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第二章 2.2 （1） ①對于浙江省預(yù)算收入與全省生產(chǎn)總值的模型，用Eviews分析結(jié)果如下： Dependent Variable: Y Method: Least Squares Date: 12/03/14 Time: 17:00 Sample (adjusted): 1 33 Included observations: 33 after adjustments Variable Coefficient Std. Error t-Statistic Prob. X 0.176124 0.004072 43.25639 0.0000 C -154.3063 39.08196 -3.948274 0.0004 R-squared 0.983702 Mean dependent var 902.5148 Adjusted R-squared 0.983177 S.D. dependent var 1351.009 S.E. of regression 175.2325 Akaike info criterion 13.22880 Sum squared resid 951899.7 Schwarz criterion 13.31949 Log likelihood -216.2751 Hannan-Quinn criter. 13.25931 F-statistic 1871.115 Durbin-Watson stat 0.100021 Prob(F-statistic) 0.000000 ②由上可知，模型的參數(shù)：斜率系數(shù)0.176124，截距為—154.3063 ③關(guān)于浙江省財(cái)政預(yù)算收入與全省生產(chǎn)總值的模型，檢驗(yàn)?zāi)Ｐ偷娘@著性： 1）可決系數(shù)為0.983702，說明所建模型整體上對樣本數(shù)據(jù)擬合較好。 2）對于回歸系數(shù)的t檢驗(yàn)：t（β2）=43.25639>t0.025(31)=2.0395，對斜率系數(shù)的顯著性檢驗(yàn)表明，全省生產(chǎn)總值對財(cái)政預(yù)算總收入有顯著影響。 ④用規(guī)范形式寫出檢驗(yàn)結(jié)果如下： Y=0.176124X—154.3063 (0.004072) (39.08196) t= (43.25639) （-3.948274） R2=0.983702 F=1871.115 n=33 ⑤經(jīng)濟(jì)意義是：全省生產(chǎn)總值每增加1億元，財(cái)政預(yù)算總收入增加0.176124億元。 （2）當(dāng)x=32000時， ①進(jìn)行點(diǎn)預(yù)測，由上可知Y=0.176124X—154.3063，代入可得： Y= Y=0.176124*32000—154.3063=5481.6617 ②進(jìn)行區(qū)間預(yù)測： 先由Eviews分析： X Y Mean 6000.441 902.5148 Median 2689.280 209.3900 Maximum 27722.31 4895.410 Minimum 123.7200 25.87000 Std. Dev. 7608.021 1351.009 Skewness 1.432519 1.663108 Kurtosis 4.010515 4.590432 Jarque-Bera 12.69068 18.69063 Probability 0.001755 0.000087 Sum 198014.5 29782.99 Sum Sq. Dev. 1.85E+09 58407195 Observations 33 33 由上表可知， ∑x2=∑（Xi—X）2=δ2x(n—1)= 7608.0212 x (33—1)=1852223.473 (Xf—X)2=(32000—6000.441)2=675977068.2 當(dāng)Xf=32000時，將相關(guān)數(shù)據(jù)代入計(jì)算得到： 5481.6617—2.0395x175.2325x√1/33+1852223.473/675977068.2≤ Yf≤5481.6617+2.0395x175.2325x√1/33+1852223.473/675977068.2 即Yf的置信區(qū)間為（5481.6617—64.9649, 5481.6617+64.9649） (3) 對于浙江省預(yù)算收入對數(shù)與全省生產(chǎn)總值對數(shù)的模型，由Eviews分析結(jié)果如下： Dependent Variable: LNY Method: Least Squares Date: 12/03/14 Time: 18:00 Sample (adjusted): 1 33 Included observations: 33 after adjustments Variable Coefficient Std. Error t-Statistic Prob. LNX 0.980275 0.034296 28.58268 0.0000 C -1.918289 0.268213 -7.152121 0.0000 R-squared 0.963442 Mean dependent var 5.573120 Adjusted R-squared 0.962263 S.D. dependent var 1.684189 S.E. of regression 0.327172 Akaike info criterion 0.662028 Sum squared resid 3.318281 Schwarz criterion 0.752726 Log likelihood -8.923468 Hannan-Quinn criter. 0.692545 F-statistic 816.9699 Durbin-Watson stat 0.096208 Prob(F-statistic) 0.000000 ①模型方程為：lnY=0.980275lnX-1.918289 ②由上可知，模型的參數(shù)：斜率系數(shù)為0.980275，截距為-1.918289 ③關(guān)于浙江省財(cái)政預(yù)算收入與全省生產(chǎn)總值的模型，檢驗(yàn)其顯著性： 1）可決系數(shù)為0.963442，說明所建模型整體上對樣本數(shù)據(jù)擬合較好。 2）對于回歸系數(shù)的t檢驗(yàn)：t（β2）=28.58268>t0.025(31)=2.0395，對斜率系數(shù)的顯著性檢驗(yàn)表明，全省生產(chǎn)總值對財(cái)政預(yù)算總收入有顯著影響。 ④經(jīng)濟(jì)意義：全省生產(chǎn)總值每增長1%，財(cái)政預(yù)算總收入增長0.980275% 2.4 （1）對建筑面積與建造單位成本模型，用Eviews分析結(jié)果如下： Dependent Variable: Y Method: Least Squares Date: 12/01/14 Time: 12:40 Sample: 1 12 Included observations: 12 Variable Coefficient Std. Error t-Statistic Prob. X -64.18400 4.809828 -13.34434 0.0000 C 1845.475 19.26446 95.79688 0.0000 R-squared 0.946829 Mean dependent var 1619.333 Adjusted R-squared 0.941512 S.D. dependent var 131.2252 S.E. of regression 31.73600 Akaike info criterion 9.903792 Sum squared resid 10071.74 Schwarz criterion 9.984610 Log likelihood -57.42275 Hannan-Quinn criter. 9.873871 F-statistic 178.0715 Durbin-Watson stat 1.172407 Prob(F-statistic) 0.000000 由上可得：建筑面積與建造成本的回歸方程為： Y=1845.475--64.18400X （2）經(jīng)濟(jì)意義：建筑面積每增加1萬平方米，建筑單位成本每平方米減少64.18400元。 （3） ①首先進(jìn)行點(diǎn)預(yù)測，由Y=1845.475--64.18400X得，當(dāng)x=4.5，y=1556.647 ②再進(jìn)行區(qū)間估計(jì)： 用Eviews分析： Y X Mean 1619.333 3.523333 Median 1630.000 3.715000 Maximum 1860.000 6.230000 Minimum 1419.000 0.600000 Std. Dev. 131.2252 1.989419 Skewness 0.003403 -0.060130 Kurtosis 2.346511 1.664917 Jarque-Bera 0.213547 0.898454 Probability 0.898729 0.638121 Sum 19432.00 42.28000 Sum Sq. Dev. 189420.7 43.53567 Observations 12 12 由上表可知， ∑x2=∑（Xi—X）2=δ2x(n—1)= 1.9894192 x (12—1)=43.5357 (Xf—X)2=(4.5—3.523333)2=0.95387843 當(dāng)Xf=4.5時，將相關(guān)數(shù)據(jù)代入計(jì)算得到： 1556.647—2.228x31.73600x√1/12+43.5357/0.95387843≤ Yf≤1556.647+2.228x31.73600x√1/12+43.5357/0.95387843 即Yf的置信區(qū)間為（1556.647—478.1231, 1556.647+478.1231） 第三章 3.2 １）對出口貨物總額計(jì)量經(jīng)濟(jì)模型，用Eviews分析結(jié)果如下：： Dependent Variable: Y Method: Least Squares Date: 12/01/14 Time: 20:25 Sample: 1994 2011 Included observations: 18 Variable Coefficient Std. Error t-Statistic Prob. X2 0.135474 0.012799 10.58454 0.0000 X3 18.85348 9.776181 1.928512 0.0729 C -18231.58 8638.216 -2.110573 0.0520 R-squared 0.985838 Mean dependent var 6619.191 Adjusted R-squared 0.983950 S.D. dependent var 5767.152 S.E. of regression 730.6306 Akaike info criterion 16.17670 Sum squared resid 8007316. Schwarz criterion 16.32510 Log likelihood -142.5903 Hannan-Quinn criter. 16.19717 F-statistic 522.0976 Durbin-Watson stat 1.173432 Prob(F-statistic) 0.000000 ①由上可知，模型為： Y = 0.135474X2 + 18.85348X3 - 18231.58 ②對模型進(jìn)行檢驗(yàn)： 1）可決系數(shù)是0.985838，修正的可決系數(shù)為0.983950，說明模型對樣本擬合較好 2）F檢驗(yàn)，F(xiàn)=522.0976>F（2,15）=4.77，回歸方程顯著 3）t檢驗(yàn)，t統(tǒng)計(jì)量分別為X2的系數(shù)對應(yīng)t值為10.58454，大于t（15）=2.131，系數(shù)是顯著的，X3的系數(shù)對應(yīng)t值為1.928512，小于t（15）=2.131，說明此系數(shù)是不顯著的。 （2）對于對數(shù)模型，用Eviews分析結(jié)果如下： Dependent Variable: LNY Method: Least Squares Date: 12/01/14 Time: 20:25 Sample: 1994 2011 Included observations: 18 Variable Coefficient Std. Error t-Statistic Prob. LNX2 1.564221 0.088988 17.57789 0.0000 LNX3 1.760695 0.682115 2.581229 0.0209 C -20.52048 5.432487 -3.777363 0.0018 R-squared 0.986295 Mean dependent var 8.400112 Adjusted R-squared 0.984467 S.D. dependent var 0.941530 S.E. of regression 0.117343 Akaike info criterion -1.296424 Sum squared resid 0.206540 Schwarz criterion -1.148029 Log likelihood 14.66782 Hannan-Quinn criter. -1.275962 F-statistic 539.7364 Durbin-Watson stat 0.686656 Prob(F-statistic) 0.000000 ①由上可知，模型為： LNY=-20.52048+1.564221 LNX2+1.760695 LNX3 ②對模型進(jìn)行檢驗(yàn)： 1）可決系數(shù)是0.986295，修正的可決系數(shù)為0.984467，說明模型對樣本擬合較好。 2）F檢驗(yàn)，F(xiàn)=539.7364> F（2,15）=4.77，回歸方程顯著。 3）t檢驗(yàn)，t統(tǒng)計(jì)量分別為-3.777363，17.57789，2.581229，均大于t（15）=2.131，所以這些系數(shù)都是顯著的。 （3） ①（1）式中的經(jīng)濟(jì)意義：工業(yè)增加1億元，出口貨物總額增加0.135474億元，人民幣匯率增加1，出口貨物總額增加18.85348億元。 ②（2）式中的經(jīng)濟(jì)意義：工業(yè)增加額每增加1%，出口貨物總額增加1.564221%，人民幣匯率每增加1%，出口貨物總額增加1.760695% 3.3 （1）對家庭書刊消費(fèi)對家庭月平均收入和戶主受教育年數(shù)計(jì)量模型，由Eviews分析結(jié)果如下： Dependent Variable: Y Method: Least Squares Date: 12/01/14 Time: 20:30 Sample: 1 18 Included observations: 18 Variable Coefficient Std. Error t-Statistic Prob. X 0.086450 0.029363 2.944186 0.0101 T 52.37031 5.202167 10.06702 0.0000 C -50.01638 49.46026 -1.011244 0.3279 R-squared 0.951235 Mean dependent var 755.1222 Adjusted R-squared 0.944732 S.D. dependent var 258.7206 S.E. of regression 60.82273 Akaike info criterion 11.20482 Sum squared resid 55491.07 Schwarz criterion 11.35321 Log likelihood -97.84334 Hannan-Quinn criter. 11.22528 F-statistic 146.2974 Durbin-Watson stat 2.605783 Prob(F-statistic) 0.000000 ①模型為：Y = 0.086450X + 52.37031T-50.01638 ②對模型進(jìn)行檢驗(yàn)： 1）可決系數(shù)是0.951235，修正的可決系數(shù)為0.944732，說明模型對樣本擬合較好。 2）F檢驗(yàn)，F(xiàn)=539.7364> F（2,15）=4.77，回歸方程顯著。 3）t檢驗(yàn)，t統(tǒng)計(jì)量分別為2.944186，10.06702，均大于t（15）=2.131，所以這些系數(shù)都是顯著的。 ③經(jīng)濟(jì)意義：家庭月平均收入增加1元，家庭書刊年消費(fèi)支出增加0.086450元，戶主受教育年數(shù)增加1年，家庭書刊年消費(fèi)支出增加52.37031元。 （2）用Eviews分析： ① Dependent Variable: Y Method: Least Squares Date: 12/01/14 Time: 22:30 Sample: 1 18 Included observations: 18 Variable Coefficient Std. Error t-Statistic Prob. T 63.01676 4.548581 13.85416 0.0000 C -11.58171 58.02290 -0.199606 0.8443 R-squared 0.923054 Mean dependent var 755.1222 Adjusted R-squared 0.918245 S.D. dependent var 258.7206 S.E. of regression 73.97565 Akaike info criterion 11.54979 Sum squared resid 87558.36 Schwarz criterion 11.64872 Log likelihood -101.9481 Hannan-Quinn criter. 11.56343 F-statistic 191.9377 Durbin-Watson stat 2.134043 Prob(F-statistic) 0.000000 ② Dependent Variable: X Method: Least Squares Date: 12/01/14 Time: 22:34 Sample: 1 18 Included observations: 18 Variable Coefficient Std. Error t-Statistic Prob. T 123.1516 31.84150 3.867644 0.0014 C 444.5888 406.1786 1.094565 0.2899 R-squared 0.483182 Mean dependent var 1942.933 Adjusted R-squared 0.450881 S.D. dependent var 698.8325 S.E. of regression 517.8529 Akaike info criterion 15.44170 Sum squared resid 4290746. Schwarz criterion 15.54063 Log likelihood -136.9753 Hannan-Quinn criter. 15.45534 F-statistic 14.95867 Durbin-Watson stat 1.052251 Prob(F-statistic) 0.001364 以上分別是y與T，X與T的一元回歸 模型分別是： Y = 63.01676T - 11.58171 X = 123.1516T + 444.5888 （3）對殘差進(jìn)行模型分析，用Eviews分析結(jié)果如下： Dependent Variable: E1 Method: Least Squares Date: 12/03/14 Time: 20:39 Sample: 1 18 Included observations: 18 Variable Coefficient Std. Error t-Statistic Prob. E2 0.086450 0.028431 3.040742 0.0078 C 3.96E-14 13.88083 2.85E-15 1.0000 R-squared 0.366239 Mean dependent var 2.30E-14 Adjusted R-squared 0.326629 S.D. dependent var 71.76693 S.E. of regression 58.89136 Akaike info criterion 11.09370 Sum squared resid 55491.07 Schwarz criterion 11.19264 Log likelihood -97.84334 Hannan-Quinn criter. 11.10735 F-statistic 9.246111 Durbin-Watson stat 2.605783 Prob(F-statistic) 0.007788 模型為： E1 = 0.086450E2 + 3.96e-14 參數(shù)：斜率系數(shù)α為0.086450，截距為3.96e-14 （3）由上可知，β2與α2的系數(shù)是一樣的?；貧w系數(shù)與被解釋變量的殘差系數(shù)是一樣的，它們的變化規(guī)律是一致的。 第五章 5.3 (1)由Eviews軟件分析得： Dependent Variable: Y Method: Least Squares Date: 12/10/14 Time: 16:00 Sample: 1 31 Included observations: 31 Variable Coefficient Std. Error t-Statistic Prob. X 1.244281 0.079032 15.74411 0.0000 C 242.4488 291.1940 0.832602 0.4119 R-squared 0.895260 Mean dependent var 4443.526 Adjusted R-squared 0.891649 S.D. dependent var 1972.072 S.E. of regression 649.1426 Akaike info criterion 15.85152 Sum squared resid 12220196 Schwarz criterion 15.94404 Log likelihood -243.6986 Hannan-Quinn criter. 15.88168 F-statistic 247.8769 Durbin-Watson stat 1.078581 Prob(F-statistic) 0.000000 由上表可知，2007年我國農(nóng)村居民家庭人均消費(fèi)支出（x）對人均純收入（y）的模型為： Y=1.244281X+242.4488 （2） ①由圖形法檢驗(yàn) 由上圖可知，模型可能存在異方差。 ②Goldfeld-Quanadt檢驗(yàn) 1）定義區(qū)間為1-12時，由軟件分析得： Dependent Variable: Y1 Method: Least Squares Date: 12/10/14 Time: 11:34 Sample: 1 12 Included observations: 12 Variable Coefficient Std. Error t-Statistic Prob. X1 1.485296 0.500386 2.968297 0.0141 C -550.5492 1220.063 -0.451247 0.6614 R-squared 0.468390 Mean dependent var 3052.950 Adjusted R-squared 0.415229 S.D. dependent var 550.5148 S.E. of regression 420.9803 Akaike info criterion 15.07406 Sum squared resid 1772245. Schwarz criterion 15.15488 Log likelihood -88.44437 Hannan-Quinn criter. 15.04414 F-statistic 8.810789 Durbin-Watson stat 2.354167 Prob(F-statistic) 0.014087 得∑e1i2=1772245. 2）定義區(qū)間為20-31時，由軟件分析得： Dependent Variable: Y1 Method: Least Squares Date: 12/10/14 Time: 16:36 Sample: 20 31 Included observations: 12 Variable Coefficient Std. Error t-Statistic Prob. X1 1.086940 0.148863 7.301623 0.0000 C 1173.307 733.2520 1.600141 0.1407 R-squared 0.842056 Mean dependent var 6188.329 Adjusted R-squared 0.826262 S.D. dependent var 2133.692 S.E. of regression 889.3633 Akaike info criterion 16.56990 Sum squared resid 7909670. Schwarz criterion 16.65072 Log likelihood -97.41940 Hannan-Quinn criter. 16.53998 F-statistic 53.31370 Durbin-Watson stat 2.339767 Prob(F-statistic) 0.000026 得∑e2i2=7909670. 3）根據(jù)Goldfeld-Quanadt檢驗(yàn)，F(xiàn)統(tǒng)計(jì)量為： F=∑e2i2 /∑e1i2 =7909670./ 1772245=4.4631 在α=0.05水平下，分子分母的自由度均為10，查分布表得臨界值F0.05（10,10）=2.98，因?yàn)镕=4.4631> F0.05（10,10）=2.98，所以拒絕原假設(shè)，此檢驗(yàn)表明模型存在異方差。 （3） 1）采用WLS法估計(jì)過程中， ①用權(quán)數(shù)w1=1/X,建立回歸得： Dependent Variable: Y Method: Least Squares Date: 12/09/14 Time: 11:13 Sample: 1 31 Included observations: 31 Weighting series: W1 Variable Coefficient Std. Error t-Statistic Prob. X 1.425859 0.119104 11.97157 0.0000 C -334.8131 344.3523 -0.972298 0.3389 Weighted Statistics R-squared 0.831707 Mean dependent var 3946.082 Adjusted R-squared 0.825904 S.D. dependent var 536.1907 S.E. of regression 536.6796 Akaike info criterion 15.47102 Sum squared resid 8352726. Schwarz criterion 15.56354 Log likelihood -237.8008 Hannan-Quinn criter. 15.50118 F-statistic 143.3184 Durbin-Watson stat 1.369081 Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.875855 Mean dependent var 4443.526 Adjusted R-squared 0.871574 S.D. dependent var 1972.072 S.E. of regression 706.7236 Sum squared resid 14484289 Durbin-Watson stat 1.532908 對此模型進(jìn)行White檢驗(yàn)得： Heteroskedasticity Test: White F-statistic 0.299395 Prob. F(2,28) 0.7436 Obs*R-squared 0.649065 Prob. Chi-Square(2) 0.7229 Scaled explained SS 1.798067 Prob. Chi-Square(2) 0.4070 Test Equation: Dependent Variable: WGT_RESID^2 Method: Least Squares Date: 12/10/14 Time: 21:13 Sample: 1 31 Included observations: 31 Collinear test regressors dropped from specification Variable Coefficient Std. Error t-Statistic Prob. C 61927.89 1045682. 0.059222 0.9532 WGT^2 -593927.9 1173622. -0.506064 0.6168 X*WGT^2 282.4407 747.9780 0.377606 0.7086 R-squared 0.020938 Mean dependent var 269442.8 Adjusted R-squared -0.048995 S.D. dependent var 689166.5 S.E. of regression 705847.6 Akaike info criterion 29.86395 Sum squared resid 1.40E+13 Schwarz criterion 30.00273 Log likelihood -459.8913 Hannan-Quinn criter. 29.90919 F-statistic 0.299395 Durbin-Watson stat 1.922336 Prob(F-statistic) 0.743610 從上可知，nR2=0.649065，比較計(jì)算的統(tǒng)計(jì)量的臨界值，因?yàn)閚R2=0.649065<0.05（2）=5.9915，所以接受原假設(shè)，該模型消除了異方差。 估計(jì)結(jié)果為： Y=1.425859X-334.8131 t=（11.97157）（-0.972298） R2=0.875855 F=143.3184 DW=1.369081 ②用權(quán)數(shù)w2=1/x2,用回歸分析得： Dependent Variable: Y Method: Least Squares Date: 12/09/14 Time: 21:08 Sample: 1 31 Included observations: 31 Weighting series: W2 Variable Coefficient Std. Error t-Statistic Prob. X 1.557040 0.145392 10.70922 0.0000 C -693.1946 376.4760 -1.841272 0.0758 Weighted Statistics R-squared 0.798173 Mean dependent var 3635.028 Adjusted R-squared 0.791214 S.D. dependent var 1029.830 S.E. of regression 466.8513 Akaike info criterion 15.19224 Sum squared resid 6320554. Schwarz criterion 15.28475 Log likelihood -233.4797 Hannan-Quinn criter. 15.22240 F-statistic 114.6875 Durbin-Watson stat 1.562975 Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.834850 Mean dependent var 4443.526 Adjusted R-squared 0.829156 S.D. dependent var 1972.072 S.E. of regression 815.1229 Sum squared resid 19268334 Durbin-Watson stat 1.678365 對此模型進(jìn)行White檢驗(yàn)得： Heteroskedasticity Test: White F-statistic 0.299790 Prob. F(3,27) 0.8252 Obs*R-squared 0.999322 Prob. Chi-Square(3) 0.8014 Scaled explained SS 1.789507 Prob. Chi-Square(3) 0.6172 Test Equation: Dependent Variable: WGT_RESID^2 Method: Least Squares Date: 12/10/14 Time: 21:29 Sample: 1 31 Included observations: 31 Variable Coefficient Std. Error t-Statistic Prob. C -111661.8 549855.7 -0.203075 0.8406 WGT^2 426220.2 2240181. 0.190262 0.8505 X^2*WGT^2 0.194888 0.516395 0.377402 0.7088 X*WGT^2 -583.2151 2082.820 -0.280012 0.7816 R-squared 0.032236 Mean dependent var 203888.8 Adjusted R-squared -0.075293 S.D. dependent var 419282.0 S.E. of regression 434780.1 Akaike info criterion 28.92298 Sum squared resid 5.10E+12 Schwarz criterion 29.10801 Log likelihood -444.3062 Hannan-Quinn criter. 28.98330 F-statistic 0.299790 Durbin-Watson stat 1.835854 Prob(F-statistic) 0.825233 從上可知，nR2=0.999322，比較計(jì)算的統(tǒng)計(jì)量的臨界值，因?yàn)閚R2=0.999322<0.05（2）=5.9915，所以接受原假設(shè)，該模型消除了異方差。 估計(jì)結(jié)果為： Y=1.557040X-693.1946 t=（10.70922）（-1.841272） R2=0.798173 F=114.6875 DW=1.562975 ③用權(quán)數(shù)w3=1/sqr（x）,用回歸分析得： Dependent Variable: Y Method: Least Squares Date: 12/09/14 Time: 21:35 Sample: 1 31 Included observations: 31 Weighting series: W3 Variable Coefficient Std. Error t-Statistic Prob. X 1.330130 0.098345 13.52507 0.0000 C -47.40242 313.1154 -0.151390 0.8807 Weighted Statistics R-squared 0.863161 Mean dependent var 4164.118 Adjusted R-squared 0.858442 S.D. dependent var 991.2079 S.E. of regression 586.9555 Akaike info criterion 15.65012 Sum squared resid 9990985. Schwarz criterion 15.74263 Log likelihood -240.5768 Hannan-Quinn criter. 15.68027 F-statistic 182.9276 Durbin-Watson stat 1.237664 Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.890999 Mean dependent var 4443.526 Adjusted R-squared 0.887240 S.D. dependent var 1972.072 S.E. of regression 662.2171 Sum squared resid 12717412 Durbin-Watson stat 1.314859 對此模型進(jìn)行White檢驗(yàn)得： Heteroskedasticity Test: White F-statistic 0.423886 Prob. F(2,28) 0.6586 Obs*R-squared 0.911022 Prob. Chi-Square(2) 0.6341 Scaled explained SS 2.768332 Prob. Chi-Square(2) 0.2505 Test Equation: Dependent Variabl