Simulating Collusion: Challenging Conventional Estimation Methods

Simulating Collusion: Challenging Conventional Estimation Methods | 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 Simulating Collusion: Challenging Conventional Estimation Methods Nicole Bellert, Andrea Günster This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4605483/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 The empirical literature in industrial economics relies on hazard rate models to estimate the probability of death and survival as well as to explain the duration of collusion. Estimations are based on detected and convicted offenses. Detected cartels are, however, a non-random sample of their population of collusive activity. We question whether hazard rate and linear estimation methods derive consistent unbiased estimators explaining collusion. We simulate collusive behavior of industries with different number of firms based on three classical models of collusion, additionally varying four variables of antitrust enforcement. It is the first easily amenable and amendable simulation tool for collusion. The simulation provides a ground-truth data set of undetected and detected cartels; a population and its sample. Applying hazard rate and linear models on the sample fails to deliver consistent unbiased estimates for the population. Controlling for sample and feature selection on the population of all potential offenders does not improve prediction. The use of average treatment effects and average duration bias shows to quantify the magnitude of any bias well; a solution for future research relying on detected cartel cases. JEL Classification: C13 , C63 , D43 , 43 , L41 , L44 Estimation Methods Simulation Horizontal Anti-competitive Practices Public Antitrust Policy 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. 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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-4605483","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321649373,"identity":"e5568509-b757-46e9-91b1-a5cd94028ff7","order_by":0,"name":"Nicole Bellert","email":"","orcid":"","institution":"Zurich University of Applied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Nicole","middleName":"","lastName":"Bellert","suffix":""},{"id":321649375,"identity":"752192c6-b0db-457c-8308-559e7f2373e1","order_by":1,"name":"Andrea Günster","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnElEQVRIiWNgGAWjYLCCDwwHQBQb8ToYZ5CshZmHJC3yEcmHP9v8uSNvcID52QOitBjeSEuTzuF5ZrjhAJu5AXFaZuSYMedIHGbcdoCHTYJILfmfP1sYHLYnXou8RA6DNEPC4UTitRjwPDOT7DlwOHn/YTYzIm1pT3784cefw7Yz25ufEWnLARiLmSj1IFsaiFU5CkbBKBgFIxcAAB9YLt/9bqlCAAAAAElFTkSuQmCC","orcid":"","institution":"Zurich University of Applied Sciences","correspondingAuthor":true,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Günster","suffix":""}],"badges":[],"createdAt":"2024-06-19 11:15:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4605483/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4605483/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80413616,"identity":"6d4ca0e3-d8ff-4397-b9b8-02ddb033ae55","added_by":"auto","created_at":"2025-04-11 16:23:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":834834,"visible":true,"origin":"","legend":"","description":"","filename":"SimulatingCollusionandTestingEstimatorsSJES.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4605483/v1_covered_757775ec-0634-4ff8-8add-7a00af8f6ef7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Simulating Collusion: Challenging Conventional Estimation Methods","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":"Estimation Methods, Simulation, Horizontal Anti-competitive Practices, Public Antitrust Policy","lastPublishedDoi":"10.21203/rs.3.rs-4605483/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4605483/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe empirical literature in industrial economics relies on hazard rate models to estimate the probability of death and survival as well as to explain the duration of collusion. 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