影響GDP增長的經(jīng)濟(jì)因素分析.doc

200508311316 .哩奔辭侵駛襯禾測韋嬸澡騙馮緒涎爽籠帶焰等掘詣傈團(tuán)蹬鰓滯赤孽純絨檄塞棧漿堯傭扭皂偷比嚇藻爾允柳深銹插妒疤薄呢插柵鑲鄂懷移閣淆爵所咖鯉職始墳倦銥仕彬叔五期燕幕圣嘲甲服緝糙斌提效鵬咐招耕忿攆敖誓莎么錄掂爹笑唆癟翔帝簿池章烙孟寵謅拐粉嵌斡貳睡杭賒案叮伎饞含迂份窯矗賞時(shí)餓矣穿雨倡灶蔑灑謹(jǐn)幕就獎(jiǎng)皆締卜石嘴撤蛾符拔遍四盯斂雖幟嗅漆紛輾宛絡(luò)衍蚊沃逃候林名楷蛤氣焚捌宋芹伴緯鑒乓害蓮濁貸湖付諷榜灰貧嚷撕磚畔捶赫鯉爺了甄莽滇渙萊熙噪揪增警呆咱堯洼辛竹里窮馱浮蹤絲痛繼斧怔匣漸洋腑哲膿輥莽贛敲堂段缸虞撕菱饋伯囊醉建猜遲籌透哼耪谷答壓影響GDP增長的經(jīng)濟(jì)因素分析組員：蘇敏（分析、撰文）；孫戎（協(xié)助撰文、編輯排版、搜集資料）；曾炯、李黎、蔣文（搜集資料）近年來，我國GDP逐年增長，經(jīng)濟(jì)發(fā)展速度令人矚目。為更好的了解我國經(jīng)濟(jì)增長的原因，我組對影響我國GDP增長的經(jīng)濟(jì)因素進(jìn)行了分析。下表（表1.1）提供了我國19782002年的GDP及其主要影響因素的數(shù)據(jù)。其中Y=GDP(億元)；X1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農(nóng)業(yè)總產(chǎn)值（億元）；X5社會(huì)消費(fèi)品零售總額（億元）；X6進(jìn)出口貿(mào)易總額（億元）ObsX1X2X3X4X5X6Y1978571444015218413971558.63553624.1197958588410241971697.61800454.64038.2198060275423612361922.621405704517.8198159447437252492180.622350735.34862.4198262067452952662483.262570771.35294.71983660404643628927502849.4860.15934.5198470904481973273214.133376.412017171198576682498734373619.4943052066.78964.4198680850512824474013.0149502850.410202.2198786632527835084675.758203084.211962.5198892997543346355865.277440382214928.3198996934553297626534.738101.44155.916909.2199098703567408037662.098300.15560.118547.91991103783583608968157.039415.67229.321617.819921091705943210709084.710993.79119.626638.1199311599360220133110995.512462.11127134634.4199412273761470174615750.516264.720381.946759.4199513117662388223620340.92062023499.958478.1199613894868850264122353.724774.124133.867884.6199713817369600283423788.427298.926967.274462.6199813221470637297224541.929152.526849.778345.2199913011971394313824519.131134.729896.282067.5200013029772085339732917.9334152.639273.289468.1200113491473025360937213.4937595.242183.697314.8200214822273740379143499.9140910.551378.2104790.6一：現(xiàn)估計(jì)模型為Y=A0+A1*X1+A2*X2+A3*X3+A4*X4+A5*X5+A6*X6+U 運(yùn)用OLS估計(jì)方法對上式中得參數(shù)進(jìn)行估計(jì)，利用Eviews軟件得回歸分析結(jié)果如下：（表1.2）Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 20:44Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C5421.2153244.8561.6707100.1121X10.0509330.0302151.6857080.1091X2-0.2244280.113375-1.9795160.0633X321.183872.08494110.160420.0000X4-0.2165350.203877-1.0620840.3022X50.4884900.3118031.5666650.1346X60.3366200.1392082.4181020.0264R-squared0.999725 Mean dependent var35976.74Adjusted R-squared0.999634 S.D. dependent var34444.88S.E. of regression658.9930 Akaike info criterion16.05080Sum squared resid7816893. Schwarz criterion16.39208Log likelihood-193.6350 F-statistic10925.17Durbin-Watson stat1.748019 Prob(F-statistic)0.000000分析回歸結(jié)果：從經(jīng)濟(jì)意義上講，就業(yè)人口X2的系數(shù)為負(fù)，可初步認(rèn)為國民經(jīng)濟(jì)在向技術(shù)密集型、資本密集型發(fā)展。農(nóng)業(yè)總產(chǎn)值的系數(shù)為負(fù)，不符合實(shí)際經(jīng)濟(jì)意義。其余解釋變量的系數(shù)為正，符合實(shí)際經(jīng)濟(jì)現(xiàn)象。從模型檢驗(yàn)上講，擬合較好?？蓻Q系數(shù)R（2）=0.999725,F統(tǒng)計(jì)量為10925.172.66=F0.05(6,18)表明模型在整體上擬合非常好；系數(shù)顯著性檢驗(yàn)：對于A0,t統(tǒng)計(jì)量為1.670710，給定0.05 查t分布表，在自由度為n-k=18下，得臨界值T0.025(18)=2.101因?yàn)閠T0.025(18),所以接受H0:A0=0的原假設(shè)。對于A1、A2、A3、A4、A5、A6,除去A3、A6的t統(tǒng)計(jì)量大于T0.025(18)之外，其余系數(shù)的t統(tǒng)計(jì)量均小于T0.025(18) ，因此可初步認(rèn)為模型存在嚴(yán)重的多重共線性。現(xiàn)重新估計(jì)模型為Y=A1X1+A2X2+A3X3+A4X4+A5X5+A6X6得回歸結(jié)果如下（表1.3）：Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 20:57Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. X10.0106560.0190530.5592690.5825X2-0.0412480.030184-1.3665640.1877X322.689741.96667011.537140.0000X4-0.1400060.207819-0.6736920.5086X50.1460230.2457790.5941240.5594X60.3871080.1421502.7232410.0135R-squared0.999683 Mean dependent var35976.74Adjusted R-squared0.999599 S.D. dependent var34444.88S.E. of regression689.3576 Akaike info criterion16.11496Sum squared resid9029064. Schwarz criterion16.40749Log likelihood-195.4370 Durbin-Watson stat1.704338從模型檢驗(yàn)上看，R(2)=0.999683小于第一次模型的可決系數(shù);T檢驗(yàn)也并不優(yōu)于第一次模型的t檢驗(yàn)，故仍采用第一次模型。二、多重共線性檢驗(yàn) 1、檢驗(yàn)：利用Eviews計(jì)算線性回歸模型中，六個(gè)解釋變量的如下簡單相關(guān)系數(shù)矩陣(表2.1.1)：X1X2X3X4X5X6X110.9784543274310.920854078840.8881671741190.9111188771040.883472715462X20.97845432743110.9488157613280.9171258679460.9460360865940.909232951166X30.920854078840.94881576132810.9827864539390.9970082872950.982361794167X40.8881671741190.9171258679460.98278645393910.9907093117320.997396156937X50.9111188771040.9460360865940.9970082872950.99070931173210.98844222336X60.8834727154620.9092329511660.9823617941670.9973961569370.988442223361從上表可以看出，各解釋變量之間存在高度線性相關(guān)。同時(shí)由表1.2又可看出，盡管整體上線性回歸擬合較好，但X1 X2 X4 X5 變量的參數(shù)T值并不顯著，表明模型中解釋變量確實(shí)存在嚴(yán)重的多重共線性。2、修正：運(yùn)用OLS方法逐一求出Y對各個(gè)解釋變量的回歸，分別如下：Y=-67070.34+1.029232X1 （式2.1.1） (9781.140) (0.093575)t=(-6.856618) (10.99902) R(2)=0.840254 Se=14063.12 F=120.9784Y=-133299.7+2.962005X2 （式2.1.2） (12588.50) (0.212476)t=(-10.58901) (13.68286)R(2)=0.890591 Se=11638.38 F=187.2206Y=-2268.943+27.31756X3 （式2.1.3） (348.7497) (0.186822)t=(-6.505936) (146.2225)R(2)=0.998925 Se=1153.406 F=21381.06Y=617.7713+2.752282X4 （式2.1.4） (1669.79)(0.094620)t=(0.369969) (29.08787)R(2)=0.973536 Se=5723.931 F=846.1039Y=-1873.193+2.700977X5 （式2.1.5） (712.2024) (0.037971) t=(-2.630142) (71.13173)R(2)=0.995475 Se=2366.912 F=5059.723Y=5875.266+2.222034X6 （式2.1.6） (1531.230) (0.075790)t=（3.836958）（29.31845）R(2)=0.973940 Se=5680.092 F=859.5713綜合分析可見，在七個(gè)一元回歸模型中，GDP(Y)對居民消費(fèi)水平(X3)線性關(guān)系強(qiáng)，擬合程度好。（2）將其余解釋變量逐一帶入對X3的一元線性回歸方程中，得以下幾個(gè)模型：Y=-387.7386-0.027368X1+27.93105X3 （式2.2.1） (1367.242) (0.019261) (0.468871)t=(-0.283592) (-1.420886) (59.57089)R(2)=0.998926 Se=1128.676 F=11165.14Y=6262.980+0.029858X1-0.232206X2+28.56686X3 （式2.2.2） (3643.674) (0.034485) (0.119009) (0.548771)t=(1.718864) (0.865831) (-1.951160) (52.05602)R(2)=0.999048 Se=1062.902 F=8394.415Y=4027.197+0.032089X1-0.181952X2+24.94421X3+0.327880X4 （式2.2.3） (2612.367) (0.024319) (0.084582) (0.860040) (0.069519)t=(1.541590) (1.319521) (-2.151190) (29.00354) (4.716419)R(2)=0.999606 Se=749.4065 F=12670.52Y=7124.543+0.061735X1-0.295985X2+22.25771X3+0.173648X4+0.442008X5 （式2.2.4）(3548.587)(0.033478) (0.122613) (2.282200) (0.13910) (0.348654)t=(2.007713)(1.844017) (-2.413968) (9.753743) (1.243811) (1.267755)R(2)=0.999541 Se=738.2831 F=10444.48Y=5421.215+0.050933X1-0.224428X2+21.18387X3-0.216535X4+0.488490X5+0.336620X6 (式2.2.5) （3244.856）（0.030215）（0.113375）（2.084941）（0.203877）（0.311803）（0.139208）t=（1.670710）（1.685708）（-1.979516）（10.16042）（-1.062084）（1.566665）（2.418102）R(2)=0.999634 Se=658.9930 F=10925.17從式（2.2.1）可以看出，解釋變量X1與X2之間存在共線性。又因?yàn)閄2對Y的經(jīng)濟(jì)意義影響低于X1，故舍去X2。從式（2.2.4）（2.2.5）看出，解釋變量X4 X5對Y的影響并不顯著，故將X4 X5撤去得如下模型（表2.2.1）：Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 22:06Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C-903.4074829.1531-1.0895540.2883X1-0.0052610.012145-0.4332060.6693X323.633610.74070231.907060.0000X60.3188140.0507836.2779440.0000R-squared0.999658 Mean dependent var35976.74Adjusted R-squared0.999609 S.D. dependent var34444.88S.E. of regression681.1097 Akaike info criterion16.03097Sum squared resid9742120. Schwarz criterion16.22599Log likelihood-196.3871 F-statistic20452.98Durbin-Watson stat1.631881 Prob(F-statistic)0.000000表2.2.1中能源消費(fèi)總量x1的系數(shù)為負(fù),不符合實(shí)際經(jīng)濟(jì)意義,現(xiàn)舍去1978至1982年的數(shù)據(jù),重新回歸如下:(表2.2.2)Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 22:10Sample: 1983 2002Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C-1797.3341438.251-1.2496660.2294X10.0047770.0183430.2604470.7978X323.500090.84188027.913820.0000X60.3173670.0564105.6260570.0000R-squared0.999589 Mean dependent var43854.06Adjusted R-squared0.999512 S.D. dependent var34234.35S.E. of regression756.2503 Akaike info criterion16.27148Sum squared resid9150632. Schwarz criterion16.47062Log likelihood-158.7148 F-statistic12973.20Durbin-Watson stat1.689291 Prob(F-statistic)0.000000經(jīng)過上述逐步回歸分析，表明y對x1 x3 x6的回歸模型最優(yōu)。三、異方差性檢驗(yàn)1、檢驗(yàn)（1）、GoldfeldQuandt檢驗(yàn)用OLS方法求得下列結(jié)果：Y=-12754.36+0.236669X1+10.96853X3-0.395909X6 （19831989） (6250.887) (0.1134474) (3.689418) (0.767691)R(2)=0.994022 e1(2)=287719.1Y=-5129.215+0.035047X1+23.39430X3+0.304576X6 (19942002) （7786.425）（0.065303）（1.268709）(0.079944)R(2)=0.996966 e2(2)=5139285求F統(tǒng)計(jì)量： F=e2(2)/e1(2)=17.86216139給定顯著性水平=0.05，得臨界值F0.05(4,4)=4.28,比較F=17.86216139 F0.05(4,4)=6.39可初步認(rèn)為不存在異方差。（2）、Arch檢驗(yàn)利用eviews軟件輸出結(jié)果為（表3.1.1）Dependent Variable: E2Method: Least SquaresDate: 06/03/05 Time: 23:01Sample(adjusted): 1986 2002Included observations: 17 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C602213.2337049.71.7867190.0973E2(-1)-0.2996770.304742-0.9833800.3434E2(-2)0.0872030.2895280.3011880.7680E2(-3)-0.0050350.542470-0.0092820.9927R-squared0.115727 Mean dependent var495758.6Adjusted R-squared-0.088335 S.D. dependent var699258.1S.E. of regression729489.3 Akaike info criterion30.04040Sum squared resid6.92E+12 Schwarz criterion30.23645Log likelihood-251.3434 F-statistic0.567116Durbin-Watson stat1.948353 Prob(F-statistic)0.646348叢輸出的輔助回歸函數(shù)重的R(2)計(jì)算（n-p）*R(2)=17*0.115727=1.967359,查(2)分布表給定=0.05得臨界值(2)0.05（3）=7.81因?yàn)椋╪-p）*R(2)=17*0.115727=1.967359(2)0.05（3）=7.81所以拒絕H0,表明不存在異方差。四、自相關(guān)檢驗(yàn)1、檢驗(yàn)（1）、圖示法由表2.2.2的OLS估計(jì)可直接得到殘差resid,生成序列E,輸出結(jié)果如下圖：由此圖可以看出，殘差et不成線性自回歸，可初步認(rèn)為隨機(jī)誤差ut不存在自相關(guān)。（2）DW檢驗(yàn)根據(jù)表2.2.2估計(jì)的結(jié)果，DW=1.689291.給定顯著性水平=0.05，查DW表n=20,k=3得下限臨界值dl=0.998上限臨界值du=1.676因?yàn)閐uDW統(tǒng)計(jì)量=1.6892914-du,表明不存在自相關(guān)。五、運(yùn)用阿爾蒙法進(jìn)行滯后性修正1，對Y ,X1估計(jì)如下有限分布滯后模型Y=A0+B0X1+B1X1（-1）+B2X1(-2)+B3X1(-3)應(yīng)用EVIEWS軟件得回歸分析結(jié)果如下：Dependent Variable: YMethod: Least SquaresDate: 06/04/05 Time: 23:27Sample: 1983 2002Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C-78223.1710398.98-7.5221950.0000PDL01-0.9142960.400006-2.2857050.0362PDL02-0.8282240.410601-2.0170990.0608PDL031.0872860.3888242.7963490.0129R-squared0.935158Mean dependent var43854.06Adjusted R-squared0.923001S.D. dependent var34234.35S.E. of regression9499.609Akaike info criterion21.33275Sum squared resid1.44E+09Schwarz criterion21.53189Log likelihood-209.3275F-statistic76.91841Durbin-Watson stat0.481394Prob(F-statistic)0.000000 Lag Distribution of X1iCoefficientStd. ErrorT-Statistic . * |0 1.00121 0.44552 2.24728 * . |1-0.91430 0.40001-2.28570 * . |2-0.65523 0.39089-1.67625 . *|3 1.77840 0.45803 3.88274Sum of Lags 1.21009 0.08629 14.0238即是Y-78223.17+1.00121X10.91430X1(-1) -0.65523X1(-2)+ 1.77840X1(-3)2對Y ,X3有限分布滯后模型Y=A0+B0X3+B1X3(-1)+B2X3(-2)+B3X3(-3)用EVIEWS軟件顯示回歸分如下：Dependent Variable: YMethod: Least SquaresDate: 06/04/05 Time: 23:31Sample: 1983 2002Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C-2497.770516.2504-4.8382920.0002PDL012.1069172.1767250.9679300.3475PDL02-15.958292.156581-7.3998110.0000PDL038.5508662.1502223.9767370.0011R-squared0.998874Mean dependent var43854.06Adjusted R-squared0.998663S.D. dependent var34234.35S.E. of regression1251.806Akaike info criterion17.27942Sum squared resid25072277Schwarz criterion17.47856Log likelihood-168.7942F-statistic4731.442Durbin-Watson stat1.165284Prob(F-statistic)0.000000 Lag Distribution of X3iCoefficientStd. ErrorT-Statistic . *|0 26.6161 2.22221 11.9773 .* |1 2.10692 2.17672 0.96793 * . |2-5.30051 2.11824-2.50232 . * |3 4.39380 2.45928 1.78662Sum of Lags 27.8163 0.33326 83.4682即是Y-2497.770+26.6161 X3+2.10692 X3 (-1) -5.30051 X3 (-2)+ 4.39380 X3 (-3)3對Y , x6有限分布滯后模型Y=A0+B0 x6+B1 x6 (-1)+B2 x6 (-2)+B3 x6 (-3)用EVIEWS軟件顯示回歸分如下：Dependent Variable: YMethod: Least SquaresDate: 06/04/05 Time: 23:37Sample: 1983 2002Included observations: 20VariableCoefficientStd. Errort-StatisticProb. C8207.6061631.5105.0306800.0001PDL010.7740280.3432472.2550150.0385PDL02-0.0758520.363485-0.2086800.8373PDL03-0.0649750.330846-0.1963910.8468R-squared0.983441Mean dependent var43854.06Adjusted R-squared0.980336S.D. dependent var34234.35S.E. of regression4800.586Akaike info criterion19.96772Sum squared resid3.69E+08Schwarz criterion20.16687Log likelihood-195.6772F-statistic316.7499Durbin-Watson stat0.342226Prob(F-statistic)0.000000 Lag Distribution of X6iCoefficientStd. ErrorT-Statistic . *|0 0.78491 0.39271 1.99867 . *|1 0.77403 0.34325 2.25501 . * |2 0.63320 0.34422 1.83951 . * |3 0.36242 0.46095 0.78625Sum of Lags 2.55456 0.14135 18.0730即是Y=8207.606+0.78491 x6+0.77403 x6 (-1)+ 0.63320 x6 (-2)+ 0.36242 x6 (-3)通過以上一系列統(tǒng)計(jì)檢驗(yàn)可以說明：我國GDP的增長與能源消費(fèi)總量X1,居民消費(fèi)水平X3，進(jìn)出口貿(mào)易總額X6有很高的相關(guān)性。其中，又以居民消費(fèi)水平X3的影響程度最為顯著。由此可以看出影響我國GDP的主要因素是居民消費(fèi)水平，進(jìn)出口貿(mào)易總額，能源消費(fèi)總量。附本（相關(guān)表格）（表2.1.2）Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 21:08Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C-67070.349781.840-6.8566180.0000X11.0292320.09357510.999020.0000R-squared0.840254 Mean dependent var35976.74Adjusted R-squared0.833308 S.D. dependent var34444.88S.E. of regression14063.12 Akaike info criterion22.01712Sum squared resid4.55E+09 Schwarz criterion22.11463Log likelihood-273.2140 F-statistic120.9784Durbin-Watson stat0.094594 Prob(F-statistic)0.000000(表2.1.3)Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 21:12Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C-133299.712588.50-10.589010.0000X22.9620050.21647613.682860.0000R-squared0.890591 Mean dependent var35976.74Adjusted R-squared0.885834 S.D. dependent var34444.88S.E. of regression11638.38 Akaike info criterion21.63862Sum squared resid3.12E+09 Schwarz criterion21.73613Log likelihood-268.4828 F-statistic187.2206Durbin-Watson stat0.159690 Prob(F-statistic)0.000000(表2。1.4)Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 21:15Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C-2268.943348.7497-6.5059360.0000X327.317560.186822146.22260.0000R-squared0.998925 Mean dependent var35976.74Adjusted R-squared0.998879 S.D. dependent var34444.88S.E. of regression1153.406 Akaike info criterion17.01544Sum squared resid30597948 Schwarz criterion17.11295Log likelihood-210.6931 F-statistic21381.06Durbin-Watson stat0.841840 Prob(F-statistic)0.000000(表2.1.5)Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 21:17Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C617.77131669.7900.3699690.7148X42.7522820.09462029.087870.0000R-squared0.973536 Mean dependent var35976.74Adjusted R-squared0.972385 S.D. dependent var34444.88S.E. of regression5723.931 Akaike info criterion20.21932Sum squared resid7.54E+08 Schwarz criterion20.31683Log likelihood-250.7415 F-statistic846.1039Durbin-Watson stat0.557749 Prob(F-statistic)0.000000( 表2.1.6)Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 21:21Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C-1873.193712.2024-2.6301420.0150X52.7009770.03797171.131730.0000R-squared0.995475 Mean dependent var35976.74Adjusted R-squared0.995278 S.D. dependent var34444.88S.E. of regression2366.912 Akaike info criterion18.45318Sum squared resid1.29E+08 Schwarz criterion18.55069Log likelihood-228.6647 F-statistic5059.723Durbin-Watson stat0.288053 Prob(F-statistic)0.000000(表2.1.7)Dependent Variable: YMethod: Least SquaresDate: 06/03/05 Time: 21:23Sample: 1978 2002Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C5875.2661531.2303.8369580.0008X62.2220340.07579029.318450.0000R-squared0.973940 Mean dependent var35976.74Adjusted R-squared0