“A multivariate neural network approach to tourism demand forecasting”
Download full text from publisher
Other versions of this item:
- Oscar Claveria & Enric Monte & Salvador Torra, 2014. "“A multivariate neural network approach to tourism demand forecasting”," IREA Working Papers 201417, University of Barcelona, Research Institute of Applied Economics, revised May 2014.
References listed on IDEAS
- MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999.
"Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 14(5), pages 563-577, Sept.-Oct.
- Mackinnon, J.G. & Haug, A.A. & Michelis, L., 1996. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," G.R.E.Q.A.M. 96a09, Universite Aix-Marseille III.
- James G. MacKinnon & Alfred A. Haug & Leo Michelis, 1996. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Working Papers 1996_07, York University, Department of Economics.
- Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
- Gary Madden & Joachim Tan, 2008.
"Forecasting international bandwidth capacity using linear and ANN methods,"
Taylor & Francis Journals, vol. 40(14), pages 1775-1787.
- Madden, Gary G & Tan, Joachim, 2008. "Forecasting international bandwidth capacity using linear and ANN methods," MPRA Paper 13005, University Library of Munich, Germany.
- Daniel Santin & Francisco Delgado & Aurelia Valino, 2004. "The measurement of technical efficiency: a neural network approach," Applied Economics, Taylor & Francis Journals, vol. 36(6), pages 627-635.
- Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
- Zhang, G. Peter & Qi, Min, 2005. "Neural network forecasting for seasonal and trend time series," European Journal of Operational Research, Elsevier, vol. 160(2), pages 501-514, January.
- De Gooijer, Jan G. & Kumar, Kuldeep, 1992. "Some recent developments in non-linear time series modelling, testing, and forecasting," International Journal of Forecasting, Elsevier, vol. 8(2), pages 135-156, October.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 20(1), pages 134-144, January.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, "undated". "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992.
"Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?,"
Journal of Econometrics,
Elsevier, vol. 54(1-3), pages 159-178.
- Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
- Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
- M. Ali Choudhary & Adnan Haider, 2012.
"Neural network models for inflation forecasting: an appraisal,"
Taylor & Francis Journals, vol. 44(20), pages 2631-2635, July.
- Ali Choudhary & Adnan Haider, 2008. "Neural Network Models for Inflation Forecasting: An Appraisal," School of Economics Discussion Papers 0808, School of Economics, University of Surrey.
- M. Ali Choudhary, 2011. "Neural Network Models for Inflation Forecasting: An Appraisal," Post-Print hal-00704670, HAL.
- Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
- Jacint Balaguer & Manuel Cantavella-Jorda, 2002.
"Tourism as a long-run economic growth factor: the Spanish case,"
Taylor & Francis Journals, vol. 34(7), pages 877-884.
- Jacint Balaguer & Manuel Cantavella-Jordá, 2000. "Tourism As A Long-Run Economic Growth Factor: The Spanish Case," Working Papers. Serie EC 2000-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- Nikolaos Vlastakis & George Dotsis & Raphael Markellos, 2008. "Nonlinear modelling of European football scores using support vector machines," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 111-118.
- Yair Eilat & Liran Einav, 2004. "Determinants of international tourism: a three-dimensional panel data analysis," Applied Economics, Taylor & Francis Journals, vol. 36(12), pages 1315-1327.
- Koon Nam Lee, 2011. "Forecasting long-haul tourism demand for Hong Kong using error correction models," Applied Economics, Taylor & Francis Journals, vol. 43(5), pages 527-549.
- Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
- Claveria, Oscar & Torra, Salvador, 2014. "Forecasting tourism demand to Catalonia: Neural networks vs. time series models," Economic Modelling, Elsevier, vol. 36(C), pages 220-228.
More about this item
Keywordsforecasting; tourism demand; cointegration; multiple-output; artificial neural networks. JEL classification: L83; C53; C45; R11;
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2014-06-02 (All new papers)
- NEP-CMP-2014-06-02 (Computational Economics)
- NEP-FOR-2014-06-02 (Forecasting)
- NEP-ORE-2014-06-02 (Operations Research)
- NEP-TUR-2014-06-02 (Tourism Economics)
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aqr:wpaper:201410. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Bibiana Barnadas). General contact details of provider: http://edirc.repec.org/data/aqrubes.html .