《我國財(cái)政收入影響因素分析》計(jì)量經(jīng)濟(jì)學(xué)論文(eviews分析)要點(diǎn)

1、-WORDB式一可編輯我國財(cái)政收入影響因素分析班級：姓名：學(xué)號：指導(dǎo)教師:完成時(shí)間:建立了數(shù)摘要：對我國財(cái)政收入影響因素進(jìn)行了定量分析，學(xué)模型，并提出了提高我國財(cái)政收入質(zhì)量的政策建議。關(guān)鍵詞：財(cái)政收入實(shí)證分析影響因素引言財(cái)政收入對于國民經(jīng)濟(jì)的運(yùn)行及社會(huì)發(fā)展具有重要影響。首先，它是一個(gè)國家各項(xiàng)收入得以實(shí)現(xiàn)的物質(zhì)保證。一個(gè)國家財(cái)政收入規(guī)模大小往往是衡量其經(jīng)濟(jì)實(shí)力的重要標(biāo)志。其次，財(cái)政收入是國家對經(jīng)濟(jì)實(shí)行宏觀調(diào)控的重要經(jīng)濟(jì)杠桿。宏觀調(diào)控的首要問題是社會(huì)總需求與總供給的平衡問題，實(shí)現(xiàn)社會(huì)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(gè)層次的內(nèi)容。財(cái)政收入的杠桿既可通過增收和減收來發(fā)揮總量調(diào)控作

2、用，也可通過對不同財(cái)政資金繳納者的財(cái)政負(fù)擔(dān)大小的調(diào)整，來發(fā)揮結(jié)構(gòu)調(diào)整的作用。止匕外，財(cái)政收入分配也是調(diào)整國民收入初次分配格局，實(shí)現(xiàn)社會(huì)財(cái)富公平合理分配的主要工具。在我國，財(cái)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(cái)政收入會(huì)隨著經(jīng)濟(jì)繁榮而增加， 隨著經(jīng)濟(jì)衰退而下降。我國的財(cái)政收入主要包括稅收、國有經(jīng)濟(jì)收入、債務(wù)收入以及其他收入四種 形式，因此，財(cái)政收入會(huì)受到不同因素的影響。從國民經(jīng)濟(jì)部門結(jié)構(gòu)看，財(cái)政收入又表現(xiàn)為來自各經(jīng)濟(jì)部門的收入。 財(cái)政收入的部門構(gòu)成就是在財(cái)政收入中，由來自國民經(jīng)濟(jì)各部門的收入所占的不同比例來表現(xiàn)財(cái)政收入來源的結(jié)構(gòu)，它體現(xiàn)國民經(jīng)濟(jì)各部門與財(cái)政收入的關(guān)系。我國

3、財(cái)政收入主要來自于工業(yè)、農(nóng)業(yè)、商業(yè)、交通運(yùn)輸和服務(wù)業(yè)等部門。因此，本文認(rèn)為財(cái)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(cái)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(jì)年鑒得到1990-200即每年的財(cái)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(jì)數(shù)據(jù)obs199019911992199319941995199619971998199920002001200220032004200

4、5200620072008財(cái)政收入Y2937.13149.483483.374348.955218.16242.27407.998651.149875.9511444.0813395.2316386.0418903.6421715.2526396.4731649.2938760.251321.7861330.35總稅收收入X12821.86 2990.17 3296.914255.3 5126.88 6038.04 6909.82 8234.049262.8 10682.58 12581.51 15301.38 17636.45 20017.31 24165.68 28778.54 34804

5、.35 45621.97 54223.79國內(nèi)生產(chǎn)總值就業(yè)人口總數(shù)X2其他收入X3X418667.8299.536474921781.5240.16549126923.5265.156615235333.9191.046680848197.9280.186745560793.7396.196806571176.6724.666895078973682.36982084402.3833.37063789677.1925.437139499214.6944.9872085109655.21218.173025120332.71328.7473740135822.81691.937443215987

6、8.32148.3275200184937.42707.8375825216314.43683.8576400265810.34457.9676990314045.45552.4677480200968518.359521.59340506.97215.7277995模型建吊1、散點(diǎn)圖分析2、35000030000025000020000015000010000050000單區(qū)X1X2X3X4010000300005000070000素或多變量也關(guān)系分析X1X2X3X40.9989134611 0.9934790452 0.87701448860.9836027198YX1X2X3X4.993

7、47904521 47853 ,90804 , 79564415080.9937402677 0.85563773470.984935296511846944782934920.99374026770.85618358020.98624116569080418469128471804590.8770144886 0.8556377347 0.85618358020.8109403346/95644 44782284711503810.9836027198 0.9849352965 0.9862411656 0.81。9403346),508， 93492 880459 15 503811由散k

8、圖分和變卜間關(guān)&分析占以看卜被解小變量6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:-專業(yè)資料分享-WORDB式一可編輯3、模型預(yù)模擬 由eviews做ols回歸得到結(jié)果:Dependent Variable: YMethod: Least SquaresDate: 11/14/11 Time: 17:51Sample: 1990 2009Included observations: 20Variable Coefficient Std. Error t-Statistic Prob.C7299.5231691.8144.

9、3146140.0006X11.0628020.02110850.349720.0000X20.0017700.0045280.3910070.7013X30.8733690.1198067.289852 0.0000X4-0.1159750.026580-4.3631600.0006R-squared0.999978 Mean dependent var20556.75S.D. dependentAdjusted R-squared0.999972 var19987.03S.E. of regression106.6264 Akaike info criterion12.38886Sum s

10、quared resid170537.9Schwarz criterion12.63779Log likelihood-118.8886F-statistic166897.90.873369X30.115975X(7.289852) ( -4.363160)166897.9 D .W 1.4 9 6 5 1 7Durbin-Watson stat1.496517 Prob(F-statistic)0.0000007299.5231.062802X10.001770X2(4.314614) ( 50.34972 ) ( 0.391007)R20.999978 R 0.9 9 9 9 7 2 F四

11、、模型檢驗(yàn)1.計(jì)量經(jīng)濟(jì)學(xué)意義檢驗(yàn)多重共線性檢驗(yàn)與解決求相關(guān)系數(shù)矩陣，得到:*Correlation MatrixYX1X2X3X4-專業(yè)貢料分享-0.9989134611 0.9934790452 0.87701448860.9836027198-WORDB式一可編輯478530.99891346119080479564415080.9937402677 0.85563773470.9849352965I-專業(yè)資料分享-478531846944782934920.9934790452 0.99374026770.85618358020.98624116569080418469128471804

12、590.8770144886 0.8556377347 0.85618358020.81094033467956444782284711503810.9836027198 0.9849352965 0.9862411656 0.8109403346415089349280459503811發(fā)現(xiàn)模型存在多重共線性。接下來運(yùn)用逐步回歸法對模型進(jìn)行修正：將各個(gè)解釋變量分別加入模型，進(jìn)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 2009Includ

13、ed observations: 20VariableCoefficientStd. Errort-StatisticProb.C-755.6610X11.144994145.2330-5.2030940.00010.005760198.79310.0000R-squaredAdjusted R-squaredS.E. of regressionSum squared resid Log likelihood Durbin-Watson stat0.999545 Mean dependent var 20556.75 S.D. dependent0.999519 var19987.03438.

14、1521 Akaike info criterion15.09765Schwarz3455590. criterion15.19722-148.9765 F-statistic39518.700.475046 Prob(F-statistic)0.000000作Y6X2的回歸,結(jié)果加下Dependent Variable: YMethod: Least Squares , Date: 11/22/11 Time: 23:06Sample: 1990 2009Included observations: 20VariableCX2Coefficient Std. Error-5222.07786

15、1.2067t-Statistic Prob.0.000-6.06367400.00037.4326700.2076890.005548-WORDB式一可編輯-專業(yè)資料分享-R-squaredAdjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat20556.7519987.0318.4247818.524351401.2050.000000VariableCoefficientStd. Errort-StatisticProb.C2607.879773.9988X310.

16、030730.2943113.3693580.003434.082090.00000.987317 Mean dependent var0.986612 S.D. dependent var2312.610 Akaike info criterion96267005 Schwarz criterion-182.2478 F-statistic0.188013 Prob(F-statistic)作Y與X3的回歸，結(jié)果如下Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:08Sample: 1990 2009Incl

17、uded observations: 20R-squared0.984740 Mean dependent var 20556.75S.D. dependentAdjusted R-squared0.983893 var19987.03Akaike infoS.E. of regression2536.645 criterion18.60971Sum squared resid 1.16E+08 Schwarz criterion18.70929Log likelihood-184.0971F-statistic1161.589Durbin-Watson stat 1.194389 Prob(

18、F-statistic)0.000000作Y與X4的回歸，結(jié)果如下：Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:08Sample: 1990 2009Included observations: 20Variable Coefficient Std. Error t-Statistic Prob.C-272959.337203.65-7.3368940.0000X44.0974030.5184677.9029180.0000R-squaredAdjusted R-squaredS.E. of regress

19、ionSum squared resid Log likelihood Durbin-Watson stat0.776276 Mean dependent varS.D. dependent 0.763846 var9712.824 Akaike info criterion20556.7519987.0321.2949221.3944962.456110.000000Schwarz1.70E+09 criterion-210.9492 F-statistic0.157356 Prob(F-statistic)-WORDB式一可編輯依據(jù)可決系數(shù)最大的原則選取X1作為進(jìn)入回歸模型的第一個(gè)解釋變量

20、，再依次將其余變量分別代入回歸得：作Y與XI、X2的回歸，結(jié)果如下Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:09Sample: 1990 2009Included observations: 20Variable Coefficient Std. Error t-Statistic Prob.C-188.4285239.0743-0.7881590.4415X11.2815940.04947225.905680.0000X2-0.0250550.009029-2.7749080.0130R-squared

21、0.999687Mean dependent var20556.75S.D. dependentAdjusted R-squared0.999650 var19987.03S.E. of regression374.0345 Akaike info criterion14.82405SchwarzSum squared resid2378330. criterion14.97341Log likelihood-145.2405F-statistic27118.20Durbin-Watson stat0.683510 Prob(F-statistic)0.000000作Y與X1、X3的回歸，結(jié)果

22、如下Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:10Sample: 1990 2009Included observations: 20Variable Coefficient Std. Error t-Statistic Prob.C-351.105483.15053-4.2225270.0006X10.9928130.01870753.071960.0000X31.3569360.1651098.2184100.0000R-squared0.999908 Mean dependent var 20556

23、.75-WORDB式一可編輯Adjusted R-squared S.E. of regressionSum squared resid Log likelihood Durbin-Watson stat19987.0313.5936113.7429792839.330.000000S.D. dependent0.999898 var202.1735 Akaike info criterionSchwarz694859.9 criterion-132.9361 F-statistic1.177765 Prob(F-statistic)-專業(yè)資料分享-作Y與XI、X4的回歸，結(jié)果如下Depend

24、ent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:10Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb.C11853.46X11.185886X4-0.186645Sum squared resid Log likelihood Durbin-Watson stat14.0082271206.900.000000C-76.04458X11.085924X31.210853X2-0.014073100.1

25、7240.0298010.1334440.003944-0.75913736.438819.073877-3.5679010.45880.00000.00000.00261824.5226.4967480.00000.006645178.46080.00000.026984-6.9170030.0000R-squared0.999881Mean dependent var20556.75S.D. dependentAdjusted R-squared0.999867 var19987.03S.E. of regression230.8464 Akaike info criterion13.85

26、886Schwarz905931.0 criterion-135.5886 F-statistic1.459938 Prob(F-statistic)在滿足經(jīng)濟(jì)意義和可決系數(shù)的條件下選取X3作為進(jìn)入模型的第二個(gè)解釋變量，再次進(jìn)行回歸則：作Y與X1、X3、X2的回歸，結(jié)果如下Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:13Sample: 1990 2009Included observations: 20Variable Coefficient Std. Error t-Statistic ProbR-squ

27、aredAdjusted R-squared S.E. of regression Sum squared resid Log likelihood0.999949 Mean dependent varS.D. dependent 0.999939 var155.5183 Akaike info criterion386975.0Schwarz criterion20556.7519987.0313.1082613.30741104602.9-127.0826 F-statistic-WORDB式一可編輯Durbin-Watson stat 1.196933 Prob(F-statistic)

28、0.000000作Y與XI、X3、X4的回歸，結(jié)果如下Dependent Variable: YMethod: Least SquaresDate: 11/22/11 Time: 23:13Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb.C6781.7641024.745X11.0686420.0145146.6180030.000073.627640.0000X30.8910690.1079498.2545510.0000X4-0.1076390.015451-6.9

29、666750.0000R-squared0.999977Mean dependent var20556.75S.D. dependentAdjusted R-squared0.999973 var19987.03S.E. of regression103.7654 Akaike info criterion12.29900SchwarzSum squared resid172276.1 criterion12.49814Log likelihood-118.9900F-statistic234970.9Durbin-Watson stat1.451447 Prob(F-statistic)0.

30、000000，故可見加入其余任何一個(gè)變量都會(huì)導(dǎo)致系數(shù)符號與經(jīng)濟(jì)意義不符 最終修正后的回歸模型為Dependent Variable: YMethod: Least Squares Date: 11/30/11 Time: 12:18Sample: 1990 2009Included observations: 20Variable Coefficient Std. Error t-Statistic Prob.C-351.105483.15053-4.2225270.0006X10.9928130.01870753.071960.0000X31.3569360.1651098.2184100.

31、0000-WORDB式一可編輯R-squared Adjusted R- squaredS.E. of regression Sum squared residLog likelihood20556.7519987.0313.5936113.7429792839.330.999908 Mean dependent varS.D. dependent 0.999898 var202.1735 Akaike info criterionSchwarz 694859.9 criterion -132.9361 F-statistic-專業(yè)資料分享-WORDB式一可編輯-專業(yè)資料分享-Durbin-W

32、atson stat1.177765 Prob(F-statistic)0.0000001.356936X3(8.218410)Y 351.1054 0.992813X(-4.222527)( 53.07196)0.9 9 9 8 9 8 F 92839 .33 D .W 1.1 7 7 7 6 5R 20.999908R異方差檢驗(yàn)與修正圖示法ee與X1的散點(diǎn)圖如下:200000160000120000800004000010000 20000 30000 40000 50000 60000X1說明ee與X1存在單調(diào)遞增型異方差性。ee 與 X3200000160000120000E E800

33、0040000002000400060008000X3說明ee與X3存在單調(diào)遞增型異方差性。G-Q檢驗(yàn)對20組數(shù)據(jù)剔除掉中間四組剩下的進(jìn)行分組后，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: 8Variable Coefficient Std. Error t-Statistic Prob.0.000X10.984123 0.01625560.54320 -00.002X30.851

34、5180.1566885.43447290.559C-28.3427545.36993-0.62470365179.79R-squared0.999686Mean dependent var1S.D. dependent2099.84Adjusted R-squared0.999560 var0S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat10.6889310.718727947.5750.000000VariableCoefficient Std. Error t-StatisticProb.X11

35、.066404X30.847228C-1184.1590.02774738.433210.00000.2151143.9385030.0110261.8258-4.5226980.0063R-squared0.999932Mean dependent varS.D. dependent39824.4144.05899 Akaike info criterion9705.972 Schwarz criterion-39.75573 F-statistic1.663630 Prob(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:Depen

36、dent Variable: YMethod: Least SquaresDate: 11/30/11 Time: 12:55Sample: 2002 2009Included observations: 8Adjusted R-squared0.999905 var18639.16S.E. of regression182.0047 Akaike info criterion 13.52594Sum squared resid Log likelihood Durbin-Watson stat13.5557336705.080.000000Schwarz165628.5 criterion-

37、51.10375 F-statistic1.326122 Prob(F-statistic)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(jī)項(xiàng)存在遞增異方差性。White方法檢驗(yàn)White Heteroskedasticity Test:F-statistic6.142010 Probability12.41812 Probability0.0039190.014498Obs*R-squar

38、ed-WORDB式一可編輯Test Equation:Dependent Variable: RESIDA2Method: Least SquaresDate: 11/30/11 Time: 13:21Sample: 19902009Included observations: 20VariableCoefficientStd. Errort-StatisticProb.CX1X1A2X3X3A224856.50-20.573270.000212237.1813-0.02407319211.301.2938480.21537.549127-2.7252520.01568.04E-052.639

39、9820.018678.613233.0170670.00870.006568-3.6652300.0023R-squared0.620906 Mean dependent var 34743.00Adjusted R-S.D. dependentsquared0.519815 var49156.00S.E. of regression Sum squared resid34062.86 Akaike info criterionSchwarz1.74E+10 criterion23.9221224.17105Log likelihood-234.2212 F-statistic6.14201

40、0Durbin-Watson stat1.560937 Prob(F-statistic)0.003919n R220 0.620906 12.418122=5%下，臨界值 0.05 (4) 9.488拒絕同方差性修正Dependent Variable: YMethod: Least SquaresDate: 11/30/11 Time: 14:29Sample: 1990 2009Included observations: 20Weighting series: 1/E1Variable Coefficient Std. Error t-Statistic Prob.0.000C-314

41、.207443.68550-7.1924860-WORDB式一可編輯-專業(yè)資料分享-X1X3R-squaredAdjusted R-squaredS.E. of regression0.9797580.008622113.63361.4572910.06592222.10629Weighted Statistics0.999999 Mean dependent var0.999999 S.D. dependent var73.91795 Akaike info criterion0.00000.000027246.2774471.1711.58127-WORDB式一可編輯Sum squared

42、 resid Log likelihood Durbin-Watson stat11.730633138195.0.00000092885.67 Schwarz criterion-112.8127 F-statistic0.956075 Prob(F-statistic)Unweighted StatisticsR-squared0.999902Adjusted R-squared0.999891S.E. of regression209.0283Durbin-Watson stat1.365483Mean dependent var20556.75S.D. dependent var199

43、87.03Sum squared resid742778.2Y 314.2074 0.979758X1.457291X3(-7.192486)R 0.999999(113.6336)( 22.10629)2F 3 1 3 8 1 9 5D.W 1.3 6 5 4 8 3R 0.9 9 9 9 9 9序列相關(guān)性檢驗(yàn)從殘差項(xiàng)e2與e2(-1)及e與時(shí)間t的關(guān)系圖(如下)看，隨機(jī)項(xiàng)呈現(xiàn)正序列相關(guān)性。600400200-200-400-600-600 -400 -2000200 400600E2600/400J， ;H i200 /ITi3*g j|Bl%Jr c Jr0 IJ r-200）：TI L

44、 I .y-400 |-600 111 IT I I II IIT iiiiTi90929496980002040608E2 Q統(tǒng)計(jì)量檢驗(yàn)Correlograni of Standardized Residuals 殘差e2與e2 (-1 )做回歸得:由圖甲骨出 J 一階詞f目, I 1* I Dependent Variable: EMethod: Least SquaresDate: 12/04/11 Time: 15:21Sample (adjusted): 1991 2009Included observations: 19 after adjustmentsVariableCoeff

45、icientStd. Errort-StatisticProb.C16.8152545.69611E(-1)0.3035700.2311140.3679800.71741.3135080.2065R-squaredAdjusted R- squared0.092138 Mean dependent var 25.28519 S.D. dependent 0.038734 var201.1252S.E. of regression Sum squared residAkaike info 197.1916 criterion13.505531.7253030.206464661036.6 Sch

46、warz criterion13.60494Log likelihood Durbin-Watson stat-126.3025 F-statistic1.776498 Prob(F-statistic)e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. Errort-StatisticP

47、rob.C7.449760E(-1)0.419564E(-2)-0.379894R-squaredAdjusted R-squaredS.E. of regressionSum squared resid Log likelihood Durbin-Watson stat46.209120.1612180.87410.2444751.7161870.10670.278641-1.3633800.19290.192570 Mean dependent var 16.45940 S.D. dependent0.084912 var203.1349194.3193 Akaike info crite

48、rion13.52789Schwarz566399.7 criterion13.67629-118.7510 F-statistic1.7887272.055382 Prob(F-statistic)0.201043-WORDB式一可編輯由上表明不存在序列相關(guān)性。D.W檢驗(yàn)由異方差檢驗(yàn)修正后的結(jié)果:-專業(yè)資料分享-Y 314.20740.979758X 1.457291X3R 2 0.999999R 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(xiàng)），查表得:dl =1.10 ,du=1.54由于dlDW=1

49、.365483 du ,故：序列相關(guān)性不確定。拉格朗日檢驗(yàn)Dependent Variable: EMethod: Least SquaresDate: 12/04/11 Time: 15:05Sample (adjusted): 1992 2009Included observations: 18 after adjustmentsVariable Coefficient Std. Error t-Statistic Prob.C-14.14792E(-1)0.392009E(-2)-0.347730Y0.0009840.0025480.3862170.705173.42247-0.1926

50、920.85000.2616331.4983160.1563R-squared0.298739-1.1639920.26390.201082 Mean dependent var 16.45940S.D. dependentAdjusted R-squared0.029885 var203.1349S.E. of regression200.0765Akaike infocriterion13.62841SchwarzSum squared resid560428.6criterion13.82627Log likelihood-118.6557F-statistic1.174565Durbin-Watson stat2.010385Prob(F-statistic)0.354679LM n * R 220 0.201082 4.02164取 =5%,2分布的臨界值 2 0.05 (3)7.815LM 呂腎 2 日0.05 (3)故：存在序列相關(guān)修正-WORDB式一可編輯為了更好的提高模型的精度，我們用廣義差分法對模型進(jìn)行修正 首先用杜賓（durbin ）兩步法估計(jì)Dependent Variable: YMethod: Least SquaresDate: 12/04/11 Time: 16:18Sam