Business cycle;
Forecast evaluation;
Structural time series model;
Tourism demand;
Seasonality;
INTERNATIONAL TOURISM;
FORECASTING TOURISM;
COINTEGRATION ANALYSIS;
MEDITERRANEAN REGION;
GERMAN DEMAND;
SPAIN;
ARRIVALS;
MODELS;
FLOWS;
SEASONALITY;
D O I:
10.1016/j.tourman.2009.03.017
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
This study provides a strategy for modelling the effect of the business cycle on tourism demand under the rationale that tourism cycles are heavily influenced by lagged effects of the overall business cycle. Using quarterly data on overnight stays in Italian hotels, both domestic and inbound between 1985 and 2004, we adopt a structural time series approach to evaluate two alternative models, the first with a latent cycle component (LCC) and the second based on specific economic explanatory variables (XCV). The two models are compared in terms of explanatory power, best-fit, residual diagnostics and forecasting ability. The results show similar performances. The policy implication is that the XCV model can be used for calibrating countercyclical interventions in tourism policy. (C) 2009 Elsevier Ltd. All rights reserved.
机构:
Hong Kong Polytech Univ, Sch Hotel & Tourism Management, Kowloon, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Sch Hotel & Tourism Management, Kowloon, Hong Kong, Peoples R China
Goh, Carey
Law, Rob
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机构:
Hong Kong Polytech Univ, Sch Hotel & Tourism Management, Kowloon, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Sch Hotel & Tourism Management, Kowloon, Hong Kong, Peoples R China
机构:
Hong Kong Polytech Univ, Sch Hotel & Tourism Management, Hong Kong, Hong Kong, Peoples R ChinaUniv Surrey, Sch Hospitality & Tourism Management, Guildford GU2 5XH, Surrey, England