Eviews實(shí)驗(yàn)報(bào)告

1、江西農(nóng)業(yè)大學(xué)經(jīng)濟(jì)貿(mào)易學(xué)院學(xué) 生 實(shí) 驗(yàn) 報(bào) 告課程名稱： 計(jì)量經(jīng)濟(jì)學(xué) 專業(yè)班級： 經(jīng)濟(jì)1201班姓 名： 學(xué) 號： 指導(dǎo)教師： 徐冬梅 職稱： 講師 實(shí)驗(yàn)日期： 2014.12.11 學(xué)生實(shí)驗(yàn)報(bào)告學(xué)生姓名學(xué)號組員：實(shí)驗(yàn)項(xiàng)目EVIEWS的使用必修 選修 演示性實(shí)驗(yàn) 驗(yàn)證性實(shí)驗(yàn) 操作性實(shí)驗(yàn) 綜合性實(shí)驗(yàn)實(shí)驗(yàn)地點(diǎn)管理模擬實(shí)驗(yàn)室實(shí)驗(yàn)儀器臺號指導(dǎo)教師實(shí)驗(yàn)日期及節(jié)次一、實(shí)驗(yàn)?zāi)康募耙?、目的會使用EVIEWS對計(jì)量經(jīng)濟(jì)模型進(jìn)行分析2、內(nèi)容及要求（1）對經(jīng)典線形回歸模型進(jìn)行參數(shù)估計(jì)、參數(shù)的檢驗(yàn)與區(qū)間估計(jì)，對模型總體進(jìn)行顯著性檢驗(yàn)；（2）異方差的檢驗(yàn)及其處理；（3）自相關(guān)的檢驗(yàn)及其處理；（4）多重共線性檢驗(yàn)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(jì)算機(jī)1無網(wǎng)絡(luò)環(huán)境Eviews1三、實(shí)驗(yàn)方法與步驟(一)數(shù)據(jù)的輸入、描述及其圖形處理；(二)方程的估計(jì)；(三)參數(shù)的檢驗(yàn)、違背經(jīng)典假定的檢驗(yàn)；(四)模型的處理與預(yù)測四、實(shí)驗(yàn)結(jié)果與數(shù)據(jù)處理實(shí)驗(yàn)一：中國城鎮(zhèn)居民人均消費(fèi)支出模型數(shù)據(jù)散點(diǎn)圖：通過Eviews估計(jì)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(jì)方程為：Y = 1.35947661442*X - 57.9065479515異方差檢驗(yàn)1、 圖示檢驗(yàn)法 圖形呈現(xiàn)離散趨勢，大致判斷存在異方差性。2、 Park檢驗(yàn)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(yàn)e1檢驗(yàn)：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(yàn)：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(gè)圖中的殘差平方和為848840.2第二個(gè)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(yàn)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(yàn)得知除了圖示檢驗(yàn)法得出異方差的結(jié)論，其他的檢驗(yàn)的結(jié)論都是不存在異方差的。5、 WLS（加權(quán)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(shí)驗(yàn)二：中國糧食生產(chǎn)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(yàn)結(jié)果可知 R2 較大且接近于1，而且F=202.6826 > F0.05(5,19) = 2.74，故認(rèn)為糧食產(chǎn)量與上述變量之間總體線性關(guān)系顯著。但是由于其中X4、X5前的參數(shù)估計(jì)值未通過t檢驗(yàn)，且符號的經(jīng)濟(jì)意義不合理，故認(rèn)為解釋變量之間存在多重共線。2、相關(guān)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(guān)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(gè)回歸方程的R2可知Y與X1的R2最大，即糧食生產(chǎn)受農(nóng)業(yè)化肥施用量最大，與經(jīng)驗(yàn)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(jié)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(yàn)，符號也合理。D.W.檢驗(yàn)也表明不存在一階自相關(guān)。可以考慮再此模型上繼續(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(jié)果可知R2再次提高且參數(shù)符號合理，變量通過t

35、檢驗(yàn)。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(yàn)。LM檢驗(yàn)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(yàn)顯示不存在一階自相關(guān)，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(jié)果可知R2有所下降，且X4的參數(shù)未能通過t檢驗(yàn)。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