Inflation Persistence and Involuntary Unemployment in Pakistan: A Keynesian Econometric Study

Inflation Persistence and Involuntary Unemployment in Pakistan: A Keynesian Econometric Study | 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 Inflation Persistence and Involuntary Unemployment in Pakistan: A Keynesian Econometric Study Houssam BOUGHABI This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7466612/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 develops a stochastic Keynesian model linking inflation, unemployment, and GDP. Inflation follows a fractional Brownian motion, capturing persistent shocks, while a temporal convolutional network forecasts conditional paths, allowing machine learning to account for nonlinear interactions and long-memory effects. Unemployment responds conditionally to inflation thresholds, permitting involuntary joblessness, while GDP depends on both variables, reflecting aggregate demand and labor market frictions. The model is applied to Pakistan, simulating macroeconomic dynamics under alternative policy scenarios. We demonstrate that sustained growth is possible even under persistent inflation, reinforcing the empirical relevance of Keynesian theory in contemporary macroeconomic analysis and highlighting the value of machine learning for policy evaluation. Macroeconomics Stagflation Fractional Brownian Motion Temporal Convolutional Networks Keynesian Policy Pakistan Full Text Additional Declarations The authors declare no competing interests. Supplementary Files ModelPythonCode.docx The model Python Code 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-7466612","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":506079182,"identity":"3033d3ad-a97d-4650-bd41-ac269bdf8c43","order_by":0,"name":"Houssam BOUGHABI","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYBACAwYeEHWAwYCZ+cABUrWwJZCqhYHHgDiHmTPwHnzM8+uOvDk7z8fDBX9s5BnYDz9gulGDW4tlA1+yMW/fM8OdzbwbDs9sSzNs4EkzYM45hsdhB3jMpHl7DjNuOAzUwttwmLGBIYeBOYeNsBb7DYd5Hhzm+fPfvoH/DVDLPwJaeH4cTgRqYTjMw3YgsUECaEtuGx4th/mSDec2HE7e2cxmcJi3LTm5TeKZweHcPjxajvcefPDmz2Hb7fyHH3/m+WNn28+f/PBxzjfcWhiYgZgR2Rkgjx/AowEK/hBWMgpGwSgYBSMYAABudFObf+hDdwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0005-3492-1910","institution":"National Institute of Statistics and Applied Economics","correspondingAuthor":true,"prefix":"","firstName":"Houssam","middleName":"","lastName":"BOUGHABI","suffix":""}],"badges":[],"createdAt":"2025-08-27 00:35:32","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-7466612/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7466612/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90144131,"identity":"724c3dd0-475e-4b24-9985-e9a168065f4f","added_by":"auto","created_at":"2025-08-29 05:08:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":496362,"visible":true,"origin":"","legend":"","description":"","filename":"Article6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7466612/v1_covered_6b772b4e-f677-4261-90c1-e9234ef15dfa.pdf"},{"id":90143947,"identity":"ef42c4a4-325f-4126-9072-f6842c5a8c90","added_by":"auto","created_at":"2025-08-29 05:00:05","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":32277,"visible":true,"origin":"","legend":"\u003cp\u003eThe model Python Code\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"ModelPythonCode.docx","url":"https://assets-eu.researchsquare.com/files/rs-7466612/v1/d096ca6c34782b345a01076b.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eInflation Persistence and Involuntary Unemployment in Pakistan: A Keynesian Econometric Study\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"National Institute of Statistics and Applied Economics","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":"Stagflation, Fractional Brownian Motion, Temporal Convolutional Networks, Keynesian Policy, Pakistan","lastPublishedDoi":"10.21203/rs.3.rs-7466612/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7466612/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper develops a stochastic Keynesian model linking inflation, unemployment, and GDP. 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