计量经济学实验报告

《计量经济学》实验报告一，数据某年中国部分省市城镇居民家庭人均年可支配收入(X)与消费性支出(Y)统计数据地区口」支配收入(X)消费性支出(Y)地区口」支配收入(X)消费性支出(Y)北京10349.698493.49浙江9279.167020.22天津8140.506121.04山东6489.975022.00河北5661.164348.47河南4766.263830.71山西4724.113941.87湖北5524.544644.5内蒙古5129.053927.75湖南6218.735218.79辽宁5357.794356.06广东9761.578016.91吉林4810.004020.87陕西5124.244276.67黑龙江4912.883824.44甘肃4916.254126.47上海11718.018868.19青海5169.964185.73江苏6800.235323.18新疆5644.864422.93二，理论模型的设计解释变量：可支配收入X被解释变量：消费性支出Y软件操作：(1)X与Y散点图9,000-8,000-7,000-6,000-5,000-4,000-3,000-4,0006,0008,00010,00012,000可支配收入(X)从散点图可以粗略的看出，随着可支配收入的增加，消费性支出也在增加，大致呈线性关系。因此，建立一元线性回归模型：(2)对模型做OLS估计回Equation:UNTITLEDWorkfile:样表::Untitled\-nx|View|Proc|ObjectPrintNameFreezeEstimateForecastStatsResidsDependentVariable:YMethod:LeastSquaresDate:05/05/18Time:16:43Sample:120Includedobservations:20VariableCoefficientStd.Errort-StatisticProb.C272.3635159.67731.7057130.1053X0.7551250.02331632.386900.0000R-squared0.983129Meandependentvar5199.515AdjustedR-squared0.982192S.D.dependentvar1625.275S.E.ofregression216.8900Akaikeinfocriterion13.69130Sumsquaredresid846743.0Schwarzcriterion13.79087Loglikelihood-134.9130Hannan-Quinncriter.13.71073F-statisticProb(F-statistic)1048.9120.000000Durbin-Watsonstat1.301684OLS估计结果为A丫=272.3635+0.755IX办=1.7057%=32.3869R?=0.9831DW.=1.3017F=1048.912三，模型检验从回归估计结果看，模型拟合较好，可决系数为0.98,表明家庭人均年可消费性支出变化的98.31%可由支配性收入的变化来解释。t检验:在5%的显著性水平下从不显著为0,表明可支配收入增加1个单位，消费性支出平均增加0.7551单位。1,预测现已知2018年人均年可支配收入为20000元，预测消费支出预测值为元=272.3635+0.7551x20000=15374.3635E(X)=6222.209,Var(X)=1994.033则在95%的置信度下，E(E)的预测区间为(874.28,16041.68)2,异方差性检验对于经济发达地区和经济落后地区，消费支出的决定因素不一定相同甚至差异很大。如经济越落后储蓄率越高，可能出现异方差性问题。G-Q检验对样本进行处理，X按从大到小排序，去掉中间4个，分为两组数据，勺=%=8分别回归®Equation:UNTITLEDWorkfile:1::1\-曰x|View|Proc|ObjectPrintNameFreezeEstimateForecastStatsResidsDependentVariable:Y1Method:LeastSquaresDate:05/05/18Time:17:42Sample:18Includedobservations:8VariableCoefficientStd.Errort-StatisticProb.C212.2118530.88920.3997290.7032X10.7618930.06034812.625050.0000R-squared0.963723Meandependentvar6760.478AdjustedR-squared0.957676S.D.dependentvar1556.814S.E.ofregression320.2790Akaikeinfocriterion14.58858Sumsquaredresid615472.0Schwarzcriterion14.60844Loglikelihood-56.35432Hannan-Quinncriter.14.45463F-statistic159.3919Durbin-Watsonstat1.722960Prob(F-statistic)0.000015回Equation:UNTITLEDWorkfile:2::2\_□XViewProcObjectPrintNameFreezeEstimateForecastStatsResidsDependentVariable:Y2Method:LeastSquaresDate:05/05/18Time:21:33Sample:18Includedobservations:8VariableCoefficientStd.Errort-StatisticProb.C1277.1611540.6040.8290000.4388X20.5541260.3114321.7792870.1255R-squared0.345397Meandependentvar4016.814AdjustedR-squared0.236296S.D.dependentvar166.1712S.E.ofregression145.2172Akaikeinfocriterion13.00666Sumsquaredresid126528.3Schwarzcriterion13.02652Loglikelihood-50.02663Hannan-Quinncriter.12.87271F-statistic3.165861Durbin-Watsonsta