中国入境游客周期波动特征及影响机理

doi:10.11821/dlyj201410014

摘要/Abstract

摘要：

以大陆入境游客的年度及月度数据为例,利用HP滤波、BP滤波及季节指数分析了大陆入境游客的周期波动特征,并结合脉冲响应模型对其影响机理进行研究。结果表明：1978年以来入境游客在波动中上升,在1989年、2003年、2009年出现较大的下滑,根据滤波分解可将入境旅游划分为五个周期,分别为起步期（1978-1983年）、探索发展期（1984-1989年）、初步发展期（1990-1996年）、快速发展期（1997-2003年）、相对成熟期（2004-2011年）,平均每个周期约为6.6年。入境游客的季节强度指数大致呈“倒V字型”分布,季节变动指数大致呈“双W型”分布,相对于年度数据,月度数据的波动效应更加显著。政策制度、区域经济、突发事件对入境游客周期波动具有重要影响。脉冲响应分析表明：对外经济交流与区域经济发展状况对入境游客有正向的冲击,不同交通方式对入境游客有不同的响应机理。针对入境游客的周期波动特征,应进一步注重游客质量的提升,加强对外宣传营销,及时调整经营方式及发展策略,同时需要平衡发展三大入境旅游市场,降低入境旅游市场的风险性。

关键词: 入境游客, 周期, 波动, 季节指数, 响应, 中国

Abstract:

This article uses the HP and BP filter, and seasonal index to analyse the periodic and fluctuant characteristics of the annual and monthly data of Chinese mainland's inbound tourists. Combined with the impulse response model, it studies the influence mechanism. The results show that: the total number of inbound tourists has risen in fluctuation since 1978, and shows a decline trend in 1989, 2003 and 2009. According to the filter decomposition, it can divide the development of inbound tourism into 5 periods: (1) the initial stage (1978-1983), (2) the period of exploration (1984-1989), (3) the preliminary development period (1990-1996), (4) the rapid development period (1997-2003), and (5) a relatively mature period (2004-2011), with the average period being about 6.6 years. The seasonal strength index of Chinese inbound tourism generally presents the "inverted-V shape" distribution; the seasonal variation index generally presents a "double-W shape" distribution. Compared with the annual data, the fluctuant effect of monthly data is more obvious. Policies and institution, regional economy and unexpected events have a significant impact on the period and fluctuation of inbound tourists. Through the analysis of impulse response, it is found that the foreign economic exchange and regional economic development have a positive impact on inbound tourists; however, different modes of transportation have different response mechanism to inbound tourists. In term of the periodic and fluctuant characteristics of inbound tourists, it is suggested that we should enhance the quality of tourists, strengthen the publicity and marketing, adjust the management mode and development strategy in time; in addition, we should balance the development of three major inbound tourism markets, and reduce the risks of the inbound tourism market in the future.

Key words: inbound tourists, period, fluctuation, seasonal index, response, China

方叶林, 黄震方, 侯兵, 王芳. 中国入境游客周期波动特征及影响机理[J]. 地理研究, 2014, 33(10): 1942-1955.

Yelin FANG, Zhenfang HUANG, Bing HOU, Fang WANG. The periodic and fluctuant characteristics of Chinese inbound tourists and its influence mechanism[J]. GEOGRAPHICAL RESEARCH, 2014, 33(10): 1942-1955.

图/表 10

图1

图2

表1

不同滤波方法的分解结果"

年份	HP滤波			BK滤波		CFa滤波			CFb滤波
年份	趋势成分		周期成分		趋势成分	周期成分	趋势成分	周期成分	趋势成分	周期成分
1978	82.32	98.60							120.63	60.29
1979	301.97	118.42							352.91	67.48
1980	522.60	47.65							529.76	40.49
1981	746.39	30.32		708.89	67.82	705.09	71.62		687.45	89.26
1982	975.98	-183.55		888.57	-96.14	861.19	-68.76		868.28	-75.85
1983	1214.32	-266.62		1122.86	-175.16	1085.66	-137.96		1105.36	-157.66
1984	1462.53	-177.31		1431.25	-146.03	1393.29	-108.07		1409.93	-124.71
1985	1719.06	64.25		1813.19	-29.88	1791.13	-7.82		1766.62	16.69
1986	1980.58	301.37		2189.62	92.33	2255.00	26.95		2139.04	142.91
1987	2244.40	445.83		2480.82	209.41	2536.11	154.12		2484.05	206.18
1988	2510.87	658.61		2689.29	480.19	2702.35	467.13		2769.28	400.20
1989	2784.76	-334.62		2866.99	-416.85	2846.70	-396.56		2986.94	-536.80
1990	3077.46	-331.28		3074.92	-328.74	3036.52	-290.34		3158.21	-412.03
1991	3396.99	-62.01		3347.57	-12.59	3291.01	43.97		3326.42	8.56
1992	3748.07	63.42		3688.41	123.08	3705.06	106.43		3541.71	269.78
1993	4134.79	17.90		4059.92	92.77	4075.78	76.91		3843.61	309.08
1994	4561.90	-193.45		4422.88	-54.43	4407.22	-38.77		4248.67	119.78
1995	5034.29	-395.64		4810.24	-171.59	4777.33	-138.68		4748.26	-109.61
1996	5554.95	-442.20		5275.09	-162.34	5218.42	-105.67		5316.71	-203.96
1997	6122.89	-364.10		5862.35	-103.56	5798.69	-39.90		5925.82	-167.03
1998	6732.71	-384.87		6562.59	-214.75	6538.36	-190.52		6558.50	-210.66
1999	7375.36	-95.80		7337.50	-57.94	7322.41	-42.85		7214.94	64.62
2000	8037.95	306.44		8078.12	266.27	8158.80	185.59		7908.35	436.04
2001	8706.64	194.65		8756.80	144.49	8765.30	135.99		8652.09	249.20
2002	9370.63	420.20		9427.53	363.30	9399.47	391.36		9444.62	346.21
2003	10021.08	-854.87		10119.68	-953.47	10088.26	-922.05		10259.88	-1093.67
2004	10653.37	250.45		10859.57	44.25	10839.41	64.41		11048.64	-144.82
2005	11254.29	774.94		11601.73	427.50	11620.91	408.32		11751.59	277.64
2006	11813.18	681.03		12232.18	262.03	12402.69	91.52		12319.33	174.88
2007	12327.09	860.24		12674.84	512.49	12738.90	448.43		12731.16	456.17
2008	12799.90	202.84		12928.11	74.63	12946.86	55.88		13004.52	-1.78
2009	13244.10	-596.51							13190.73	-543.14
2010	13674.19	-297.97							13358.30	17.92
2011	14098.72	-556.37							13570.48	-28.13

表1

表2

图3

图4

图5

图6

表3

图7

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	HP周期	BK周期	CFa周期	CFb周期
HP周期	1.000	0.923^**	0.874^**	0.795^**
BK周期	0.923^**	1.000	0.988^**	0.950^**
CFa周期	0.874^**	0.988^**	1.000	0.939^**
CFb周期	0.795^**	0.950^**	0.939^**	1.000

变量	检验形式（C,T,K)	ADF统计值	P值	1%临界值	5%临界值	10%临界值	结论
lnvisitor	(C,N,0)	-5.476	0.000	-3.646	-2.954	-2.616	平稳
lnhwjck	(C,N,1)	-4.721	0.000	-3.915	-2.948	-2.636	平稳
lnydyw	(C,T,2)	-5.870	0.000	-4.285	-3.563	-3.215	平稳
lnwzsy	(C,T,2)	-6.656	0.000	-4.928	-3.663	-3.520	平稳
lntielc	(C,T,2)	-4.907	0.002	-4.297	-3.568	-3.218	平稳
lngllc	(C,N,1)	-5.530	0.000	-3.677	-2.857	-2.633	平稳
lnnhhd	(C,N,1)	-4.560	0.000	-3.648	-2.925	-2.617	平稳
lnmhlc	(C,N,1)	-5.380	0.000	-3.665	-2.852	-2.601	平稳
lnGDP	(C,N,1)	-3.723	0.009	-3.679	-2.968	-2.623	平稳
lnschxz	(C,N,1)	-4.781	0.001	-3.654	-2.957	-2.617	平稳