稅收收入影響因素分析.doc

稅收收入影響因素分析實(shí)驗(yàn)名稱(chēng)：稅收收入影響因素分析姓 名： 張鳳鳳 學(xué) 號(hào)： 902016112 班 級(jí)： 09注稅 指導(dǎo)教師： 劉勇 時(shí) 間： 二一一年十二月 稅收收入影響因素分析十一屆三中全會(huì)以后，中國(guó)的經(jīng)濟(jì)一直處于高速增長(zhǎng)之中。經(jīng)濟(jì)增長(zhǎng)的高速發(fā)展，勢(shì)必會(huì)影響國(guó)家財(cái)政政策和國(guó)家福利水平。而稅收作為國(guó)家財(cái)政收入中最主要的部分對(duì)這些政策的實(shí)施也會(huì)有很大的影響。近些年來(lái)，國(guó)家的稅收也受到多種因素的影響。所以，這篇文章將以計(jì)量經(jīng)濟(jì)學(xué)的角度分析一下影響我國(guó)稅收的因素。關(guān)鍵字：稅收收入 國(guó)內(nèi)生產(chǎn)總值 商品零售價(jià)格指數(shù) 進(jìn)出口總額 一、引言： 經(jīng)濟(jì)發(fā)展水平?jīng)Q定稅收收入水平，稅收同時(shí)也反作用于經(jīng)濟(jì)。要實(shí)現(xiàn)經(jīng)濟(jì)的持續(xù)增長(zhǎng)，必須要求與經(jīng)濟(jì)緊密關(guān)聯(lián)的稅收符合其發(fā)展的要求，即政府籌集的稅收收入應(yīng)盡可能的滿足其實(shí)現(xiàn)職能的需求，同時(shí)又不至于損害經(jīng)濟(jì)的發(fā)展。影響未來(lái)的需求，我們需要研究影響中國(guó)稅收收入的主要原因，分析中央和地方稅收收入增長(zhǎng)的數(shù)量規(guī)律，從結(jié)構(gòu)上對(duì)稅收收入的影響做一個(gè)很好的了解，對(duì)于預(yù)測(cè)中國(guó)稅收未來(lái)的增長(zhǎng)趨勢(shì)具有重要的作用，對(duì)于我國(guó)的社會(huì)主義現(xiàn)代化建設(shè)具有重要意義。二、模型設(shè)定研究影響中國(guó)稅收未來(lái)增長(zhǎng)的主要原因，需要考慮以下幾個(gè)方面的內(nèi)容：1，對(duì)固定資產(chǎn)投資資金來(lái)源的衡量，用什么數(shù)據(jù)來(lái)表現(xiàn)呢？我們選用中國(guó)稅收收入作為被解釋變量（y）分析影響中國(guó)稅收未來(lái)增長(zhǎng)的主要原因。 2，數(shù)據(jù)性質(zhì)的選擇?？紤]到截面數(shù)據(jù)受到制約，時(shí)間序列數(shù)據(jù)更加合理，所以本項(xiàng)目選擇了1990年到2009年的時(shí)間序列數(shù)據(jù)來(lái)建立模型。3，影響因素的分析。從宏觀經(jīng)濟(jì)看，經(jīng)濟(jì)整體增長(zhǎng)是稅收增長(zhǎng)的基本源泉，所以經(jīng)濟(jì)整體增長(zhǎng)是影響中國(guó)稅收未來(lái)增長(zhǎng)的主要原因的主要影響因素，所以選用國(guó)內(nèi)生產(chǎn)總值（GDP）作為經(jīng)濟(jì)整體增長(zhǎng)水平的代表。除此之外，根據(jù)經(jīng)濟(jì)理論，還有眾多因素會(huì)影響中國(guó)稅收未來(lái)增長(zhǎng)的主要原因：首先，公共財(cái)政的需求。稅收收入是財(cái)政收入的主體，社會(huì)經(jīng)濟(jì)的發(fā)展和社會(huì)保障的完善等都對(duì)公共財(cái)政提出了要求，因此對(duì)預(yù)算支出所表現(xiàn)的公共財(cái)政的需求（即財(cái)政支出）對(duì)當(dāng)年的稅收收入可能會(huì)產(chǎn)生影響，但是其數(shù)據(jù)獲得比較困難，因?yàn)楣藏?cái)政的需求與財(cái)政支出關(guān)系密切，所以選擇財(cái)政支出作為其代表。其次，物價(jià)水平。居民的收入水平與物價(jià)水平有一定的關(guān)系，我們選擇商品零售價(jià)格指數(shù)作為物價(jià)水平的代表。再次，進(jìn)出口總額。進(jìn)出口的收入水平與稅收收入存在一定的聯(lián)系，所以我們選擇進(jìn)出口總額來(lái)作為解釋變量。因此，準(zhǔn)備將“國(guó)內(nèi)生產(chǎn)總值（）”、“財(cái)政支出（）”、“商品零售價(jià)格指數(shù)（）”、“進(jìn)出口總額（）”作為解釋變量建立模型。4，模型形式的設(shè)計(jì) 我們將方程形式設(shè)定為二次型 然后將影響因素以某種方式引入模型。三、數(shù)據(jù)的收集本文收集了從1990年到2009年20年的數(shù)據(jù)，如表所示年份稅收收入（Y）/億元國(guó)內(nèi)生產(chǎn)總值（X1）/億元財(cái)政支出（X2）/億元商品零售價(jià)格指數(shù)（X3）/進(jìn)出口總額（X4）/億元19902821.8618667.83083.59102.15560.119912990.1721781.53386.62102.97225.819923296.9126923.53742.2105.49119.619934255.335333.94642.3113.21127119945126.8848197.95792.62121.720381.919956038.0460793.76823.72114.823499.919966909.8271176.67937.55106.124133.819978234.04789739233.56100.826967.219989262.884402.310798.1897.426849.7199910682.5889677.113187.679729896.2200012581.5199214.615886.598.539273.2200115301.38109655.218902.5899.242183.6200217636.45120332.722053.1598.751378.2200320017.31135822.824649.9599.970483.5200424165.68159878.328486.89102.895539.1200528778.54184937.433930.28100.8116921.8200634804.35216314.440422.73101140971.4466200745621.97265810.349781.35103.8166740.1884200854223.79314045.462592.66105.9179921.4702200959521.59340506.976299.9398.8150648.0635數(shù)據(jù)來(lái)源：國(guó)家統(tǒng)計(jì)局10年統(tǒng)計(jì)年鑒四、模型的估計(jì)與調(diào)整方程形式設(shè)定為二次型 EVIEWS的最小二乘估計(jì)結(jié)果為 Dependent Variable: YMethod: Least SquaresDate: 12/21/11 Time: 23:07Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C-3278.0383482.277-0.9413490.3614X10.0114630.0217940.5259560.6066X20.6168330.0762298.0918460.0000X328.8526931.667380.9111170.3766X40.0623210.0147474.2259460.0007R-squared0.998283 Mean dependent var18613.55Adjusted R-squared0.997825 S.D. dependent var17452.03S.E. of regression813.9629 Akaike info criterion16.45402Sum squared resid9938033. Schwarz criterion16.70296Log likelihood-159.5402 F-statistic2179.867Durbin-Watson stat1.267206 Prob(F-statistic)0.000000經(jīng)濟(jì)意義檢驗(yàn)：從回歸的結(jié)果可以看出，國(guó)內(nèi)生產(chǎn)總值（）、財(cái)政支出（）、商品零售價(jià)格指數(shù)（）、進(jìn)出口總額（）符號(hào)均為正，符合經(jīng)濟(jì)意義。統(tǒng)計(jì)推斷檢驗(yàn)。該模型R2=0.998283,修正的R2=0.997825，可決系數(shù)很高，擬合優(yōu)度較好，F(xiàn)檢驗(yàn)值=2179.867，明顯顯著。但是當(dāng)a=0.05時(shí)，t a/2(n-k-1)= t a/2(20-7-1)= t 0.025(12)=2.179, x1 x3 的系數(shù)t檢驗(yàn)不顯著，這表明可能存在多重共線性。 相關(guān)系數(shù)表X1X2X3X4X110.99179395592-0.2811048125370.969178531911X20.991793955921-0.2781042468630.948919334761X3-0.281104812537-0.2781042468631-0.214155020717X40.9691785319110.948919334761-0.2141550207171由相關(guān)系數(shù)表可以看出，各解釋變量之間除了x3之外的相關(guān)系數(shù)較高，證實(shí)確實(shí)存在嚴(yán)重的多重共線性。修正多重共線性：運(yùn)用OLS方法逐一求Y對(duì)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。Dependent Variable: YMethod: Least SquaresDate: 12/21/11 Time: 23:55Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C-3927.648663.6284-5.9184440.0000X10.1816050.00427542.476350.0000R-squared0.990122 Mean dependent var18613.55Adjusted R-squared0.989573 S.D. dependent var17452.03S.E. of regression1782.051 Akaike info criterion17.90356Sum squared resid57162682 Schwarz criterion18.00313Log likelihood-177.0356 F-statistic1804.240Durbin-Watson stat0.192210 Prob(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 12/21/11 Time: 23:56Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C286.7356497.35000.5765270.5714X20.8299550.01653550.192540.0000R-squared0.992906 Mean dependent var18613.55Adjusted R-squared0.992512 S.D. dependent var17452.03S.E. of regression1510.211 Akaike info criterion17.57253Sum squared resid41053290 Schwarz criterion17.67210Log likelihood-173.7253 F-statistic2519.291Durbin-Watson stat1.279618 Prob(F-statistic)0.000000Dependent Variable: YMethod: Least SquaresDate: 12/21/11 Time: 23:56Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C91495.3464602.741.4162760.1738X3-703.8998622.8170-1.1301870.2732R-squared0.066260 Mean dependent var18613.55Adjusted R-squared0.014386 S.D. dependent var17452.03S.E. of regression17326.05 Akaike info criterion22.45245Sum squared resid5.40E+09 Schwarz criterion22.55202Log likelihood-222.5245 F-statistic1.277323Durbin-Watson stat0.098220 Prob(F-statistic)0.273233Dependent Variable: YMethod: Least SquaresDate: 12/21/11 Time: 23:57Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C559.77001482.3310.3776280.7101X40.2914330.01767616.487550.0000R-squared0.937897 Mean dependent var18613.55Adjusted R-squared0.934446 S.D. dependent var17452.03S.E. of regression4468.319 Akaike info criterion19.74205Sum squared resid3.59E+08 Schwarz criterion19.84162Log likelihood-195.4205 F-statistic271.8394Durbin-Watson stat0.719107 Prob(F-statistic)0.000000其中加入x2的方程修正的R2最大，其方程為：Y=286.7356 + 0.829955X2 (0.576527) (50.19254) 修正的R2= 0.992512 S E=1510.211 F=2519.291所以，以x2為基礎(chǔ)，順次加入其他的自變量逐步回歸：當(dāng)a=0.05時(shí)，t a/2(n-k-1)= t a/2(20-7-1)= t 0.025(12)=2.179Y= -1543.209 + 0.487335X2 + 0.075696X1 -2.279957 4.712918 3.340826 修正的R2=0.995214 S E= 1207.394 F= 1976.304應(yīng)為x1的引入改進(jìn)了修正的R2和F值且其他回歸參數(shù)的t檢驗(yàn)在統(tǒng)計(jì)上仍然顯著，所以保留x1，方程為： Y= -1543.209 + 0.487335X2 + 0.075696X1繼續(xù)： Y = -8430.382 + 0.486494X2 + 0.077099X1+ 65.01505X3 -1.803502 4.869821 3.518878 1.487996 修正的R2=0.995533 S E= 1166.458 F= 1412.372式中X3不顯著，刪去，繼續(xù)： Y = -144.6187 + 0.624773X2 + 0.007062X1+ 0.065952X4 -0.265949 8.294223 0.334068 4.669806 修正的R2= 0.997848 S E= 809.6306 F= 2937.398X4雖然顯著，但是它的引入影響了其他回歸參數(shù)的估計(jì)值的數(shù)值，使得隨機(jī)項(xiàng)和x1的回歸參數(shù)通不過(guò)t檢驗(yàn)，所以刪去x4所以： Y= -1543.209+ 0.075696X1 + 0.487335X2 -2.279957 4.712918 3.340826 修正的R2=0.995214 S E= 1207.394 F= 1976.304即為最優(yōu)模型obs稅收收入（Y）/億元國(guó)內(nèi)生產(chǎn)總值（X1）/億元財(cái)政支出（X2）/億元19902821.8618667.83083.5919912990.1721781.53386.6219923296.9126923.53742.219934255.335333.94642.319945126.8848197.95792.6219956038.0460793.76823.7219966909.8271176.67937.5519978234.04789739233.5619989262.884402.3107985889677.113187.67200012581.5199214.615886.5200115301.38109655.218902.58200217636.45120332.72205331135822.824649.95200424165.68159878.328486.89200528778.54184937.433930.28200634804.35216314.440422.73200745621.97265810.349781.35200854223.79314045.462592.66200959521.59340506.976299.93最小二乘估計(jì)為：Dependent Variable: YMethod: Least SquaresDate: 12/22/11 Time: 15:25Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C-1543.209676.8588-2.2799570.0358X10.0756960.0226583.3408260.0039X20.4873350.1034044.7129180.0002R-squared0.995717 Mean dependent var18613.55Adjusted R-squared0.995214 S.D. dependent var17452.03S.E. of regression1207.394 Akaike info criterion17.16780Sum squared resid24782606 Schwarz criterion17.31716Log likelihood-168.6780 F-statistic1976.304Durbin-Watson stat0.857004 Prob(F-statistic)0.000000殘差平方和對(duì)解釋變量的散點(diǎn)圖：由散點(diǎn)圖可以看出，殘差平方和e2對(duì)解釋變量x的散點(diǎn)圖主要分布在圖形中的下三角形，殘差平方和e2隨解釋變量x的變動(dòng)呈現(xiàn)增大的趨勢(shì)，所以，模型可能存在異方差。White檢驗(yàn)：White Heteroskedasticity Test:F-statistic6.050557 Probability0.003476Obs*R-squared13.67271 Probability0.017828Test Equation:Dependent Variable: RESID2Method: Least SquaresDate: 12/22/11 Time: 15:26Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C4420714.1170077.3.7781390.0020X1-398.0270123.7104-3.2174100.0062X120.0082460.0026193.1486040.0071X1*X2-0.0719370.023553-3.0542430.0086X21736.983591.84002.9348870.0109X220.1571550.0524732.9949850.0096R-squared0.683636 Mean dependent var1239130.Adjusted R-squared0.570648 S.D. dependent var1774942.S.E. of regression1163029. Akaike info criterion31.01428Sum squared resid1.89E+13 Schwarz criterion31.31300Log likelihood-304.1428 F-statistic6.050557Durbin-Watson stat2.063062 Prob(F-statistic)0.003476從表中可以看出，nR2=20*0.683636=13.67272由white檢驗(yàn)知，在a=0.05下，查表得知 (5)= 11.0705，因?yàn)閚R2=13.67272 (5)= 11.0705，所以拒絕原假設(shè)，表明模型中的隨機(jī)誤差存在異方差。修正異方差：使用w5=1/abs（e）作為權(quán)數(shù)，得出：Dependent Variable: YMethod: Least SquaresDate: 12/22/11 Time: 18:31Sample: 1990 2009Included observations: 20Weighting series: W5VariableCoefficientStd. Errort-StatisticProb. C73.239403.19641422.912990.0000X10.0097450.00028134.729310.0000X20.7913250.002771285.55340.0000Weighted StatisticsR-squared1.000000 Mean dependent var3338.463Adjusted R-squared1.000000 S.D. dependent var14493.59S.E. of regression0.279064 Akaike info criterion0.422729Sum squared resid1.323904 Schwarz criterion0.572089Log likelihood-1.227294 F-statistic1763274.Durbin-Watson stat1.048047 Prob(F-statistic)0.000000Unweighted StatisticsR-squared0.993469 Mean dependent var18613.55Adjusted R-squared0.992701 S.D. dependent var17452.03S.E. of regression1491.022 Sum squared resid37793490Durbin-Watson stat1.274612估計(jì)的結(jié)果為：y =73.23940 +0.009745x1 + 0.791325x2 （22.91299）（34.7293） (285.5534) R2=0.993469 DW=1.048047 F=1763274.再次做懷特檢驗(yàn)：White Heteroskedasticity Test:F-statistic0.559656 Probability0.729260Obs*R-squared3.331625 Probability0.649004Test Equation:Dependent Variable: STD_RESID2Method: Least SquaresDate: 12/22/11 Time: 18:24Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C52.3387739.959311.3098020.2113X1-0.0012810.004225-0.3032000.7662X124.33E-088.94E-080.4846640.6354X1*X2-4.32E-078.04E-07-0.5369940.5997X20.0083010.0202120.4106760.6875X221.04E-061.79E-060.5808120.5706R-squared0.166581 Mean dependent var63.29112Adjusted R-squared-0.131068 S.D. dependent var37.34648S.E. of regression39.71862 Akaike info criterion10.44484Sum squared resid22085.96 Schwarz criterion10.74356Log likelihood-98.44842 F-statistic0.559656Durbin-Watson stat1.527039 Prob(F-statistic)0.729260從表中可以看出，nR2=20*0.166581=3.33162,由white檢驗(yàn)知，在a=0.05下，查表得知 (5)= 11.0705，因?yàn)閚R2=3.33162 (5)= 11.0705，所以不拒絕原假設(shè)，表明模型中的隨機(jī)誤差不存在異方差。自相關(guān)檢驗(yàn)：查表得出上限為1.100，下限為1.537，因?yàn)?.100DW=1.2746121.537，所以不能確定是否存在自相關(guān)。 修正自相關(guān)：使用迭代法修正得到：Dependent Variable: YMethod: Least SquaresDate: 12/22/11 Time: 19:08Sample(adjusted): 1991 2009Included observations: 19 after adjusting endpointsConvergence achieved after 8 iterationsVariableCoefficientStd. Errort-StatisticProb. C-6698.2632196.930-3.0489190.0081X10.1792020.0203608.8016570.0000X20.0663370.0775250.8556810.4056AR(1)0.8174370.0872539.3686100.0000R-squared0.998913 Mean dependent var19444.69Adjusted R-squared0.998696 S.D. dependent var17518.87S.E. of regression632.5987 Akaike info criterion15.92221Sum squared resid6002716. Schwarz criterion16.12104Log likelihood-147.2610 F-statistic4596.579Durbin-Watson stat1.471722 Prob(F-statistic)0.000000Inverted AR Roots .82DW