我國國內(nèi)生產(chǎn)總值的影響因素的實證分析

1、我國國內(nèi)生產(chǎn)總值的影響因素的實證分析內(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)的時間序列數(shù)據(jù)，應用計量經(jīng)濟 學所學知識對根據(jù)經(jīng)濟理論選取的影響我國國內(nèi)生產(chǎn)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(guān)的經(jīng)濟學知識。關(guān)鍵詞：國內(nèi)生產(chǎn)總值 計量經(jīng)濟學 模型 檢驗一、問題的提出改革開放以來，中國經(jīng)濟釋放了難以置信的增長潛力，國民經(jīng)濟迅猛發(fā)展，經(jīng)濟總體規(guī)模更是躍居前列，雖然整個經(jīng)濟規(guī)模的絕對值大幅度增長，然而有關(guān)經(jīng)濟學者通過研究發(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

2、年國內(nèi)生產(chǎn)總值的相關(guān)的時間序列數(shù)據(jù)，應用計量經(jīng) 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(shù)據(jù)的收集在進行實證分析的過程中，所需要的數(shù)據(jù)，是能夠反應國民生產(chǎn)總值的影響的指標。在數(shù)據(jù)的選擇上，均來源于中國統(tǒng)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(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199560793.720019.31403.7199671176.622913.51019.0199778973.024941.13354.2199884402.328406.23597.5199989677.129854.72423.4200

3、099214.632917.71995.62001109655.237213.51865.22002120332.743499.92517.62003135822.855566.62092.32004159878.370477.42667.52005184937.488773.68374.42006216314.4109998.214217.72007265810.3137323.920171.12008314045.4172828.420868.42009340506.9224598.813411.3三、理論模型的設計建立模型假設擬建立如下二元回歸模型：7? V ? V其中:Y 01X12X

4、 2Y國內(nèi)生產(chǎn)總值0常數(shù)項?1, ?2 待定參數(shù)X1 總投資X2貨物凈出口隨機干擾項四、模型的參數(shù)估計最小二乘法表2、國內(nèi)生產(chǎn)總值 Y對總投資Xi與貨物凈出口 X2的回歸( 1995 2009)Dependent Variable: YMethod: Least SquaresDate: 06/02/11Time: 07:59Sample: 1995 2009Included observations: 15VariableCoefficientStd. Errort-StatisticProb.C51129.714642.13411.014270.0000X11.2138020.094657

5、12.823200.0000X22.3027150.8414282.7366750.0180R-squared0.986420Mean dependent var155436.0Adjusted R-squared0.984157S.D. dependent var90369.87S.E. of regression11374.90Akaike info criterion21.69306Sum squared resid1.55E+09Schwarz criterion21.83467Log likelihood-159.6980F-statistic435.8249Durbin-Watso

6、n stat0.488763Prob(F-statistic)0.000000表2給出了采用Eviews軟件表1中的數(shù)據(jù)進行回歸分析的計算結(jié)果，可建立如下GDP影響因素函數(shù)：Y? 51129.71 1.213802X12.302715X2(11.01427)(12.8232)(2.736675)R2 0.98642R2 0.984157 F 435.8249DW. 0.488763五、模型的檢驗(一)、經(jīng)濟意義檢驗其中，Y代表1995年至2009年國內(nèi)生產(chǎn)總值，X1代表總投資， X2代表貨物凈出口。模型 中所有參數(shù)符號、大小、相互之間的關(guān)系都是合理的。(二)、統(tǒng)計意義檢驗從回歸估計結(jié)果看，模型

7、擬合較好：可決系數(shù)R20.98642 ,接近于1。5%顯著水平下，自由度為 n 2 15 2 13的臨界值t (n 2) 1.771-2截距與斜率項的t檢驗值均大于1.771F 435.8249 F0.05(2,13) 3.8故認為國內(nèi)生產(chǎn)總值與上述解釋變量間總體線形關(guān)系顯著。(三)、計量經(jīng)濟學檢驗1、異方差性采用懷特檢驗： 2記ei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 X1，X2及其平方項與交叉項作輔助回歸，如圖：White Heteroskedasticity Test:F-statistic1.406235Probability0.308949Obs*R-square

8、d6.578907Probability0.253887Test Equation:Dependent Variable: RESIDA2Method: Least SquaresDate: 06/02/11 Time: 09:23Sample: 1995 2009Included observations: 15Std.VariableCoefficientErrort-StatisticProb.C1.30E+08773045631.6816380.1269X11844.7342715.6210.6793050.5140X1A20.0122210.0249380.4900350.6358X

9、1*X2-0.3029780.522211-0.5801820.5760X2-33147.1925348.68-1.3076500.2234X2A22.2507832.7201110.8274600.4294R-squared0.438594Mean dependent var1.04E+08AdjustedR-squared0.126701S.D. dependent var1.00E+08S.E.ofAkaikeinforegression93853739criterion39.84155Sum squaredresid7.93E+16Schwarz criterion40.12477Lo

10、g-292.8116F-statistic1.406235likelihood Durbin-WatsonProb(F-statistic)0.308949_ _2 33147.19X22.250783X20.302978X1 X2(0.82746)(-0.580182)stat1.3383462e2 1.301844.734X10.012221X1(1.681638) (0.679305) (0.490035) (-1.30765)_ 2_R 0.43859422懷特統(tǒng)計量nR 15* 0.438594 6.57891 ,該值小于5痂著水平下、自由度為 5的 分2布的相應臨界值0.051 1

11、.07,因此接受同方差的原假設。去掉交叉項后的輔助回歸結(jié)果為：White Heteroskedasticity Test:F-statistic1.792556Obs*R-squared6.2639470.20691Probability60.18028Probability5Test Equation:Dependent Variable: RESIDA2Method: Least SquaresDate: 06/02/11 Time: 09:21Sample: 1995 2009Included observations: 15VariableCoefficiStd.ict-Statist

12、Prob.entErrorC1.29E+08746641271.7234470.1155X12139.761-0.001302577.5860.8301420.4258X1A24-35925.10.008562-0.1523040.8820X2524052.53-1.4936120.1661X2A20.7670450.8954960.8565590.4117Meandependent1.04E+0R-squared0.417596varS.D.dependent81.00E+0Adjusted R-squared0.184635varAkaikeinfo839.7449S.E. of regr

13、ession90687249criterion3Schwarz39.9809Sum squared resid8.22E+16criterion5-293.0871.79255Log likelihood0F-statistic6Durbin-Watson stat1.383838Prob(F-statisti0.20691c)2_2_2e 1.292139.761Xi 0.008562Xi 35925.15X2 0.767045X2(1.723447) (0.830142) ( -0.152304) (-1.493612)(0.856559)_ 2R 0.41759622懷特統(tǒng)計量nR 15

14、 * 0.417596 6.26394,該值小于5痂著水平下、自由度為5的 分2布的相應臨界值0.051 1.07,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(guān)性20000從殘差項et與時間t以及e與et1的關(guān)系圖(下圖)看，隨機項呈現(xiàn)正序列相關(guān)性。10000,*0. »-10000 - 1»-20000 ,|,-20000-1000001000020000RESID(-1)殘差相關(guān)圖卜面進行相關(guān)性的拉格朗日乘數(shù)檢驗 含1階滯后殘差項的輔助回歸:Breusch-Godfrey Serial Correlation LM Test:F-statistic10.7

15、1122Probability0.007428Obs*R-squared7.400242Probability0.006522Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 06/14/11 Time: 08:08Presample missing value lagged residuals set to zero.VariableStd.Prob.CoefficientErrort-StatisticC2965.8373568.1620.8311950.4235X1-0.0978590.076461-1.2

16、798570.2269X2RESID(-1)0.5126420.8382160.6448680.2561160.7949583.2728000.44350.0074R-squared0.493349Mean dependent var1.82E-11AdjustedR-squared0.355172S.D. dependent var10531.11S.E.ofAkaikeinforegression8456.606criterion21.14646Sum squaredresid7.87E+08Schwarz criterion21.33528Log likelihood-154.5985F

17、-statistic3.570406Durbin-Watsonstat1.500292Prob(F-statistic)0.050605 et 2965.8370.097859X10.512642X2_ _ _ _ _ _0.838216et 1(0.831195) (-1.279857) (0.794958)(3.2728)R2 0.493349 2 于是，LM 14*0.493349 6.906886,該值大于顯著水平為5%自由度為1的 分布的2臨界值 0.05(1) 3.84,由此判斷原模型存在1階序列相關(guān)性。含2階滯后殘差項的輔助回歸：Breusch-Godfrey Serial Co

18、rrelation LM Test:4.89580.0329F-statistic54Probability297.42100.0244Obs*R-squared68Probability64Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 06/14/11 Time: 08:09Presample missing value lagged residuals set to zero.VariablecientCoeffiStd. Error ict-StatistProb.C832881.83771.3490.

19、7641520.4624X1609-0.0990.080776-1.2331550.2457X2310.54370.7009710.7756840.4559RESID(-1)170.88380.3842282.3002380.0442-0.062RESID(-2)9740.379892-0.1657670.87160.4947Mean dependent1.82E-R-squared38var110.2926S.D.dependent10531.Adjusted R-squared33var118857.2Akaikeinfo21.277S.E. of regression02criterio

20、n057.85E+21.513Sum squared resid08Schwarz criterion 07-154.52.4479Log likelihood779F-statistic271.5719Prob(F-statistic0.1143Durbin-Watson stat82)86t 2881.883 0.099609X10.543731X2 0.883817t 10.062974t 2(0.764152) (-1.233155) (0.775684)(0.384228)(-0.165767 )R2 0.4947382于是，LM 13* 0.494738 6.431594,該值大于

21、顯著水平為5%自由度為2的 分布的 2臨界值 0.05(2) 5.99,由此判斷原模型存在2階序列相關(guān)性。但t 2的參數(shù)未通過5%勺顯著性檢驗，表明并不存在2階序列相關(guān)性。結(jié)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(guān)性。用廣義差分法進行自相關(guān)的處理：1階廣義差分的估計結(jié)果為：Dependent Variable: YMethod: Least SquaresDate: 06/15/11 Time: 08:41Sample (adjusted): 1996 2009Included observations: 14 after adjustmentsConvergence

22、 achieved after 9 iterationsVariableCoefficient Std. Error t-StatisticProb.C80417.8536441.802.2067480.0518X11.0165820.1180158.6139830.0000X22.5139720.5172634.8601440.0007AR(1)0.8280620.1831504.5212220.0011R-squared0.996394Mean dependent var162196.2Adjusted R-squared0.995312S.D. dependent var89759.08

23、S.E. of regression6145.537Akaike info criterionSum squared resid3.78E+08Schwarz criterionLog likelihood-139.6386F-statisticDurbin-Watson stat1.884308Prob(F-statistic)20.5198020.70238921.06510.000000Inverted AR Roots.83吊 80417.85 1.016582X1 2.5139712X2 0.828062AR(1)(2.206748 )(8.613983 ) ( 4.860144 )

24、(4.521222 )2R 0.996394 R 0.995312 DW. 1.884308式中，AR(1)前的參數(shù)植即為隨機擾動項的1階序列相關(guān)系數(shù)，但拉格朗日檢驗值LM小于顯著水平為5%!由度為1的2分布的臨界值，表明模型干擾項已不存在自相關(guān)性。3、多重共線性由于R2較大且接近于1,而且F 435.8249 F0.05(22)“8，故認為國內(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X1X2Xi10.856612677779084X20.8566126777790841由表中數(shù)據(jù)發(fā)現(xiàn) X 1與X 2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Y與Xi，X2間的回歸

25、：Dependent Variable: YMethod: Least SquaresDate: 06/09/11 Time: 07:57Sample: 1995 2009Included observations: 15Std.VariableCoefficientErrort-StatisticProb.C50215.045669.1318.8576250.0000X11.4357030.05979924.008760.0000R-squared0.977944Mean dependent var155436.0AdjustedR-squared0.976248S.D. dependent

26、 var90369.87S.E.ofAkaikeinforegression13927.56criterion22.04469Sum squared2.52E+09Schwarz criterion22.13910residLog likelihood Durbin-Watson-163.3352F-statistic576.4206stat1.006101Prob(F-statistic)0.000000DependentVariable: YMethod: Least Squares Date: 06/09/11 Time: 17:49Sample: 1995 2009Included o

27、bservations: 15VariablecientCoeffiErrorStd.t-StatisticProb .78482.151890.00C97.215.1670220211.5451.5990.00X2403857.218646000.80031554R-squared34Mean dependent var36.0Adjusted0.78499036R-squared75S.D. dependent var9.87S.E.of41905.24.2regression18Akaike info criterion4777Sum squared2.28E+24.3resid10Schwarz criterion4218Log-179.852.1likelihood583F-statistic0884Durbin-Watson0.86090.00stat07Prob(F-statistic)0007Y? 50215.041.435703X1(8.857625) (24.00876)R 0.977944 DW. 1.006101、Y? 78482.97 11.5454 X2(5.167022) (7.218646)