我国采矿业龙头企业利润因素分析.doc

我国采矿业龙头企业利润因素分析 内容摘要：本文是根据我国采矿业的现状，想从计量经济学的角度来验证一下是否产品销售收入，资产总计，全年从业人员平均人数对利润总额的影响。因此，在模型中引入3个变量：产品销售收入，资产总计，全年从业人员平均人数关键词：产品销售收入 资产总计 全年从业人员平均人数 利润一、 导论采矿业是指煤炭开采和洗选业、石油和天然气开采业、黑色金属矿采选业、有色金属矿采选业、非金属矿采选业、其他采矿业（采用新标准国民经济行业分类标准 gb/t 47542002）二、 模型设定.根据经济学理论本该把模型设定为：y =c+u其中：y : 利润总额(千元)x1:产品销售收入(千元)x2: 资产总计(千元)x3: 全年从业人员平均人数(人)数据如下2005年0103月采矿业龙头企业基本情况（按产品销售收入排序）单位:千元名次产品销售收入资产总计利润总额全年从业人员平均人数（人）12939945091280100200378108929521369093049228390723849061164367081704075932041734901268445971350330029803018900155505527653416131376280588455865239410376874906000009893374995660302587602232530292788417125021993070248088010089936107125848652272266624310327882017470440228310137684资料来源：中经网数据中心三、 参数估计将原始模型简化为：y =c+u用eviews估计结果为： dependent variable: ymethod: least squaresdate: 05/07/05 time: 19:09sample: 1 10included observations: 10variablecoefficientstd. errort-statisticprob. c-398461.3470822.2-0.8463100.4298x10.8459040.08396810.074150.0001x2-0.0392770.028850-1.3614010.2223x3-14.359875.345114-2.6865420.0362r-squared0.989692 mean dependent var4562896.adjusted r-squared0.984538 s.d. dependent var5769938.s.e. of regression717469.5 akaike info criterion30.09402sum squared resid3.09e+12 schwarz criterion30.21506log likelihood-146.4701 f-statistic192.0245durbin-watson stat2.290820 prob(f-statistic)0.000002四、 检验及修正1经济意义检验从上表中可以看出，x1符号与先验信息相符，所估计结果没有与经济原理向悖，说明具有经济意义。x2,x3待检验。2统计推断检验从回归结果可以看出，模型的拟和优度非常好（r2=0.989692），f统计量的值在给定显著性水平=0.05的情况下也较显著，但是x2、x3的t统计值均不显著（x2、x3的t统计量的值的绝对值均小于3），说明x2、x3这两个变量对y的影响不显著，或者变量之间存在多重共线的影响使其t值不显著。3计量经济学检验（1）多重共线性检验 检验修正：采用逐步回归法对其进行补救dependent variable: ymethod: least squaresdate: 06/05/05 time: 19:53sample: 1 10included observations: 10variablecoefficientstd. errort-statisticprob. c-620266.1636943.2-0.9738170.3626x10.8721800.1145977.6108600.0001x2-0.0581500.038450-1.5123430.1742r-squared0.977292 mean dependent var4562896.adjusted r-squared0.970804 s.d. dependent var5769938.s.e. of regression985891.8 akaike info criterion30.68381sum squared resid6.80e+12 schwarz criterion30.77458log likelihood-150.4190 f-statistic150.6332durbin-watson stat2.277256 prob(f-statistic)0.000002x2的t检验值不显著，故删去。dependent variable: ymethod: least squaresdate: 06/05/05 time: 19:55sample: 1 10included observations: 10variablecoefficientstd. errort-statisticprob. c-794396.0392181.0-2.0255850.0824x10.7398640.03322022.271720.0000x3-16.131835.491156-2.9377840.0218r-squared0.986508 mean dependent var4562896.adjusted r-squared0.982653 s.d. dependent var5769938.s.e. of regression759947.7 akaike info criterion30.16321sum squared resid4.04e+12 schwarz criterion30.25399log likelihood-147.8161 f-statistic255.9104durbin-watson stat1.485457 prob(f-statistic)0.000000x3系数为负，与经济意义不符，故删去。模型修改为如下形式： y=c+x1+新模型估计结果dependent variable: ymethod: least squaresdate: 05/07/05 time: 19:16sample: 1 10included observations: 10variablecoefficientstd. errort-statisticprob. c-1286484.495671.8-2.5954340.0318x10.7103910.04426616.048100.0000r-squared0.969873 mean dependent var4562896.adjusted r-squared0.966107 s.d. dependent var5769938.s.e. of regression1062249. akaike info criterion30.76653sum squared resid9.03e+12 schwarz criterion30.82705log likelihood-151.8327 f-statistic257.5415durbin-watson stat2.308206 prob(f-statistic)0.000000(2)异方差检验 检验：利用quandt检验法检验模型是否存在异方差。dependent variable: ymethod: least squaresdate: 06/05/05 time: 20:05sample: 1 4included observations: 4variablecoefficientstd. errort-statisticprob. c-1204487.3762374.-0.3201400.7792x10.7774030.9252250.8402320.4892r-squared0.260899 mean dependent var1916096.adjusted r-squared-0.108652 s.d. dependent var1142846.s.e. of regression1203331. akaike info criterion31.14594sum squared resid2.90e+12 schwarz criterion30.83909log likelihood-60.29188 f-statistic0.705990durbin-watson stat2.158508 prob(f-statistic)0.489217dependent variable: ymethod: least squaresdate: 06/05/05 time: 20:08sample: 7 10included observations: 4variablecoefficientstd. errort-statisticprob. c-1297256.923708.5-1.4044000.2954x10.7127350.05489912.982630.0059r-squared0.988273 mean dependent var8639672.adjusted r-squared0.982410 s.d. dependent var7797801.s.e. of regression1034210. akaike info criterion30.84303sum squared resid2.14e+12 schwarz criterion30.53617log likelihood-59.68605 f-statistic168.5487durbin-watson stat3.049667 prob(f-statistic)0.005881求f统计量：f=e22/e12=2.90e+12/2.14e+12=1.35514查f分布表，给定显著性水平0.05，f0.05（4，4）=4.111.35514，则接受h0， 发现该模型不存在异方差。（3）一阶自相关检验 检验：从模型设定来看，没有违背d-w检验的假设条件，因此可以用d-w检验来检验模型是否存在一阶自相关。查表,由dw=2.308206，在0.05显著性水平下，dl=0.879,du=1.320，du=1.320dw=