1、我國國內生產總值的影響因素的實證分析內容摘要：本文選取1995年至2009年國內生產總值的相關的時間序列數據，應用計量經濟學所學知識對根據經濟理論選取的影響我國國內生產總值的各因素進行檢驗，并對其影響程度的大小進行定量分析，進一步明確和完善相關的經濟學知識。關鍵詞：國內生產總值 計量經濟學 模型 檢驗一、問題的提出改革開放以來，中國經濟釋放了難以置信的增長潛力，國民經濟迅猛發展，經濟總體規模更是躍居前列，雖然整個經濟規模的絕對值大幅度增長，然而有關經濟學者通過研究發現我國國內生產總值受多方面的影響，那么國內生產總值的影響因素具體是哪些，各因素的影響程度如何，本文選取1995年至2009年國內生

2、產總值的相關的時間序列數據，應用計量經濟學所學過的知識進行定量分析，試圖回答以上的問題。二、樣本數據的收集在進行實證分析的過程中，所需要的數據，是能夠反應國民生產總值的影響的指標。在數據的選擇上，均來源于中國統計年鑒。所設模型的樣本容量為15個左右。表11995年至2009年國內生產總值、總投資與貨物凈出口年份國內生產總值總投資貨物凈出口199560793.720019.31403.7199671176.622913.51019.0199778973.024941.13354.2199884402.328406.23597.5199989677.129854.72423.4200099214.

3、632917.71995.62001109655.237213.51865.22002120332.743499.92517.62003135822.855566.62092.32004159878.370477.42667.52005184937.488773.68374.42006216314.4109998.214217.72007265810.3137323.920171.12008314045.4172828.420868.42009340506.9224598.813411.3三、理論模型的設計建立模型假設擬建立如下二元回歸模型：其中：國內生產總值常數項待定參數總投資貨物凈出口隨機

4、干擾項四、模型的參數估計最小二乘法 表2、國內生產總值對總投資與貨物凈出口的回歸（19952009）：Dependent Variable: YMethod: Least SquaresDate: 06/02/11 Time: 07:59Sample: 1995 2009Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  C51129.714642.13411.014270.0000X11.2138020.09465712.823200.0000X22.3027150.8414282

5、.7366750.0180R-squared0.986420    Mean dependent var155436.0Adjusted R-squared0.984157    S.D. dependent var90369.87S.E. of regression11374.90    Akaike info criterion21.69306Sum squared resid1.55E+09    Schwarz criterio

6、n21.83467Log likelihood-159.6980    F-statistic435.8249Durbin-Watson stat0.488763    Prob(F-statistic)0.000000表2給出了采用Eviews軟件對表1中的數據進行回歸分析的計算結果，可建立如下GDP影響因素函數：（11.01427） （12.8232） （2.736675） 五、模型的檢驗（一）、經濟意義檢驗其中，代表1995年至2009年國內生產總值，代表總投資，代表貨物凈出口。模型中所有參數符號、大小、相互

7、之間的關系都是合理的。（二）、統計意義檢驗從回歸估計結果看，模型擬合較好：可決系數，接近于1。5%顯著水平下，自由度為的臨界值截距與斜率項的t檢驗值均大于1.771故認為國內生產總值與上述解釋變量間總體線形關系顯著。（三）、計量經濟學檢驗1、異方差性采用懷特檢驗：記為對原始模型進行普通最小二乘回歸得到的殘差平方項，將其與及其平方項與交叉項作輔助回歸，如圖：White Heteroskedasticity Test:F-statistic1.406235    Probability0.308949Obs*R-squared6.578907 &#

8、160;  Probability0.253887Test Equation:Dependent Variable: RESID2Method: Least SquaresDate: 06/02/11 Time: 09:23Sample: 1995 2009Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  C1.30E+08773045631.6816380.1269X11844.7342715.6210.6793050.5140X120.0122210.024

9、9380.4900350.6358X1*X2-0.3029780.522211-0.5801820.5760X2-33147.1925348.68-1.3076500.2234X222.2507832.7201110.8274600.4294R-squared0.438594    Mean dependent var1.04E+08Adjusted R-squared0.126701    S.D. dependent var1.00E+08S.E. of regression93853739 

10、0;  Akaike info criterion39.84155Sum squared resid7.93E+16    Schwarz criterion40.12477Log likelihood-292.8116    F-statistic1.406235Durbin-Watson stat1.338346    Prob(F-statistic)0.308949 (1.681638) (0.679305) (0.490035) (-1.3076

11、5) (0.82746) (-0.580182) 懷特統計量，該值小于5%顯著水平下、自由度為5的分布的相應臨界值，因此接受同方差的原假設。去掉交叉項后的輔助回歸結果為：White Heteroskedasticity Test:F-statistic1.792556    Probability0.206916Obs*R-squared6.263947    Probability0.180285Test Equation:Dependent Variable: RESID2Method: Least Squar

12、esDate: 06/02/11 Time: 09:21Sample: 1995 2009Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  C1.29E+08746641271.7234470.1155X12139.7612577.5860.8301420.4258X12-0.0013040.008562-0.1523040.8820X2-35925.1524052.53-1.4936120.1661X220.7670450.8954960.8565590.4117R-square

13、d0.417596    Mean dependent var1.04E+08Adjusted R-squared0.184635    S.D. dependent var1.00E+08S.E. of regression90687249    Akaike info criterion39.74493Sum squared resid8.22E+16    Schwarz criterion39.98095Log likeliho

14、od-293.0870    F-statistic1.792556Durbin-Watson stat1.383838    Prob(F-statistic)0.206916 (1.723447) (0.830142) ( -0.152304) (-1.493612) (0.856559) 懷特統計量，該值小于5%顯著水平下、自由度為5的分布的相應臨界值，仍是接受同方差的原假設。因此，不存在異方差性。2、序列相關性從殘差項與時間t以及與的關系圖（下圖）看，隨機項呈現正序列相關性。殘差相關圖下面進行相關性的拉格朗

15、日乘數檢驗含1階滯后殘差項的輔助回歸：Breusch-Godfrey Serial Correlation LM Test:F-statistic10.71122    Probability0.007428Obs*R-squared7.400242    Probability0.006522Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 06/14/11 Time: 08:08Presample missing value la

16、gged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.  C2965.8373568.1620.8311950.4235X1-0.0978590.076461-1.2798570.2269X20.5126420.6448680.7949580.4435RESID(-1)0.8382160.2561163.2728000.0074R-squared0.493349    Mean dependent var1.82E-11Adjusted R-sq

17、uared0.355172    S.D. dependent var10531.11S.E. of regression8456.606    Akaike info criterion21.14646Sum squared resid7.87E+08    Schwarz criterion21.33528Log likelihood-154.5985    F-statistic3.570406Durbin-Watson stat

18、1.500292    Prob(F-statistic)0.050605 (0.831195) (-1.279857) (0.794958) (3.2728) 于是，,該值大于顯著水平為5%、自由度為1的分布的臨界值，由此判斷原模型存在1階序列相關性。含2階滯后殘差項的輔助回歸：Breusch-Godfrey Serial Correlation LM Test:F-statistic4.895854    Probability0.032929Obs*R-squared7.421068  &

19、#160; Probability0.024464Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 06/14/11 Time: 08:09Presample missing value lagged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.  C2881.8833771.3490.7641520.4624X1-0.0996090.080776-1.2331550.2457X20.54373

20、10.7009710.7756840.4559RESID(-1)0.8838170.3842282.3002380.0442RESID(-2)-0.0629740.379892-0.1657670.8716R-squared0.494738    Mean dependent var1.82E-11Adjusted R-squared0.292633    S.D. dependent var10531.11S.E. of regression8857.202    Akai

21、ke info criterion21.27705Sum squared resid7.85E+08    Schwarz criterion21.51307Log likelihood-154.5779    F-statistic2.447927Durbin-Watson stat1.571982    Prob(F-statistic)0.114386 (0.764152) (-1.233155) (0.775684) (0.384228) （-0.165767） 于是

22、，,該值大于顯著水平為5%、自由度為2的分布的臨界值，由此判斷原模型存在2階序列相關性。但的參數未通過5%的顯著性檢驗，表明并不存在2階序列相關性。結合1階滯后殘差項的輔助回歸情況，可判斷該式存在顯著的1階序列相關性。用廣義差分法進行自相關的處理：1階廣義差分的估計結果為：Dependent Variable: YMethod: Least SquaresDate: 06/15/11 Time: 08:41Sample (adjusted): 1996 2009Included observations: 14 after adjustmentsConvergence achieved aft

23、er 9 iterationsVariableCoefficientStd. Errort-StatisticProb.  C80417.8536441.802.2067480.0518X11.0165820.1180158.6139830.0000X22.5139720.5172634.8601440.0007AR(1)0.8280620.1831504.5212220.0011R-squared0.996394    Mean dependent var162196.2Adjusted R-squared0.995312 

24、;   S.D. dependent var89759.08S.E. of regression6145.537    Akaike info criterion20.51980Sum squared resid3.78E+08    Schwarz criterion20.70238Log likelihood-139.6386    F-statistic921.0651Durbin-Watson stat1.884308 

25、0;  Prob(F-statistic)0.000000Inverted AR Roots      .83 （2.206748） （8.613983） (4.860144) (4.521222) 式中，前的參數植即為隨機擾動項的1階序列相關系數，但拉格朗日檢驗值小于顯著水平為5%自由度為1的分布的臨界值，表明模型干擾項已不存在自相關性。3、多重共線性由于較大且接近于1，而且,故認為國內生產總值與解釋變量間總體線性關系顯著。(1)、相關系數表10.8566126777790840.8566126777790841

26、由表中數據發現與間存在較高的相關性。(2)、找出最簡單的回歸形式分別作出與間的回歸：Dependent Variable: YMethod: Least SquaresDate: 06/09/11 Time: 07:57Sample: 1995 2009Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  C50215.045669.1318.8576250.0000X11.4357030.05979924.008760.0000R-squared0.977944  

27、;  Mean dependent var155436.0Adjusted R-squared0.976248    S.D. dependent var90369.87S.E. of regression13927.56    Akaike info criterion22.04469Sum squared resid2.52E+09    Schwarz criterion22.13910Log likelihood-163.3352 

28、60;  F-statistic576.4206Durbin-Watson stat1.006101    Prob(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 06/09/11 Time: 17:49Sample: 1995 2009Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  C78482.9715189.215.16702

29、20.0002X211.545401.5993857.2186460.0000R-squared0.800334    Mean dependent var155436.0Adjusted R-squared0.784975    S.D. dependent var90369.87S.E. of regression41905.18    Akaike info criterion24.24777Sum squared resid2.28E+10    Schwarz criterion24.34218Log likelihood-179.8583