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1、第二章2.2(1) 对于浙江省预算收入与全省生产总值的模型,用Eviews分析结果如下:Depe ndent Variable: YMethod: Least SquaresDate: 12/03/14 Time: 17:00Sample (adjusted): 1 33In cluded observati ons: 33 after adjustme ntsCoefficieProb.Variablent Std. Error t-StatisticX0.1761240.004072 43.256390.0000-154.306C339.08196 -3.9482740.0004Mean
2、depe ndent902.514R-squared0.983702var8AdjustedS.D. dependent1351.00R-squared0.983177var9S.E. ofAkaike info13.2288regressi on175.2325criterio n0Sum squared13.3194resid951899.7Schwarz criterio n9-216.275Hannan-Qu inn13.2593Log likelihood1 criter.1Durbi n-Wats on0.10002F-statistic1871.115stat1Prob(F-st
3、atistic)0.000000由上可知,模型的参数:斜率系数0.176124,截距为一154.3063 关于浙江省财政预算收入与全省生产总值的模型,检验模型的显著性:1) 可决系数为0.983702,说明所建模型整体上对样本数据拟合较好。2) 对于回归系数的t检验:t (B 2) =43.25639>t 0.025 (31)=2.0395,对斜率系数的显著性 检验说明,全省生产总值对财政预算总收入有显著影响。 用标准形式写出检验结果如下:Y =0.176124X 154.3063(0.004072)(39.08196)t= (43.25639)( -3.948274)R2=0.9837
4、02F=1871.115n=33 经济意义是:全省生产总值每增加1亿元,财政预算总收入增加0.176124亿元(2)当 x=32000 时,进行点预测,由上可知Y=0.176124X 154.3063,代入可得:Y= Y=0.176124*32000154.3063=5481.6617 进行区间预测:先由Eviews分析:XYMea n6000.441902.5148Media n2689.280209.3900Maximum27722.314895.410Minimum123.720025.87000Std. Dev.7608.0211351.009Skew ness1.4325191.66
5、3108Kurtosis4.0105154.590432Jarque-Ber a12.6906818.69063Probability0.0017550.000087Sum198014.529782.99Sum Sq. Dev.1.85E+09 ;58407195Observati on s3333由上表可知,_ - 2 _ . 2 2 2Ex =E( X X) =3 x (n 1)=7608.021 x (33 1)=1852223.473(Xf X)2=(32000 6000.441) 2=675977068.2当Xf=32000时,将相关数据代入计算得到:即 Yf 的置信区间为(5481
6、.6617 64.9649, 5481.6617+64.9649)(3)对于浙江省预算收入对数与全省生产总值对数的模型,由Eviews分析结果如下:Depe nde nt Variable: LN YMethod: Least SquaresDate: 12/03/14 Time: 18:00Sample (adjusted): 1 33In cluded observati ons: 33 after adjustme ntsCoefficieProb.Variablent Std. Error t-StatisticLNX0.9802750.034296 28.582680.0000-1.
7、91828C90.268213 -7.1521210.0000Mean depe ndent5.57312R-squared0.963442var0AdjustedS.D. dependent1.68418R-squared0.962263var9S.E. ofAkaike info0.66202regressi on0.327172criterio n8Sum squared0.75272resid3.318281Schwarz criterio n6-8.92346Hannan-Qu inn0.69254Log likelihood8 criter.5Durbi n-Wats on0.09
8、620F-statistic816.9699stat8Prob(F-statistic)0.000000模型方程为:InY二 0.980275In X-1.918289 由上可知,模型的参数:斜率系数为0.980275,截距为-1.918289 关于浙江省财政预算收入与全省生产总值的模型,检验其显著性:1) 可决系数为0.963442,说明所建模型整体上对样本数据拟合较好。2) 对于回归系数的t检验:t (B 2)=28.58268>t 0.025 (31)=2.0395,对斜率系数的显著性 检验说明,全省生产总值对财政预算总收入有显著影响。 经济意义:全省生产总值每增长1%,财政预算总
9、收入增长 0.980275%2.4(1) 对建筑面积与建造单位本钱模型,用Eviews分析结果如下:Depe ndent Variable: YMethod: Least SquaresDate: 12/01/14 Time: 12:40Sample: 1 12In eluded observati ons: 12CoefficieProb.Variablent Std. Error t-Statistic-64.1840X04.809828 -13.344340.0000C1845.47519.26446 95.796880.0000Mean depe ndent1619.33R-squar
10、ed0.946829var3AdjustedS.D. dependent131.225R-squared0.941512var2S.E. ofAkaike info9.90379regressi on31.73600criterio n2Sum squared9.98461resid10071.74Schwarz criterio n0-57.4227Hannan-Qu inn9.87387Log likelihood5 criter.1Durbi n-Wats on1.17240F-statistic178.0715stat7Prob(F-statistic)0.000000由上可得:建筑面
11、积与建造本钱的回归方程为:(3) 首先进行点预测,由 Y=1845.475-64.18400X 得,当 x=4.5 , y=1556.647 再进行区间估计:用 Eviews 分析:YXMea n1619.3333.523333Media n1630.0003.715000Maximum1860.0006.230000Minimum1419.0000.600000Std. Dev.131.22521.989419Skew ness0.003403-0.060130Kurtosis2.3465111.664917Jarque-Ber a0.2135470.898454Probability0.8
12、987290.638121Sum19432.0042.28000Sum Sq. Dev.189420.743.53567Observati on s1212由上表可知,Ex2=E( X X) 2=S 2x(n 1)=1.989419 2 x (12 1)=43.53572 2(Xf X) =(4.5 3.523333 ) =0.95387843当Xf=4.5时,将相关数据代入计算得到:1556.647 2.228x 31.73600 xV 1/12+43.5357/0.95387843<Yf< 1556.647 +2.228x31.73600 xV 1/12+43.5357/0.9
13、5387843即 Yf 的置信区间为(1556.647 478.1231,1556.647 +478.1231 )第三章3.21 对出口货物总额计量经济模型,用Eviews分析结果如下:Depe ndent Variable: YMethod: Least SquaresDate: 12/01/14 Time: 20:25Sample: 1994 2021In cluded observati ons: 18CoefficieProb.Variablent Std. Error t-StatisticX20.1354740.012799 10.584540.0000X318.853489.77
14、61811.9285120.0729-18231.5C88638.216 -2.1105730.0520Mean depe ndent6619.19R-squared0.985838var1AdjustedS.D. dependent5767.15R-squared0.983950var2S.E. ofAkaike info16.1767regressi on730.6306criterio n0Sum squared16.3251resid8007316.Schwarz criterio n0-142.590Hannan-Qu inn16.1971Log likelihood3 criter
15、.7Durbi n-Wats on1.17343F-statistic522.0976stat2Prob(F-statistic)0.000000由上可知,模型为:Y = 0.135474X 2 + 18.85348X 3 - 18231.58对模型进行检验:1可决系数是0.985838,修正的可决系数为 0.983950,说明模型对样本拟合较好2F 检验,F=522.0976>F2,15=4.77,回归方程显著3t检验,t统计量分别为X2的系数对应t值为10.58454,大于t 15=2.131,系数是 显著的,X3的系数对应t值为1.928512,小于t 15 =2.131,说明此系
16、数是不显著的(2) 对于对数模型,用Eviews分析结果如下:Depe nde nt Variable: LN YMethod: Least SquaresDate: 12/01/14 Time: 20:25Sample: 1994 2021In cluded observati ons: 18CoefficieVariablent Std. Error t-StatisticProb.LNX21.5642210.088988 17.577890.0000LNX31.7606950.682115 2.5812290.0209-20.5204C85.432487 -3.7773630.0018M
17、ean depe ndent8.40011R-squared0.986295var2AdjustedS.D. dependent0.94153R-squared0.984467var0S.E. ofAkaike info-1.2964regressi on0.117343criterio n24Sum squared-1.1480resid0.206540Schwarz criterio n29Hannan-Qu inn-1.2759Log likelihood14.66782criter.62Durbi n-Wats on0.68665F-statistic539.7364stat6Prob
18、(F-statistic)0.000000 由上可知,模型为:LNY=-20.52048+1.564221 LNX 2+1.760695 LNX 3 对模型进行检验:1 可决系数是0.986295,修正的可决系数为 0.984467,说明模型对样本拟合较好。2F 检验,F=539.7364> F 2,15=4.77,回归方程显著。3t 检验,t 统计量分别为-3.777363,17.57789,2.581229,均大于 t 15=2.131,所以这些系数都是显著的(3)©( 1)式中的经济意义:工业增加1亿元,出口货物总额增加 0.135474亿元,人民币汇率增加1,出口货物总
19、额增加 18.85348亿元。购(2 )式中的经济意义:工业增加额每增加1%,出口货物总额增加1.564221%,人民币汇率每增加1%,出口货物总额增加1.760695%3.3(1) 对家庭书刊消费对家庭月平均收入和户主受教育年数计量模型,由Eviews分析结果如下:Depe ndent Variable: YMethod: Least SquaresDate: 12/01/14 Time: 20:30Sample: 1 18In cluded observati ons: 18CoefficieProb.Variablent Std. Error t-StatisticX0.0864500.
20、029363 2.9441860.0101T52.370315.202167 10.067020.0000-50.0163C849.46026 -1.0112440.3279Mean depe ndent755.122R-squared0.951235var2AdjustedS.D. dependent258.720R-squared0.944732var6S.E. ofAkaike info11.2048regressi on60.82273criterio n2Sum squared11.3532resid55491.07Schwarz criterio n1-97.8433Hannan-
21、Qu inn11.2252Log likelihood4 criter.8Durbi n-Wats on2.60578F-statistic146.2974stat3 模型为:Y 二 0.086450X + 对模型进行检验:1 可决系数是0.951235,修正的可决系数为 0.944732,说明模型对样本拟合较好。2F 检验,F=539.7364> F 2,15=4.77,回归方程显著。3t检验,t统计量分别为2.944186,10.06702,均大于t 15=2.131,所以这些系数 都是显著的。 经济意义:家庭月平均收入增加1元,家庭书刊年消费支出增加 0.086450元,户主受教育
22、年数增加1年,家庭书刊年消费支出增加52.37031元。2用 Eviews 分析:Depe ndent Variable: YMethod: Least SquaresDate: 12/01/14 Time: 22:30Sample: 1 18In eluded observati ons: 18CoefficieVariablent Std. Error t-Statistic Prob.T63.016764.54858113.854160.0000-11.5817C158.02290 -0.1996060.8443Mean depe ndent755.122R-squared0.92305
23、4var2AdjustedS.D. dependent258.720R-squared0.918245var6S.E. ofAkaike info11.5497regressi on73.97565criterio n9Sum squared11.6487resid87558.36Schwarz criterio n2Log likelihoodF-statistic-101.948Hannan-Qu inn1 criter.Durbi n-Watson191.9377 stat11.56342.13404Prob(F-statistic) 0.000000Depe ndent Variabl
24、e: XMethod: Least SquaresDate: 12/01/14 Time: 22:34Sample: 1 18In cluded observati ons: 18CoefficieProb.Variablent Std. Error t-StatisticT123.151631.84150 3.8676440.0014C444.5888406.1786 1.0945650.2899Mean depe ndent1942.93R-squared0.483182var3AdjustedS.D. dependent698.832R-squared0.450881var5S.E. o
25、fAkaike info15.4417regressi on517.8529criterio n0Sum squared15.5406resid4290746.Schwarz criterio n3-136.975Hannan-Qu inn15.4553Log likelihood3 criter.4Durbi n-Wats on1.05225F-statistic14.95867stat1Prob(F-statistic)0.001364以上分别是y与T, X与T的一元回归模型分别是:Y 二 63.01676T - 11.58171X = 123.1516T + 444.5888(3) 对残
26、差进行模型分析,用 Eviews分析结果如下:Depe ndent Variable: E1Method: Least SquaresDate: 12/03/14 Time: 20:39Sample: 1 18In cluded observati ons: 18CoefficieProb.Variablent Std. Error t-StatisticE20.0864500.0284313.0407420.0078C3.96E-1413.88083 2.85E-151.0000Mean depe ndent2.30E-1R-squared0.366239var4AdjustedS.D. d
27、ependent71.7669R-squared0.326629var3S.E. ofAkaike info11.0937regressi on58.89136criterio n0Sum squared11.1926resid55491.07Schwarz criterio n4-97.8433Hannan-Qu inn11.1073Log likelihood4 criter.5Durbi n-Wats on2.60578F-statistic9.246111stat3Prob(F-statistic)0.007788模型为:E1 = 0.086450E 2 + 3.96e-14参数:斜率
28、系数a为 0.086450,截距为3.96e-14(3) 由上可知,B 2与a 2的系数是一样的。回归系数与被解释变量的残差系数是一样的, 它们的变化规律是一致的。第五章5.3 (1)由Eviews软件分析得:Depe ndent Variable: YMethod: Least SquaresDate: 12/10/14 Time: 16:00y的模型为:Sample: 1 31In eluded observati ons: 31CoeffieieVariablent Std. Error t-StatistieProb.X1.2442810.079032 15.744110.0000C2
29、42.4488 291.1940 0.8326020.4119Mean depe ndent4443.52R-squared0.895260 var6AdjustedS.D. dependent1972.07R-squared0.891649 var2S.E. ofAkaike info15.8515regressi on649.1426 eriterio n2Sum squared122202115.9440resid6 Sehwarz eriterio n4-243.698 Hannan-Quinn15.8816Log likelihood6 eriter.8Durbi n-Wats on
30、1.07858F-statistie247.8769 stat1Prob(F-statistie)0.000000由上表可知,2007年我国农村居民家庭人均消费支出x对人均纯收入Y=1.244281X+242.44882 由图形法检验由上图可知,模型可能存在异方差。 Goldfeld-Qua nadt 检验1定义区间为1-12时,由软件分析得:Depe ndent Variable: Y1Method: Least SquaresSample: 1 12In eluded observati ons: 12CoefficieProb.Variablent Std. Error t-Statis
31、ticX11.4852960.500386 2.9682970.0141-550.549C21220.063 -0.4512470.6614Mean depe ndent3052.95R-squared0.468390var0AdjustedS.D. dependent550.514R-squared0.415229var8S.E. ofAkaike info15.0740regressi on420.9803criterio n6Sum squared15.1548resid1772245.Schwarz criterio n8-88.4443Hannan-Qu inn15.0441Log
32、likelihood7 criter.4Durbi n-Wats on2.35416F-statistic8.810789stat7Prob(F-statistic)0.014087得刀 e=1772245.2定义区间为20-31时,由软件分析得:Depe ndent Variable: Y1Method: Least SquaresDate: 12/10/14 Time: 16:36Sample: 20 31In cluded observati ons: 12CoefficieVariablent Std. Errort-StatisticProb.X11.0869400.1488637.
33、3016230.0000C1173.307733.25201.6001410.1407Mean depe ndent6188.32R-squared0.842056var9AdjustedS.D. dependent2133.69R-squared0.826262var2S.E. ofAkaike info16.5699regressi on889.3633criterio n0Sum squared16.6507resid7909670.Schwarz criterio n2-97.4194Hannan-Qu inn16.5399Log likelihood0 criter.8Durbi n
34、-Wats on2.33976F-statistic53.31370stat7ProbF-statistic0.000026得刀 e2i2=7909670.3根据Goldfeld-Quanadt 检验,F统计量为:F=Ee2i2 / 刀eii2 =7909670./ 1772245=4.4631在a =0.05水平下,分子分母的自由度均为10,查分布表得临界值F0.05 10,10 =2.98 ,因为F=4.4631> F 0.05 10,10=2.98,所以拒绝原假设,此检验说明模型存在异方差。31采用WLS法估计过程中,用权数w1=1/X,建立回归得:Depe ndent Varia
35、ble: YMethod: Least SquaresDate: 12/09/14 Time: 11:13Sample: 1 31In eluded observati ons: 31Weighti ng series: W1CoefficieVariablent Std. Error t-Statistic Prob.X1.425859 0.119104 11.97157 0.0000C-334.813 344.3523 -0.972298 0.3389Weighted StatisticsMean depe ndent3946.08R-squared0.831707var2Adjusted
36、S.D. dependent536.190R-squared0.825904var7S.E. ofAkaike info15.4710regressi on536.6796criterio n2Sum squared15.5635resid8352726.Schwarz criterio n4-237.800Hannan-Qu inn15.5011Log likelihood8 criter.8Durbi n-Wats on1.36908F-statistic143.3184stat1Prob(F-statistic)0.000000Un weightedStatisticsMean depe
37、 ndent4443.52R-squared0.875855var6AdjustedS.D. dependent1972.07R-squared0.871574var2S.E. ofSum squared144842regressi on706.7236resid89Durbi n-Wats onstat1.532908对此模型进行White检验得:Heteroskedasticity Test: WhiteF-statistic0.299395Prob. F(2,28) Prob.0.7436Obs*R-squared0.649065Chi-Square(2)0.7229Scaled exp
38、la inedProb.SS1.798067Chi-Square(2)0.4070Test Equati on:Depe ndent Variable: WGT_RESIDA2Method: Least SquaresDate: 12/10/14 Time: 21:13Sample: 1 31In eluded observati ons: 31Colli near test regressors dropped from speeifieati onCoeffieiet-StatistieProb.Variablent Std. ErrorC61927.891045682.0.0592220
39、.9532-593927.WGTA291173622.-0.5060640.6168X*WGTA2282.4407 747.9780 0.377606 0.7086Mean depe ndent269442.R-squared0.020938 var8Adjusted-0.04899 S.D. depe ndent689166.R-squared5 var5S.E. ofAkaike info29.8639regressi on705847.6 eriterio n5Sum squared1.40E+130.0027resid3 Sehwarz eriterio n3-459.891Hanna
40、n-Qu inn29.9091Log likelihood3 eriter.9Durbi n-Wats on1.92233F-statistie0.299395 stat6Prob(F-statistie)0.743610Sample: 1 31In eluded observati ons: 31Weighti ng series: W2CoefficieProb.Variablent Std. Error t-StatisticX1.557040 0.145392 10.709220.0000-693.194C6 376.4760 -1.8412720.0758Weighted Stati
41、sticsMean depe ndent3635.02R-squared0.798173 var8AdjustedS.D. dependent1029.83R-squared0.791214 var0S.E. ofAkaike info15.1922regressi on466.8513 criterio n4Sum squared15.2847resid6320554. Schwarz criterio n5-233.479 Hannan-Quinn15.2224Log likelihood7 criter.0Durbi n-Wats on1.56297F-statistic114.6875
42、 stat5Prob(F-statistic)0.000000Un weightedStatisticsMean depe ndent4443.52R-squared0.834850 var6AdjustedS.D. dependent1972.07R-squared0.829156 var2S.E. ofSum squared192683regressi on815.1229 resid34Durbi n-Wats onstat1.678365对此模型进行White检验得:F-statistic0.299790Prob. F(3,27) Prob.0.8252Obs*R-squared0.9
43、99322Chi-Square(3)0.8014Scaled expla inedProb.SS1.789507Chi-Square(3)0.6172Test Equati on:Depe ndent Variable: WGT_RESIDA2Method: Least SquaresDate: 12/10/14 Time: 21:29Sample: 1 31In eluded observati ons: 31CoefficieVariablent Std. Error t-Statistic Prob.-111661.C8549855.7 -0.2030750.8406WGTA242622
44、0.22240181. 0.1902620.8505XA2*WGTA20.1948880.516395 0.3774020.7088-583.215X*WGTA212082.820 -0.2800120.7816Mean depe ndent203888.R-squared0.032236var8Adjusted-0.07529S.D. dependent419282.R-squared3 var0S.E. ofAkaike info28.9229regressi on434780.1criterio n8Sum squared5.10E+129.1080resid2Schwarz crite
45、rio n1-444.306Hannan-Qu inn28.9833Log likelihood2 criter.0Durbi n-Wats on1.83585F-statistic0.299790stat4Prob(F-statistic)0.825233从上可知,nR2=0.999322,比较计算的;统计量的临界值,因为nR2=0.999322v0.05(2) =5.9915,所以接受原假设,该模型消除了异方差。估计结果为:t=( 10.70922)( -1.841272)R2=0.798173 F=114.6875DW=1.562975 用权数w3=1/sqr (x),用回归分析得:De
46、pe ndent Variable: YMethod: Least SquaresDate: 12/09/14 Time: 21:35Sample: 1 31In eluded observati ons: 31Weighti ng series: W3Coefficiet-StatisticProb.Variablent Std. ErrorX1.3301300.09834513.525070.0000-47.4024C2313.1154-0.1513900.8807Weighted StatisticsMean depe ndent4164.11R-squared0.863161var8A
47、djustedS.D. dependent991.207R-squared0.858442var9S.E. ofAkaike info15.6501regressi on586.9555criterio n2Sum squared15.7426resid9990985.Schwarz criterio n3-240.576Hannan-Qu inn15.6802Log likelihood8 criter.7Durbi n-Wats on1.23766F-statistic182.9276stat4Prob(F-statistic)0.000000Un weightedStatisticsMe
48、an depe ndent4443.52R-squared0.890999var6AdjustedS.D. dependent1972.07R-squared0.887240var2S.E. ofSum squared127174regressi on662.2171resid12Durbi n-Wats onstat1.314859对此模型进行White检验得:Heteroskedasticity Test: WhiteF-statistic0.423886Prob. F(2,28) Prob.0.6586Obs*R-squared0.911022Chi-Square(2)0.6341Sca
49、led expla inedProb.SS2.768332Chi-Square(2)0.2505Test Equati on:Depe ndent Variable: WGT_RESIDA2Method: Least SquaresDate: 12/09/14 Time: 20:36Sample: 1 31In eluded observati ons: 31Colli near test regressors dropped from specificati onCoefficiet-StatisticProb.Variablent Std. ErrorC1212308.-715673.2141958.0.5659810.5759WGTA20-0.015191301839.-0.5497400.5869XA2*WGTA240.082276-0.1846770.8548R-s
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