對中國經(jīng)濟(jì)增長影響因素的實(shí)證分析

1、影響中國經(jīng)濟(jì)增長因素的實(shí)證分析學(xué)院：經(jīng)濟(jì)學(xué)院專業(yè)：金融教學(xué)號： 21140731姓名：王月影響中國經(jīng)濟(jì)增長因素的實(shí)證分析摘要：改革開放以來， 中國的社會經(jīng)濟(jì)取得了飛速發(fā)展， 經(jīng)濟(jì)增長速度更是舉世 矚目，已成為世界第二大經(jīng)濟(jì)體，僅次于美國。本文根據(jù)計(jì)量經(jīng)濟(jì)學(xué)、中級宏觀 經(jīng)濟(jì)學(xué)、 Eviews 軟件相關(guān)知識，采用時(shí)間序列數(shù)據(jù)模型和多元線性回歸分析方 法對 1985年-2015 年三十多年間中國經(jīng)濟(jì)增長因素進(jìn)行研究，分析了居民消費(fèi) 價(jià)格指數(shù)、固定資產(chǎn)投資、公共預(yù)算支出、進(jìn)出口總額對國內(nèi)生產(chǎn)總值（GDP）的影響，建立計(jì)量經(jīng)濟(jì)學(xué)模型， 尋求這些變量與國內(nèi)生產(chǎn)總值的數(shù)量關(guān)系， 進(jìn)行 定量分析，對模型進(jìn)行檢

2、驗(yàn)，最終得出結(jié)論。關(guān)鍵詞：CPI、GDP投資、預(yù)算支出、進(jìn)出口、經(jīng)濟(jì)增長一、研究的目的要求（一）經(jīng)濟(jì)增長理論經(jīng)濟(jì)增長是指一個(gè)國家生產(chǎn)商品和勞務(wù)能力的擴(kuò)大。 在實(shí)際核算中， 常以一國 生產(chǎn)的商品和勞務(wù)總量的增加來表示， 即以國民生產(chǎn)總值和國內(nèi)生產(chǎn)總值 （GDP） 的增長來計(jì)算。 經(jīng)濟(jì)增長是經(jīng)濟(jì)學(xué)研究的永恒主題。 古典經(jīng)濟(jì)增長理論以社會財(cái) 富的增長為中心，指出生產(chǎn)勞動是財(cái)富增長的源泉。 現(xiàn)代經(jīng)濟(jì)增長理論認(rèn)為知識、 人力資本、技術(shù)進(jìn)步是經(jīng)濟(jì)增長的主要因素。（二）影響因素的分析在曼昆中級宏觀經(jīng)濟(jì)學(xué)第七版中指出，國民收入核算把GDP分為四大類支出：消費(fèi)（C）、投資（I）、政府購買（G）、凈出口（ NX）

3、。用丫代表GDP有，丫二C+I+G+NX從公式可知，GDP主要受這四方面影響，因此本文用公共預(yù)算支出衡量一部分政 府購買，用全社會固定資產(chǎn)投資總額衡量投資。居民消費(fèi)需求也是經(jīng)濟(jì)增長的主 導(dǎo)因素。經(jīng)濟(jì)增長問題既受各國政府和居民的關(guān)注也是經(jīng)濟(jì)學(xué)理論研究的一個(gè)重 要方面。在過去的幾十年里，我國經(jīng)濟(jì)年均增長率高達(dá)9.6%,綜合國力大大增強(qiáng)， 居民收入水平與生活水平不斷提高，居民的消費(fèi)需求的數(shù)量和質(zhì)量有了很大的提 高。但是,我國目前仍然面臨消費(fèi)需求不足問題。 因此，研究消費(fèi)需求對經(jīng)濟(jì)增長 的影響，并對我國消費(fèi)需求對濟(jì)增長的影響程度進(jìn)行實(shí)證分析，可以更好的理解 消費(fèi)對我國經(jīng)濟(jì)增長的作用。所以，選取了 CP

4、I物價(jià)指數(shù)來進(jìn)行進(jìn)一步分析。同 時(shí)隨著對外經(jīng)濟(jì)加強(qiáng)，進(jìn)出口貿(mào)易已成為中國經(jīng)濟(jì)重要組成部分， 所以進(jìn)出口額 也是值得分析的因素。二、模型設(shè)定與參數(shù)設(shè)計(jì)（一）數(shù)據(jù)的收集中國經(jīng)濟(jì)增長影響因素模型時(shí)間序列表年份GDP億元）CPI(%)全社會固定 資產(chǎn)投資總 額（億元）一般公共預(yù) 算支出（億 元）進(jìn)出口總額（億美元）19859064.6109.32543.192004.25696198610308106.53120.632204.91738.5198712094.2107.33791.692262.18826.5198815095.1111.84753.842491.211027.8198917098.

5、91184410.382823.781116.8199018824.8103.14517.453083.591154.4199121940.2103.45594.553386.621357199227082106.48080.13742.21655.3199335450.4114.712457.884642.31957199448370.3124.116370.335792.622366.2199560146.5117.120019.266823.722808.6199670538.3108.322974.037937.552898.8199778517.3102.824941.119233.

6、563251.6199883505.799.228406.1710798.183239.5199988989.898.629854.7113187.673606.3200098562.2100.432917.7315886.54742.92001108683.4100.737213.4918902.585096.5200211976599.243499.922053.156207.72003135718.9101.255566.6124649.958509.92004160289.7103.970477.4528486.8911545.52005184575.8101.888773.62339

7、30.2814219.12006217246.6101.5109998.1640422.7317604.42007268631104.8137323.9449781.3521765.72008318736.7105.9172828.462592.6625632.62009345046.499.3224598.876299.9322075.42010407137.8103.3278121.989874.16297402011479576.1105.4311485.1109247.7936418.62012532872.1102.6374675.7125952.9738671.2201358319

8、6.7102.6446294.09140212.141589.92014634043.4102512020.65151785.5643030.32015676708103.456200017576829041.4資料來源：中國統(tǒng)計(jì)年鑒、中國政府網(wǎng)（二）模型設(shè)計(jì)為了具體分析各要素對我國經(jīng)濟(jì)增長影響的大小，我們可以用國內(nèi)生產(chǎn)總值（Y）作為對經(jīng)濟(jì)發(fā)展的衡量，代表經(jīng)濟(jì)發(fā)展；用 CPI（XI）消費(fèi)需求；用固定 資產(chǎn)投資總額（X2）衡量資本投入：用預(yù)算支出（X3）去代表政府購買X4代表進(jìn) 出口總額。運(yùn)用這些數(shù)據(jù)進(jìn)行回歸分析。采用的模型如下:Y= B 0+ B 1X1+B 2X2+B 3X3+B 4X4+i

9、其中，Y代表國內(nèi)生產(chǎn)總值，X3代表 預(yù)算支出，X2代表固定資產(chǎn)投資，X1代表消費(fèi)價(jià)格指數(shù)，X4代表進(jìn)出口總額， i代表隨機(jī)擾動項(xiàng)。通過對該模型的回歸分析，得出各個(gè)變量與我國經(jīng)濟(jì)增長的 變動關(guān)系。三、模型檢驗(yàn)及修正1. 可以得到如下回歸分析結(jié)果：Dependent Variable: YMethod: Least SquaresDate: 06/20/16 Time: 08:55Sample: 1985 2015Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C83300.8048323.231.7238

10、250.0966X1-606.6547443.4283-1.3681010.1830X2-0.3189730.225021-1.4175230.1682X34.1766020.8022165.2063310.0000X43.1914390.5848195.4571420.0000R-squared0.996436Mean dependent var189284.4Adjusted R -squared0.995888S.D. dependent var204842.6S.E. of regression13135.92Akaike info criterion21.95078Sum squar

11、ed resid4.49E+09Schwarz criterion22.18207Log likelihood-335.2371 Hannan -Quinn criter.22.02617F-statistic1817.315 Durbin -Watson stat0.322178Prob(F - statistic)0.000000Y=833300.8606.6547 B 1X10.318973 B 2X2+4.18 B 3X3+3.19 B 4X4 R2=0.996436?=0.995888 F=1817.315從數(shù)據(jù)可以看出模型擬合優(yōu)度很好。分別做出丫與XXXX52. 多重共線性檢驗(yàn)X1

12、X2X3X4X11.000000-0.288341-0.314340-0.324767X2-0.2883411.0000000.9970620.932732X3-0.3143400.9970621.0000000.945955X4-0.3247670.9327320.9459551.000000從上面結(jié)果來看，X2, X3, X4之間存在高度相關(guān)性,間的回歸，結(jié)果如下:Dependent Variable: YMethod: Least SquaresDate: 06/20/16Time: 09:32Sample: 1985 2015Included observations: 31Varia

13、bleCoefficientStd. Errort-StatisticProb.C1400826.620793.22.2565090.0317X1-11490.485878.258-1.9547420.0603R-squared0.116420Mean dependent var189284.4Adjusted R -squared0.085952S.D. dependent var204842.6S.E. of regression195841.6Akaike info criterion27.27034Sum squared resid1.11E+12Schwarz criterion27

14、.36286Log likelihood-420.6903Hannan -Quinn criter.27.30050F-statistic3.821017Durbin -Watson stat0.119399Prob(F - statistic)0.060314Dependent Variable: YMethod: Least SquaresDate: 06/20/16Time:09:34Sample: 1985 2015Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C43248.597332.91

15、65.8978710.0000X21.2404290.03685333.659130.0000R-squared0.975042Mean dependent var189284.4Adjusted R -squared0.974181S.D. dependent var204842.6S.E. of regression32914.68Akaike info criterion23.70357Sum squared resid3.14E+10Schwarz criterion23.79608Log likelihood-365.4053Hannan -Quinn criter.23.73372

16、F-statistic1132.937Durbin -Watson stat0.209259Prob(F - statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 06/20/16 Time: 20:01Sample: 1985 2015Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C28127.894993.0775.6333790.0000X34.0086720.07782951.506430.0000R-squared

17、0.989187Mean dependent var189284.4Adjusted R -squared0.988814S.D. dependent var204842.6S.E. of regression21665.00Akaike info criterion22.86712Sum squared resid1.36E+10Schwarz criterion22.95964Log likelihood-352.4404Hannan -Quinn criter.22.89728F-statistic2652.912Durbin -Watson stat0.339632Prob(F - s

18、tatistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 06/20/16Time: 20:02Sample: 1985 2015Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C13363.3212872.161.0381560.3078X414.180120.69533820.393120.0000R-squared0.934814Mean dependent var189284.4Adjusted R -squared0.93

19、2566S.D. dependent var204842.6Sum squared resid8.21E+10Schwarz criterion24.75612Log likelihood-380.2859Hannan -Quinn criter.24.69376F-statistic415.8795Durbin -Watson stat0.847523Prob(F - statistic)0.000000從數(shù)據(jù)可以看出丫與X3回歸具有最大的可決系數(shù)，因此選 丫=28127.89+4.009X3作為初始的回歸模型，逐步回歸Dependent Variable: YMethod: Least S

20、quaresDate: 06/20/16 Time: 20:26Sample: 1985 2015Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C142300.971534.191.9892710.0565X1-1067.525667.3011-1.5997650.1209X33.9685100.07986549.689990.0000R-squared0.990092Mean dependent var189284.4Adjusted R -squared0.989385S.D. dependent

21、 var204842.6S.E. of regression21105.05Akaike info criterion22.84418Sum squared resid1.25E+10Schwarz criterion22.98295Log likelihood-351.0848Hannan -Quinn criter.22.88941F-statistic1399.055Durbin -Watson stat0.471700Prob(F - statistic)0.000000引X1模型？2提高且變量通過了顯著水平為10%的t檢驗(yàn)但參數(shù)符號與經(jīng)濟(jì)意義 不符Dependent Variable

22、: YMethod: Least SquaresDate: 06/20/16 Time: 20:39Sample: 1985 2015Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C18313.315238.7093.4957670.0016X2-0.9021900.273468-3.2990650.0026X36.8948350.8774217.8580690.0000R-squared0.992213Mean dependent var189284.4Adjusted R -squared0.99

23、1657S.D. dependent var204842.6S.E. of regression18709.98Akaike info criterion22.60327Sum squared resid9.80E+09Schwarz criterion22.74204Log likelihood-347.3506Hannan -Quinn criter.22.64850F-statistic1783.983Durbin -Watson stat1.004618Prob(F - statistic)0.000000X2同X1被舍棄Dependent Variable: YMethod: Lea

24、st SquaresDate: 06/20/16 Time: 20:41Sample: 1985 2015Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C21030.713414.0226.1600970.0000X33.0649690.15526819.739900.0000X43.6301200.5649856.4251580.0000R-squared0.995630Mean dependent var189284.4Adjusted R -squared0.995318S.D. depende

25、nt var204842.6S.E. of regression14016.69Akaike info criterion22.02565Sum squared resid5.50E+09Schwarz criterion22.16442Log likelihood-338.3976Hannan -Quinn criter.22.07089F-statistic3189.620Durbin -Watson stat0.189253Prob(F - statistic)0.000000引入X4模型？2變大且通過了顯著性檢驗(yàn)水平為 10%的t檢驗(yàn)所以最終擬合結(jié)果為 Y=21030.71+3.065

26、X3+3.630X43. 異方差性檢驗(yàn)X3與殘差散點(diǎn)圖從散點(diǎn)圖可以看出二者沒有異方差性做殘差X4散點(diǎn)圖20,000010,00020,00030,00040,00050,00015,000 -10,000 _5,000 _0-5,000-10,000-15,000-20,000-25,000X4Heteroskedasticity Test: WhiteF-statistic2.189999Prob.F(5,25)0.0875Obs*R -squared9.442279Prob.Chi-Square(5)0.0927Scaled explained SS1.688973Prob.Chi-Squ

27、are(5)0.8903Test Equation:Dependent Variable: RESIDEMethod: Least SquaresDate: 06/20/16 Time: 21:15Sample: 1985 2015Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C2.75E+087.6809430.0000X33095.2528924.4070.3468300.7316X3A20.0903030.0541421.6678940.1078X3*X4-0.9053370.571022-1.

28、5854670.1254X4-34791.9028733.42-1.2108510.2373X4A22.5611311.5096231.6965370.10222R-squared0.304590Mean dependent var1.77E+08Adjusted R -squared0.165508S.D. dependent var1.19E+08S.E. of regression1.09E+08Akaike info criterion40.02581Sum squared resid2.98E+17Schwarz criterion40.30335Log likelihood-614

29、.4000Hannan -Quinn criter.40.11628F-statistic2.189999Durbin -Watson stat0.932391Prob(F - statistic)0.087469由數(shù)據(jù)可知X3,X4在顯著水平為5%水平下都不顯著接受原假設(shè)所以不存在異方 差4.D.W.檢驗(yàn)已知：DW=0.189,查表得dL=1.35, dU=1.49。由此可知，存在相關(guān)性。Breusch -Godfrey Serial Correlation LM Test:S.E. of regression6319.872 Akaike info criterion20.46070S.E

30、. of regression6319.872 Akaike info criterion20.46070F-statistic110.7312 Prob. F(1,27)0.0000S.E. of regression6319.872 Akaike info criterion20.46070S.E. of regression6319.872 Akaike info criterion20.46070Obs*R -squared24.92295 Prob. Chi -Square(1)0.0000Test Equation:Dependent Variable: RESIDMethod:

31、Least SquaresDate: 06/20/16 Time: 21:33Sample: 1985 2015Included observations: 31Presample missing value lagged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.C1057.7181542.5990.6856730.4988X30.1990460.0725182.7447830.0106X4-0.7020570.263333-2.6660370.0128RESID( -1)0.9407670.0894

32、0210.522890.0000R-squared0.803966Mean dependent var0.000000Adjusted R -squared0.782184S.D. dependent var13541.41S.E. of regression6319.872 Akaike info criterion20.46070Sum squared resid1.08E+09Schwarz criterion20.64573Log likelihood-313.1408Hannan -Quinn criter.20.52101F-statistic36.91041Durbin -Wat

33、son stat0.833123Prob(F - statistic)0.000000LM=30*0.78=23.4大于顯著性水平為5%自由度為1的2分布的臨界值為3.84, 所以存在一階序列相關(guān)性Breusch -Godfrey Serial Correlation LM Test:F-statistic67.96992Prob. F(2,26)0.0000Obs*R -squared26.02284Prob. Chi -Square(2)0.0000Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 06/20

34、/16 Time: 21:46Sample: 1985 2015Included observations: 31Presample missing value lagged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.X30.1396350.0713231.9577890.0611X4-0.4411530.266130-1.6576600.1094C315.13741455.9710.2164450.8303RESID( -1)1.3574780.1924067.0552770.0000RESID( -

35、2)-0.4885490.203815-2.3970210.0240R-squared0.839447Mean dependent var-9.74E -12Adjusted R -squared0.814746S.D. dependent var13541.41S.E. of regression5828.377Akaike info criterion20.32555Sum squared resid8.83E+08Schwarz criterion20.55684Log likelihood-310.0461Hannan -Quinn criter.20.40095F-statistic

36、33.98496Durbin -Watson stat1.621557Prob(F - statistic)0.000000LM顯著但et-2不顯著不存在二階序列相關(guān)性Dependent Variable: YMethod: Least SquaresDate: 06/20/16 Time: 21:55Sample (adjusted): 1986 2015Included observations: 30 after adjustmentsConvergence achieved after 16 iterationsVariableCoefficientStd. Errort-StatisticProb.X33.0203180.19775315.273210.0000X42.5095860.24221110.361150.0000C158613.0503632.20.3149380.7553AR(1)0.9806480.06939614.131270.0000R-squared0.