A Bayesian Gravity Model for Italian domestic tourism

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dc.contributor.advisor Casarin, Roberto it_IT
dc.contributor.author Rodriguez Ameal, Carlos <1997> it_IT
dc.date.accessioned 2021-06-28 it_IT
dc.date.accessioned 2021-10-07T12:38:29Z
dc.date.available 2021-10-07T12:38:29Z
dc.date.issued 2021-07-12 it_IT
dc.identifier.uri http://hdl.handle.net/10579/20003
dc.description.abstract The gravity model has been used extensively to model trade flows among countries with proven succcess, and when applied to tourism flows it have provided even better results. In this paper I propose a Bayesian approach based on a MCMC algorithm to estimate the coefficients of the model. Then I apply this method to a Panel Data dataframe with the monthly number of tourists travelling from every Italian region to every Italian province between 2008 and 2018. Then I use it to predict the flows for 2019 and I compare the results. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Carlos Rodriguez Ameal, 2021 it_IT
dc.title A Bayesian Gravity Model for Italian domestic tourism it_IT
dc.title.alternative A gravity model for Italian domestic tourism flows it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Economia e finanza it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Economia it_IT
dc.description.academicyear 2020/2021-Sessione Estiva it_IT
dc.rights.accessrights openAccess it_IT
dc.thesis.matricno 883259 it_IT
dc.subject.miur SECS-P/06 ECONOMIA APPLICATA it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend it_IT
dc.provenance.upload Carlos Rodriguez Ameal (883259@stud.unive.it), 2021-06-28 it_IT
dc.provenance.plagiarycheck Roberto Casarin (r.casarin@unive.it), 2021-07-12 it_IT

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