《计量经济学》课程论文 产业结构变动对我国经济增长影响

1、计量经济学课程论文产业结构变动对我国经济增长影响2011级金融7班于晓琪摘要：经济发展是以经济增长为前提的，而经济增长与产业结构变动又有着密不可分的关系。本文采用1978年至2012年的统计数据，根据经济学原理，在模型中我们引入了三个变量：GDP增长率、第一产业增长率、第二产业增长率和第三产业增长率，利用EVIEWS软件对计量模型进行了参数估计和检验，多重共线性的检验，异方差的检验和自相关的检验并加以修正。研究三大产业增长对我国经济增长的贡献，从而得出调整产业结构对转变经济发展方式，促进我国经济可持续发展的重要性。一、问题提出：经济增长通常是指在一个较长的时间跨度上，一个国家人均产出(或人均收

2、入)水平的持续增加。经济增长率的高低体现了一个国家或地区在一定时期内经济总量的增长速度，也是衡量一个国家或地区总体经济实力增长速度的标志。它构成了经济发展的物质基础，而产业结构的调整与优化升级对于经济增长乃至经济发展至关重要。一个国家产业结构的状态及优化升级能力，是经济发展的重要动力。十六大报告提出，推进产业结构优化升级，形成以高新技术产业为先导、基础产业和制造业为支撑、服务业全面发展的产业格局。十七大报告明确指出，推动产业结构优化升级，这是关系国民经济全局紧迫而重大的战略任务。十二五规划纲要又将经济结构战略性调整作为主攻方向和核心任务。产业结构优化升级对于促进我国经济全面协调可持续发展具有重

3、要作用。二、模型的设定及数据说明1、模型设定通过对数据观察，根据搜集的1978年至2012年的统计数据，建立模型。其模型表达式为：Yt二a+BX+B2X2+83X3+(i=1,2,3)其中：Y表示国内生产总值(GDP)的年增长率，Xi、“、3分别表示第一、二、三产业的年增长率，a表示在不变情况下，经济固有增长率。可近似认为，表明国内生产总值增长为三次产业增加值增长率的加权和，而Bi分别表示各产业部门在经济增长中的权数；BiXj则表示各产业部门对经济增长的贡献。表示随机误差项。通过上式，我们可以了解到，各产业每增长1个百分点，国内生产总值(GDP)会如何变化。从而进行经济预测，为产业政策调整提供

4、依据与参考。2、数据说明本数据来源自中国数据统计年鉴2013年年份GDP增长率第产业增长率第一产业增长率第三产业增长率19828.827241413.97515535.65284868.0208682198312.009364211.307901911.044901415.0577269198420.886683317.069563417.364522733.4960063198525.082850910.720975824.500112744.7178167198613.96558938.746458916.192520615.8120866198717.356737715.93400631

5、6.891846819.3796508198824.747517519.558093825.432249228.4357596198912.959642610.362829510.487005118.694693719909.860356718.66130566.03737298.0762545199116.679385.535361517.943867124.602125199223.60708489.816180628.534859727.5350916199331.238344318.701852840.642175427.3405059199436.406744637.46439813

6、6.409448835.784899199526.133678326.775288727.774326623.4780803199617.078837915.487869117.976286716.7569587199710.95366213.043052510.959206915.69864719986.87480832.60173683.892033813.310726919996.2495646-0.32121915.203013110.7682434200010.63538451.182760311.020964314.289982200110.52327085.59760518.68

7、4747614.588168220029.737364.7889098.855330112.4821692200312.87270075.107921915.844260612.2363905200417.711009923.191127718.367516215.2782921200515.67381264.704051118.529070316.0436429200616.96631527.225691318.403879718.2004019200722.881451219.080698821.318852925.7434286200818.146445117.72801918.4151

8、88617.950327520098.55207024.52198685.795394112.713606317.779255715.067279918.868729717.264446817.830379117.152709317.626767518.08022769.688790210.2922826.691616612.8908其中，GDP增长率、第一产业增长率、第二产业增长率和第三产业增长率都是由2013年国家统计年鉴数据库中用下一年的数据减去上一年的数据除以上一年的数据得出来的。三、模型参数估计运用eview5软件，采用最小二乘法，对表一中的数据进行线性回归，对所建模型进行估计，估计

9、结果见下图。从估计结果可得模型：Y=1.310433+0.212649X1+0.498946X2+0.223825X3AADependentVariable:YMethod:LeastSquaresDate:05/28/14Time:20:26Sample:19812011Includedobservations:31VariableCoefficientStd.Errort-StatisticProb.C1.3104330.2405815.4469530.0000X10.2126490.01464614.519080.0000X20.4989460.01836027.174980.0000X

10、30.2238250.01712513.069740.0000R-squared0.995409Meandependentvar16.44891AdjustedR-squared0.994899S.D.dependentvar7.250511S.E.ofregression0.517821Akaikeinfocriterion1.641540Sumsquaredresid7.239742Schwarzcriterion1.826571Loglikelihood-21.44387F-statistic1951.550Durbin-Watsonstat1.510010Prob(F-statisti

11、c)0.000000四、模型的检验通过上述线性回归得到模型，现在就其具体形式进行检验：1、经济意义检验通过估计所得到参数，可进行经济意义检验：a=1.310433，表示当三大产业保持原有规模，我国GDP仍能增加1.310433个百分点。这种结果符合经济发展规律，合理。B1=0.212649,表示在其他条件不变的情况下，第一产业每增长1个百分点，GDP增加0.212649个百分点；反之，降低0.212649，符合经济现实。32=0.498946，表示在其他条件不变的情况下，第产业每增长1个百分点，GDP增加0.498946个百分点；反之，降低0.498946，符合现实。B3=0.223825,表

12、示在其他条件不变的情况下，第一产业每增长1个百分点，GDP增加0.223825个百分点；反之，降低0.223825，合理。综上可知，该模型符合经济意义，经济意义检验通过。2、统计检验拟合优度检验样本决定系数R辽的值越接近1,说明回归直线对观测值的拟合程度越好；反之，R辽的值越接近0,说明回归直线对观测值的拟合程度越差。由图1参数估计结果可得，样本决定系数R2=0.9954090.8,可见其拟合优度不错。调整后的样本决定系数因解释变量为多元，使用调整的拟合优度，以消除解释变量对拟合优度的影响。调整后的R2=0.9948990.8,所以，其拟合程度不错。方程显著性检验有模型可知总离差平方和TSS的

13、自由度为30(n-1),回归平方和ESS的自由度为3。所以，残差平方和的自由度为27(n-k-1)。Ho：Bi=0H1：BiHOAADependentVariable:Y在Ho成立的条件下，统计量F=（ESS/k）/（RSS/（nKl）=1951.35722而在a=0.05,n=31,k=3时，查表得F0.05（3,27）=2.96T0.o25（27）=2.056,则拒绝原假设，接受备选假设，即认为Bi显著不为0。3、计量经济学检验解释变量之间的多重共线性检验检验：由F0o5（3,27）=2.961951.550（显著性水平a=0.05）表明模型从整体上看GDP增长率与解释变量间线形关系显著。

14、这里采用简单相关系数矩阵法对其进行检验AAX1X2X11.00000000.6323488X20.63234881.0000000X30.45307250.7505386X30.45307250.75053861.0000000XX从结果可知2，3，之间存在高度相关。找出最简单的回归形式分别作Y与1，X，X3间的回归:Method:LeastSquaresDate:05/28/14Time:21:38Sample:19812011Includedobservations:31VariableCoefficientStd.Errort-StatisticProb.C8.4112331.57254

15、75.3487950.0000X10.6538440.1064036.1450020.0000R-squared0.565615Meandependentvar16.44891AdjustedR-squared0.550636S.D.dependentvar7.250511S.E.ofregression4.860351Akaikeinfocriterion6.062439Sumsquaredresid685.0674Schwarzcriterion6.154955Loglikelihood-91.96781F-statistic37.76105Durbin-Watsonstat1.32829

16、9Prob(F-statistic)0.000001(5.348795)(6.145002)R2=0.565615F=37.76105D.W.=1.328299AADependentVariable:YMethod:LeastSquaresDate:05/28/14Time:21:44Sample:19812011Includedobservations:31VariableCoefficientStd.Errort-StatisticProb.C3.5756210.7258294.9262580.0000X20.7804120.03879520.116520.0000R-squared0.9

17、33130Meandependentvar16.44891AdjustedR-squared0.930824S.D.dependentvar7.250511S.E.ofregression1.906985Akaikeinfocriterion4.191265Sumsquaredresid105.4612Schwarzcriterion4.283780Loglikelihood-62.96461F-statistic404.6745Durbin-Watsonstat1.867814Prob(F-statistic)0.000000zY=3.575621+0.780412X2(4.926258)(

18、20.11652)R2=0.933130F=404.6745D.W.=1.867814Method:LeastSquaresDate:05/28/14Time:21:49Sample:19812011Includedobservations:31VariableCoefficientStd.Errort-StatisticProb.C2.6000461.8623871.3960820.1733X30.7218680.0892228.0907250.0000R-squared0.692991Meandependentvar16.44891AdjustedR-squared0.682405S.D.

19、dependentvar7.250511S.E.ofregression4.086069Akaikeinfocriterion5.715385Sumsquaredresid484.1828Schwarzcriterion5.807900Loglikelihood-86.58846F-statistic65.45983Durbin-Watsonstat0.955791Prob(F-statistic)0.0000000二2.600046+Og(1.396082)(8.090725)R2=0.692991F=65.45983D.W.=0.955791可见，第二产业对GDP影响最大，因此选为初始的回

20、归模型。从而得出最有简单回归方程用二3-575621+0-780412X2逐步回归将其余变量逐一引入Y二3575621+0780412X2AADependentVariable:YMethod:LeastSquaresDate:05/28/14Time:22:00Sample:19812011Includedobservations:31VariableCoefficientStd.Errort-StatisticProb.C3.0436880.5335375.7047350.0000X10.2045990.0388955.2602800.0000X20.6601860.03614418.26

21、5580.0000R-squared0.966367Meandependentvar16.44891AdjustedR-squared0.963965S.D.dependentvar7.250511S.E.ofregression1.376365Akaikeinfocriterion3.568534Sumsquaredresid53.04264Schwarzcriterion3.707307Loglikelihood-52.31228F-statistic402.2568Durbin-Watsonstat1.909921Prob(F-statistic)0.000000由表可知，引入Xi后拟合

22、优度改善,各项指标符合经济意义。AADependentVariable:YMethod:LeastSquaresDate:05/28/14Time:22:05Sample:19812011Ineludedobservations:31VariableCoefficientStd.Errort-StatisticProb.C1.3104330.2405815.4469530.0000X10.2126490.01464614.519080.0000X20.4989460.01836027.174980.0000X30.2238250.01712513.069740.0000R-squared0.9

23、95409Meandependentvar16.44891AdjustedR-squared0.994899S.D.dependentvar7.250511S.E.ofregression0.517821Akaikeinfocriterion1.641540Sumsquaredresid7.239742Schwarzcriterion1.826571Loglikelihood-21.44387F-statistic1951.550Durbin-Watsonstat1.510010Prob(F-statistic)0.000000引入X3后，各项指标都符合经济意义。逐步回归cX1X2X3R2D.

24、W.Y二f(X)23.5756210.7804120.9308241.867814t值(4.926258)(20.11652)Y=f(X,X)123.0436880.2045990.6601860.9639651.909921t值(5.704735)(5.260280)(18.26558)Y二f(X,X,X)1231.3104330.2126490.4989460.2238250.9948991.510010t值(5.446953)(14.51908)(27.17498)(13.06974)综上所述，该模型不存在共线性问题。其模型为Y二1.310433+0.212649X+0.498946X+

25、0.223825X“曰小屮钿123为取优模型。(2)异方差性检验怀特检验:有交叉项的:AAWhiteHeteroskedasticityTest:F-statistic0.698698Probability0.703120Obs*R-squared7.143604Probability0.622171TestEquation:DependentVariable:RESIDA2Method:LeastSquaresDate:06/08/14Time:20:17Sample:19812011Ineludedobservations:31CoefficienVariabletStd.Errort-S

26、tatisticProb.-0.01950C40.689859-0.0282720.9777-0.01612X180.031261-0.5158960.6113X1A20.0014520.0023370.6212570.5411-0.00014X1*X220.003633-0.0391200.9692-0.00062X1*X390.002759-0.2278420.8220X20.0443640.0497210.8922560.3824-0.00059X2A260.002179-0.2735850.7871-0.00053X2*X360.004123-0.1300170.8978-0.0146

27、7X320.074546-0.1968210.8459X3A20.0006750.0017390.3881840.7018R-squared0.230439Meandependentvar0.233540-0.09937AdjustedR-squared3S.D.dependentvar0.362203S.E.ofregression0.379774Akaikeinfocriterion1.157215Sumsquaredresid3.028791Schwarzcriterion1.619791-7.93683Loglikelihood0F-statistic0.698698Durbin-Wa

28、tsonstat1.943068Prob(F-statistic)0.703120e2=-0.019504-0.016128X+0.044364X-0.014672X+0.001452X2-0.000596X2+0.000675X2-0.000142XX-0.000629XX-0.000536XX123123121323R2=0.230439怀特统计量nR2=31*0.230439=7.143609，该值小于5%显著水平下、自由度为9的12分布的相应临界值10.05=11.07，因此，接受同方差的原假设。所以不存在异方差性。(3)序列相关性检验2JI-1.284048aaaaa-990O002

29、O20YResiduals-0.4-0.8-1.21.2-1.2-0.8-0.40.00.40.8RESID(-I)在给定a=0.05,n=31,k=3,查D-W统计表，得dL=l.23,dU=1.65。由dL=l.23DW=l.5l00l0du=i.65,不能确定是否存在自相关性。引入时间变量T(T=l,2,31)以平方的形式出现,AADependentVariable:YMethod:LeastSquaresDate:06/08/14Time:22:52Sample:19812011Includedobservations:31VariableCoefficientStd.Errort-S

30、tatisticProb.C0.9388890.2857923.2852230.0029X10.2132860.01377715.481150.0000X20.4950740.01736328.513800.0000X30.2343730.01685113.908460.0000TA20.0006700.0003152.1279240.0430R-squared0.996900Meandependentvar16.44891AdjustedR-squared0.995489S.D.dependentvar7.250511S.E.ofregression0.486981Akaikeinfocri

31、terion1.545506Sumsquaredresid6.165911Schwarzcriterion1.776795Loglikelihood-18.95535F-statistic1656.049Durbin-Watsonstat1.653514Prob(F-statistic)0.000000回归函数变化为：Y二0.938889+0.213286X+0.495074X+0.234373X+0.000670T2123(3.285223)(15.48115)(28.51380)(13.90846)(2.127924)R2=0.996900R2=0.995489F=1656.049D.W.

32、=1.653514这里，D.W.值大于5%显著水平下的D.W.检验，因此存在虚假序列相关。LM检验：AABreusch-GodfreySerialCorrelationLMTest:F-statistic0.659367Probability0.424448Obs*R-squared0.796605Probability0.372110TestEquation:DependentVariable:RESIDMethod:LeastSquaresDate:06/08/14Time:23:11Presamplemissingvaluelaggedresidualssettozero.Variabl

33、eCoefficientStd.Errort-StatisticProb.C0.0024250.2876980.0084310.9933X1-0.0021410.014117-0.1516700.8807X20.0010370.0175240.0591860.9533X30.0005150.0169740.0303420.9760TA2-1.60E-050.000318-0.0502880.9603RESID(-1)0.1663640.2048780.8120140.4244R-squared0.025697Meandependentvar-1.64E-15AdjustedR-squared-0.169164S.D.dependentvar0.453355S.E.ofregression0.490203Akaikeinfocriterion1.583990Sumsquaredresid6.007466Schwarzcriterion1.861536Loglikelihood-18.55184F-statistic0.131873Durbin-Watsonstat1.929507Prob(F-statistic)0.983571含1阶滞后残差项的辅助回归为：二0.002425-0.002141X+0.00103