从图3中可以看出从2008年3季度到2014年间,中国大陆赴澳门的游客量整体呈现出平稳上升趋势,各个季度存在波动。但这个趋势存在的前提是中国大陆的经济持续稳定增长,政治环境稳定向好。
本模型的主要特点在于克服了传统计量经济学模型的一些局限性,使得预测的结果更加准确、可靠。传统的计量经济学的局限性主要表现为:一是自变量之间的共线性问题;第二是,经济模型中系数估计的变化性。因为系数的评估会随着时间而变化,这就使得建立的模型仅仅运用于短期预测。针对这二个问题,本模型采取了有效的方法加以克服。本文在建模过程中采用VIF检验和分步回归的方法对共线性问题进行有效的控制;系数的变化性是任何预测方法都无法完全克服的障碍,因为任何预测模型的预测时间都不可能是无限期的。本模型主要是通过加强检验和增加数据的时效性来加以控制。
(1)Archer. Brian. H., “Demand Forecasting —Quantitative and Intuitive Techniques”, Tourism Management, 1 (1980), 5-12.
(2)Calantone, R. J., di Benesetto, C., &Bojanic, D. (1987)., A comprehensive review of the tourism forecasting literature. Journal of Travel Research, 26(2), 28-39.
(3)Crouch, G. I. (1994d). The study of international tourism demand: A review of findings. Journal of Travel Research, 33(1), 12-33.
(4)Crouch, G. I. (1994e). The study of international tourism demand: A survey of practice. Journal of Travel Research, 32(4), 41-57.
(5)Crouch, G.I., & Shaw, R. N. (1992)., International tourism demand: A meta- analytical integration of research findings. In P. Johnson & B. homas (Eds.), Choice and demand in tourism. (pp. 175-207).London, UK: Cassel.
(6)Hanke, J.e., Reitsch, A.G., &Wichern, D.W. (2001).Business forecasting (7th ed).Upper Saddle River, NJ: Prentice Hall Inc.
(7)Hiemstra, S. J., &Ismail, J. A. (1999).CHPTER 5: Behavioral models related to tourism. In T. Baum& R. Mudambi (Eds.), Economic and management methods for tourism and hospitality research (pp.47-66). Chichester, UK: John Wiley & Sons. Inc.
(8)Lim, C. (1997a). an econometric classification and review of international tourism demand models. Tourism Economics, 3(1), 69-81
(9)Lim, C. (1997c)., Review of International Tourism Demand Models. Annals of Tourism Research, 24(4), 835-849
(10)Lim, C.,&McAleer, M. (1999)., A Seasonal Analysis of Malaysian Tourist Arrivals to Australia.
(11)Morley, C.l. (1991)., Modeling international tourism demand: Model specification and structure. Journal of Travel Research, 30(1), 40-44.
(12)Morley, C.l. (1995)., Tourism demand: Characteristics, segmentation and aggregation. Tourism Economics, I(4), 315-328
(13)Morley, C.L. (1999)., Estimating integrated time series and other problems in modeling tourism demand. (Working paper 99/3). Melbourne, Victoria, Australia: Research Development Unit, RMIT (Royal Melbourne Institute of Technology) business.
(14Morley, C.L. (2000).Demand modeling methodologies: Integration and other issues. Tourism Economics, 6(1), 5-19.
(15)Sheldon, P. J. (1982)., Tourism forecasting the state-of -the –art, (Working paper 82-03-04). Burnaby, British Columbia, Canada: Faculty Of Business Administration, Simon Fraser University
(16)Sheldon, P. J.,&Var, T. (1985). Tourism Forecasting: A Review of empirical research. Journal of Forecasting, 4(2), 183-195.
( 17)Uysal, M. S., &Crompton, J. L. (1985a)., Deriving a relative price index for inclusion in international tourism demand. Journal of Travel Research, 24(1), 32-34.
(18)Vanhove, N., ”Forecasting in tourism”, Recue de Tourisme,35(1980),2-7
(19)Witt, s.f., & witt, c.a. (1995)., Forecasting tourism demand: A review of empirical research International Journal of Forecasting, 11(3), 447-475.
(20)曾忠禄,“澳门游客分析与预测”,4-20,澳门理工学院出版社,2007年出版