adjemian","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Adjemian","suffix":""},{"id":313790830,"identity":"ced66139-d2fa-41f7-bd1e-2cdc123c76e2","order_by":2,"name":"Xiaoli Etienne","email":"","orcid":"","institution":"University of Idaho","correspondingAuthor":false,"prefix":"","firstName":"Xiaoli","middleName":"","lastName":"Etienne","suffix":""},{"id":313790831,"identity":"09e2a3bf-4849-4a2e-b513-485e06dcc3d8","order_by":3,"name":"Megan Sweitzer","email":"","orcid":"","institution":"USDA, Economic Research Service","correspondingAuthor":false,"prefix":"","firstName":"Megan","middleName":"","lastName":"Sweitzer","suffix":""},{"id":313790832,"identity":"40dceb12-4c9b-4f20-9814-e0d83bf6d942","order_by":4,"name":"Richard Volpe","email":"","orcid":"","institution":"California Polytechnic State University","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Volpe","suffix":""},{"id":313790833,"identity":"ee2c1481-9faa-4531-af3a-f2fdb118cdb1","order_by":5,"name":"Wendy Zeng","email":"","orcid":"","institution":"USDA, Economic Research Service","correspondingAuthor":false,"prefix":"","firstName":"Wendy","middleName":"","lastName":"Zeng","suffix":""}],"badges":[],"createdAt":"2024-04-29 21:05:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4345029/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4345029/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58253546,"identity":"6310d7d4-7e58-4f04-91e0-241078ae6796","added_by":"auto","created_at":"2024-06-13 04:19:19","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2003260,"visible":true,"origin":"","legend":"","description":"","filename":"Foodpricemanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345029/v1_covered_16077791-709a-4cb5-9967-01ad3cb61fe2.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Adaptive food price forecasts enhance public information during rapid economic changes","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4345029/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4345029/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The advent of COVID-19 ended an era of stable US retail food prices that followed the world food price crisis of 2010-2012. Pandemic-related disruptions, avian influenza outbreaks, and the Russia-Ukraine war drove 2022 food-at-home inflation to its highest rate since 1974 (11.4%). In 2023, US Department of Agriculture (USDA) economists responded to these changes by updating food price forecasts with statistical learning protocols to select time-series models and prediction intervals to convey their uncertainty. We characterise the public good provided by these \"adaptive\" inflation forecasts and enhance them by continuously selecting exogenous variables, improving their precision and explanatory power. The all-items-less-food-and-energy (\"core\") index helps predict food prices until 2017; then, the money supply, wholesale-food prices, and food service wages help generate optimal forecasts. 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