Eviews实际案例：序列相关性

1、Eviews实际案例：序列相关性中国19802000年投资总额与匚业总产值资料年份全社会固定 资产投资X工业增加值Y年份全社会固定资产投资X工业增加 值 Y1980910. 91996.519915594. 58087. 11981961.02048. 419928080. 110284. 519821230. 42162.34 99313072.314143. 819831430 12375. 6199417042. 119359.619841832.92789. 0199520019.324718. 319852543. 23448. 7199622913.529082.619863120

2、. 63967. 0199724941.132412. 119873791.74585. 8199828854. 733087. 219884753. 85777. 2199929854. 735087.219894410. 46484.0200032917.739570. 319904517.06858. 0一、当设定模型为lnX=0o + AhiXt+"时，序列相关性检验 步骤：1. 将数据输入Eviews2. 在建立公式中输入“log(y)clog(x)”3. 得到结果Dependent Variable: LOG(Y) Method: Least Squares Date:

3、05/14/12 Time: 20:15 Sample: 1980 2000Inc luded observatio ns: 21CoefficientStd. Erort-SiafisticProb.c1.4613140.1903217.6781440.0000LOG(X)0.8692380.02165640.138460.0000R-squared0.988344Mean dependentvar9030748Adjusted R-squared0.987731S.D. dependent var1 061708S.E. of regression0.117602Akaike info c

4、riterion-1.352635Sum squared resid0.262773Schwarz criteri on-1.253157Log likelihood16.20267Hannan-Quinn criter.-1.331046F-statistic1611.096Durbin-Watson stat0.472045Prob(F-statistic)0.000000结果显示：该回归方程的DW统计量的值为0.47。在5%的显著性水平下，样本容量为21的DW分布的下限临界值为。0.47小于1.22,则表明存在正的自相关。二、若按一阶自相关假设“ =PZ + 6 ,试用杜宾两步法和广义最

5、小二乘法估 计原模型(一)杜宾两步法第一步：1.估计模型为：lnX= plnX-i + AC1 - P)+ AOnXtPlnXt-i)或者In X = P In X_j + % (1 - p) + A 1【】呂 - A P In 心2.在 Eviews 中输入的公式：“ log(y) c log(y(-l) log(x) log(x(-l)w3.运行结果:Dependent Vanable: LOG(Y)Method: Least SquaresDate: 05/14/12 Time: 20:52Sample (adjusted): 1981 2000In eluded observatio

6、ns: 20 after adjustmentsCoefficientStd. Errort-StatisticProb.C0.4568710.1570642.9088170.0103L0G(YH)0 6278730.0874307.1814730.0000LOG(X)0.4657910 0799945.8228360.0000LOG 阳)-0.1247940.116974-1.0668570.3019R-squared0.998506Me an dependentv39.102328Adjusted R-squared0.998226S D. dependentvar1.035997S.E.

7、 of regression0.043633Akalke info criterio n-3.249153Sum squared resid0.030461Schwarz criten on3.050006Log likelihood36.49153Hannan-Quinn criter.-3 210277F-statistic3565.099Durbin-Watson stat1.119350Prob(F-statistic)0.000000得到佔计方程如卜：111Q = 0.4568 +0.6278111+0.4658111 斗-01248111斗_1(2.908) (7.1814)(5.

8、8228)(-1.0669) R2 = 0.9985第二步:1将估计的p = 0.6278代入差分模粘 得到广义模陽 进行eviews运行2输入公式为:ulog(y)-0.6278*log(y(-l) c log(x)-0.6278#log(x(-l)M3 运行结果：Dependent Vanable: LOG(Y>0.6278*LOG(Y(-1)> Method: Least SquaresDate: 05/14/12 Time: 21:23Sample (adjusted): 1981 2000Included observations: 20 合fter adjustment

9、sCoefficientStd. Errort-StatisticProb.C0.4256570.1301073.2715940.0042LOG(X>0.6278*LOG(X(-1)0.9017320.03809523.670850.0000R-squared0.968875Uoan dependentmr3.481639Adjusted R-squared0.967146S.D. dependent var0.397956S.E.of regression0.072133Aka ike info criterion2325982Sum squared resid0.093656Schw

10、arz criterion-2.226408Log likelihood25.25982Han nan-Qum n crter.-2.306544F-statistic560.3093Durbin-Watson stat1.393141Prob(F-statistic)0.000000最小二乘估计结果为:ln 一 0.6278111= 0.4257 + 0.9017(ln 斗 一 0.6278111 口)(3.272 )(23.671) D.W. =1.393由于D.W.4393,在5%的显著性水平下,样本容最为19的D.W检验的临界值为I：卜限为dL=1.18, *=140,检验值落在(,*

11、)上.故不能确定是否存在一阶序列相关。根据 LM 法进行检验。在 eviews 输出结果後fl I选择44ViewResidual TestsSeries Correlation LM Test"，在随后出现的对话框屮填入滞后期数V笃得到：Breusch-Godfrey Serial Correlation LM TestF-statistic1.131572Prob. F(117)0.3023Obs-squared1.248282Prob. Chi-Squared)0.2639检验统计彊值为1248.査询7?分布，Z2005(l) = 3.841- =2.59,检验伍小丁临界值,因

12、而不能拒绝原假设，认为模型不存在一阶序列相关。因此佔讣原模型为:0.42571-0.6278+ 0.9017111 4酔客天涯之计童经济学#酔客天涯之计童经济学gp： In* = 1.156+ 0.9017In 斗#酔客天涯之计童经济学(二)广义最小二乘法在 Eviews '1',选择 u QuickEstimate Equation M，输入 *log(y) c log(x) AR(1)AR表示随机干扰项是一阶自回归形式的序列相关。运行结果如F：Dependent Variable: LOG(Y) Method: Least Squares Date: 05/14/12 Ti

13、me: 22:24 Sample (adjusted): 1981 2000 In eluded observations: 20 after adjustments Convergence achieved after20 iterationsCoefficient Std. Error t-Statistic Prob.C1 1642330 4135682.8150970.0119L0G(X)0.8994470.04444820.235880.0000AR0.6451280.1517384.2515930.0005R-squared0.995321Mean dependent var910

14、2328Adjusted R-squared0.994771S.D. dependentvar1.035997S.E. of regressio n0.074916AKaike into criterion-2.207425Sum squared resid0.095410Schwarz criterion-2.058065Log likelihood25.07425HsnnarbQuinn enter.-2.178268F-statistic1808.248Durbin-Watso n stat1.407464Prob(F-statistic)0.000000Inverted AR Root

15、s.65根据LM法进 行检验。在 eviews 输出结果窗 I I选择 ° ViewResidual TestsSeries Correlation LM Test"，在随 后出现的对话框屮填入滞后期数得到：Breusch-Godfrey Serial Correlation LU TestF-statistic1.707900Prob.F(1J6)0.2097ObsrR-squared1.928969Prob. Chi-Squared)0.1649同上，町以判定模型随机干扰项中不再存在一阶序列相关，因而广义最小二乘估计结果为：In X = 1.164 + 0.899411

16、1 斗 + 0.6451 AR 三、天用差分形芬与¥>¥-百作为新数据，估计模型 ¥>內+ qX； + .该模型是否存在序列相关选择u QuickEstimate Equation °，在出现的对话框中输入“D(Y)C D(X)”,其 中D(Y)与D(X)分别表示对序列Y与X取差分。得到运行结果如下；Dependent Variable: D(Y)Method: Least SquaresDate: 05/14/12 Time: 22:40Sample (adjusted): 1981 2000Included observations: 20 after adjustmentsCoefficientStd. Errort-StatisticProb.C411.0327384.80721.0681520.2996D(X)0.9180280 1741135.2725910.0001R-squared0606989I伽n dependent var1880.190Adjisted R-squared0585155S.D. dependent var1842.763S.E. of regressio n1186.896Akaike info