Eviews實驗報告

1、江西農業(yè)大學經濟貿易學院學 生 實 驗 報 告課程名稱： 計量經濟學 專業(yè)班級： 經濟1201班姓 名： 學 號： 指導教師： 徐冬梅 職稱： 講師 實驗日期： 2014.12.11 學生實驗報告學生姓名學號組員：實驗項目EVIEWS的使用必修 選修 演示性實驗 驗證性實驗 操作性實驗 綜合性實驗實驗地點管理模擬實驗室實驗儀器臺號指導教師實驗日期及節(jié)次一、實驗目的及要求1、目的會使用EVIEWS對計量經濟模型進行分析2、內容及要求（1）對經典線形回歸模型進行參數(shù)估計、參數(shù)的檢驗與區(qū)間估計，對模型總體進行顯著性檢驗；（2）異方差的檢驗及其處理；（3）自相關的檢驗及其處理；（4）多重共線性檢驗及其

2、處理；二、儀器用具儀器名稱規(guī)格/型號數(shù)量備注計算機1無網絡環(huán)境Eviews1三、實驗方法與步驟(一)數(shù)據的輸入、描述及其圖形處理；(二)方程的估計；(三)參數(shù)的檢驗、違背經典假定的檢驗；(四)模型的處理與預測四、實驗結果與數(shù)據處理實驗一：中國城鎮(zhèn)居民人均消費支出模型數(shù)據散點圖：通過Eviews估計參數(shù)方程回歸方程：Dependent Variable: YMethod: Least SquaresDate: 11/27/14 Time: 15:02Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-Statis

3、ticProb. X1.3594770.04330231.395250.0000C-57.90655377.7595-0.1532890.8792R-squared0.971419 Mean dependent var11363.69Adjusted R-squared0.970433 S.D. dependent var3294.469S.E. of regression566.4812 Akaike info criterion15.57911Sum squared resid9306127. Schwarz criterion15.67162Log likelihood-239.4761

4、 F-statistic985.6616Durbin-Watson stat1.294974 Prob(F-statistic)0.000000得出估計方程為：Y = 1.35947661442*X - 57.9065479515異方差檢驗1、 圖示檢驗法 圖形呈現(xiàn)離散趨勢，大致判斷存在異方差性。2、 Park檢驗Dependent Variable: LOG(E2)Method: Least SquaresDate: 11/27/14 Time: 16:16Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-

5、StatisticProb. C19.8256219.853590.9985910.3263LOG(X)-0.9564032.204080-0.4339240.6676R-squared0.006451 Mean dependent var11.21371Adjusted R-squared-0.027809 S.D. dependent var2.894595S.E. of regression2.934568 Akaike info criterion5.053338Sum squared resid249.7389 Schwarz criterion5.145854Log likelih

6、ood-76.32674 F-statistic0.188290Durbin-Watson stat2.456500 Prob(F-statistic)0.667555看到圖中LOG(E2)中P值為0.6676 > 0.05，所以不存在異方差性3、 G-Q檢驗e1檢驗：Dependent Variable: XMethod: Least SquaresDate: 11/27/14 Time: 16:41Sample: 1 12Included observations: 12VariableCoefficientStd. Errort-StatisticProb. C4642.02820

7、14.1832.3046710.0439Y0.2310460.2158241.0705300.3095R-squared0.102820 Mean dependent var6796.390Adjusted R-squared0.013102 S.D. dependent var293.2762S.E. of regression291.3486 Akaike info criterion14.33793Sum squared resid848840.2 Schwarz criterion14.41875Log likelihood-84.02758 F-statistic1.146034Du

8、rbin-Watson stat0.445146 Prob(F-statistic)0.309538e2檢驗：Dependent Variable: XMethod: Least SquaresDate: 11/27/14 Time: 16:42Sample: 20 31Included observations: 12VariableCoefficientStd. Errort-StatisticProb. C583.4526593.43700.9831750.3487Y0.6977480.04019617.358700.0000R-squared0.967879 Mean dependen

9、t var10586.89Adjusted R-squared0.964667 S.D. dependent var2610.864S.E. of regression490.7655 Akaike info criterion15.38082Sum squared resid2408507. Schwarz criterion15.46164Log likelihood-90.28493 F-statistic301.3245Durbin-Watson stat2.748144 Prob(F-statistic)0.000000第一個圖中的殘差平方和為848840.2第二個圖中的殘差平方和為

10、2408507所以F值為2408507/848840.2 = 2.8374 < 2.97，所以不存在異方差性4、 White檢驗White Heteroskedasticity Test:F-statistic2.240402 Probability0.125152Obs*R-squared4.276524 Probability0.117860Test Equation:Dependent Variable: RESID2Method: Least SquaresDate: 11/27/14 Time: 16:50Sample: 1 31Included observations: 3

11、1VariableCoefficientStd. Errort-StatisticProb. C-2135113.1158576.-1.8428760.0760X503.7331242.20782.0797560.0468X2-0.0236090.011650-2.0265900.0523R-squared0.137952 Mean dependent var300197.6Adjusted R-squared0.076378 S.D. dependent var347663.4S.E. of regression334122.9 Akaike info criterion28.36817Su

12、m squared resid3.13E+12 Schwarz criterion28.50694Log likelihood-436.7067 F-statistic2.240402Durbin-Watson stat1.871252 Prob(F-statistic)0.125152P值為0.11786 > 0.05，所以不存在異方差性通過四種不同的檢驗得知除了圖示檢驗法得出異方差的結論，其他的檢驗的結論都是不存在異方差的。5、 WLS（加權最小二乘法）修正Dependent Variable: YMethod: Least SquaresDate: 11/27/14 Time: 1

13、7:14Sample: 1 31Included observations: 31Weighting series: E3VariableCoefficientStd. Errort-StatisticProb. C-85.6942624.15675-3.5474250.0013X1.3622210.002307590.56150.0000Weighted StatisticsR-squared1.000000 Mean dependent var13474.53Adjusted R-squared1.000000 S.D. dependent var61353.74S.E. of regre

14、ssion27.93264 Akaike info criterion9.559810Sum squared resid22626.73 Schwarz criterion9.652325Log likelihood-146.1770 F-statistic348762.9Durbin-Watson stat2.061818 Prob(F-statistic)0.000000Unweighted StatisticsR-squared0.971413 Mean dependent var11363.69Adjusted R-squared0.970427 S.D. dependent var3

15、294.469S.E. of regression566.5415 Sum squared resid9308110.Durbin-Watson stat2.178992實驗二：中國糧食生產函數(shù)1、回歸方程Dependent Variable: LOG(Y)Method: Least SquaresDate: 12/11/14 Time: 15:06Sample: 1983 2007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LOG(X1)0.3811450.0502427.5861820.000

16、0LOG(X2)1.2222890.1351799.0420300.0000LOG(X3)-0.0811100.015304-5.3000240.0000LOG(X4)-0.0472290.044767-1.0549800.3047LOG(X5)-0.1011740.057687-1.7538530.0956C-4.1731741.923624-2.1694340.0429R-squared0.981597 Mean dependent var10.70905Adjusted R-squared0.976753 S.D. dependent var0.093396S.E. of regress

17、ion0.014240 Akaike info criterion-5.459968Sum squared resid0.003853 Schwarz criterion-5.167438Log likelihood74.24960 F-statistic202.6826Durbin-Watson stat1.791427 Prob(F-statistic)0.000000得出回歸方程為：LOG(Y) = 0.381144581612*LOG(X1) + 1.22228859801*LOG(X2) - 0.0811098881534*LOG(X3) - 0.04722870996*LOG(X4

18、) - 0.101173736285*LOG(X5) - 4過檢驗結果可知 R2 較大且接近于1，而且F=202.6826 > F0.05(5,19) = 2.74，故認為糧食產量與上述變量之間總體線性關系顯著。但是由于其中X4、X5前的參數(shù)估計值未通過t檢驗，且符號的經濟意義不合理，故認為解釋變量之間存在多重共線。2、相關系數(shù)表LNX1LNX2LNX3LNX4LNX5LNX1 1.000000-0.568744 0.451700 0.964357 0.440205LNX2-0.568744 1.000000-0.214097-0.697625-0.073270

19、LNX3 0.451700-0.214097 1.000000 0.398780 0.411279LNX4 0.964357-0.697625 0.398780 1.000000 0.279528LNX5 0.440205-0.073270 0.411279 0.279528 1.000000由表可知LnX1與LnX2之間存在高度的線性相關性3、簡單的回歸形式LnY與LnX1Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:15Sample: 1983 2007Included observations: 2

20、5VariableCoefficientStd. Errort-StatisticProb. LNX10.2240050.0255158.7792930.0000C8.9020080.20603443.206570.0000R-squared0.770175 Mean dependent var10.70905Adjusted R-squared0.760182 S.D. dependent var0.093396S.E. of regression0.045737 Akaike info criterion-3.255189Sum squared resid0.048114 Schwarz

21、criterion-3.157679Log likelihood42.68986 F-statistic77.07599Durbin-Watson stat0.939435 Prob(F-statistic)0.000000LnY與LnX2Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:16Sample: 1983 2007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LNX2-0.3834340.509669-

22、0.7523210.4595C15.157485.9129712.5634290.0174R-squared0.024017 Mean dependent var10.70905Adjusted R-squared-0.018417 S.D. dependent var0.093396S.E. of regression0.094252 Akaike info criterion-1.809063Sum squared resid0.204321 Schwarz criterion-1.711553Log likelihood24.61329 F-statistic0.565986Durbin

23、-Watson stat0.335219 Prob(F-statistic)0.459489LnY與LnX3Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:18Sample: 1983 2007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LNX30.1080670.0852711.2673350.2177C9.6197220.85974411.189050.0000R-squared0.065274 Mean

24、dependent var10.70905Adjusted R-squared0.024634 S.D. dependent var0.093396S.E. of regression0.092239 Akaike info criterion-1.852255Sum squared resid0.195684 Schwarz criterion-1.754745Log likelihood25.15319 F-statistic1.606139Durbin-Watson stat0.597749 Prob(F-statistic)0.217717LnY與LnX4Dependent Varia

25、ble: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:18Sample: 1983 2007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LNX40.1669760.0282745.9056700.0000C8.9490900.29825530.004790.0000R-squared0.602605 Mean dependent var10.70905Adjusted R-squared0.585327 S.D. dependent var0.0

26、93396S.E. of regression0.060143 Akaike info criterion-2.707578Sum squared resid0.083194 Schwarz criterion-2.610068Log likelihood35.84472 F-statistic34.87693Durbin-Watson stat0.625528 Prob(F-statistic)0.000005LnY與LnX5Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:19Sample: 1983 2

27、007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LNX50.4887310.2346062.0831990.0485C5.6007492.4522072.2839620.0319R-squared0.158733 Mean dependent var10.70905Adjusted R-squared0.122156 S.D. dependent var0.093396S.E. of regression0.087506 Akaike info criterion-1.957599Sum squ

28、ared resid0.176118 Schwarz criterion-1.860089Log likelihood26.46999 F-statistic4.339718Durbin-Watson stat0.327932 Prob(F-statistic)0.048538比較各個回歸方程的R2可知Y與X1的R2最大，即糧食生產受農業(yè)化肥施用量最大，與經驗相符，因此選為初始的回歸方程。且初始化回歸方程為：LOG(Y) = 0.224004867873*LOG(X1) + 8.90200821784R2 = 0.770175 D.W.= 0.9394354、逐步回歸LnY與LnX1Depen

29、dent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:28Sample: 1983 2007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LNX10.2240050.0255158.7792930.0000C8.9020080.20603443.206570.0000R-squared0.770175 Mean dependent var10.70905Adjusted R-squared0.760182 S.D. depend

30、ent var0.093396S.E. of regression0.045737 Akaike info criterion-3.255189Sum squared resid0.048114 Schwarz criterion-3.157679Log likelihood42.68986 F-statistic77.07599Durbin-Watson stat0.939435 Prob(F-statistic)0.000000LnY與LnX1、LnX2Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:2

31、9Sample: 1983 2007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LNX10.2978540.01548219.239290.0000LNX21.2586220.1500668.3871270.0000C-6.2956821.814941-3.4688090.0022R-squared0.945246 Mean dependent var10.70905Adjusted R-squared0.940269 S.D. dependent var0.093396S.E. of regre

32、ssion0.022826 Akaike info criterion-4.609666Sum squared resid0.011463 Schwarz criterion-4.463401Log likelihood60.62083 F-statistic189.9002Durbin-Watson stat1.595748 Prob(F-statistic)0.000000由輸出結果可知R2有所提高，且各解釋變量前得參數(shù)均通過t檢驗，符號也合理。D.W.檢驗也表明不存在一階自相關?？梢钥紤]再此模型上繼續(xù)引入X3。LnY與LnX1、LnX2、LnX3Dependent Variable: L

33、NYMethod: Least SquaresDate: 12/11/14 Time: 15:30Sample: 1983 2007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LNX10.3233850.01086129.775520.0000LNX21.2907290.09615313.423650.0000LNX3-0.0867540.015155-5.7244840.0000C-5.9996381.162078-5.1628520.0000R-squared0.978616 Mean dep

34、endent var10.70905Adjusted R-squared0.975561 S.D. dependent var0.093396S.E. of regression0.014601 Akaike info criterion-5.469854Sum squared resid0.004477 Schwarz criterion-5.274834Log likelihood72.37318 F-statistic320.3438Durbin-Watson stat1.412883 Prob(F-statistic)0.000000由輸出結果可知R2再次提高且參數(shù)符號合理，變量通過t

35、檢驗。但是D.W.=1.419（dL=1.12、dU=1.66）落入無法判斷的區(qū)域，且X4的參數(shù)沒有通過t檢驗。LM檢驗Breusch-Godfrey Serial Correlation LM Test:F-statistic1.241319 Probability0.278428Obs*R-squared1.460972 Probability0.226776Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 12/11/14 Time: 15:43VariableCoefficientStd. Errort-

36、StatisticProb. LNX10.0024030.0110120.2182250.8295LNX20.0069520.0958090.0725610.9429LNX3-0.0054780.015850-0.3455890.7333C-0.0447291.156156-0.0386880.9695RESID(-1)0.2574590.2310821.1141450.2784R-squared0.058439 Mean dependent var1.07E-16Adjusted R-squared-0.129873 S.D. dependent var0.013658S.E. of reg

37、ression0.014517 Akaike info criterion-5.450070Sum squared resid0.004215 Schwarz criterion-5.206295Log likelihood73.12588 F-statistic0.310330Durbin-Watson stat1.794969 Prob(F-statistic)0.867655LM檢驗顯示不存在一階自相關，繼續(xù)引入X4。LnY與LnX1、LnX2、LnX3、LnX4Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time

38、: 15:32Sample: 1983 2007Included observations: 25VariableCoefficientStd. Errort-StatisticProb. LNX10.3220610.0391618.2239570.0000LNX21.2940010.1353689.5591170.0000LNX3-0.0866650.015730-5.5095090.0000LNX40.0013030.0369720.0352510.9722C-6.0415541.682783-3.5902150.0018R-squared0.978617 Mean dependent v

39、ar10.70905Adjusted R-squared0.974341 S.D. dependent var0.093396S.E. of regression0.014961 Akaike info criterion-5.389916Sum squared resid0.004476 Schwarz criterion-5.146141Log likelihood72.37395 F-statistic228.8316Durbin-Watson stat1.413284 Prob(F-statistic)0.000000由輸出結果可知R2有所下降，且X4的參數(shù)未能通過t檢驗。去掉X4引入X5。LnY與LnX1、LnX2、LnX3、LnX5Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:33Sample: 1983 2007Included obse