关于国内旅游需求的计量经济学分析报告.doc

关于国内旅游需求的计量经济学分析报告 关于国内旅游需求的计量经济学分析报告 一、模型设定根据旅游经济学理论旅游需求是指在不同的价格水平下旅游者愿意购买的旅游产品数量旅游需求的主要影响因素包括：旅游者可支配收入、出游的偏好和动机、旅游产品的价格、非旅游消费品的价格、闲暇时间、旅游客源地与旅游目的地之间的距离旅游地的安全状况和旅游地的形象等等综合上述因素和变量的可观测性我们首先建立一个多元线性回归模型：y=b0+b1x1+b2x2+b3x3+b4x4+b5x5+u其中：y国内旅游需求使用国内旅游出游数量衡量x1旅游者可支配收入使用居民可支配收入衡量x2经济发展状况使用GDP衡量x3旅游业发展状况使用国内旅行社职工人数衡量x4旅游价格指数x5人口数量b0,b1,b2,b3,b4,b5,回归系数；u为随机扰动项收集数据如下表表示： obsY（万人）x1（元）x2（亿元）x3（人）x4x5（万人）19934102577.434560.578172114.711851719945243496.24667077553124.111985019956294282.9557494.991592117.112112119966404838.966850.587555108.312238919976445160.373142.794829102.812362619986955425.176967.210044899.21247611999719585480579.410883098.612578620007446279.9888254164336100.41267437846859.695727.9192408100.71276278787702.8103935.322914799.21284538708472.2116603.2249802101.212922711029422136584.3263245103.9129988 表1二、估计参数与模型检验1、直接对模型进行OLS法估计结果如下：DependentVariable:YMethod:LeastSquaresDate:05/29/05Time:11:21Sample:1993Includedobservations:12VariableCoefficientStd.ErrortStatisticProb.C29.023023247.8940.0089360.9932X10.0315960.1074020.2941840.7785X20.0060830.0059001.0311210.3422X30.0006250.0005491.1390180.2981X43.1394703.5302560.8893040.4081X50.0013900.0252310.0550940.9579Rsquared0.977694Meandependentvar719.9167AdjustedRsquared0.959105S.D.dependentvar179.3065S.E.ofregression36.26027Akaikeinfocriterion10.32618Sumsquaredresid7888.843Schwarzcriterion10.56863Loglikelihood55.95705Fstatistic52.59632DurbinWatsonstat3.131017Prob(Fstatistic)0.000071表22、分析由上表我们看到解释变量t值不显著而可决系数R和F统计量显著说明极有可能存在多重共线性3、多重共线性检验计算解释变量之间的简单相关系数结果如下： x1x2x3x4x5x110.9974780.9401150.677710.976511x20.99747810.9288830.678650.971951x30.9401150.92888310.529530.902582x40.677710.678650.5295310.79203x50.9765110.9719510.9025820.792031表3由表3可以看出解释变量之间存在严重的多重共线性 4、多重共线性修正（1）运用OLS法逐一求y对各个解释变量的回归发现y对x1的线性关系很强拟合度最好如下：y=209.33+0.087x1t(5.82)(14.95)se(35.96)(0.0058)R2=0.957S.E.=38.93F=223.41212逐步回归,将其余解释变量逐一代入：（2）将x2代入后y=186.32+0.124x10.000462x2t6.310.4381.5797R2=0.961S.E.=36.305F=129.659R2提高到了0.966,F统计量也有所提高但对其它参数有明显影响b1下降到了0.033,此外代入x2后t统计量的值大副下降分别为b0:6.31,b1:0.438,b2:1.5797,因此决定舍去变量x2保留x1（3）将x3代入后y=186.32+0.124x10.000462x3t4.282865.963010.95R2=0.961S.E.=39.116F=111.069R2提高到了0.9611,但t统计量的值有所降低而且该变量对y的影响很小斜率系数只有0.000462故将该变量舍去（4）将x4代入后y=51.783+0.093x1+2.133x4t0.22322311.924971.138959R2=0.962555S.E.=38.359F=115.67R2的值提高了但是x4的t统计量并不显著因为x4为旅游物价指数因此我们发现x4的回归系数符号跟经济意义发生了背离根据表一我们看到x1与x4的相关系数为0.67771相关程度不高因此推断有可能是模型的设定出现了偏差或是数据不或是模型遗漏了其它的重要影响变量因此首先改变模型的形式采用对数模型进行回归回归结果如下：DependentVariable:Y1Method:LeastSquaresDate:05/29/05Time:14:28Sample:1993Includedobservations:12VariableCoefficientStd.ErrortStatisticProb.C2.1869921.4685041.4892650.1706Z10.7503660.04957015.137510.0000Z40.4874040.2411652.0210380.0740Rsquared0.978856Meandependentvar6.550016AdjustedRsquared0.974158S.D.dependentvar0.255534S.E.ofregression0.041079Akaikeinfocriterion3.334340Sumsquaredresid0.015187Schwarzcriterion3.213113Loglikelihood23.00604Fstatistic208.3285DurbinWatsonstat2.633801Prob(Fstatistic)0.000000表5回归系数符号跟经济意义仍然发生了背离用x4的平方值、立方值和开平方值进行回归系数符号仍然没有改变于是猜想有可能是数据出现了偏差因为由于没有直接的旅游价格指数我们简单地使用了居民消费价格指数来代替旅游价格指数于是改变旅游价格指数的衡量方式首先采用交通价格指数来代替回归后发现系数符号仍然没有改变再使用居民文娱价格指数来代替回归后发现系数符号也没有改变此外还有可能是缺失了某些重要的解释变量留在异方差和自相关检验中进行分析（5）再将x5带入：DependentVariable:YMethod:LeastSquaresDate:05/29/05Time:14:45Sample:1993Includedobservations:12VariableCoefficientStd.ErrortStatisticProb.C2394.3781572.2011.5229460.1621X10.1221650.0258564.7249020.0011X50.0191510.0137771.3901330.1979Rsquared0.964730Meandependentvar719.9167AdjustedRsquared0.956893S.D.dependentvar179.3065S.E.ofregression37.22815Akaikeinfocriterion10.28433Sumsquaredresid12473.42Schwarzcriterion10.40555Loglikelihood58.70595Fstatistic123.0886DurbinWatsonstat2.381878Prob(Fstatistic)0.000000表6可以看出t统计量的值大副下降而且x5的回归系数仅为0.019对y影响很小故舍去5、异方差检验OLS估计法估计的参数为：Y=51.78329206+0.09309258196*X1+2.133003771*X4DependentVariable:YMethod:LeastSquaresDate:05/29/05Time:15:59Sample:1993Includedobservations:12VariableCoefficientStd.ErrortStatisticProb.C51.78329231.98030.2232230.8283X10.0930930.00780711.924970.0000X42.1330041.8727651.1389590.2841Rsquared0.962555Meandependentvar719.9167AdjustedRsquared0.954233S.D.dependentvar179.3065S.E.ofregression38.35928Akaikeinfocriterion10.34419Sumsquaredresid13242.91Schwarzcriterion10.46541Loglikelihood59.06513Fstatistic115.6749DurbinWatsonstat2.359411Prob(Fstatistic)0.000000图示法GoldfeldQuandt检验由于样本数目太少不能用Quandt检验ARCH检验DependentVariable:E2Method:LeastSquaresDate:05/29/05Time:17:13Sample(adjusted):1996Includedobservations:9afteradjustingendpointsVariableCoefficientStd.ErrortStatisticProb.C1878.2751431.2051.3123730.2464E2(1)0.2570250.4358990.5896440.5811E2(2)0.0334290.4475240.0746980.9434E2(3)0.1874270.4318260.4340320.6824Rsquared0.130019Meandependentvar1343.563AdjustedRsquared0.391970S.D.dependentvar2274.618S.E.ofregression2683.634Akaikeinfocriterion18.92883Sumsquaredresid36009468Schwarzcriterion19.01649Loglikelihood81.17975Fstatistic0.249083DurbinWatsonstat2.120898Prob(Fstatistic)0.859007计算（np）*R*R=（123）*0.130019*0.130019=0.1521444它远远小于临界值说明没有存在异方差 6.自相关的检验对模型：y=b0+b1x1+b4x4进行估计为：DependentVariable:YMethod:LeastSquaresDate:05/29/05Time:14:54Sample:1993Includedobservations:12VariableCoefficientStd.ErrortStatisticProb.C51.78329231.98030.2232230.8283X10.0930930.00780711.924970.0000X42.1330041.8727651.1389590.2841Rsquared0.962555Meandependentvar719.9167AdjustedRsquared0.954233S.D.dependentvar179.3065S.E.ofregression38.35928Akaikeinfocriterion10.34419Sumsquaredresid13242.91Schwarzcriterion10.46541Loglikelihood59.06513Fstatistic115.6749DurbinWatsonstat2.359411Prob(Fstatistic)0.000000表7图示法： 从图中看到残差分布均匀基本不存在自相关（2）DW检验根据表7的统计结果由DW=2.359411,对于给定的显著性水平a=0.05查DurbinWatson表n=12,k=2,得下限临界值dl=0.812,du=1.579,4du=2.421,因为DW=2.359411大于du=1.579小于4du=2.421所以认为不存在自相关 三、关于经济意义的检验由表7看到x1的斜率系数为0.093x4的斜率系数为2.133,从模型上来说收入对旅游需求的影响为人均可支配收入每增加1000元旅游需求增加93万人符合经济意义对于x4斜率系数为2.133003771很明显该斜率系数的符号与经济意义不相吻合模型中的系数意味着价格越高旅游需求越大这完全违背的客观现实然而单独用x4对y做回归我们看到：DependentVariable:YMethod:LeastSquaresDate:05/29/05Time:17:42Sample:1993Includedobservations:12VariableCoefficientStd.ErrortStatisticProb.C2096.188568.44453.6875860.0042X413.002095.3548542.4280940.0356Rsquared0.370897Meandependentvar719.9167AdjustedRsquared0.307986S.D.dependentvar179.3065S.E.ofregression149.1603Akaikeinfocriterion12.99893Sumsquaredresid222488.0Schwarzcriterion13.07975Loglikelihood75.99359Fstatistic5.895640DurbinWatsonstat0