nep-tur 2017-02-12 papers

on Tourism Economics

Issue of 2017‒02‒12
two papers chosen by
Laura Vici
Università di Bologna

“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting" By Oscar Claveria; Enric Monte; Salvador Torra
Analysis and prospects of development of the tourism industry in Russia By Dmitriy Demyanov

“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting"

By:	Oscar Claveria (AQR Research Group-IREA. University of Barcelona. Av.Diagonal 696; 08034 Barcelona, Spain.); Enric Monte (Department of Signal Theory and Communications, Polytechnic University of Catalunya (UPC).); Salvador Torra (Riskcenter-IREA, University of Barcelona, Av. Diagonal 690, 08034 Barcelona, Spain.)
Abstract:	This study presents a multiple-input multiple-output (MIMO) approach for multi-step-ahead time series prediction with a Gaussian process regression (GPR) model. We assess the forecasting performance of the GPR model with respect to several neural network architectures. The MIMO setting allows modelling the cross-correlations between all regions simultaneously. We find that the radial basis function (RBF) network outperforms the GPR model, especially for long-term forecast horizons. As the memory of the models increases, the forecasting performance of the GPR improves, suggesting the convenience of designing a model selection criteria in order to estimate the optimal number of lags used for concatenation.
Keywords:	Regional forecasting, tourism demand, multiple-input multiple-output (MIMO), Gaussian process regression, neural networks, machine learning. JEL classification:
Date:	2017–01
URL:	http://d.repec.org/n?u=RePEc:ira:wpaper:201701&r=tur

Analysis and prospects of development of the tourism industry in Russia

By:	Dmitriy Demyanov (Russian Presidential Academy of National Economy and Public Administration, Chelyabinsk branch)
Abstract:	The article analyses the development of tourism industry in Russia. The author states the background for economic and investment rise of the industry on the basis of comparative methods of statistic selection of data. The main factors preventing from encouraging investments are defined
Keywords:	quality of life, tourist cluster, Russian tourism product
JEL:	R0
Date:	2015–11
URL:	http://d.repec.org/n?u=RePEc:rnp:ppaper:ch1638&r=tur

This nep-tur issue is ©2017 by Laura Vici. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.

General information on the NEP project can be found at http://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.

NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.