计量经济学论文-中国旅游业收入影响分析.doc

1、计量经济学论文中国旅游业收入影响分析 前言改革开放后的几十年来，生活节奏的加快使得越来越多的人选择旅游这种方式释放紧张的状态，也就使得旅游业发展迅速。近年来，旅游更是成为每个人日常不可缺少的因素。中国作为世界五大文明古国（包括古希腊），同时也是当今世界著名的旅游大国，旅游业在我国的发展更是欣欣向荣，是不折不扣的朝阳产业。按照联合国世界旅游组织预测，到2015年中过奖成为世界上第一大入境旅游接待国和第四大出境旅游客源国。本文以我国旅游业收入为被解释变量，利用eviews软件对其进行了多因素变量分析。亦在得出一些中国旅游影响因子的分析及对未来一段时间内旅游业发展提出一些建议。关键词 国内旅游收入

2、计量经济学 模型 检验一问题的提出近年来旅游如此火爆，旅游业及其相关产业的发展也如火如荼。那究竟是哪些因素影响着旅游业的发展，他们之间有着什么联系，我们又该如何中国旅游未来的发展呢？本文将从计量经济学的角度对以上问题进行定量分析，并试图对其更深层次的因素进行探索以及进行一个短期内旅游行业发展的预测。二影响因素的确定城镇人均可支配收入（国内旅游暂时只考虑城镇）国内游客数量入境游客数量旅行社数量三计量经济学模型的建立我们建立一般模型如下：Yi=1+2*x1+3*x2+4*x3+5*x4在此 Y为我国的旅游收入（万元） x1为入境游客人数（万人） x2为我国国内游客人数（百万人） x3为城镇人口可支

3、配收入指数 x4为旅行社数量（个）四 模型求解和检验对该模型执行OLS回归 详见（表二）显然，该模型的可绝系数很高（0.990525），F检验显著，但是x2 x3 x4 t检验结果不显著，并且x4系数符号不符合经济意义，说明存在严重的多重共线性。这说明我们的模型本身存在很大缺陷。更改模型为：logY=1+2*log(x1)+3*log(x2)+4*log(x3)+5*log(x4)对新模型进行OLS回归详见（表三）明显得出结果好得多了。R2为0.989061，F检验显著除x4外其他因素t检验结果显著。多重共线性依然存在。因此，利用软件对4个变量进行相关系数检测。详见（表四）结果显示，4个变量因

4、素相关性很高，因此我们必须剔除一个变量。严谨起见，利用eviews分别对他们进行两两分析详见（表五表十）。综合得出，变量x4必须从模型中剔除，因此更新后的模型为：logY=1+2*log(x1)+3*log(x2)+4*log(x3)对新模型进行分析详见（表十一)R2=0.988906 Dw=1.794877 说明修正后明显好转。进行了一系列检验和修正后的最终结果如下：logY=1.275850*log(x1)+1.374221*log(x2)-1.171586*log(x3)-5.243261五经济分析以上模型得知，我国旅游业收入与人均可支配收入，国内旅游人数，入境旅游人数密切相关。众所周知

5、，旅游业是一个低投资高回报的产业，同时也是二十一世纪最为环保的经济产业之一。作为世界上的文化，经济大国，在今后势必会增加旅游行业的投入发展。同时对着人民生活状况的提高（x1），国内旅游人数（x2）势必会增加，这不仅带动了旅游收入（y）的增加，同时拉动了gdp的上升，也带动了相关产业如餐饮，运输业的发展。因此，在发展旅游业的同时，也应注意相关产业发展的跟进，正所谓全面发展，整体跟进。这么一来，y的增加才会不仅仅是昙花一现，而更加稳定。另一方面，近年来通货膨胀严重，房价也成为头号问题。在一定程度上，旅游业的发展，人们将更多的x1投入旅游，可以一定程度的减缓现金流过度投向房地产行业的情况。不过，随着

6、y收入占国民经济收入的增加。其资金使用的相应监管及用途也更应值得每个人注意。模型同时说明，入境游客人数（x3）也与旅游收入（y）有着密切相关性。随着全球化地扩大，越来越多的外国客人会进入我国旅游。从经济角度讲，更多开放型行业的发展（如娱乐行业）会进一步提升我国旅游在全球的竞争力，同时以海纳百川的态度面对外国客人，外来文化乃至自己生活中的点点滴滴是每个中国人成为一个合格的大国公民所必需学会的技能。总而言之，旅游业是个朝阳产业，但同时他也是一个充满竞争的行业。若想在全球化中脱颖而出。中国所做的不仅仅是突出自我迎接挑战，更要突破自我紧跟时代。参考文献中华人民共和国国家统计局、中经网数据统计库计量经济

7、学 庞皓 科学出版社 旅游规划的性质与方法 吴承照 同济大学出版社附录（表一）：数据入境旅游者人数国内旅游人数城镇家庭人均可支配收入指数(可比价，1978=100)旅行社数量(万人次)(百万人次)(-)(个)19934152.69410255.1323819944368.45524276.8438219954638.65629290.3384619965112.75640301.6425219975758.79644311.9498619986347.84695329.9622219997279.56719360.6732620008344.39744383.7899320018901.297

8、84416.31053220029790.83878472.11155220039166.21870514.613361200410903.821102554.214927200512029.231212607.416245200612494.211394670.717957200713187.331610752.518943200813002.741712815.720110国际旅游收入国内旅游者总花费(亿美元)(亿元)199346.83864199473.231023.5199587.331375.719961021638.41997120.742112.71998126.022391.2

9、1999140.992831.92000162.243175.52001177.923522.42002203.853878.42003174.063442.32004257.394710.72005292.965285.92006339.496229.72007419.197770.62008408.438749.3年度旅游收入（万元）19931273.762519941664.262519952139.837519962530.919973169.17519983493.87519994065.562520004595.120014723.3620025254.387520034573.6

10、920046383.73520057190.1420068436.385200710495.335200811404.095资料来源：中经数据 http:/192.168.30.168:81/旅行社的数据只更新到了08年，因此笔者就只选取至2008年。（表二）Dependent Variable: YMethod: Least SquaresDate: 06/08/11 Time: 19:14Sample: 1993 2008Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-4956.6321262.

11、903-3.9247940.0024X10.7063190.2267673.1147370.0098X23.5499382.1293461.6671490.1237X313.909398.4190811.6521270.1267X4-0.5299180.232836-2.2759320.0438R-squared0.990525Mean dependent var5087.100Adjusted R-squared0.987079S.D. dependent var3009.755S.E. of regression342.1208Akaike info criterion14.75851Su

12、m squared resid1287513.Schwarz criterion14.99995Log likelihood-113.0681F-statistic287.4748Durbin-Watson stat1.193159Prob(F-statistic)0.000000（表三）Dependent Variable: LOG(Y)Method: Least SquaresDate: 06/09/11 Time: 00:17Sample: 1993 2008Included observations: 16VariableCoefficientStd. Errort-Statistic

13、Prob.C-5.6779631.257576-4.5150070.0009LOG(X1)1.4126050.3947173.5787750.0043LOG(X2)1.3194620.2799404.7133750.0006LOG(X3)-1.0590570.444222-2.3840710.0362LOG(X4)-0.1216520.308999-0.3936980.7013R-squared0.989061Mean dependent var8.360787Adjusted R-squared0.985083S.D. dependent var0.630739S.E. of regress

14、ion0.077037Akaike info criterion-2.038767Sum squared resid0.065281Schwarz criterion-1.797333Log likelihood21.31014F-statistic248.6339Durbin-Watson stat1.036456Prob(F-statistic)0.000000（表四）LOG(X1)LOG(X2)LOG(X3)LOG(X4)LOG(X1)10.9401083050061820.9650545194380580.990799187972388LOG(X2)0.9401083050061821

15、0.9790385341285260.937513596119842LOG(X3)0.9650545194380580.97903853412852610.973379982347374LOG(X4)0.9907991879723880.9375135961198420.9733799823473741(表五）Dependent Variable: YMethod: Least SquaresDate: 06/08/11 Time: 20:50Sample: 1993 2008Included observations: 16VariableCoefficientStd. Errort-Sta

16、tisticProb.C-2201.792282.8948-7.7830770.0000X10.1999330.0887262.2533640.0421X26.1464690.7363808.3468670.0000R-squared0.985641Mean dependent var5087.100Adjusted R-squared0.983432S.D. dependent var3009.755S.E. of regression387.4049Akaike info criterion14.92418Sum squared resid1951073.Schwarz criterion

17、15.06904Log likelihood-116.3934F-statistic446.1819Durbin-Watson stat0.707547Prob(F-statistic)0.000000（表六）Dependent Variable: YMethod: Least SquaresDate: 06/08/11 Time: 20:51Sample: 1993 2008Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2557.203432.3708-5.9143760.0001X10.105

18、6550.1747820.6044980.5559X314.766703.1510204.6863240.0004R-squared0.966047Mean dependent var5087.100Adjusted R-squared0.960824S.D. dependent var3009.755S.E. of regression595.7221Akaike info criterion15.78479Sum squared resid4613503.Schwarz criterion15.92965Log likelihood-123.2783F-statistic184.9414D

19、urbin-Watson stat0.846654Prob(F-statistic)0.000000（表七）Dependent Variable: YMethod: Least SquaresDate: 06/08/11 Time: 20:51Sample: 1993 2008Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-851.96741414.204-0.6024360.5572X10.2874650.4707760.6106190.5520X40.3360640.2578731.303215

20、0.2151R-squared0.919239Mean dependent var5087.100Adjusted R-squared0.906815S.D. dependent var3009.755S.E. of regression918.7662Akaike info criterion16.65130Sum squared resid10973706Schwarz criterion16.79616Log likelihood-130.2104F-statistic73.98472Durbin-Watson stat0.517678Prob(F-statistic)0.000000（

21、表八）Dependent Variable: YMethod: Least SquaresDate: 06/08/11 Time: 20:52Sample: 1993 2008Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2078.661338.2520-6.1453030.0000X26.0802871.8210883.3388210.0053X33.5661443.9558120.9014950.3837R-squared0.981208Mean dependent var5087.100Ad

22、justed R-squared0.978316S.D. dependent var3009.755S.E. of regression443.1971Akaike info criterion15.19327Sum squared resid2553508.Schwarz criterion15.33813Log likelihood-118.5461F-statistic339.3833Durbin-Watson stat0.706488Prob(F-statistic)0.000000（表九）Dependent Variable: YMethod: Least SquaresDate:

23、06/08/11 Time: 20:52Sample: 1993 2008Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-1715.254333.0433-5.1502440.0002X26.5965730.9609576.8645890.0000X40.0763780.0634231.2042680.2500R-squared0.982037Mean dependent var5087.100Adjusted R-squared0.979273S.D. dependent var3009.755S

24、.E. of regression433.3095Akaike info criterion15.14814Sum squared resid2440843.Schwarz criterion15.29300Log likelihood-118.1851F-statistic355.3486Durbin-Watson stat0.756232Prob(F-statistic)0.000000（表十）Dependent Variable: YMethod: Least SquaresDate: 06/08/11 Time: 20:53Sample: 1993 2008Included obser

25、vations: 16VariableCoefficientStd. Errort-StatisticProb.C-3170.934753.0737-4.2106550.0010X321.564554.7481954.5416310.0006X4-0.1533010.144267-1.0626200.3073R-squared0.967882Mean dependent var5087.100Adjusted R-squared0.962941S.D. dependent var3009.755S.E. of regression579.3978Akaike info criterion15.

26、72922Sum squared resid4364123.Schwarz criterion15.87408Log likelihood-122.8337F-statistic195.8810Durbin-Watson stat0.989069Prob(F-statistic)0.000000（表十一）Dependent Variable: LOG(Y)Method: Least SquaresDate: 06/09/11 Time: 00:39Sample: 1993 2008Included observations: 16VariableCoefficientStd. Errort-S

27、tatisticProb.C-5.2432610.580374-9.0342840.0000LOG(X1)1.2758500.1807427.0589650.0000LOG(X2)1.3742210.2342325.8669280.0001LOG(X3)-1.1715860.327862-3.5734120.0038R-squared0.988906Mean dependent var8.360787Adjusted R-squared0.986133S.D. dependent var0.630739S.E. of regression0.074275Akaike info criterion-2.149775Sum squared resid0.066201Schwarz criterion-1.956628Log likelihood21.19820F-statistic356.5687Durbin-Watson stat1.794877Prob(F-statistic)0.000000word文档 可自由复制编辑