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dc.contributor.authorDi, Chen
dc.contributor.authorDimitrov, Stanko
dc.contributor.authorHe, Qi-Ming
dc.date.accessioned2020-09-09 19:39:00 (GMT)
dc.date.available2020-09-09 19:39:00 (GMT)
dc.date.issued2019-01
dc.identifier.urihttps://doi.org/10.1016/j.ijforecast.2018.07.005
dc.identifier.urihttp://hdl.handle.net/10012/16270
dc.descriptionThe final publication is available at Elsevier via https://doi.org/10.1016/j.ijforecast.2018.07.005. © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.description.abstractWe consider a multi-round prediction market in which two agents, Alice and Bob, are trading on an event on which each may take action to influence its outcome. The existing literature assumes that there is no net difference between the costs of different actions the agents may take outside the prediction market when external incentives exist. For example, the cost for Alice to work hard to complete the project is the same as it is for her to “loaf” and not work hard. In this work we consider first a two-round and later a four-round setting in which the agents’ costs of external actions differ between actions. We show that a prediction market is incentive-compatible when external action costs differ as long as they remain within a proper range, regardless of the initial market estimate, something that is not shown in the existing literature.en
dc.language.isoenen
dc.publisherElsevieren
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectprediction marketsen
dc.subjectexternal incentivesen
dc.subjectcostly actionsen
dc.subjectincentive compatibilityen
dc.subjectdecisionmakingen
dc.titleIncentive compatibility in prediction markets: Costly actions and external incentivesen
dc.typeArticleen
dcterms.bibliographicCitationDi, Chen, Stanko Dimitrov, and Qi-Ming He. “Incentive Compatibility in Prediction Markets: Costly Actions and External Incentives.” International Journal of Forecasting, Special Section: Supply Chain Forecasting, 35, no. 1 (January 1, 2019): 351–70. https://doi.org/10.1016/j.ijforecast.2018.07.005.en
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Management Sciencesen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen
uws.scholarLevelGraduateen


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