计量经济学eviews上机实验

-2012学年第二学期计量经济学eviews上机实验姓名：学号：班级：实验一：研究国民生产总值对财政收入的影响。（本实验30分）下表是我国1978－1997年的财政收入Y和国民生产总值X的数据资料，试根据资料完成下列问题：建立财政收入对国民生产总值的一元线性回归方程；（10分）对所建立的回归方程进行检验并对结果进行说明，然后解释方程的经济意义；（15分）若1998年国民生产总值为78017.8亿元，求1998年财政收入预测值。（5分）实验一的数据：obsXY19783624.1001132.26019794038.2001146.38019804517.8001159.93019814860.3001175.79019825301.8001212.33019835957.4001366.95019847206.7001642.86019858989.1002004.820198610201.402122.010198711954.502199.350198814922.302357.240198916917.802664.900199018598.402937.100199121662.503149.480199226651.903483.370199334560.504348.950199446670.005218.100199557494.906242.200199666850.507407.990199773452.508651.140解：（1）由题意可知，y=0.100031x+858.3108（46.05）（12.79）R2=0.99F=2120.41（2）由数据统计得，x的t方检验为46.04788>2，因此具有高度显著性，同理C也具有高度显著性，所以此方程有效；经济意义：财政收入与国民生产总值成正比，即财政收入随国民生产总值的增长而增长。（3）将X=78017.8代入方程得，Y=8662.5093518。实验二：研究某企业员工的工资是否受性别的影响。（本实验20分）表中列出了24个不同性别的企业员工的工资收入情况。要求根据所给出的数据资料建立虚拟变量模型。（注：要先说明以哪一个变量作为虚拟变量，并说明1代表什么，0代表什么。）（5分）根据你得到的虚拟变量回归方程，判断该方程是否有效。若方程有效，则分析该企业员工的男女平均工资是否存在差距，差距是多少。（15分）实验二的数据：工资性别2561.1女2626.8女2737.5女2764.7男3793.0男3802.4男3833.2男2918.1男3551.9女2613.1女2717.1女3745.0男解：（1）定义虚拟变量D：当D=0时表示女性，D=1时表示男性，Y表示工资，X表示性别由题意可知，Y=3476.07-674.82X（19.42）（-2.67）R2=0.42F=7.11(2)由数据统计得，T检验：二者绝对值均大于2，即性别对工资有显著影响；R检验：值小于0.8，即真实值与估计值偏差较大；F检验：通过，即方程整体具有显著性；所以方程有效。该企业员工的男女平均工资存在差距，且差距为674.82。实验三：研究财政收入及其影响因素。（本实验50分）Y-财政收入；x1-受灾面积；x2-工业增加值；x3-建筑业增加值；x4-总人口；X5-最终消费。试根据资料完成下列问题：建立多元回归方程。（5分）判断是否存在多重共线性（用直观判断法和相关系数检验法进行判断）。（10分）若存在多重共线性，请运用逐步回归法进行修正并列出修正了的回归方程。（30分）对修正了的多元回归方程进行经济意义的解释。（5分）实验三的数据：yx1x2x3x4x51978 1132.31018.41607138.2962592239.119791146.41258.91769.7143.8975422619.419801159.91359.41996.5195.5987052976.119811175.81545.62048.4207.11000723309.119821212.31761.62162.3220.71016543637.9198313671960.82375.6270.61030084020.519841642.92295.52789316.71043574694.519852004.82541.63448.7417.91058515773198621222763.93967525.7107507654219872199.43204.34585.8665.81093007451.219882357.238315777.28101110269360.119892664.94228648479411270410556.519902937.150176858859.411433311365.219913149.485288.68087.11015.111582313145.919923483.37580010284.5141511717115952.119934348.956882.114143.82284.711851720182.119945218.19457.219359.63012.61198502679619956242.21199324718.33819.61211213363519967407.9913844.229082.64530.512238940003.919978651.1414211.232412.14810.612362643579.419989875.9514552.433387.95231.412476146405.9199911444.081447235087.25470.612578649722.7200013395.2314628.239047.3588812674354600.9200116386.0415411.842374.66375.412762758927.4200218903.6416117.345975.2700512845362798.5200321715.2517092.153092.98181.312922767442.5解：（1）由题意可知，y=-1.528223X1+0.832924X2-1.278645X3+0.130423X4+0.122710X5-11210.53（-10.99）（3.19）（-0.99）（3.79）（1.09）R2=0.99F=659.42（2）存在，直观判断法：①X3的回归系数为负，与预期不符，不能合理解释经济现实，故存在多重共线性；②用X5对X4进行相关系数检验时，X5=1.889618X4-191999.2（11.24）（-9.98）R2=0.840458F=126.4303得X5的t方检验为11.24>2，即存在高度显著性；同理X5对X1，X2，X3都存在高度显著性；综上所述，存在多重共线性。相关系数检验法：得变量的相关系数矩阵，可知，变量之间存在高度显著性，故存在多重共线性。YX5X4X3X2X1Y

1.000000

0.965198

0.838835

0.966870

0.970290

0.910084X5

0.965198

1.000000

0.916765

0.997693

0.998503

0.984829X4

0.838835

0.916765

1.000000

0.904118

0.904274

0.945544X3

0.966870

0.997693

0.904118

1.000000

0.999434

0.981597X2

0.970290

0.998503

0.904274

0.999434

1.000000

0.980662X1

0.910084

0.984829

0.945544

0.981597

0.980662

1.000000（3）用逐步回归法来修正模型的多重共线性：①确定基础回归方程：DependentVariable:YMethod:LeastSquaresDate:05/31/12Time:11:21Sample:19782003Includedobservations:26CoefficitStd.Errort-StatistcProb.X20.3486150.01774419.646790.0000C93.08109412.55930.2256190.8234R-squared0.941463

Meandependentvar5897.824AdjustedR-squared0.939024

S.D.dependentvar5945.854S.E.ofregression1468.230

Akaikeinfocriterion17.49531Sumsquaredresid51736798

Schwarzcriterion17.59208Loglikelihood-225.4390

Hannan-Quinncriter.17.52317F-statistic385.9965

Durbin-Watsonstat0.183350Prob(F-statistic)0.000000由y与各解释变量分别进行一元回归的结果，知X2与y的一元回归方程的可决系数最大因此将X2作为基础方程：Y=0.348615X2+93.08109（19.65）（0.23）R2=0.941463F=385.99②在基础方程中依次引入其余解释变量进行回归：DependentVariable:YMethod:LeastSquaresDate:05/31/12Time:11:29Sample:19782003Includedobservations:26CoefficietStd.Errort-StatisticProb.

X20.7298480.04479916.291780.0000X1-1.1125990.128213-8.6777520.0000C1984.283298.41376.6494370.0000R-squared0.986304

Meandependentvar5897.824AdjustedR-squared0.985113

S.D.dependentvar5945.854S.E.ofregression725.4634

Akaikeinfocriterion16.11967Sumsquaredresid12104836

Schwarzcriterion16.26483Loglikelihood-206.5556

Hannan-Quinncriter.16.16147F-statistic828.1677

Durbin-Watsonstat0.708865Prob(F-statistic)0.000000

在基础方程中依次对其他解释变量进行回归，由回归结果知，引入X1的回归方程的R2最大，且R2检验、T检验、F检验均通过，故在基础方程中保留x1,即：Y=0.73X2-1.11X1+1984.283(16.29)(-8.68)(6.65)R2=0.986F=828.1677③在含X1、X2的回归方程中依次引入其余3个解释变量，再分别进行回归：DependentVariable:YMethod:LeastSquaresDate:05/31/12Time:11:26Sample:19782003Includedobservations:26CoefficietStd.Errort-StatisticProb.

X1-1.5405640.130990-11.760890.0000X20.7883440.03489322.593340.0000X40.1511820.0325394.6462240.0001C-13051.933243.474-4.0240590.0006R-squared0.993087

Meandependentvar5897.824AdjustedR-squared0.992145

S.D.dependentvar5945.854S.E.ofregression526.9859

Akaikeinfocriterion15.51286Sumsquaredresid6109710.

Schwarzcriterion15.70642Loglikelihood-197.6672

Hannan-Quinncriter.15.56860F-statistic1053.505

Durbin-Watsonstat1.728162Prob(F-statistic)0.000000同上得，Y=-1.540564X1+0.788344X2+0.151182X4-13051.93（-11.76）（22.59）（4.65）（-4.02）R2=0.993F=1053.505④在含X1、X2、X4的回归方程中依次引入其余两个解释变量，分别进行回归：DependentVariable:YMethod:LeastSquaresDate:05/31/12Time:11:35Sample:19782003Includedobservations:26CoefficietStd.Errort-StatisticProb.

X1-1.4885460.134856-11.038070.0000X21.0310640.1881705.4794440.0000X40.1428710.0326394.3772940.0003X3-1.6385041.248930-1.3119260.2037C-12459.903223.332-3.8655350.0009R-squared0.993611

Meandependentvar5897.824AdjustedR-squared0.992394

S.D.dependentvar5945.854S.E.ofregression518.5554

Akaikeinfocriterion15.51101Sumsquaredresid5646894.

Schwarzcriterion15.75295Loglikelihood-196.6432

Hannan-Quinncriter.15.58068F-statistic816.4592

Durbin-Watsonstat2.090964Prob(F-statistic)0.000000由以上结果可知，X3未通过t检验，故不能加入模型；DependentVariable:YMethod:LeastSquaresDate:05/31/12Time:11:35Sample:19782003Includedobservations:26CoefficietStd.Errort-StatisticProb.

X1-1.5754030.130683-12.055180