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.
A Bayesian Gravity Model for Italian domestic tourism
Rodriguez Ameal, Carlos
2021/2022
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.File in questo prodotto:
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Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.14247/8234