计量课后习题第六章.docx

1、计量课后习题第六章6.1Dependent Variable: YMethod: Least SquaresDate: 06/09/15 Time: 15:54Sample: 1 19Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C79.9300412.399196.4463900.0000X0.6904880.01287753.620680.0000R-squared0.994122Mean dependent var700.2747Adjusted R-squared0.993776S.D. de

2、pendent var246.4491S.E. of regression19.44245Akaike info criterion8.872095Sum squared resid6426.149Schwarz criterion8.971510Log likelihood-82.28490Hannan-Quinn criter.8.888920F-statistic2875.178Durbin-Watson stat0.574663Prob(F-statistic)0.000000Y=0.690488x+79.93004Dw=0.574663 n=19 dl=1.18 du=1.401模型

3、存在自相关Dependent Variable: YMethod: Least SquaresDate: 06/09/15 Time: 16:02Sample (adjusted): 2 19Included observations: 18 after adjustmentsConvergence achieved after 5 iterationsVariableCoefficientStd. Errort-StatisticProb.C104.044923.876184.3576870.0006X0.6692620.02083132.127570.0000AR(1)0.6300150.

4、1642183.8364620.0016R-squared0.997097Mean dependent var719.1867Adjusted R-squared0.996710S.D. dependent var238.9866S.E. of regression13.70843Akaike info criterion8.224910Sum squared resid2818.814Schwarz criterion8.373306Log likelihood-71.02419Hannan-Quinn criter.8.245372F-statistic2575.896Durbin-Wat

5、son stat1.787878Prob(F-statistic)0.000000Inverted AR Roots.63DW=1.787878 可以判断在5%显著水平下广义差分法后模型中已无自相关。Y=104.0449+0.669262x,居民家庭收入每增加一元，平均说来人均实际消费支出将增加0.669262元。6.2Dependent Variable: YMethod: Least SquaresDate: 06/09/15 Time: 17:08Sample: 1985 2011Included observations: 27VariableCoefficientStd. Error

6、t-StatisticProb.C-1666.930555.8502-2.9988830.0061X0.2650280.01172122.611840.0000R-squared0.953384Mean dependent var8522.312Adjusted R-squared0.951519S.D. dependent var7680.271S.E. of regression1691.069Akaike info criterion17.77530Sum squared resid71492818Schwarz criterion17.87128Log likelihood-237.9

7、665Hannan-Quinn criter.17.80384F-statistic511.2954Durbin-Watson stat0.601332Prob(F-statistic)0.000000y=-1666.930+0.265028x n=27 a=0.05 dl=1.316 du=1.469 dw=0.601332说明模型具有相关性。Dependent Variable: YMethod: Least SquaresDate: 06/09/15 Time: 17:09Sample (adjusted): 1986 2011Included observations: 26 afte

8、r adjustmentsConvergence achieved after 6 iterationsVariableCoefficientStd. Errort-StatisticProb.C-1632.8311445.298-1.1297540.2702X0.2609320.02477610.531830.0000AR(1)0.7018650.1517804.6242300.0001R-squared0.975284Mean dependent var8801.717Adjusted R-squared0.973135S.D. dependent var7691.158S.E. of r

9、egression1260.628Akaike info criterion17.22477Sum squared resid36551200Schwarz criterion17.36994Log likelihood-220.9221Hannan-Quinn criter.17.26658F-statistic453.7857Durbin-Watson stat1.654943Prob(F-statistic)0.000000Inverted AR Roots.70Y=-1632.831+0.260932x n=27 a=0.05 dl=1.316 du=1.469 dw=1.654943

10、可知在5%显著性水平下广义差分法模型中已无自相关。6.3Dependent Variable: YMethod: Least SquaresDate: 06/09/15 Time: 20:55Sample: 1981 2006Included observations: 26VariableCoefficientStd. Errort-StatisticProb.C-2123.864324.8012-6.5389660.0000X0.7841060.04127618.996800.0000R-squared0.937643Mean dependent var3604.775Adjusted R

11、-squared0.935044S.D. dependent var2414.000S.E. of regression615.2413Akaike info criterion15.75571Sum squared resid9084525.Schwarz criterion15.85249Log likelihood-202.8242Hannan-Quinn criter.15.78358F-statistic360.8784Durbin-Watson stat0.440822Prob(F-statistic)0.000000Y=-2123.864+0.784106X N=26 a=0.0

12、5 dl=1.302 du=1.461 dw=0.440822由此可知此模型存在自相关。Dependent Variable: YMethod: Least SquaresDate: 06/09/15 Time: 20:56Sample (adjusted): 1982 2006Included observations: 25 after adjustmentsConvergence achieved after 7 iterationsVariableCoefficientStd. Errort-StatisticProb.C-2914.2861192.273-2.4443110.0230

13、X0.8650500.1199837.2097630.0000AR(1)0.7870170.1327525.9284590.0000R-squared0.975002Mean dependent var3717.661Adjusted R-squared0.972730S.D. dependent var2392.713S.E. of regression395.1262Akaike info criterion14.90845Sum squared resid3434744.Schwarz criterion15.05472Log likelihood-183.3557Hannan-Quin

14、n criter.14.94902F-statistic429.0384Durbin-Watson stat0.912240Prob(F-statistic)0.000000Inverted AR Roots.79y=-2914.286+0.865050x N=26 a=0.05 dl=1.302 du=1.461 dw=0.9122406.46.51.葡萄酒价格的对数对hrain的回归Dependent Variable: YMethod: Least SquaresDate: 06/09/15 Time: 21:18Sample: 1 28Included observations: 28

15、VariableCoefficientStd. Errort-StatisticProb.C607.769963.269869.6059940.0000X7.66708841.511420.1846980.8549R-squared0.001310Mean dependent var597.1071Adjusted R-squared-0.037101S.D. dependent var134.5212S.E. of regression136.9939Akaike info criterion12.74650Sum squared resid487950.5Schwarz criterion

16、12.84166Log likelihood-176.4510Hannan-Quinn criter.12.77559F-statistic0.034113Durbin-Watson stat1.302665Prob(F-statistic)0.854899y=7.667088X+607.7699 r2=0.001310 a=0.05 dl=1.328 du=1.476 dw=1.302665模型中存在自相关。修正后：Dependent Variable: YMethod: Least SquaresDate: 06/09/15 Time: 21:40Sample (adjusted): 2

17、28Included observations: 27 after adjustmentsConvergence achieved after 7 iterationsVariableCoefficientStd. Errort-StatisticProb.C538.734072.143907.4674920.0000X-43.6110438.94329-1.1198600.2739AR(1)0.4656070.1907732.4406330.0224R-squared0.166824Mean dependent var597.0000Adjusted R-squared0.097393S.D

18、. dependent var137.0825S.E. of regression130.2361Akaike info criterion12.68101Sum squared resid407074.8Schwarz criterion12.82500Log likelihood-168.1937Hannan-Quinn criter.12.72383F-statistic2.402718Durbin-Watson stat1.783005Prob(F-statistic)0.111903Inverted AR Roots.47Y=-43.61104X+538.7340 a=0.05 DL

19、=1.316 DU=1.469 DW=1.783005此模型不具备自相关。2.葡萄酒价格的对数对wrain的回归Dependent Variable: Y1Method: Least SquaresDate: 06/09/15 Time: 21:57Sample: 1 28Included observations: 28VariableCoefficientStd. Errort-StatisticProb.C156.117282.389021.8948780.0693X-28.6009154.05552-0.5291030.6012R-squared0.010653Mean depende

20、nt var195.8929Adjusted R-squared-0.027399S.D. dependent var175.9965S.E. of regression178.3913Akaike info criterion13.27458Sum squared resid827409.7Schwarz criterion13.36974Log likelihood-183.8442Hannan-Quinn criter.13.30368F-statistic0.279950Durbin-Watson stat1.154326Prob(F-statistic)0.601223y=-28.6

21、0091x+156.1172 a=0.05 dl=1.328 du=1.476 dw=1.154326模型存在自相关修正后：Dependent Variable: Y1Method: Least SquaresDate: 06/09/15 Time: 22:01Sample (adjusted): 2 28Included observations: 27 after adjustmentsConvergence achieved after 9 iterationsVariableCoefficientStd. Errort-StatisticProb.C78.6216591.819880.

22、8562600.4003X-82.2661746.91906-1.7533640.0923AR(1)0.4957580.1785602.7764200.0105R-squared0.222035Mean dependent var197.2222Adjusted R-squared0.157204S.D. dependent var179.2058S.E. of regression164.5179Akaike info criterion13.14836Sum squared resid649587.5Schwarz criterion13.29234Log likelihood-174.5

23、028Hannan-Quinn criter.13.19117F-statistic3.424853Durbin-Watson stat1.730821Prob(F-statistic)0.049150Inverted AR Roots.50y=-82.26617x+78.62165 a=0.05 dl=1.316 du=1.469 dw=1.730821此模型不存在自相关。3.葡萄酒价格的对数对degrees的回归Dependent Variable: Y2Method: Least SquaresDate: 06/09/15 Time: 22:25Sample: 1 28Included observations: 28VariableCoefficientStd. Errort-StatisticProb.C17.177950.28221260.868870.0000X0.5403850.1851602.9184800.0072R-squared0.246759Mean dependent var16.42643Adjusted R-squared0.217789S.D. dependent var0.690905S.E. of regression0.611055Akaike info criterion1.921490S