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1、计量经济学实验报告异方差（五）一、实验内容为了了解某社区居民的消费情况，现从该社区随机抽取了35个家庭，取得了如下的一组数据，其中X为可支配收入，Y为消费性支出，试建立两者适当的回归模型，然后检验该模型是否存在异方差，如果存在异方差，请设法消除异方差。可支配收入X消费性支出Y1386.10991.85958.87723.42803.65641.091143.23904.842148.232106.02961.54900.841114.11913.081542.581120.301200.28881.47963.62890.942089.991712.491061.86952.361187.20
2、845.292499.902348.212194.692036.461819.521306.841457.141214.63944.28751.32912.00786.791432.821000.25922.04710.301063.761010.86893.70852.141193.401132.181684.751463.391931.581677.381993.191403.991548.981190.10968.36791.05894.15858.101931.021512.941035.20807.162260.952240.592065.011529.551084.21972.27
3、二、实验目的1、掌握异方差出现的来源、后果、检验及修正的原理，以及相关的EViews软件操作方法。2、建立工作文件，输入数据3、利用最小二乘法建立方程，进行残差的怀特（white）异方差检验；4、利用加权最小二乘法修正异方差，列出方程及主要统计量，检验是否消除了异方差性，列出检验结果。三、实验步骤（简要写明实验步骤）1、首先建立一个工作文件、建立回归模型；2、由于这是截面数据，所以要检验是否存在异方差1）、可以从图形的角度来检验，为此首先生成该残差序列;2）、WHITE检验3、消除异方差，WLS估计法1-165.02202-54.761413J4933684-36.755475273.6069
4、6120.29197-2.7039238-175.2736g-110.693810108.548311-68.2099612328B97313-135.279914204.081715162865518-234209217-S.210795佃-13.929051950.15348nn点击resid得到残差项12723-22522998.81230.24341241350.95557486076614470.1577.311202a30720.83g12253.1110117S272114664.884126370.707n18300.64u4164934is7RS7S1R16540339617
5、27.15239储15401341925153了2203921742211241.5642219517.65-1LJIi-s11hrI.nIIXIivi；rriir*-:nr.nIIXIiv1rr.Hl点击e2和x右键asgrop得到散点图11.61936720.9074503779543140.603061&0.85336562.47004615.71760081.30616691.404429102.255820111.810249121.322795131.850017140.34725-5150.27043-6-16-1.21634-1175l494004181763393190.93
6、4376201.8496&9210.1S4430222359598E12M0.0001557iiviil气rr11V1-r11r-*i-厂h1IIii鼻i在上方输入lsycX,点击view中的White检验得到数据#urviiwihhu*vwbi*wSampiec135Includedobservations:35Weightingseries:1/XWeighttype:Standarddeviation(averagescaling;AVariableCoefTicientStri.Errort-StatisticProb.C-227.5470109.4062-2.0798370.0454
7、X0.9798490.0603716.226060.0000Weighted&tatisliceR.-squared0.8SS621Meandependentvar1553.226AdjustedR-squared0.8S5246S.D.dependentvar9&4.4&48S.E.ofregression176.8146Maikeinfocriterion13.24J53SumsquaredreGid1031692.Schwarzcriterion1333240Loglikelihood-229.7617Hannan-Q-Uinncriter.13.27421F-statistic263.
8、2849urbin-Watsonstat2.281674Prob(F-statiStic)0.000000Weightedmeandep.1400.162UnweightedStatisticsR-squared0.-8S7S32Meandependentvar1176.&S5AQjlistedR-squared0.5S4434SLD.dependentvar62.0307S.E.ofregression157.0671Sumsquaredr&sidS1411ZEurbin-Watsonstat2.084174四、实验结果及分析1、回归估计结果:y=-71.74720+0.886386x2、残差序列得到的图形为
