《我國財政收入影響因素分析》計量經(jīng)濟學(xué)論文(eviews分析)

1、我國財政收入影響因素分析班級： 姓名： 學(xué)號： 指導(dǎo)教師： 完成時間：摘要：對我國財政收入影響因素進行了定量分析， 建立了數(shù) 學(xué)模型，并提出了提高我國財政收入質(zhì)量的政策建議。關(guān)鍵詞 ：財政收入 實證分析 影響因素一、 引言 財政收入對于國民經(jīng)濟的運行及社會發(fā)展具有重要影響。首先， 它是一個國家各項收入得以實現(xiàn)的物質(zhì)保證。 一個國家財政收入規(guī)模 大小往往是衡量其經(jīng)濟實力的重要標志。 其次，財政收入是國家對經(jīng) 濟實行宏觀調(diào)控的重要經(jīng)濟杠桿。 宏觀調(diào)控的首要問題是社會總需求 與總供給的平衡問題， 實現(xiàn)社會總需求與總供給的平衡， 包括總量上 的平衡和結(jié)構(gòu)上的平衡兩個層次的內(nèi)容。 財政收入的杠桿既可通過

2、增 收和減收來發(fā)揮總量調(diào)控作用， 也可通過對不同財政資金繳納者的財 政負擔大小的調(diào)整，來發(fā)揮結(jié)構(gòu)調(diào)整的作用。此外，財政收入分配也 是調(diào)整國民收入初次分配格局， 實現(xiàn)社會財富公平合理分配的主要工 具。在我國，財政收入的主體是稅收收入。因此，在稅收體制及政策 不變的情況下， 財政收入會隨著經(jīng)濟繁榮而增加， 隨著經(jīng)濟衰退而下 降。我國的財政收入主要包括稅收、 國有經(jīng)濟收入、 債務(wù)收入以及其 他收入四種形式，因此，財政收入會受到不同因素的影響。從國民經(jīng) 濟部門結(jié)構(gòu)看， 財政收入又表現(xiàn)為來自各經(jīng)濟部門的收入。 財政收入 的部門構(gòu)成就是在財政收入中， 由來自國民經(jīng)濟各部門的收入所占的 不同比例來表現(xiàn)財政收

3、入來源的結(jié)構(gòu)， 它體現(xiàn)國民經(jīng)濟各部門與財政收入的關(guān)系。我國財政收入主要來自于工業(yè)、農(nóng)業(yè)、商業(yè)、交通運輸和服務(wù)業(yè)等部門。因此，本文認為財政收入主要受到總稅收收入、國內(nèi)生產(chǎn)總值、 其他收入和就業(yè)人口總數(shù)的影響。二、 預(yù)設(shè)模型令財政收入 Y（億元）為被解釋變量，總稅收收入 X1 （億元）、 國內(nèi)生產(chǎn)總值 X2（億元）、其他收入 X3 （億元）、就業(yè)人口總數(shù)為 X4（萬人）為解釋變量，據(jù)此建立回歸模型。二、 數(shù)據(jù)收集從 2010 中國統(tǒng)計年鑒得到 1990-2009年每年的財政收入、 總稅收收入、國內(nèi)生產(chǎn)總值工、 其他收入和就業(yè)人口總數(shù)的統(tǒng)計數(shù)據(jù)如下：obs財政收入 Y總稅收收入 X1國內(nèi)生產(chǎn)總值 X

4、2其他收入 X3就業(yè)人口總數(shù) X419902937.12821.8618667.8299.536474919913149.482990.1721781.5240.16549119923483.373296.9126923.5265.156615219934348.954255.335333.9191.046680819945218.15126.8848197.9280.186745519956242.26038.0460793.7396.196806519967407.996909.8271176.6724.666895019978651.148234.0478973682.369820199

5、89875.959262.884402.3833.370637199911444.0810682.5889677.1925.4371394200013395.2312581.5199214.6944.9872085200116386.0415301.38109655.21218.173025200218903.6417636.45120332.71328.7473740200321715.2520017.31135822.81691.9374432200426396.4724165.68159878.32148.3275200200531649.2928778.54184937.42707.8

6、375825200638760.234804.35216314.43683.8576400200751321.7845621.97265810.34457.9676990200861330.3554223.79314045.45552.46774802009 68518.3 59521.59三、 模型建立1、 散點圖分析340506.97215.7277995350000300000250000200000150000X1X2X3X4100000500000 100003000050000700002、 單因素或多變量間關(guān)系分析YX10.9989134611X20.9934790452X30.

7、8770144886X40.9836027198Y1478539080479564415080.99891346110.99374026770.85563773470.9849352965X14785311846944782934920.99347904520.99374026770.85618358020.9862411656X29080418469128471804590.87701448860.85563773470.85618358020.8109403346X37956444782284711503810.98360271980.98493529650.98624116560.810

8、9403346X4415089349280459503811由散點圖分析和變量間關(guān)系分析可以看出被解釋變量財政收入Y 與解釋變量總稅收收入 X1、國內(nèi)生產(chǎn)總值 X2、其他收入 X3 、就 業(yè)人口總數(shù) X4 呈線性關(guān)系，因此該回歸模型設(shè)為：Y 0 1X1 2X 2 3X 3 4X 43、 模型預(yù)模擬由 eviews 做 ols 回歸得到結(jié)果：Dependent Variable: YMethod: Least SquaresDate: 11/14/11Time: 17:51Sample: 1990 2009 Included observations: 20VariableCoefficient

9、Std. Error t-StatisticProb.C7299.5231691.814 4.3146140.0006X11.0628020.021108 50.349720.0000X20.0017700.004528 0.3910070.7013X30.8733690.119806 7.2898520.0000X4-0.1159750.026580 -4.3631600.0006R-squared0.999978Mean dependent var20556.75Adjusted R-squared0.999972S.D. dependent var19987.03S.E. of regr

10、ession106.6264Akaike info criterion12.38886Sum squared resid170537.9Schwarz criterion12.63779Log likelihood-118.8886F-statistic166897.9Durbin-Watson stat1.496517Prob(F-statistic)0.000000Y7299.5231.062802X10.001770X 20.873369X30.115975X 4(4.314614)( 50.34972 )( 0.391007)( 7.289852)( -4.363160)R20.999

11、9782R 0.999972 F166897.9 D.W 1.496517四、 模型檢驗1.計量經(jīng)濟學(xué)意義檢驗多重共線性檢驗與解決求相關(guān)系數(shù)矩陣，得到：Correlation MatrixYX1X2X3X40.99891346110.99347904520.87701448860.98360271981478539080479564415080.998913461110.99374026770.85563773470.9849352965478531846944782934920.99347904520.99374026770.85618358020.986241165690804184691

12、28471804590.87701448860.85563773470.85618358020.81094033467956444782284711503810.98360271980.98493529650.98624116560.8109403346415089349280459503811發(fā)現(xiàn)模型存在多重共線性。接下來運用逐步回歸法對模型進行 修正: 將各個解釋變量分別加入模型 ,進行一元回歸 :作Y 與X1的回歸，結(jié)果如下 :Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:02Sample: 1990

13、2009Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C-755.6610145.2330 -5.2030940.0001X11.1449940.005760 198.79310.0000R-squared0.999545Mean dependent var20556.75Adjusted R-squared0.999519S.D. dependent var19987.03S.E. of regression438.1521Akaike info criterion15.09765Sum squa

14、red resid3455590.Schwarz criterion15.19722Log likelihood-148.9765F-statistic39518.70Durbin-Watson stat0.475046Prob(F-statistic)0.000000作Y 與X2的回歸，結(jié)果如下Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:06Sample: 1990 2009 Included observations: 20VariableCoefficientStd. Errort-Statistic

15、Prob.C-5222.077861.2067-6.0636740.0000X20.2076890.00554837.432670.0000R-squared0.987317Mean dependent var20556.75Adjusted R-squared0.986612S.D. dependent var19987.03S.E. of regression2312.610Akaike info criterion18.42478Sum squared resid96267005Schwarz criterion18.52435Log likelihood-182.2478F-stati

16、stic1401.205Durbin-Watson stat0.188013Prob(F-statistic)0.000000作Y 與X3的回歸，結(jié)果如下Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:08Sample: 1990 2009 Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C2607.879773.9988 3.3693580.0034X310.030730.294311 34.082090.0000R

17、-squared0.984740Mean dependent var20556.75Adjusted R-squared0.983893S.D. dependent var19987.03S.E. of regression2536.645Akaike info criterion18.60971Sum squared resid1.16E+08Schwarz criterion18.70929Log likelihood-184.0971F-statistic1161.589Durbin-Watson stat1.194389Prob(F-statistic)0.000000作Y 與X4的回

18、歸，結(jié)果如下 Dependent Variable: Y Method: Least SquaresDate: 11/22/11 Time: 23:08Sample: 1990 2009 Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C-272959.337203.65 -7.3368940.0000X44.0974030.518467 7.9029180.0000R-squared0.776276Mean dependent var20556.75Adjusted R-squared0.76384

19、6S.D. dependent var19987.03S.E. of regression9712.824Akaike info criterion21.29492Sum squared resid1.70E+09Schwarz criterion21.39449Log likelihood-210.9492F-statistic62.45611Durbin-Watson stat0.157356Prob(F-statistic)0.000000 依據(jù)可決系數(shù)最大的原則選取 X1 作為進入回歸模型的第一個解釋 變量 ,再依次將其余變量分別代入回歸得 :作Y與X1、X2的回歸，結(jié)果如下Depen

20、dent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:09Sample: 1990 2009Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C-188.4285239.0743 -0.7881590.4415X11.2815940.049472 25.905680.0000X2-0.0250550.009029 -2.7749080.0130R-squared0.999687Mean dependent var20556.75Adju

21、sted R-squared0.999650S.D. dependent var19987.03S.E. of regression374.0345Akaike info criterion14.82405Sum squared resid2378330.Schwarz criterion14.97341Log likelihood-145.2405F-statistic27118.20Durbin-Watson stat0.683510Prob(F-statistic)0.000000作Y與X1、X3的回歸，結(jié)果如下Dependent Variable: YMethod: Least Squ

22、aresDate: 11/22/11 Time: 23:10Sample: 1990 2009Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C-351.105483.15053 -4.2225270.0006X10.9928130.018707 53.071960.0000X31.3569360.165109 8.2184100.0000R-squared0.999908Mean dependent var20556.75Adjusted R-squared0.999898S.D. dependen

23、t var19987.03S.E. of regression202.1735Akaike info criterion13.59361Sum squared resid694859.9Schwarz criterion13.74297Log likelihood-132.9361F-statistic92839.33Durbin-Watson stat1.177765Prob(F-statistic)0.000000作Y與X1、X4的回歸，結(jié)果如下 Dependent Variable: Y Method: Least SquaresDate: 11/22/11 Time: 23:10 Sa

24、mple: 1990 2009Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C11853.461824.522 6.4967480.0000X11.1858860.006645 178.46080.0000X4-0.1866450.026984 -6.9170030.0000R-squared0.999881Mean dependent var20556.75Adjusted R-squared0.999867S.D. dependent var19987.03S.E. of regression2

25、30.8464Akaike info criterion13.85886Sum squared resid905931.0Schwarz criterion14.00822Log likelihood-135.5886F-statistic71206.90Durbin-Watson stat1.459938Prob(F-statistic)0.000000 在滿足經(jīng)濟意義和可決系數(shù)的條件下選取 X3 作為進入模型的第二 個解釋變量 ,再次進行回歸則 :作Y與X1、X3、X2的回歸，結(jié)果如下Dependent Variable: YMethod: Least SquaresDate: 11/22

26、/11Time: 23:13Sample: 1990 2009Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C-76.04458100.1724 -0.7591370.4588X11.0859240.029801 36.438810.0000X31.2108530.133444 9.0738770.0000X2-0.0140730.003944 -3.5679010.0026R-squared0.999949Mean dependent var20556.75Adjusted R-squared0.

27、999939S.D. dependent var19987.03S.E. of regression155.5183Akaike info criterion13.10826Sum squared resid386975.0Schwarz criterion13.30741Log likelihood-127.0826F-statistic104602.9Durbin-Watson stat1.196933Prob(F-statistic)0.000000作Y與X1、X3、X4的回歸，結(jié)果如下Dependent Variable: YMethod: Least SquaresDate: 11/

28、22/11Time: 23:13Sample: 1990 2009Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C6781.7641024.745 6.6180030.0000X11.0686420.014514 73.627640.0000X30.8910690.107949 8.2545510.0000X4-0.1076390.015451 -6.9666750.0000R-squared0.999977Mean dependent var20556.75Adjusted R-squared0.

29、999973S.D. dependent var19987.03S.E. of regression103.7654Akaike info criterion12.29900Sum squared resid172276.1Schwarz criterion12.49814Log likelihood-118.9900F-statistic234970.9Durbin-Watson stat1.451447Prob(F-statistic)0.000000 可見加入其余任何一個變量都會導(dǎo)致系數(shù)符號與經(jīng)濟意義不符,故最終修正后的回歸模型為Dependent Variable: YMethod:

30、Least SquaresDate: 11/30/11Time: 12:18Sample: 1990 2009Included observations: 20VariableCoefficientStd. Error t-StatisticProb.C-351.105483.15053 -4.2225270.0006X10.9928130.018707 53.071960.0000X31.3569360.165109 8.2184100.0000R-squared0.999908Mean dependent var20556.75Adjusted R-squared0.999898S.D.

31、dependent var19987.03S.E. of regression202.1735Akaike info criterion13.59361Sum squared resid694859.9Schwarz criterion13.74297Log likelihood-132.9361F-statistic92839.33Durbin-Watson stat1.177765 Prob(F-statistic)0.000000Y 351.1054 0.992813X1 1.356936 X 3 (-4.222527)( 53.07196)( 8.218410)22 R2 0.9999

32、08 R 0.999898 F 92839.33 D.W 1.177765異方差檢驗與修正 圖示法 ee與 X1的散點圖如下：20000016000012000080000400000 10000 20000 30000 40000 50000 600000X1說明 ee與 X1存在單調(diào)遞增型異方差性。10.6889310.718727947.5750.000000ee與 X3的散點圖如下：200000160000120000800004000000 2000 4000 6000 8000X3說明 ee與 X3存在單調(diào)遞增型異方差性。 G-Q 檢驗對 20 組數(shù)據(jù)剔除掉中間四組剩下的進行分組后

33、，第一組( 1990-1997 )數(shù)據(jù)的回歸結(jié)果：Dependent Variable: YMethod: Least SquaresDate: 11/30/11 Time: 12:54Sample: 1990 1997Included observations: 8VariableCoefficientStd. Errort-StatisticProb.X10.9841230.01625560.543200.0000X30.8515180.1566885.4344720.0029C-28.3427545.36993-0.6247030.5596R-squared0.999686Mean de

34、pendent var5179.791Adjusted R-squared0.999560S.D. dependent var2099.840S.E. of regression44.05899Akaike info criterionSum squared resid9705.972Schwarz criterionLog likelihood-39.75573F-statisticDurbin-Watson stat1.663630Prob(F-statistic)殘差平方和 RSS1=9705.972第二組( 2002-2009 )數(shù)據(jù)的回歸結(jié)果：Dependent Variable:

35、YMethod: Least SquaresDate: 11/30/11 Time: 12:55Sample: 2002 2009Included observations: 8VariableCoefficientStd. Errort-StatisticProb.X11.0664040.02774738.433210.0000X30.8472280.2151143.9385030.0110C-1184.159261.8258-4.5226980.0063R-squared0.999932Mean dependent var39824.41Adjusted R-squared0.999905

36、S.D. dependent var18639.16S.E. of regression182.0047Akaike info criterion13.52594Sum squared resid165628.5Schwarz criterion13.55573Log likelihood-51.10375F-statistic36705.08Durbin-Watson stat1.326122Prob(F-statistic)0.000000殘差平方和 RSS2= 165628.5所以 F= RSS2/RSS1= 165628.5/9705.972=17.0646 在給定 =5%下查得臨界值

37、 F0.05(4,4) 6.39， F F0.05(4,4) 因此否定兩組子樣方差相同的假設(shè)，從而該總體隨機項存在遞增 異方差性。 White 方法檢驗White Heteroskedasticity Test:F-statistic6.142010Probability0.003919Obs*R-squared12.41812Probability0.014498Test Equation:Dependent Variable: RESID2Method: Least SquaresDate: 11/30/11 Time: 13:21Sample: 1990 2009Included obs

38、ervations: 20VariableCoefficientStd. Error t-StatisticProb.C24856.5019211.30 1.2938480.2153X1-20.573277.549127 -2.7252520.0156X120.0002128.04E-05 2.6399820.0186X3237.181378.61323 3.0170670.0087X32-0.0240730.006568 -3.6652300.0023R-squared0.620906Mean dependent var34743.00Adjusted R-squared0.519815S.

39、D. dependent var49156.00S.E. of regression34062.86Akaike info criterion23.92212Sum squared resid1.74E+10Schwarz criterion24.17105Log likelihood-234.2212F-statistic6.142010Durbin-Watson stat1.560937Prob(F-statistic)0.0039192n R2 20 0.620906 12.41812=5%下，臨界值 20.05(4) 9.488 拒絕同方差性 修正Dependent Variable:

40、 YMethod: Least SquaresDate: 11/30/11Time: 14:29Sample: 1990 2009Included observations: 20Weighting series: 1/E1VariableCoefficientStd. Errort-StatisticProb.C-314.207443.68550-7.1924860.0000X10.9797580.008622113.63360.0000X31.4572910.06592222.106290.0000Weighted StatisticsR-squared0.999999 Mean depe

41、ndent var27246.27Adjusted R-squared0.999999 S.D. dependent var74471.17S.E. of regression 73.91795 Akaike info criterion 11.58127Sum squared resid92885.67Schwarz criterion11.73063Log likelihood-112.8127F-statistic3138195.Durbin-Watson stat0.956075Prob(F-statistic)0.000000Unweighted StatisticsR-square

42、d0.999902Mean dependent var20556.75Adjusted R-squared0.999891S.D. dependent var19987.03S.E. of regression209.0283Sum squared resid742778.2Durbin-Watson stat1.365483Y 314.20740.979758 X1 1.457291X 3(-7.192486)( 113.6336) ( 22.10629)2R2 0.9999992R 0.999999 F 3138195 D.W 1.365483序列相關(guān)性檢驗從殘差項 e2與e2(-1) 及

43、e與時間 t的關(guān)系圖(如下)看，隨機項 呈現(xiàn)正序列相關(guān)性。600400200(-120-200-400-600 -400 -200 0 200 400 600E2-600由圖可以看出，存在一階序列相關(guān)回歸檢驗殘差e2與e2（ -1 ）做回歸得：Dependent Variable: EMethod: Least SquaresDate: 12/04/11Time: 15:21Sample (adjusted): 1991 2009Included observations: 19 after adjustmentsVariableCoefficientStd. Error t-Statisti

44、cProb.C16.8152545.69611 0.3679800.7174E(-1)0.3035700.231114 1.3135080.2065R-squared0.092138Mean dependent var25.28519Adjusted R-squared0.038734S.D. dependent var201.1252S.E. of regression197.1916Akaike info criterion13.50553Sum squared resid661036.6Schwarz criterion13.60494Log likelihood-126.3025F-s

45、tatistic1.725303Durbin-Watson stat1.776498Prob(F-statistic)0.206464e與 e(-1) 、e(-2) 做回歸得：Dependent Variable: EMethod: Least SquaresDate: 12/04/11 Time: 15:24Sample (adjusted): 1992 2009Included observations: 18 after adjustmentsVariableCoefficientStd. Error t-StatisticProb.C7.44976046.20912 0.1612180

46、.8741E(-1)0.4195640.244475 1.7161870.1067E(-2)-0.3798940.278641 -1.3633800.1929R-squared0.192570Mean dependent var16.45940Adjusted R-squared0.084912S.D. dependent var203.1349S.E. of regression194.3193Akaike info criterion13.52789Sum squared resid566399.7Schwarz criterion13.67629Log likelihood-118.75

47、10F-statistic1.788727Durbin-Watson stat2.055382Prob(F-statistic)0.201043由上表明不存在序列相關(guān)性。 D.W檢驗由異方差檢驗修正后的結(jié)果：Y 314.2074 0.979758 X1 1.457291X 3 22R2 0.999999 R 0.999999 F 3138195 D.W 1.365483得D.W=1.365483取 =5%，由于 n=20，k=3（包含常數(shù)項 ） ，查表得：dl =1.10 ， du=1.54由于dlDW=1.365483 du ，故: 序列相關(guān)性不確定。 拉格朗日檢驗Dependent Var

48、iable: EMethod: Least SquaresDate: 12/04/11 Time: 15:05Sample (adjusted): 1992 2009Included observations: 18 after adjustmentsVariableCoefficientStd. Error t-StatisticProb.Y0.0009840.002548 0.3862170.7051C-14.1479273.42247 -0.1926920.8500E(-1)0.3920090.261633 1.4983160.1563E(-2)-0.3477300.298739 -1.

49、1639920.2639R-squared0.201082Mean dependent var16.45940Adjusted R-squared0.029885S.D. dependent var203.1349S.E. of regression200.0765Akaike info criterion13.62841Sum squared resid560428.6Schwarz criterion13.82627Log likelihood-118.6557F-statistic1.174565Durbin-Watson stat2.010385Prob(F-statistic)0.3

50、546792LM n* R2 20 0.201082 4.02164取 =5%， 2 分布的臨界值 20.05 (3) 7.815LM 20.05 (3)故 : 存在序列相關(guān)。 修正為了更好的提高模型的精度，我們用廣義差分法對模型進行修正首先用杜賓（ durbin ）兩步法估計Dependent Variable: YMethod: Least SquaresDate: 12/04/11Time: 16:18Sample (adjusted): 1992 2009Included observations: 18 after adjustmentsVariableCoefficientStd. Errort-StatisticProb.C-36.8579081.18933-0.4539750.6606Y(-1)0.7306100.3453042.1158470.0635Y(-2)0.3581040.3645190.9824020.3516X11.0973550.03037736.124880.0000X1(-1)-0.8724