關(guān)于GDP與其他經(jīng)濟因素關(guān)系的計量分析.doc

關(guān)于GDP與其他經(jīng)濟因素關(guān)系的計量分析【摘要】本文主要是以GDP與其他經(jīng)濟因素關(guān)系建立模型，想通過計量經(jīng)濟學(xué)的研究手段來闡述影響GDP的因素，但因水平有限，中間不乏缺陷，還希望大家多多見諒。GDP是指一個國家或地區(qū)范圍內(nèi)的所有常住單位，在一定時期內(nèi)生產(chǎn)最終產(chǎn)品和提供勞務(wù)價值的總和。GDP的增長對于一個國家有著十分重要的意義。它是衡量一國在過去的一年里所創(chuàng)造的勞動成果的重要指標，而研究它的影響因素不僅可以很好的了解GDP的經(jīng)濟內(nèi)涵，而且還有利于我們根據(jù)這些因素對GDP影響大小來制定工作的重點以便更好的促進國民經(jīng)濟的發(fā)展。我把GDP的影響因素分為以下四個因素： x2 能源消費總量（單位：萬噸標準煤） x3 進出口貿(mào)易總額（單位：億元） x4 固定資產(chǎn)投資（單位：億元）x5貨幣供應(yīng)量（單位：億元） 隨機擾動項。數(shù)據(jù)如下：obsX2X3X4X5Y1990 98703.00 5560.100 4516.900 15293.40 18667.801991 103783.0 7225.800 5594.500 19349.90 21781.501992 109170.0 9119.600 8080.100 25402.20 26923.501993 115993.0 11271.00 13072.30 34879.80 35333.901994 122737.0 20381.90 17042.10 46923.50 48197.901995 131176.0 23499.90 20019.30 60750.50 60793.701996 138948.0 24133.80 22913.50 76094.90 71176.601997 137798.0 26967.20 24941.10 90995.30 78973.001998 132214.0 36849.70 28406.20 104498.5 84402.301999 133831.0 29896.20 29854.70 119897.9 89677.102000 138553.0 39273.20 32917.70 134610.4 99214.602001 143199.0 42183.60 37213.49 158301.9 109655.22002 151797.0 51378.20 43499.91 185007.0 120332.72003 174990.0 70483.50 55566.60 21222.80 135822.82004 203227.0 95539.10 70477.40 254107.0 159878.32005 224682.0 116921.8 88773.60 298755.7 183217.42006 246270.0 140971.4 109998.1 345603.6 211923.52007 265583.0 166740.2 137324.0 403442.2 249529.9一、建立模型：根據(jù)GDP的定義,GDP=消費+投資+凈出口，而x2，x3 ，x4，x5與消費，投資及凈出口有著一定的線性相關(guān)關(guān)系，基于數(shù)據(jù)的有限和操作的方便，我們把模型設(shè)成以下形式：Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:16Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C-38947.5460558.91-0.6431350.5313X20.6449730.5911301.0910850.2950X3-0.6747281.030052-0.6550420.5239X41.6084601.1480351.4010560.1846X50.0548000.0759730.7213040.4835R-squared0.968877 Mean dependent var100305.7Adjusted R-squared0.959301 S.D. dependent var66546.65S.E. of regression13425.08 Akaike info criterion22.07777Sum squared resid2.34E+09 Schwarz criterion22.32510Log likelihood-193.6999 F-statistic101.1758Durbin-Watson stat0.255805 Prob(F-statistic)0.000000將上述的回歸結(jié)果整理如下：54320.054800X1.608460X0.674728X-0.644973X-38947.54+=Y0.968877 0.959301 F=101.1758從回歸結(jié)果看，可決系數(shù)很高，F(xiàn)值很大，但在顯著性水平下，各項的回歸系數(shù)都不顯著，因此回歸方程不能投入使用；該模型很可能存在多重共線性。和F值大反映了模型中各解釋變量聯(lián)合對Y的影響力顯著，而t值小于臨界值恰好反映了由于解釋變量共線性的作用，使得不能分解出各個解釋變量對Y獨立影響。二、多重共線性的檢驗用Eviews計算解釋變量之間的簡單相關(guān)系數(shù)：X2X3X4X5X2 1.000000 0.993682 0.991121 0.923330X3 0.993682 1.000000 0.996958 0.929735X4 0.991121 0.996958 1.000000 0.933410X5 0.923330 0.929735 0.933410 1.000000由相關(guān)系數(shù)矩陣可以看出，各解釋變量相互之間的相關(guān)關(guān)系系數(shù)較高，證實確實存在嚴重多重共線性。同時也證明了，雖然整體上擬合較好，但不能分解出各個解釋變量對Y獨立影響。三、模型修正（1）運用OLS方法逐一求Y對各個解釋變量的回歸，結(jié)合經(jīng)濟意義和統(tǒng)計檢驗選出擬合效果最好的一元線性回歸方程。Eviews過程如下：Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:45Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C-103838.411106.77-9.3491110.0000X21.3252980.06886819.243950.0000R-squared0.958585 Mean dependent var100305.7Adjusted R-squared0.955996 S.D. dependent var66546.65S.E. of regression13959.55 Akaike info criterion22.03016Sum squared resid3.12E+09 Schwarz criterion22.12909Log likelihood-196.2714 F-statistic370.3298Durbin-Watson stat0.290962 Prob(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:46Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C31237.784890.4606.3874940.0000X31.3536880.07065919.158010.0000R-squared0.958228 Mean dependent var100305.7Adjusted R-squared0.955617 S.D. dependent var66546.65S.E. of regression14019.57 Akaike info criterion22.03874Sum squared resid3.14E+09 Schwarz criterion22.13767Log likelihood-196.3486 F-statistic367.0293Durbin-Watson stat0.256686 Prob(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:48Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C27509.404610.2185.9670490.0000X41.7466180.08334320.957000.0000R-squared0.964850 Mean dependent var100305.7Adjusted R-squared0.962653 S.D. dependent var66546.65S.E. of regression12860.31 Akaike info criterion21.86612Sum squared resid2.65E+09 Schwarz criterion21.96505Log likelihood-194.7951 F-statistic439.1958Durbin-Watson stat0.171800 Prob(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:49Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C31482.029092.6503.4623590.0032X50.5172250.05147610.047870.0000R-squared0.863201 Mean dependent var100305.7Adjusted R-squared0.854651 S.D. dependent var66546.65S.E. of regression25370.71 Akaike info criterion23.22502Sum squared resid1.03E+10 Schwarz criterion23.32395Log likelihood-207.0252 F-statistic100.9597Durbin-Watson stat1.896935 Prob(F-statistic)0.000000其中，加入X4方程0.962653為最大，故以X4為基礎(chǔ)，順次加入其他變量逐步回歸。（2）逐步回歸，將其余解釋變量逐一代入上式Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:52Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C-14713.1648169.12-0.3054480.7642X20.4231870.4805400.8806480.3924X41.1956480.6312461.8941070.0777R-squared0.966578 Mean dependent var100305.7Adjusted R-squared0.962122 S.D. dependent var66546.65S.E. of regression12951.48 Akaike info criterion21.92682Sum squared resid2.52E+09 Schwarz criterion22.07521Log likelihood-194.3414 F-statistic216.9050Durbin-Watson stat0.145011 Prob(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:53Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C27296.175188.8485.2605450.0001X3-0.0886100.858638-0.1031980.9192X41.8602081.1040641.6848740.1127R-squared0.964875 Mean dependent var100305.7Adjusted R-squared0.960192 S.D. dependent var66546.65S.E. of regression13277.36 Akaike info criterion21.97652Sum squared resid2.64E+09 Schwarz criterion22.12492Log likelihood-194.7887 F-statistic206.0245Durbin-Watson stat0.179436 Prob(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:54Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C27043.904727.0335.7211150.0000X41.5889870.2358966.7359610.0000X50.0528720.0738540.7158930.4851R-squared0.966012 Mean dependent var100305.7Adjusted R-squared0.961480 S.D. dependent var66546.65S.E. of regression13060.83 Akaike info criterion21.94363Sum squared resid2.56E+09 Schwarz criterion22.09203Log likelihood-194.4927 F-statistic213.1633Durbin-Watson stat0.203890 Prob(F-statistic)0.000000再次依據(jù)調(diào)整后的可決系數(shù)最大原則，選取調(diào)整后可決系數(shù)最大所對應(yīng)的解釋變量作為新進入模型的候選變量，將這個候選變量的調(diào)整后可決系數(shù)與上一步中進入模型解釋變量的調(diào)整后可決系數(shù)加以比較，若是大于上一步的調(diào)整后可決系數(shù)，則將候選變量加入模型，若是小于，則將停止逐步回歸。經(jīng)查X2的調(diào)整后可決系數(shù)最大，故X2作為第二個解釋變量進入回歸模型。（3） 繼續(xù)逐步回歸Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:56Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C-37401.6559475.04-0.6288630.5396X20.6341080.5807251.0919250.2933X3-0.6832711.012184-0.6750470.5106X41.7969351.0985831.6356850.1242R-squared0.967632 Mean dependent var4100305.7Adjusted R-squared0.960696 S.D. dependent var66546.65S.E. of regression13193.06 Akaike info criterion22.00590Sum squared resid2.44E+09 Schwarz criterion22.20376Log likelihood-194.0531 F-statistic139.5079Durbin-Watson stat0.215166 Prob(F-statistic)0.0000004Dependent Variable: YMethod: Least SquaresDate: 12/22/09 Time: 22:574Sample: 1990 2007Included observations: 18VariableCoefficientStd. Errort-StatisticProb. C-16561.8548964.90-0.3382390.7402X20.4368290.4881940.8947870.3860X41.01