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dc.contributor.authorSgroi, Danielen_GB
dc.date.accessioned2004-06-16T16:05:03Z
dc.date.available2004-06-16T16:05:03Z
dc.date.created2002-03en_GB
dc.date.issued2004-06-16T16:05:03Z
dc.identifier.urihttp://www.dspace.cam.ac.uk/handle/1810/303
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/303
dc.description.abstractExperience gained in a workplace characterised by decision-making and learning-by-doing is modelled via a process of signal accumulation under several different frameworks. We initially look at the probability of success based on uninterrupted signal accumulation, then consider the impact of rapid labour turnover under two alternative regimes. The first allows new workers to gain some of their predecessor�s experience through Bayesian inference on reported earlier actions. The means of information transfer between workers is therefore similar to observational learning in herding or informational cascade models. The second regime considers all experience to be lost when a worker is replaced. We see that although with valuable experience the first regime appears a much better outcome for firms, transferring some knowledge to future workers carries with it the risk of excess inertia in decision-making.en_GB
dc.format.extent222760 bytes
dc.format.mimetypeapplication/pdfen_GB
dc.format.mimetypeapplication/pdf
dc.language.isoen_GB
dc.publisherFaculty of Economics
dc.relation.ispartofseriesCambridge Working Papers in Economics
dc.rightsAll Rights Reserveden
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/en
dc.subject.classificationClassification-JEL: D82, D83, J63en_GB
dc.subject.otherherding, private information, experience, labour turnover, excess inertiaen_GB
dc.titleModelling Experience as Signal Accumulationen_GB
dc.typeWorking Paperen
dc.identifier.doi10.17863/CAM.4994


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