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 4754—2002》）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 01—03 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）129399450912801002003781089295 213690930492283907238490611643670817040759320417349012684 4597135033002980301890015550 55276534161313762805884558 652394103768749060000098933 7499566030258760223253029278 8417125021993070248088010089 9361071258486522722666243 10327882017470440228310137684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: 05/07/05Time: 19:09Sample: 1 10Included observations: 10Variable Coefficient C-398461.3Std. Error470822.2t-Statistic-0.846310Prob.0.4298X10.8459040.08396810.074150.0001X2-0.0392770.028850-1.3614010.2223X3-14.35987 5.345114-2.6865420.0362R-squared0.989692Mean dependent var4562896.Adjusted R-squared0.984538S.D. dependent var5769938.S.E. of regression717469.5Akaike info criterion30.09402Sum squared resid 3.09E+12Schwarz criterion30.21506Log likelihood-146.4701F-statistic192.0245Durbin-Watson stat 2.290820Prob(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（R^2=0.989692 ）， F 统计量的值在给定显著性水平α=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①检验②修正：采用逐步回归法对其进行补救Dependent Variable: YMethod: Least SquaresDate: 06/05/05Time: 19:53Sample: 1 10Included observations: 10Variable Coefficient Std. Error t-Statistic Prob.C-620266.1636943.2-0.9738170.3626X10.8721800.1145977.6108600.0001X2-0.0581500.038450-1.5123430.1742 R-squared0.977292Mean dependent var4562896. Adjusted R-squared0.970804S.D. dependent var5769938.S.E. of regression985891.8Akaike info criterion30.68381 Sum squared resid 6.80E+12Schwarz criterion30.77458 Log likelihood-150.4190F-statistic150.6332 Durbin-Watson stat 2.277256Prob(F-statistic)0.000002 X2 的 T 检验值不显著，故删去。
Dependent Variable: YMethod: Least SquaresDate: 06/05/05Time: 19:55Sample: 1 10Included observations: 10Variable Coefficient Std. Error t-Statistic Prob.C-794396.0392181.0-2.0255850.0824X10.7398640.03322022.271720.0000X3-16.13183 5.491156-2.9377840.0218 R-squared0.986508Mean dependent var4562896. Adjusted R-squared0.982653S.D. dependent var5769938. S.E. of regression759947.7Akaike info criterion30.16321 Sum squared resid 4.04E+12Schwarz criterion30.25399 Log likelihood-147.8161F-statistic255.9104 Durbin-Watson stat 1.485457Prob(F-statistic)0.000000 X3 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: 05/07/05Time: 19:16Sample: 1 10Included observations: 10Variable Coefficient Std. Error t-Statistic Prob.C-1286484.495671.8-2.5954340.0318X10.7103910.04426616.048100.0000 R-squared0.969873Mean dependent var4562896. Adjusted R-squared0.966107S.D. dependent var5769938. S.E. of regression1062249.Akaike info criterion30.76653 Sum squared resid9.03E+12Schwarz criterion30.82705 Log likelihood-151.8327F-statistic257.5415 Durbin-Watson stat 2.308206Prob(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: 06/05/05Time: 20:05Sample: 1 4Included observations: 4Variable Coefficient Std. Error t-Statistic Prob.C-1204487.3762374.-0.3201400.7792X10.7774030.9252250.8402320.4892 R-squared0.260899Mean dependent var1916096. Adjusted R-squared-0.108652S.D. dependent var1142846. S.E. of regression1203331.Akaike info criterion31.14594 Sum squared resid 2.90E+12Schwarz criterion30.83909 Log likelihood-60.29188F-statistic0.705990 Durbin-Watson stat 2.158508Prob(F-statistic)0.489217Dependent Variable: YMethod: Least SquaresDate: 06/05/05Time: 20:08Sample: 7 10Included observations: 4Variable Coefficient Std. Error t-Statistic Prob.C-1297256.923708.5-1.4044000.2954X10.7127350.05489912.982630.0059 R-squared0.988273Mean dependent var8639672. Adjusted R-squared0.982410S.D. dependent var7797801. S.E. of regression1034210.Akaike info criterion30.84303 Sum squared resid 2.14E+12Schwarz criterion30.53617 Log likelihood-59.68605F-statistic168.5487 Durbin-Watson stat 3.049667Prob(F-statistic)0.005881求 F 统计量： F=∑e2^2/ ∑ e1^2=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） =4.11>1.35514，则接受H0 ，发现该模型不存在异方差。