Panel Data模型EViews操作过程(2013)

1、OK #-CancelOK -CancelorkfilestructuretypeBalancedPanelPanelData模型的EViews操作过程两种模式：I.关于Panel工作文件；II.关于Pool对象。数据的预处理1在EXCEL文件中，将每个变量各年的原始数据按照年份顺序排成一列，称之为堆积数据（见表“汇总0”）。2输入截面单元的标识（表示地区的符号，前面加如：_HB、_NMG等）。3将数据表按照时间分类（即排序，见表“汇总”）。I.关于Panel工作文件的操作过程案例1：我国农村居民消费函数（2000-2010年，27个省市数据，工作文件：NXF）一、输入数据1、创建Panel工

2、作文件选择File/New/Workfile，在出现的创建工作文件对话框中：（1）在文件结构类型中，选择“平衡面板（BalancedPanel）”2）输入起始、终止期，截面单元个数。WorkfileCreateIrregularDatedandPanelworkfilesmaybemadefromUnstructuredworkfilesbylaterspecifyingdateand/orotheridentifierseries.園Workfile:PANELDATA-(c:documentsandsettingszhaowyM.-nx園Workfile:PANELDATA-(c:docu

3、mentsandsettingszhaowyM.-nx- - #-ViewProc|ObjectPrintSav已Details+/-ShowFetchSto已DeleteG已|Sampl已Range:20002010 x27-297obsFilter:1Sample:20002010-297obs0crossid工作文件中将生成分别表示截0dateid0resid面标识和时期标识的两个序列：Crossid截面标识2更改截面标识（可以省略）序列crossid中是以数字1、2、标记截面标识，为了便于区分，可以重新定义一个字符串序列。NXF/NewPage/（1）点击object/Newobjec

4、t，选择seriesAlpha并输入序列名（设为dq）；（2）双击dq序列，在打开的序列窗口中粘贴截面标识的字符串序列；（3）双击工作文件窗口中的Range，在弹出的对话框中，将截面标识的的ID序列改成新的标识序列：dq園Workfile:PANELDATA-(c:documentsandsettingszhaowy桌面paneldata.wfl)ProcObjectPrintSaveDetails+/|ShowFetchStore|Delete|Genr|Sample|Filter:*Range:20002010 x27-297obsSample:20002010-297obsc0cross

5、id0dateidffldq0residWorkfileStructureObservationInclusion/creation0BalancebEtwEe门starts&endsBalancestartsBalanceendsOKCanceliIInsertobstoremovedategapssodatefollowsregularfrequency3键入命令：DATAYX,然后用复制+粘贴方式从Excel文件中将各个变量的堆积数据（注意：数据事先要按照截面单元堆积，本例中是按照“地区”）复制到工作文件之中；此时工作文件中各个变量都是堆积数据。- -二、模型估计过程1估计混合模型直接在

6、命令窗口键入命令：LSYCX2估计变截距模型在方程窗口中点击Estimate按钮,在弹出的方程描述框中选择PanelOptions选项卡,此时可以在截面和时期列表中选择None、Fixed、Random，用来选择单因素（或双因素）固定效应、随机效应变截距模型；同时可以选择GMM、GLS、SUR等估计方法。ViewProcObjectPrintNameFreezeEstimateForecastStatsResidsDependentVariable:YMethod:PanelLeastSquares双因素Date:03/25/12Time:21:02八Sample:20002010Period

7、sincluded:11Cross-sectionsincluded:27Totalpanel(balanced)observations:297VariableCoefficientStd.Errort-StatisticProb.C190.090575.648422.5128150.0126X0.6905910.02489027.745660.0000EffectsSpecificationCross-sectionfixed(dummyvariables)Periodfixed(dummyvariables)1一小1厶士田.i+rLJ口緘血巳隈tR-squared0.988079View

8、FiXed/RafidomIEffects中显示込3了G112.1552I57905.S.E.ofregression11三、paneiDta模型的检验过程1渕验是单因素或双因素或混合模型日9）估啊雅效应双因素模型;乡曳X11IU|IJbL?庵XiMeandependEntvarS.D.dependmntvarAkaikeinfocriterionSchwarzcriterionarman-Quinncriter.ubin-Watsonstat结果要在2281.225960.859012.3966312.8692312.585830.971575(2)在方程窗口中选择ViewFixed/Ran

9、domEffectsTesting/RedundantFixedEffect检验固定效应“冗余”假设是否成立。目Equation:EQ01Workfile:PANELDATA:NXF-DXviewProc|Object|Print|NanneFreezeEstimateForecastStatsResideRepresentationsEstimationOutputFixed/RandomEffectsActualFitted,ResidualGradientsandDerivativesARMAStructure.?97CovarianceMatrixQldFrrnrPmhCoeffici

10、entDiagnostics卜Fixed/RandomEffectsTestingRedundantFixedEffects-LikelihoodRatioResidualDiagnosticsCorrectedRandomEffects-HausmanTestLabelciflcationCross-sectionfixed(dummyvariables)Periodfixed(dummyvariables)R-squared0,988079Meandependentvar2231.225AdjustedR-squared0.986376:-4-depeiMferit960.8590S.E.

11、ofregression112J552Akaikeinfocriterion12.39663Sumsquaredrestd3257905.Schwarzcriterion12.86923Loglikelihood-1802.900Hannan-Quinncriter.12.58583F-statisflc580.1792Durbin-Watsonstat0.971575EffectsTestStatisticd.f.Prob.Cross-sectionF34.963907(26,259)0.0000Cross-sectionChi-square447.363031260.0000PeriodF

12、9.408621(10,259)0.0000PeriodChi-square92.035603100.0000Cross-Section/PeriodF29.672097(36,259)0.0000Cross-Section/PeriodChi-square485.296597360.0000同时存在个体效应和时间效应RedundantFixedEffectsTestsEquation:EQ01Testcross-sectionandperiodfixedeffects2检验是随机效应或固定效应。（1）估计（双因素）随机效应模型（2）在方程窗口中选择：ViewFixed/RandomEffec

13、tsTesting/CorrelateRandomEffects进行Hausman检验。CorrelatedRandomEffects-HausmanTestEquation:EQ01Testcross-sectionandperiodrandomeffectsCross-sectionrandom1.126524Periodrandom9.057539Cross-sectionandperiodrandom4.2155760.28850.00260.0401个体随机效应TestSuinmaryChi-Sq.StatisticChi-Sq.d.f.Prob.时期固定效应所以模型是双因素模型同时

14、存在着个体效应和时间效应；其中个体随机效应时期固定效应。估计结果为：- - -DependentVariable:YMethod:PanelEGLS(Cross-sectionrandomeffects)Date:03/25/12Time:21:32Sample:20002010Periodsincluded:11Cross-sectionsineluded:27Totalpanel(balanced)observations:297SwamyandAroraestimatorofcomporientvariancesVariableCoefficientStd.Errort-Statisti

15、cProb.C186.539963.087622.9568390.0034X0.6917640.02072333.380870.0000EffectsSpecificationS.D.RhoCross-sectionandom201.0S920.7627Periodfixed(dummyvariables)Idiosyncaticandom112.15520.2373WeightedStatisticsR-squared0.967207Meandependentvar2281.225AdjustedR-squared0.965942S.D.dependentvar606.6648S.E.ofr

16、egression111.9597Sumsquaredresid3572465.F-statistic764.仃54Durbin-Watsonstat0.886411Prob(F-statistic)0.000000UnweightedStatisticsR-squared0.946228Meandependsntvar2281.225Sumsquaredresid14694836Dubin-Watsonstat0.215496II关于Pool对象的操作过程案例2（来源：格林经济计量分析，工作文件：10_1）时期：1935-1954年；截面单元：5家企业GM：通用汽车公司、CH：克莱斯勒公司、

17、GE：通用电器公司、WE：西屋公司US：美国钢铁公司3个变量：I：总投资M：前一年企业的市场价值（反映企业的预期利润）K：前一年末工厂存货和设备的价值（反映企业必要重置投资期望值）obsIGMICHIGEIWEIUSMGMMCH1935317.600040.2900033.1000012.93000209.90003078.500417.50001936391.800072.7600045.0000025.90000355.30004661.700837.80001937410.600066.2600077.2000035.05000469.90005387.100883.9000193825

18、7.700051.6000044.6000022.89000262.30002792.200437.90001939330.800052.4100048.1000018.84000230.40004313.200679.70001940461.200069.4100074.4000028.57000261.60004643.900727.80001941512.000068.35000113.000048.51000472.80004551.200643.60001942448.000046.S000091.9000043.34000445.60003244.100410.9000194349

19、9.600047.4000061.3000037.02000361.60004053.70058S.40001944547.500059.5700056.8000037.810002S8.20004379.30069S.40001945561.200088.7800093.6000039.27000258.70004840.900846.40001946688.100074.12000159.900053.46000420.30004900.900893.80001947568.900062.68000147.200055.56000420.50003526.500579.0000194852

20、9.200089.36000146.300049.56000494.50003254.700694.60001949555.100078.9800098.3000032.04000405.10003700.200590.30001950642.9000100.660093.5000032.24000418.80003755.600693.50001951755.9000160.6200135.200054.38000588.20004833.000809.00001952891.2000145.0000157.300071.78000645.20004924.900727.0000195313

21、04.400174.9300179.600090.08000641.00006241.7001001.60019541486.700172.4900189.600068.60000459.30005693.600703.2000内容：一、建立包含Pool对象的工作文件二、Pool对象中的数据处理三、模型估计过程四、模型检验过程2)- -2)- #-、在工作文件中创建Pool对象1、创建工作文件（年度数据）2、创建Pool对象点击Objects/NewObject,选择Pool对象，在弹出的窗口中输入各个截面单元的识别标识（习惯上加上前缀“_”）：0Pool:POOLWorkfile:10_l:

22、Untitled_nxViewProcObj已ctPrintN日m已FreezeEstimateDefinePoolG已nr已已tCrossSectionIdentifiers:(Enteridentifiersbelowthisline)_GM_CH_GE-屈输入截面单元标识US二、Pool对象中的数据处理1输入数据输入方式：键盘输入、文件导入、复制+粘贴（适用于堆积数据）（1）双击Pool对象，点击View/Spreadsheet（stackeddata），系统要求输入序列名列表：进入输入/编辑状态进入输入/编辑状态回Pool:POOLWorkfile:10_l:UntitledProcl

23、Obj已ctPrintNam已F已已z已Edit+/-Order+/-Smpl+/-FormatTitlenxobsGM-1935I?K?M?根据原始数据表的数据排列格式的排列方式：元/时期GM-1936NANANA转换堆积数据GM-1937NANANA按截面单.GM-193SNANANAGM-1939NANANAGM-1940NANANAGM-1941NANANAGM-1942NANANAGM-1943NANANAGM-1944NANANAGM-1945NANANAGM-1946NANANAGM-1947NANANAGM-1948NANANAGM-1949NANANAGM-1950NANANAGM-1951NANANA.数据的步骤为NANANAI先将EIxcel中的数居整理成堆积数据，每个变量一列数据；