我國國內(nèi)生產(chǎn)總值的影響因素的實(shí)證分析

1、我國國內(nèi)生產(chǎn)總值的影響因素的實(shí)證分析內(nèi)容摘要：本文選取1995年至2009年國內(nèi)生產(chǎn)總值的相關(guān)的時(shí)間序列數(shù)據(jù)，應(yīng)用計(jì)量經(jīng)濟(jì)學(xué)所學(xué)知識對根據(jù)經(jīng)濟(jì)理論選取的影響我國國內(nèi)生產(chǎn)總值的各因素進(jìn)行檢驗(yàn)，并對其影響程度的大小進(jìn)行定量分析，進(jìn)一步明確和完善相關(guān)的經(jīng)濟(jì)學(xué)知識。關(guān)鍵詞：國內(nèi)生產(chǎn)總值 計(jì)量經(jīng)濟(jì)學(xué) 模型 檢驗(yàn)一、問題的提出改革開放以來，中國經(jīng)濟(jì)釋放了難以置信的增長潛力，國民經(jīng)濟(jì)迅猛發(fā)展，經(jīng)濟(jì)總體規(guī)模更是躍居前列，雖然整個經(jīng)濟(jì)規(guī)模的絕對值大幅度增長，然而有關(guān)經(jīng)濟(jì)學(xué)者通過研究發(fā)現(xiàn)我國國內(nèi)生產(chǎn)總值受多方面的影響，那么國內(nèi)生產(chǎn)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(nèi)生

2、產(chǎn)總值的相關(guān)的時(shí)間序列數(shù)據(jù)，應(yīng)用計(jì)量經(jīng)濟(jì)學(xué)所學(xué)過的知識進(jìn)行定量分析，試圖回答以上的問題。二、樣本數(shù)據(jù)的收集在進(jìn)行實(shí)證分析的過程中，所需要的數(shù)據(jù)，是能夠反應(yīng)國民生產(chǎn)總值的影響的指標(biāo)。在數(shù)據(jù)的選擇上，均來源于中國統(tǒng)計(jì)年鑒。所設(shè)模型的樣本容量為15個左右。表11995年至2009年國內(nèi)生產(chǎn)總值、總投資與貨物凈出口年份國內(nèi)生產(chǎn)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(shè)計(jì)建立模型假設(shè)擬建立如下二元回歸模型：其中：國內(nèi)生產(chǎn)總值常數(shù)項(xiàng)待定參數(shù)總投資貨物凈出口隨機(jī)

4、干擾項(xiàng)四、模型的參數(shù)估計(jì)最小二乘法 表2、國內(nèi)生產(chǎn)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(shù)據(jù)進(jìn)行回歸分析的計(jì)算結(jié)果，可建立如下GDP影響因素函數(shù)：（11.01427） （12.8232） （2.736675） 五、模型的檢驗(yàn)（一）、經(jīng)濟(jì)意義檢驗(yàn)其中，代表1995年至2009年國內(nèi)生產(chǎn)總值，代表總投資，代表貨物凈出口。模型中所有參數(shù)符號、大小、相互

7、之間的關(guān)系都是合理的。（二）、統(tǒng)計(jì)意義檢驗(yàn)從回歸估計(jì)結(jié)果看，模型擬合較好：可決系數(shù)，接近于1。5%顯著水平下，自由度為的臨界值截距與斜率項(xiàng)的t檢驗(yàn)值均大于1.771故認(rèn)為國內(nèi)生產(chǎn)總值與上述解釋變量間總體線形關(guān)系顯著。（三）、計(jì)量經(jīng)濟(jì)學(xué)檢驗(yàn)1、異方差性采用懷特檢驗(yàn)：記為對原始模型進(jìn)行普通最小二乘回歸得到的殘差平方項(xiàng)，將其與及其平方項(xiàng)與交叉項(xiàng)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(tǒng)計(jì)量，該值小于5%顯著水平下、自由度為5的分布的相應(yīng)臨界值，因此接受同方差的原假設(shè)。去掉交叉項(xiàng)后的輔助回歸結(jié)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(tǒng)計(jì)量，該值小于5%顯著水平下、自由度為5的分布的相應(yīng)臨界值，仍是接受同方差的原假設(shè)。因此，不存在異方差性。2、序列相關(guān)性從殘差項(xiàng)與時(shí)間t以及與的關(guān)系圖（下圖）看，隨機(jī)項(xiàng)呈現(xiàn)正序列相關(guān)性。殘差相關(guān)圖下面進(jìn)行相關(guān)性的拉格朗

15、日乘數(shù)檢驗(yàn)含1階滯后殘差項(xiàng)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(guān)性。含2階滯后殘差項(xiàng)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(guān)性。但的參數(shù)未通過5%的顯著性檢驗(yàn)，表明并不存在2階序列相關(guān)性。結(jié)合1階滯后殘差項(xiàng)的輔助回歸情況，可判斷該式存在顯著的1階序列相關(guān)性。用廣義差分法進(jìn)行自相關(guān)的處理：1階廣義差分的估計(jì)結(jié)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(shù)植即為隨機(jī)擾動項(xiàng)的1階序列相關(guān)系數(shù)，但拉格朗日檢驗(yàn)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(xiàng)已不存在自相關(guān)性。3、多重共線性由于較大且接近于1，而且,故認(rèn)為國內(nèi)生產(chǎn)總值與解釋變量間總體線性關(guān)系顯著。(1)、相關(guān)系數(shù)表10.8566126777790840.8566126777790841

26、由表中數(shù)據(jù)發(fā)現(xiàn)與間存在較高的相關(guān)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