Shock Waves: Mapping the Impact of Uncertainty on U.S. Urban Housing Markets

preprint OA: closed
Full text JSON View at publisher

Abstract

Abstract This research yields a new measure of uncertainty, and investigates how macroeconomic uncertainty shocks influence major Metropolitan Statistical Area (MSA)-level housing markets in the US. Utilizing an extended factor augmented vector autoregression (FAVAR) model, this study spotlights different impacts of aggregate uncertainty shocks on housing markets across MSAs while controlling for effects of MSA-specific uncertainty shocks. The results indicate that the 3-month risk-free interest rate, consumer sentiments, REIT total returns, and the oil market respond to uncertainty shocks considerably. There are marked differences in responses of metropolitan housing price returns to uncertainty shocks in terms of persistence and magnitude. MSAs with high ratios of house value over household income are likely to experience greater housing price appreciation as they are hit by uncertainty shocks, and uncertainty shocks reduce housing price returns to a larger degree in MSAs whose housing price dynamics are more volatile in the housing boom 2002-6. The empirical results are helpful in policy-making for stabilizing local housing markets owing to differences in monetary-policy effectiveness across cities, and shed light on geographic diversification mechanism.
Full text 9,637 characters · extracted from preprint-html · click to expand
Shock Waves: Mapping the Impact of Uncertainty on U.S. Urban Housing Markets | 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 Shock Waves: Mapping the Impact of Uncertainty on U.S. Urban Housing Markets MeiChi Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7548047/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 research yields a new measure of uncertainty, and investigates how macroeconomic uncertainty shocks influence major Metropolitan Statistical Area (MSA)-level housing markets in the US. Utilizing an extended factor augmented vector autoregression (FAVAR) model, this study spotlights different impacts of aggregate uncertainty shocks on housing markets across MSAs while controlling for effects of MSA-specific uncertainty shocks. The results indicate that the 3-month risk-free interest rate, consumer sentiments, REIT total returns, and the oil market respond to uncertainty shocks considerably. There are marked differences in responses of metropolitan housing price returns to uncertainty shocks in terms of persistence and magnitude. MSAs with high ratios of house value over household income are likely to experience greater housing price appreciation as they are hit by uncertainty shocks, and uncertainty shocks reduce housing price returns to a larger degree in MSAs whose housing price dynamics are more volatile in the housing boom 2002-6. The empirical results are helpful in policy-making for stabilizing local housing markets owing to differences in monetary-policy effectiveness across cities, and shed light on geographic diversification mechanism. uncertainty shock Metropolitan Statistical Area (MSA)-level housing market factor augmented vector autoregression (FAVAR) model Full Text 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-7548047","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":511526061,"identity":"e6126b9f-c3a0-4c31-92a5-a5a6334d7082","order_by":0,"name":"MeiChi Huang","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-7951-4842","institution":"National Taipei University","correspondingAuthor":true,"prefix":"","firstName":"MeiChi","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2025-09-06 03:43:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7548047/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7548047/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97671694,"identity":"938f219e-5af1-480f-bcb8-c91307f18cdf","added_by":"auto","created_at":"2025-12-08 09:32:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":997752,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptallwithcover.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7548047/v1_covered_ed8ad985-c0c5-4178-8ebb-4468831bbf68.pdf"}],"financialInterests":"","formattedTitle":"Shock Waves: Mapping the Impact of Uncertainty on U.S. Urban Housing Markets","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":"uncertainty shock, Metropolitan Statistical Area (MSA)-level housing market, factor augmented vector autoregression (FAVAR) model","lastPublishedDoi":"10.21203/rs.3.rs-7548047/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7548047/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis research yields a new measure of uncertainty, and investigates how macroeconomic uncertainty shocks influence major Metropolitan Statistical Area (MSA)-level housing markets in the US. Utilizing an extended factor augmented vector autoregression (FAVAR) model, this study spotlights different impacts of aggregate uncertainty shocks on housing markets across MSAs while controlling for effects of MSA-specific uncertainty shocks. The results indicate that the 3-month risk-free interest rate, consumer sentiments, REIT total returns, and the oil market respond to uncertainty shocks considerably. There are marked differences in responses of metropolitan housing price returns to uncertainty shocks in terms of persistence and magnitude. MSAs with high ratios of house value over household income are likely to experience greater housing price appreciation as they are hit by uncertainty shocks, and uncertainty shocks reduce housing price returns to a larger degree in MSAs whose housing price dynamics are more volatile in the housing boom 2002-6. The empirical results are helpful in policy-making for stabilizing local housing markets owing to differences in monetary-policy effectiveness across cities, and shed light on geographic diversification mechanism.\u003c/p\u003e","manuscriptTitle":"Shock Waves: Mapping the Impact of Uncertainty on U.S. Urban Housing Markets","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-12 17:39:23","doi":"10.21203/rs.3.rs-7548047/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":"bb56db37-f3f6-452b-ba91-f7f08c921814","owner":[],"postedDate":"September 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T00:30:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-12 17:39:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7548047","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7548047","identity":"rs-7548047","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