實驗十分布滯后模型

1、實驗九分布滯后模型【實驗?zāi)康摹空莆辗植紲竽Ｐ偷慕⒑凸烙嫛緦嶒瀮?nèi)容】表9.1給出了中國電力行業(yè)基本建設(shè)投資X與發(fā)電量Y的相關(guān)資料，擬建立 一多項式分布滯后模型來考察兩者的關(guān)系。表9.1中國電力行業(yè)基本建設(shè)投資與發(fā)電量年份基本建設(shè)投發(fā)電量（億千年份基本建設(shè)投發(fā)電量（億千資（億元）X瓦時）Y資（億元）X瓦時）Y197530.6519581986161.64495197639.9820311987210.884973197734.7222341988249.735452197850.9125661989267.855848197950.9928201990334.556212198048.1430

2、061991377.756775198140.1430931992489.697539198246.2332771993675.138395198357.46351419941033.429218198476.99377019951124.15100701985107.864107由于無法預(yù)知電力行業(yè)基本建設(shè)投資對發(fā)電量影響的時滯期，需取不同的滯后期試算。經(jīng)過試算發(fā)現(xiàn)，在2階阿爾蒙多項式變換下，滯后期數(shù)取到第6期， 估計結(jié)果的經(jīng)濟意義比較合理。估計過程如下：輸出結(jié)果如下：Dependent Variable: Y Method: Least Squares Date: 07/04/00 Tim

3、e: 16:14 Sample (adjusted): 1981 1995Included observations: 15 after adjustmentsVariableCoefficientStd. Error t-StatisticProb.C3319.534243.746313.610010.0000PDU013.0611091.6437691.8622500.0895PDU020.1006950.6932920.1452420.8871PDU03-0.2706400.404731-0.6687100.5175R-squared0.953279Vlean dependent var

4、5702.533Adjusted R-squared0.940537S.D. dependent var2223.354S.E. of regression542.1650 Akaike info criterion15.65220Sum squared resid3233381.Schwarz criterion15.84101Log likelihood-113.3915-statistic74.81340Durbin-Watson stat0.422552mbIF-statistic)0.000000Lag Distribution of XiCoefficientStd. Errort

5、-Statistic100.323201.737240.18604111.777130.831282.13701122.689771.432441.87775i33.061111.643771.862251J42.891161.474461.96002152.179911.982981.0993160.927373.920710.23653Sum of Lags13.84964.365903.17223輸出結(jié)果的下邊部分給出了分布滯后模型的各滯后期的參數(shù)。最后得到分布滯后模型估計式為：Y = 3319.5 + 0.323X +1.777X + 2.69X + 3.061X + 2.891X +

6、 2.18X + 0.927 Xttt1t2t3t4t5t6(13.62) (0.19)(2.14)(1.88)(1.86)(1.96)(1.1)(0.24)表5.3給出了中國1978-2000年按當年價測度的GDP與居民消費CONS數(shù) 據(jù)，檢驗兩者的因果關(guān)系。表5.3中國GDP與消費支出單位：億元年份CONSGDP年份CONSGDP19781759.1003605.60019909113.20018319.5019792005.4004074.000199110315.9021280.4019802317.1004551.300199212459.8025863.7019812604.100

7、4901.400199315682.4034500.7019822867.9005489.200199420809.8046690.7019833182.5006076.300199526944.5058510.5019843674.5007164.400199632152.3068330.4019854589.0008792.100199734854.6074894.2019865175.00010132.80199836921.1079003.3019875961.20011784.70199939334.4082673.1019887633.10014704.00200042911.90

8、89112.5019898523.50016466.00取兩階滯后，過程如下:SEViews日回國File Edi + Ubj ect Vi ew Froc quick Oiti ore jVindow HelpS：dJTiple.GerLerate Seri es.Shu,ili,.Cj-rap hL： consresid Ernjity Group Edit Series)Series StatisticsGrout Stati sti csEstimate Equation.Estimate VAR.| Untitled X New Page / CONSF a th = c: docu

9、irientE :and e e 11 i ngs zhuy i x i my docuiriHntEHB = nijrieWF = untitled輸入要檢驗的變量。輸入滯后階數(shù)。輸出結(jié)果如下：Pairwise Granger Causality TestsDate: 07/04/08 Time: 16:37Sample: 1978 2000Lags: 2Null Hypothesis:ObsF-StatisticProbabilityGDP does not Granger Cause CONS CONS does not Granger Cause GDP214.297491.82325

10、0.03208D.193 即從上面的輸出結(jié)果可以看出，根據(jù)伴隨概率值知道，在5%的顯著水平下: 拒絕GDP不是CONS的格蘭杰檢驗，即GDP是CONS的格蘭杰檢驗。 接受CONS不是GDP的格蘭杰檢驗。已知1970-1991年美國制造業(yè)固定廠房設(shè)備投資Y和銷售量X的相關(guān)數(shù)據(jù) 如表5.4所示。（1） 假定銷售量對廠房設(shè)備支出有一個分部滯后效應(yīng)，使用4期滯后和2次 多項式去估計此分布滯后模型。（2） 檢驗銷售量與廠房設(shè)備支出的Granger因果關(guān)系，使用直至6期為止的 滯后并評述結(jié)果。表5.4單位：10億美元年份廠房開支Y銷售額X年份廠房開支Y銷售額X197036.9952.8051981128.

11、68168.129197133.655.9061982123.97163.351197235.4263.0271983117.35172.547197342.3572.9311984139.61190.682197452.4884.791985152.88194.538197553.6686.5891986137.95194.657197668.5398.7971987141.06206.326197767.48113.2011988163.45223.547197878.13126.9051989183.8232.724197995.13143.9361990192.61239.459198

12、0112.6154.3911991182.81235.142估計分布滯后模型，過程如下:100.832420.189974.3818410.317420.097923.241512-0.011740.13431-0.087413-0.155060.09237-1.67865 i4-0.112530.19627-0.57334Lag Distribution of XSum of Lags 0.870520.0327226.6025估計結(jié)果如下:Dependent Variable: YMethod: Least SquaresDate: 07/04/08 Time: 19:33Sample (

13、adjusted): 1974 1991Included observations: 18 after adjustmentsVariableCoefficientStd. Errort-StatisticProb.C-30.825548.916420-3.4571660.0038PDU01-0.0117400.134307-0.0874100.9316PDU02-0.2362370.067956-3.4763120.0037PDU030.0929210.0678101.3703170.1922R-squared0.981227Mean dependent var1217878Adjusted

14、 R-squared0.977204S.D. dependent var44.87987S.E. of regression6.776057Akaike info criterion6.857798Sum squared resid642.8093Schwarz criterion7.055658Log likelihood-57.72018F-statistic243.9194Durbin-Watson stat1.358472Prob(F-statistic)0.000000i Coefficient Std. Error t-Statistic對應(yīng)的分布滯后模型的表達式為:Y =30.8

15、3 + 0.83X + 0.32X 1 -0.01X 2-0.16X 3-0.11X 4做格蘭杰檢驗，以一階滯后為例，過程如下:結(jié)果如下:Pairwise Granger Causality TestsDate: 07/04/08 Time: 19:44Sample: 1970 1991Lags: 1Null Hypothesis:ObsF-StatisticProbabilityX does not Granger Cause Y2131.90612.3E-05Y does not Granger Cause X23.83390.00012從上面F檢驗的伴隨概率值可以知道，X與Y互為因果關(guān)系

16、。按上述過程分別做從1直到6期滯后的Granger因果關(guān)系檢驗，結(jié)果分別如下:2階:Pairwise Granger Causality TestsDate: 07/04/08 Time: 19:48Sample: 1970 1991Lags: 2Null Hypothesis:ObsF-StatisticProbabilityY does not Granger Cause X X does not Granger Cause Y2013.165318.46840.000509.CIE-D53階:Paiiwise Granger Causality TestsDate: 07/04/08 T

17、ime: 19:49Sample: 1970 1991Lags: 3Null Hypothesis:ObsF-StatisticProbabilityY does not Granger Cause X197.190290.00509X does not Granger Cause Y6.161960.008874階:Pairwise Granger Causality TestsDate: 07/04/08 Time: 19:50Sample: 1970 1991Lags: 4Null Hypothesis:ObsF-StatisticProbabilityY does not Granger Cause X X does not Granger Cause Y184.446783.717610.02946D.D4T195階:Pairwise Granger Causality TestsDate: 07/04/08 Time: 19:51Sample: 1970 1991Lags: 5Null Hypothesis:ObsF-StatisticProbabilityY does not Granger Cause X X does not Granger Cause Y172.772972.280540.123270.171246階:Paiiwise Gra