1、PAGE PAGE 8計量經濟學實驗報告 四 開課(ki k)實驗室： 崇德樓315 2013年 5月19日姓 名金超龍成 績年級專業2010級國貿專業學 號20102811課程名稱計量經濟學實驗名稱多重共線性實驗一、實驗內容 依據經濟學理論，以實際數據（實驗數據五）為基礎，建立反映天津市糧食市場需求狀況的糧食需求函數。檢驗所建立的糧食需求函數是否存在多重共線性。如果存在多重共線性，使用恰當的方法加以解決。二、實驗目的 熟練使用EViews軟件進行計量分析，理解多重共線性的檢驗和估計的基本方法。三、實驗步驟STEP1：參數估計STEP2：檢驗STEP3：消除多重共線性四、實驗結果及分析（附上必

2、要的回歸分析報告，并作以分析）經分析，影響天津糧食需求的主要因素，除了市常住人口和人均收入以外，還可能與相關其他農畜產品有關。為此，考慮的影響因素主要有市常住人口X1，人均收入X2、肉銷售量X3、蛋銷售量X4和魚蝦銷售量X5。為此設定如下的對數形式的計量經濟模型：Y=糧食銷售量（萬噸/年）；X1=市常住人口數（萬人）；X2=人均收入（元/年）；X3=肉銷售量（萬噸/年）；X4=蛋銷售量（萬噸/年）；X5=魚蝦銷售量（萬噸/年）。數據見實驗指導數據五，來源于中國統計年鑒年STEP1：參數估計在Eviews中點擊NEW項，建立Workfile輸入Y、X1、X2、X3、X4、X5的數據。點擊Quic

3、k，選Estimate Equation項，在OLS對話框中，鍵入Y C X1 X2 X3 X4 X5，輸出結果。見圖6.4.1。圖6.4.1 Eviews輸出的回歸結果分析：模型R2=0.970391 可決系數很高，F檢驗值52.43740，顯著。但當=5%時，t統計值=1.7613，X4和X5系數的t檢驗不顯著，同時X5的系數為負號不符合實際，這表明很可能存在多重共線性。STEP2：檢驗計算各解釋變量的相關系數，選擇X1、X2、X3、X4、X5數據，點擊“quickgroup statisticscorrelation”的相關系數矩陣，見表6.4.1。有相關系數矩陣可以看出：各解釋變量相關

4、之間的相關系數較高，證實存在嚴重多重共線性。表6.4.1 自變量相關系數矩陣STEP3：消除多重共線性采用逐步回歸的辦法，檢驗和解決多重共線性問題。分別作Y對X1、X2、X3、X4、X5的一元回歸，結果如表6.4.2。Dependent Variable: YMethod: Least SquaresDate: 05/12/03 Time: 13:56Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb.C-90.9207419.32929-4.7037810.0005X10

5、.3169250.02608112.151610.0000R-squared0.924841Mean dependent var142.7129Adjusted R-squared0.918578S.D. dependent var26.09805S.E. of regression7.446964Akaike info criterion6.985054Sum squared resid665.4873Schwarz criterion7.076347Log likelihood-46.89537F-statistic147.6617Durbin-Watson stat1.536885Pro

6、b(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 05/12/03 Time: 13:59Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb.C99.552516.42336415.498500.0000X20.0815190.0107187.6055060.0000R-squared0.828188Mean dependent var142.7129Adjusted R-square

7、d0.813870S.D. dependent var26.09805S.E. of regression11.25942Akaike info criterion7.811851Sum squared resid1521.294Schwarz criterion7.903145Log likelihood-52.68296F-statistic57.84372Durbin-Watson stat0.642278Prob(F-statistic)0.000006Dependent Variable: YMethod: Least SquaresDate: 05/12/03 Time: 14:0

8、0Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb.C74.648248.2889899.0057110.0000X34.8927120.5635788.6815140.0000R-squared0.862651Mean dependent var142.7129Adjusted R-squared0.851205S.D. dependent var26.09805S.E. of regression10.06704Akaike info criterion7.58797

9、4Sum squared resid1216.144Schwarz criterion7.679268Log likelihood-51.11582F-statistic75.36868Durbin-Watson stat0.813884Prob(F-statistic)0.000002Dependent Variable: YMethod: Least SquaresDate: 05/12/03 Time: 14:01Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb.C

10、108.86475.93433018.344900.0000X45.7397520.8387566.8431750.0000R-squared0.796019Mean dependent var142.7129Adjusted R-squared0.779021S.D. dependent var26.09805S.E. of regression12.26828Akaike info criterion7.983475Sum squared resid1806.129Schwarz criterion8.074769Log likelihood-53.88433F-statistic46.8

11、2904Durbin-Watson stat0.769006Prob(F-statistic)0.000018Dependent Variable: YMethod: Least SquaresDate: 05/12/03 Time: 14:02Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb.C113.37476.07713318.655960.0000X53.0808110.5123006.0136880.0001R-squared0.750854Mean depen

12、dent var142.7129Adjusted R-squared0.730091S.D. dependent var26.09805S.E. of regression13.55865Akaike info criterion8.183490Sum squared resid2206.044Schwarz criterion8.274784Log likelihood-55.28443F-statistic36.16444Durbin-Watson stat0.593639Prob(F-statistic)0.000061表6.4.2 回歸結果變 量X1X2X3X4X5參數估計值0.316

13、9250.0815194.8927125.7397523.080811t統計值12.151617.6055068.6815146.8431756.013688R20.9248410.8281880.8626510.7960190.750854按R2的大小排序為：X1、X3、X2、X4、X5。以X1為基礎，順次加入其他變量逐步回歸。首先加入X3回歸結果為：Dependent Variable: YMethod: Least SquaresDate: 05/12/03 Time: 14:05Sample: 1974 1987Included observations: 14VariableCoef

14、ficientStd. Errort-StatisticProb.C-39.7947925.01570-1.5907930.1400X10.2115430.0453024.6695810.0007X31.9092460.7241532.6365230.0231R-squared0.953945Mean dependent var142.7129Adjusted R-squared0.945571S.D. dependent var26.09805S.E. of regression6.088671Akaike info criterion6.638146Sum squared resid407

15、.7910Schwarz criterion6.775087Log likelihood-43.46702F-statistic113.9220Durbin-Watson stat1.655554Prob(F-statistic)0.000000 t (-1.590793) (4.669581) （2.636523） R2=0.953945當=5%時，X3參數的t檢驗顯著，不予剔除，加入X2回歸得：Dependent Variable: YMethod: Least SquaresDate: 05/12/03 Time: 14:10Sample: 1974 1987Included obser

16、vations: 14VariableCoefficientStd. Errort-StatisticProb.C-34.6287927.82151-1.2446770.2416X10.2063280.0480164.2970540.0016X31.4486691.1753251.2325690.2459X20.0096050.0188750.5088970.6219R-squared0.955107Mean dependent var142.7129Adjusted R-squared0.941640S.D. dependent var26.09805S.E. of regression6.

17、304735Akaike info criterion6.755435Sum squared resid397.4968Schwarz criterion6.938023Log likelihood-43.28805F-statistic70.91803Durbin-Watson stat1.682728Prob(F-statistic)0.000000 t (4.297054) (1.232569) (0.508897) R2=0.955107當=5%時，X3、X2參數的t檢驗均不顯著，但單獨對x1、x2進行回歸得：Dependent Variable: YMethod: Least Squ

18、aresDate: 05/13/13 Time: 23:05Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb.C-40.7838528.00819-1.461400.1733X10.2291490.0453375.0543810.0004X20.0275200.0123232.2332290.0473R-squared0.948287Mean dependent var142.7129Adjusted R-squared0.938885S.D. dependent var

19、26.09805S.E. of regression6.451819Akaike info criterion6.754010Sum squared resid457.8856Schwarz criterion6.890951Log likelihood-44.27807Hannan-Quinn criter.6.741334F-statistic100.8568Durbin-Watson stat1.803344Prob(F-statistic)0.000000 t (5.054381) （2.233229） R2=0.948287 =0.938885因為=0.9388850.941640，

20、X2參數不顯著，需要剔除x2保留X1和X3并加入X4回歸得：Dependent Variable: YMethod: Least SquaresDate: 05/12/0 Time: 14:16Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb.C-37.9988428.00654-1.3567850.2047X10.2103140.0479194.3889780.0014X31.7457671.1785901.4812340.1694X40.2347891.2958740

21、.1811820.8598R-squared0.954096Mean dependent var142.7129Adjusted R-squared0.940324S.D. dependent var26.09805S.E. of regression6.375396Akaike info criterion6.777726Sum squared resid406.4568Schwarz criterion6.960314Log likelihood-43.44408F-statistic69.28123Durbin-Watson stat1.673512Prob(F-statistic)0.

22、000001t (4.388978) (1.481234) (0.181182) R2=0.954096當=5%時，X3和X4參數的t檢驗不顯著，但單獨對X1和X4做回歸得Dependent Variable: YMethod: Least SquaresDate: 05/13/13 Time: 23:25Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb.C-46.1079228.91860-1.5944040.1392X10.2425030.0449665.393027

23、0.0002X41.7042870.8777941.9415570.0782R-squared0.944024Mean dependent var142.7129Adjusted R-squared0.933846S.D. dependent var26.09805S.E. of regression6.712509Akaike info criterion6.833232Sum squared resid495.6355Schwarz criterion6.970173Log likelihood-44.83262Hannan-Quinn criter.6.820556F-statistic

24、92.75612Durbin-Watson stat1.915578Prob(F-statistic)0.000000 t (5.393027) （1.941557） R2=0.944024 =0.933846因為=0.9338460.940324，X4參數不顯著，需要剔除x4加入X5回歸得：Dependent Variable: YMethod: Lest SquaresDate: 05/12/03 Time: 14:19Sample: 1974 1987Included observations: 14VariableCoefficientStd. Errort-StatisticProb

25、.C-40.8233326.65152-1.5317450.1566X10.2105270.0476684.4165360.0013X32.1447981.3704411.5650420.1486X5-0.1574380.763156-0.2062980.8407R-squared0.954140Mean dependent var142.7129Adjusted R-squared0.940382S.D. dependent var26.09805S.E. of regression6.372306Akaike info criterion6.776756Sum squared resid406.0629Schwarz criterion6.959344Log likelihood-43.43729F-statistic69.35167Durbin-Watson stat1.634831Prob(F-statistic)0.000001