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(jí)：經(jīng)濟(jì)1201班姓 名：學(xué) 號(hào)：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(hào)組員：實(shí)驗(yàn)項(xiàng)目EVIEWS勺使用日必修口選修日演示性實(shí)驗(yàn) R驗(yàn)證性實(shí)驗(yàn)口操作性實(shí)驗(yàn)口綜合性實(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(tái)號(hào)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(huì)使用EVIEWS寸計(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)及其處理；二、儀器用具儀器名

2、稱規(guī)格/型號(hào)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25000 20000 -:»*Y 15000 -） *10000 - 1 噂*5000 -I11116000800010000 12000 14000 16000X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)支由模型數(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:

3、02Sample: 1 31Included observations: 31VariableCoefficien Std. Error t-StatisticProb.1.3594770.04330231.395250.0000-57.90655377.7595-0.1532890.8792R-squared0.971419Mean dependent var11363.6915000001000000500000Adjusted R-squared0.970433S.D. dependent var3294.4690 6000800010000 12000 14000 16000XS.E.

4、 of regression566.4812Akaike info15.57911criterionSum squared resid9306127.Schwarz criterion15.67162Log likelihood-239.4761F-statistic985.6616Durbin-Watson stat1.294974Prob(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(

5、E2)Method: Least SquaresDate: 11/27/14 Time: 16:16Sample: 1 31Included observations: 31VariableCoefficienStd. Error t-StatisticProb.CLOG(X)19.82562-0.95640319.853590.9985912.204080-0.4339240.32630.6676R-squared0.006451Mean dependent var11.21371Adjusted R-squared-0.027809S.D.dependent var2.894595S.E.

6、 of regression2.934568Akaike info5.053338criterionSum squared resid249.7389Schwarz criterion5.145854Log likelihood-76.32674F-statistic0.188290Durbin-Watson stat2.456500Prob(F-statistic)0.667555看到圖中LOG(E2沖P值為0.6676 > 0.05，所以不存在異方差性3、G-Q檢驗(yàn)ei檢驗(yàn)：Dependent Variable: XMethod: Least SquaresDate: 11/27/1

7、4 Time: 16:41Sample: 1 12Included observations: 12VariableCoefficientStd. Error t-StatisticProb.C4642.0282014.1832.3046710.0439Y0.2310460.2158241.0705300.3095R-squared0.102820Mean dependent var6796.390Adjusted R-squared0.013102S.D.dependent var293.2762S.E. of regression291.3486Akaike info14.33793cri

8、terionSum squared resid848840.2Schwarz criterion14.41875Log likelihood-84.02758F-statistic1.146034Durbin-Watson stat0.445146Prob(F-statistic)0.309538e2檢驗(yàn)：Dependent Variable: X Method: Least SquaresDate: 11/27/14 Time: 16:42Sample: 20 31Included observations: 12VariableCoefficientStd. Error t-Statist

9、icProb.C583.4526593.43700.9831750.3487Y0.6977480.04019617.358700.0000R-squared0.967879Mean dependent var10586.89Adjusted R-squared0.964667S.D.dependent var2610.864S.E. of regression490.7655Akaike info15.38082criterionSum squared resid2408507.Schwarz criterion15.46164Log likelihood-90.28493F-statisti

10、c301.3245Durbin-Watson stat2.748144Prob(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 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-statistic2.240402Probability0.125152Obs*R-squared4.276524Probability0.117860Test Equation:Dependent Variabl

11、e: RESIDA2Method: Least SquaresDate: 11/27/14 Time: 16:50Sample: 1 31Included observations: 31VariableCoefficientStd. Error t-StatisticProb.C-2135113.1158576.-1.8428760.0760X503.7331242.20782.0797560.0468XA2-0.0236090.011650-2.0265900.0523R-squared0.137952Mean dependent var300197.6Adjusted R-squared

12、0.076378S.D.dependent var347663.4S.E. of regression334122.9Akaike info28.36817criterionSum squared resid3.13E+12Schwarz criterion28.50694Log likelihood-436.7067F-statistic2.240402Durbin-Watson stat1.871252Prob(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

13、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: 17:14Sample: 1 31Included observations: 31Weighting series: E3VariableCoefficientStd. Error t-StatisticProb.C-85.6942624.15675-3.5474250.0013X1.3622210.002307590.56150.0000Weighted StatisticsR-squared1.000000Mean dep

14、endent var13474.53Adjusted R-squared1.000000S.D.dependent var61353.74S.E. of regression27.93264Akaike info9.559810criterionSum squared resid22626.73Schwarz criterion9.652325Log likelihood-146.1770F-statistic348762.9Durbin-Watson stat2.061818Prob(F-statistic)0.000000UnweightedStatisticsR-squared0.971

15、413Mean dependent var11363.69Adjusted R-squared0.970427S.D.dependent var3294.469S.E. of regression566.5415Sum 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: 25VariableCo

16、efficien Std. Error t-StatisticProb.LOG(X1)0.3811450.0502427.5861820.0000LOG(X2)1.2222890.1351799.0420300.0000LOG(X3)-0.0811100.015304-5.3000240.0000LOG(X4)-0.0472290.044767-1.0549800.3047LOG(X5)C-0.101174-4.1731740.057687-1.7538531.923624-2.1694340.09560.0429R-squared0.981597Mean dependent var10.70

17、905Adjusted R-squared0.976753S.D.dependent var0.093396S.E. of regression0.014240Akaike info-5.459968criterionSum squared resid0.003853Schwarz criterion-5.167438Log likelihood74.24960F-statistic202.6826Durbin-Watson stat1.791427Prob(F-statistic)0.000000得出回歸方程為:LOG(Y) = 0.381144581612*LOG(X1) + 1.2222

18、8859801*LOG(X2) - 0.0811098881534*LOG(X3) -0.04722870996*LOG(X4) - 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 閂。5（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X、X5前的參數(shù)估計(jì)值未通過t檢驗(yàn)，且符號(hào)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LNX1LNX2LNX3LNX4LNX5LNX11.000000-0.5687440.4517000.9643570.4402

19、05LNX2-0.5687441.000000-0.214097-0.697625-0.073270LNX30.451700-0.2140971.0000000.3987800.411279LNX40.964357-0.6976250.3987801.0000000.279528LNX50.440205-0.0732700.4112790.2795281.000000由表可知LnX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 LnXDependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:15Sam

20、ple: 1983 2007Included observations: 25VariableCoefficientStd. Error t-StatisticProb.LNX10.2240050.0255158.7792930.0000C8.9020080.20603443.206570.0000R-squared0.770175Mean dependent var10.70905Adjusted R-squared0.760182S.D.dependent var0.093396S.E. of regression0.045737Akaike info-3.255189criterionS

21、um squared resid0.048114Schwarz criterion-3.157679Log likelihood42.68986F-statistic77.07599Durbin-Watson stat0.939435Prob(F-statistic)0.000000LnY 與 LnXDependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:16Sample: 1983 2007Included observations: 25VariableCoefficientStd. Error t-Stati

22、sticProb.LNX2-0.3834340.509669-0.7523210.4595C15.157485.9129712.5634290.0174R-squared0.024017Mean dependent var10.70905Adjusted R-squared-0.018417S.D.dependent var0.093396S.E. of regression0.094252Akaike info-1.809063criterionSum squared resid0.204321Schwarz criterion-1.711553Log likelihood24.61329F

23、-statistic0.565986Durbin-Watson stat0.335219Prob(F-statistic)0.459489LnY 與 LnX3Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:18Sample: 1983 2007Included observations: 25VariableCoefficientStd. Error t-StatisticProb.LNX30.1080670.0852711.2673350.2177C9.6197220.85974411.189050.00

24、00R-squared0.065274Mean dependent var10.70905Adjusted R-squared0.024634S.D.dependent var0.093396S.E. of regression0.092239Akaike info-1.852255criterionSum squared resid0.195684Schwarz criterion-1.754745Log likelihood25.15319F-statistic1.606139Durbin-Watson stat0.597749Prob(F-statistic)0.217717LnY 與

25、LnX4Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:18Sample: 1983 2007Included observations: 25VariableCoefficientStd. Error t-StatisticProb.LNX40.1669760.0282745.9056700.0000C8.9490900.29825530.004790.0000R-squared0.602605Mean dependent var10.70905Adjusted R-squared0.585327S.D.

26、dependent var0.093396S.E. of regression0.060143Akaike info-2.707578criterionSum squared resid0.083194Schwarz criterion-2.610068Log likelihood35.84472F-statistic34.87693Durbin-Watson stat0.625528 Prob(F-statistic)0.000005LnY 與 LnX5Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:19

27、Sample: 1983 2007Included observations: 25VariableCoefficientStd. Error t-StatisticProb.LNX50.4887310.2346062.0831990.0485C5.6007492.4522072.2839620.0319R-squared0.158733Mean dependent var10.70905Adjusted R-squared0.122156S.D.dependent var0.093396S.E. of regression0.087506Akaike info-1.957599criteri

28、onSum squared resid0.176118Schwarz criterion-1.860089Log likelihood26.46999F-statistic4.339718Durbin-Watson stat0.327932Prob(F-statistic)0.048538比較各個(gè)回歸方程的R2可知Y與X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 = 0.770175D.W. = 0.9394354、逐步回歸LnY 與 Ln

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

30、endent var0.093396S.E. of regression0.045737Akaike info-3.255189criterionSum squared resid0.048114Schwarz criterion-3.157679Log likelihood42.68986F-statistic77.07599Durbin-Watson stat0.939435Prob(F-statistic)0.000000LnY與 LnX、Ln%Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:29Sa

31、mple: 1983 2007Included observations: 25VariableCoefficientStd. Error t-StatisticProb.LNX10.2978540.01548219.239290.0000LNX21.2586220.1500668.3871270.0000C-6.2956821.814941-3.4688090.0022R-squared0.945246Mean dependent var10.70905Adjusted R-squared0.940269S.D.dependent var0.093396S.E. of regression0

32、.022826Akaike info-4.609666Sum squared resid0.011463 Schwarz criterion-4.463401Log likelihood60.62083F-statistic189.9002Durbin-Watson stat1.595748Prob(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(hào)也合理D.W.檢驗(yàn)也表明不存在一階自相關(guān)?？梢钥紤]再此模型上繼續(xù)引入X3。LnY 與 LnX、Ln%、LnXDependent Variable: LNYMethod: Least Squar

33、esDate: 12/11/14 Time: 15:30Sample: 1983 2007Included observations: 25VariableCoefficien Std. Error t-StatisticProb.LNX10.3233850.01086129.775520.0000LNX21.2907290.09615313.423650.0000LNX3-0.0867540.015155-5.7244840.0000C-5.9996381.162078-5.1628520.0000R-squared0.978616Mean dependent var10.70905Adju

34、sted R-squared0.975561S.D.dependent var0.093396S.E. of regression0.014601Akaike info-5.469854criterionSum squared resid0.004477Schwarz criterion-5.274834Log likelihood72.37318F-statistic320.3438Durbin-Watson stat1.412883Prob(F-statistic)0.000000由輸出結(jié)果可知R2再次提高且參數(shù)符號(hào)合理，變量通過t檢驗(yàn)。但是D.W.=1.419（a=1.12、dU=1.6

35、6）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-statistic1.241319Probability0.278428Obs*R-squared1.460972Probability0.226776Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 12/11/14 Time: 15:43VariableCoefficien Std. Error t-StatisticProb.LNX10.0024030.01

36、10120.2182250.8295LNX20.0069520.0958090.0725610.9429LNX3-0.0054780.015850-0.3455890.7333C-0.0447291.156156-0.0386880.9695RESID(-1)0.2574590.2310821.1141450.2784R-squared0.058439Mean dependent var1.07E-16Adjusted R-squared-0.129873S.D.dependent var0.013658S.E. of regression0.014517Akaike info-5.45007

37、0criterionSum squared resid0.004215Schwarz criterion-5.206295Log likelihood73.12588F-statistic0.310330Durbin-Watson stat1.794969Prob(F-statistic)0.867655LM檢驗(yàn)顯示不存在一階自相關(guān)，繼續(xù)引入 XLnY 與 LnX、Ln%、LnX、LnX4Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:32Sample: 1983 2007Included observat

38、ions: 25VariableCoefficientStd. Error t-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-squared0.978617Mean dependent var10.70905Adjusted R-squared0.974341S.D.de

39、pendent var0.093396S.E. of regression0.014961Akaike info-5.389916Sum squared resid0.004476Schwarz criterionLog likelihood72.37395F-statisticDurbin-Watson stat1.413284Prob(F-statistic)criterion-5.146141228.83160.0000002 .由輸出結(jié)果可知R有所下降，且X4的參數(shù)未能通過t檢驗(yàn)。去掉X4引入X5LnY 與 LnX1、LnX2、LnK、LnX5Dependent Variable: LNYMethod: Least SquaresDate: 12/11/14 Time: 15:33Sample: 1983 2007Included observations: 2