我國國內(nèi)生產(chǎn)總值(GDP)影響因素的回歸分析

1、精選文檔我國國內(nèi)生產(chǎn)總值（GDP）影響因素的實(shí)證分析摘要：本文以國民收入核算理論為基礎(chǔ)，引入能源消費(fèi)、就業(yè)人數(shù)、居民消費(fèi)水平、社會消費(fèi)品零售總額、進(jìn)出口貿(mào)易總額、外商直接投資（FDI）等解釋變量，運(yùn)用計(jì)量經(jīng)濟(jì)學(xué)分析的方法，分析國內(nèi)生產(chǎn)總值與這些解釋變量之間的關(guān)系。從中國的實(shí)際情況出發(fā)，在利用從1985到2001的年度時(shí)間序列數(shù)據(jù)分析的基礎(chǔ)上，分析各因素對國內(nèi)生產(chǎn)總值的不同程度的影響及其原因，最后得出結(jié)論、提出觀點(diǎn)。關(guān)鍵詞：GDP 影響因素 實(shí)證分析 Eviews一、問題提出：國內(nèi)生產(chǎn)總值（GDP）是指在一定時(shí)期內(nèi)(一個(gè)季度或一年)，一個(gè)國家或地區(qū)的經(jīng)濟(jì)中所生產(chǎn)出的全部最終產(chǎn)品和勞務(wù)的價(jià)值，常被

2、公認(rèn)為衡量國家經(jīng)濟(jì)狀況的最佳指標(biāo)。它不但可反映一個(gè)國家的經(jīng)濟(jì)表現(xiàn)，更可以反映一國的國力與財(cái)富。國民經(jīng)濟(jì)，作為一個(gè)復(fù)雜的綜合體，它的影響因素一直是人們探索和爭論的熱點(diǎn)，根據(jù)西方經(jīng)濟(jì)學(xué)中關(guān)于國民收入核算的經(jīng)典理論，我們建立以GDP為被解釋變量的線性回歸模型，引入能源消費(fèi)、就業(yè)人數(shù)、居民消費(fèi)水平、社會消費(fèi)品零售總額、進(jìn)出口貿(mào)易總額以及外商直接投資等解釋變量，對GDP的影響因素作實(shí)證分析，試圖揭示這幾個(gè)解釋變量對GDP的影響程度。二、樣本數(shù)據(jù)選取及模型設(shè)定：回歸模型設(shè)立如下：Y =0 +1 X1 +2 X2+3 X3+4 X4 +5 X5+6 X6+UY-國內(nèi)生產(chǎn)總值GDP X1-能源消費(fèi)X2-就業(yè)人

3、數(shù)X3-居民消費(fèi)水平X4-社會消費(fèi)品零售總額X5-進(jìn)出口貿(mào)易總額X6-外商直接投資（FDI）U-隨機(jī)擾動項(xiàng)1、2、3、4、5、6為待估參數(shù)。變量采用時(shí)間序列數(shù)據(jù)，具體數(shù)據(jù)(現(xiàn)價(jià)計(jì)算)見表一：表1：年份GDPX1能源消費(fèi)總量（萬噸標(biāo)準(zhǔn)煤）X2就業(yè)人員（萬人）X3居民消費(fèi)水平（元）X4社會消費(fèi)品零售總額（億元）X5進(jìn)出口貿(mào)易總額（億元）X6外商直接投資（FDI）19858964.4766824987343743052066.748. 69198610202.2808505128244749502850.464. 71198711962.5866325278350858203084.286. 131

4、98814928.3929975433463574403822118. 88198916909.296934553297628101.44155.9127. 71199018547.998703567408038300.15560.1166. 79199121617.8103783583608969415.67229.3232. 42199226638.110917059432107010993.79119.6606. 99199334634.411599360220133112462.1112711585. 41199446759.412273761470174616264.720381.9

5、2910. 28199558478.11311766238822362062023499.93133. 38199667884.613894868850264124774.124133.83469. 1199774462.613817369600283427298.926967.23751. 71199878345.213221470637297229152.526849.73763. 93199982067.513011971394313831134.729896.23337. 73200089442.213029772085339734152.639273.23370. 552001959

6、33.313491473025360937595.242183.63880. 09（數(shù)據(jù)來源于中國統(tǒng)計(jì)年鑒。）三、參數(shù)的初步估計(jì)與檢驗(yàn)將第一個(gè)模型的樣本導(dǎo)入Eviews軟件進(jìn)行OLS估計(jì)，得到輸出結(jié)果如下：表2：Dependent Variable: YMethod: Least SquaresDate: 06/17/12 Time: 15:27Sample: 1985 2001Included observations: 17VariableCoefficientStd. Errort-StatisticProb.  C-13277.729457.897-1.403876

7、0.1939X10.0527430.0507771.0387200.3260X20.1338460.2417630.5536240.5933X318.576204.2627744.3577740.0018X40.3772430.4597350.8205670.4331X50.1697060.6896380.2460790.8111X60.0022220.0009742.2801980.0485R-squared0.999741    Mean dependent var44575.16Adjusted R-squared0.999539 

8、60;  S.D. dependent var31239.02S.E. of regression670.8163    Akaike info criterion16.16006Sum squared resid4049950.    Schwarz criterion16.55216Log likelihood-129.3605    F-statistic4955.607Durbin-Watson stat1.833054  &#

9、160; Prob(F-statistic)0.000000將上述回歸結(jié)果整理如下： =-13277.72+0.052743X10.133846X218.57620X30.377243X40.169706X50.002222X6 0.999741， 0.999539， F=4955.607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，很多項(xiàng)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(gè)解釋變量對Y獨(dú)立影響。1.模型檢驗(yàn)：(1)

10、經(jīng)濟(jì)意義檢驗(yàn)由回歸估計(jì)結(jié)果可以看出，能源消費(fèi)、就業(yè)人數(shù)、居民消費(fèi)水平、社會消費(fèi)品零售總額、進(jìn)出口貿(mào)易總額以及FDI與GDP線性正相關(guān)，這與現(xiàn)實(shí)中GDP隨能源消費(fèi)、就業(yè)人數(shù)、居民消費(fèi)水平、社會消費(fèi)品零售總額、進(jìn)出口貿(mào)易總額以及FDI的增加而增長是相符的。(2)統(tǒng)計(jì)推斷檢驗(yàn)從估計(jì)的結(jié)果可以看出，可決系數(shù)R2=0.999741，F(xiàn)統(tǒng)計(jì)量=4955.607，表明模型在整體上擬合地比較理想。系數(shù)顯著性檢驗(yàn)：給定=0.05，X3、X6的t的P值小于給定的顯著性水平，表明居民消費(fèi)水平、FDI對GDP有顯著性影響。2.計(jì)量經(jīng)濟(jì)學(xué)檢驗(yàn)(1)多重共線性的檢驗(yàn) 用Eviews計(jì)算解釋變量之間的簡單相關(guān)系數(shù)：表3：X

11、1X2X3X4X5X6X11.0000000.9426950.9183470.8946260.8877610.945640X20.9426951.0000000.9806900.9776240.9521690.930263X30.9183470.9806901.0000000.9968550.9851270.958071X40.8946260.9776240.9968551.0000000.9866140.936663X50.8877610.9521690.9851270.9866141.0000000.938836X60.9456400.9302630.9580710.9366630.938

12、8361.000000由此可見，模型存在嚴(yán)重的多重共線。模型修正:運(yùn)用OLS方法逐一求Y對各個(gè)解釋變量的回歸，結(jié)合經(jīng)濟(jì)意義和統(tǒng)計(jì)檢驗(yàn)選出擬合效果最好的一元線性回歸方程。過程如下：表4：Dependent Variable: YMethod: Least SquaresDate: 06/17/12 Time: 17:08Sample: 1985 2001Included observations: 17VariableCoefficientStd. Errort-StatisticProb. X11.3543760.1497619.0435770.0000C-108415.317195.21-6

13、.3049670.0000R-squared0.845019 Mean dependent var44575.16Adjusted R-squared0.834687 S.D. dependent var31239.02S.E. of regression12701.37 Akaike info criterion21.84694Sum squared resid2.42E+09 Schwarz criterion21.94496Log likelihood-183.6990 F-statistic81.78629Durbin-Watson stat0.176301 Prob(F-statis

14、tic)0.000000表5：Dependent Variable: YMethod: Least SquaresDate: 06/17/12 Time: 17:09Sample: 1985 2001Included observations: 17VariableCoefficientStd. Errort-StatisticProb. X23.8902240.20673518.817480.0000C-195200.412839.45-15.203180.0000R-squared0.959360 Mean dependent var44575.16Adjusted R-squared0.

15、956651 S.D. dependent var31239.02S.E. of regression6504.094 Akaike info criterion20.50838Sum squared resid6.35E+08 Schwarz criterion20.60641Log likelihood-172.3212 F-statistic354.0975Durbin-Watson stat0.801484 Prob(F-statistic)0.000000表6：Dependent Variable: YMethod: Least SquaresDate: 06/17/12 Time:

16、 17:11Sample: 1985 2001Included observations: 17VariableCoefficientStd. Errort-StatisticProb. X327.106670.178293152.03420.0000C-2402.301367.6774-6.5337200.0000R-squared0.999351 Mean dependent var44575.16Adjusted R-squared0.999308 S.D. dependent var31239.02S.E. of regression821.6280 Akaike info crite

17、rion16.37058Sum squared resid10126089 Schwarz criterion16.46861Log likelihood-137.1500 F-statistic23114.40Durbin-Watson stat1.345961 Prob(F-statistic)0.000000表7：Dependent Variable: YMethod: Least SquaresDate: 06/17/12 Time: 17:10Sample: 1985 2001Included observations: 17VariableCoefficientStd. Error

18、t-StatisticProb. X42.7586460.06065445.482060.0000C-2935.3201237.736-2.3715220.0315R-squared0.992801 Mean dependent var44575.16Adjusted R-squared0.992321 S.D. dependent var31239.02S.E. of regression2737.464 Akaike info criterion18.77758Sum squared resid1.12E+08 Schwarz criterion18.87561Log likelihood

19、-157.6094 F-statistic2068.618Durbin-Watson stat0.372005 Prob(F-statistic)0.000000表8：Dependent Variable: YMethod: Least SquaresDate: 06/17/12 Time: 17:12Sample: 1985 2001Included observations: 17VariableCoefficientStd. Errort-StatisticProb. X52.3014710.09675423.786840.0000C6351.1542040.4923.1125600.0

20、071R-squared0.974174 Mean dependent var44575.16Adjusted R-squared0.972452 S.D. dependent var31239.02S.E. of regression5184.883 Akaike info criterion20.05501Sum squared resid4.03E+08 Schwarz criterion20.15304Log likelihood-168.4676 F-statistic565.8137Durbin-Watson stat1.015958 Prob(F-statistic)0.0000

21、00表9：Dependent Variable: YMethod: Least SquaresDate: 06/17/12 Time: 17:20Sample: 1985 2001Included observations: 17VariableCoefficientStd. Errort-StatisticProb. X618.139351.34119913.524730.0000C11876.313238.2063.6675590.0023R-squared0.924211 Mean dependent var44575.16Adjusted R-squared0.919159 S.D.

22、dependent var31239.02S.E. of regression8882.076 Akaike info criterion21.13159Sum squared resid1.18E+09 Schwarz criterion21.22961Log likelihood-177.6185 F-statistic182.9182Durbin-Watson stat0.444848 Prob(F-statistic)0.000000從以上一系列表的回歸結(jié)果中看出，僅表六中X3與Y的擬合優(yōu)度最大，達(dá)到0.999351，接近于1，所以只保留X3變量。 (2)異方差檢驗(yàn)e2和x3散點(diǎn)圖：由

23、圖可見，可能存在異方差。GoldfieldQuanadt檢驗(yàn)：樣本容量n17，刪除中間1/4的觀測值，大約4個(gè)觀測值，余下不奉分為兩個(gè)樣本區(qū)間：19851990，19962001樣本數(shù)均為6個(gè)，即n1n26。OLS方法求得一下結(jié)果：表10：Dependent Variable: YMethod: Least SquaresDate: 06/18/12 Time: 14:12Sample: 1985 1990Included observations: 6VariableCoefficientStd. Errort-StatisticProb. X323.704061.71213513.8447

24、30.0002C-605.07841054.857-0.5736120.5969R-squared0.979558 Mean dependent var13585.75Adjusted R-squared0.974448 S.D. dependent var3818.663S.E. of regression610.4173 Akaike info criterion15.92736Sum squared resid1490437. Schwarz criterion15.85795Log likelihood-45.78209 F-statistic191.6766Durbin-Watson

25、 stat1.749082 Prob(F-statistic)0.000158表11：Dependent Variable: YMethod: Least SquaresDate: 06/18/12 Time: 14:16Sample: 1996 2001Included observations: 6VariableCoefficientStd. Errort-StatisticProb. X328.228480.69755840.467570.0000C-6110.0402173.479-2.8111790.0483R-squared0.997563 Mean dependent var81355.90Adjusted R-squared0.996954 S.D. dependent var10163.20S.E. of regression560.891