TY - JOUR
T1 - An alternative approach to estimating demand
T2 - Neural network regression with conditional volatility for high frequency air passenger arrivals
AU - Medeiros, Marcelo C.
AU - McAleer, Michael
AU - Slottje, Daniel
AU - Ramos, Vicente
AU - Rey-Maquieira, Javier
N1 - Funding Information:
The first author is thankful to CNPq/Brazil for partial financial support. The second author wishes to acknowledge the financial support of the Australian Research Council, the Japanese Ministry of Education, and the Faculty of Economics at Yokohama National University. The suggestions of two anonymous referees are greatly acknowledged. The last two authors acknowledge the financial support from the Government of the Balearic Islands through the “Dicecció General d’Investigació, Desenvolupament Tecnológic i Innovació” PROGECIB-14B and AENA for providing the data used in the paper.
PY - 2008/12
Y1 - 2008/12
N2 - In this paper we provide an alternative approach to analyze the demand for international tourism in the Balearic Islands, Spain, by using a neural network model that incorporates time-varying conditional volatility. We consider daily air passenger arrivals to Palma de Mallorca, Ibiza and Mahon, which are located in the islands of Mallorca, Ibiza and Menorca, respectively, as a proxy for international tourism demand for the Balearic Islands. Spain is a world leader in terms of total international tourist arrivals and receipts, and Mallorca is one of the most popular destinations in Spain. For tourism management and marketing, it is essential to forecast high frequency international tourist demand accurately. As it is important to provide sensible international tourism demand forecast intervals, it is also necessary to model their variances accurately. Moreover, time-varying variances provide useful information regarding the risks associated with variations in international tourist arrivals.
AB - In this paper we provide an alternative approach to analyze the demand for international tourism in the Balearic Islands, Spain, by using a neural network model that incorporates time-varying conditional volatility. We consider daily air passenger arrivals to Palma de Mallorca, Ibiza and Mahon, which are located in the islands of Mallorca, Ibiza and Menorca, respectively, as a proxy for international tourism demand for the Balearic Islands. Spain is a world leader in terms of total international tourist arrivals and receipts, and Mallorca is one of the most popular destinations in Spain. For tourism management and marketing, it is essential to forecast high frequency international tourist demand accurately. As it is important to provide sensible international tourism demand forecast intervals, it is also necessary to model their variances accurately. Moreover, time-varying variances provide useful information regarding the risks associated with variations in international tourist arrivals.
KW - Neural networks
KW - Nonlinear models
KW - Passenger arrivals
KW - Semi-parametric models
KW - Smooth transition
KW - Time series
KW - Tourism demand
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U2 - 10.1016/j.jeconom.2008.09.018
DO - 10.1016/j.jeconom.2008.09.018
M3 - Article
AN - SCOPUS:55949136826
SN - 0304-4076
VL - 147
SP - 372
EP - 383
JO - Journal of Econometrics
JF - Journal of Econometrics
IS - 2
ER -