Eviews面板数据之固定效应模型

.word.zl..word.zl.Eviews面板数据之固定效应模型在面板数据线性回归模型中，如果对于不同的截面或不同的时间序列，只是模型的截距项是不同的，而模型的斜率系数是一样的，那么称此模型为固定效应模型。固定效应模型分为三类：个体固定效应模型个体固定效应模型是对于不同的纵剖面时间序列〔个体〕只有截距项不同的模型：y=九+◎卩x+uitikkitit(1)k=2从时间和个体上看，面板数据回归模型的解释变量对被解释变量的边际影响均是一样的，而且除模型的解释变量之外，影响被解释变量的其他所有〔未包括在回归模型或不可观测的〕确定性变量的效应只是随个体变化而不随时间变化时。检验：采用无约束模型和有约束模型的回归残差平方和之比构造F统计量，以检验设定个体固定效应模型的合理性。F模型的零假设：H:九二九二九二…二九二00123N-1(RRSS-URSS)F=URSSN^1F(N-1,N(T-1)-K+1)/(NT-N-K+1)RRSS是有约束模型〔即混合数据回归模型〕的残差平方和，URSS是无约束模型ANCOVA估计的残差平方和或者LSDV估计的残差平方和。实践：一、数据：1996—2002年中国东北、华北、华东15个省级地区的居民家庭人均消费〔cp，不变价格〕和人均收入〔ip，不变价格〕居民，利用数据〔1〕

建立面板数据〔paneldata］工作文件；〔2〕定义序列名并输入数据；〔3〕估计选择面板模型；〔4〕面板单位根检验。年人均消费〔consume〕和人均收入〔ine〕数据以及消费者价格指数〔p〕分别见表1，2和3。表11996—2002年中国东北、华北、华东15个省级地区的居民家庭人均消费〔元〕数据人均消费1996199719981999200020012002CONSUMEAH3607.433693.553777.413901.814232.984517.654736.52CONSUMEBJ5729.526531.816970.837498.488493.498922.7210284.6CONSUMEFJ4248.474935.955181.455266.695638.746015.116631.68CONSUMEHB3424.354003.713834.434026.34348.474479.755069.28CONSUMEHLJ3110.923213.423303.153481.743824.444192.364462.08CONSUMEJL3037.323408.033449.743661.684020.874337.224973.88CONSUMEJS4057.54533.574889.435010.915323.185532.746042.6CONSUMEJX2942.113199.613266.813482.333623.563894.514549.32CONSUMELN3493.023719.913890.743989.934356.064654.425342.64CONSUMENMG2767.843032.33105.743468.993927.754195.624859.88CONSUMESD3770.994040.634143.964515.0550225252.415596.32CONSUMESH6763.126819.946866.418247.698868.199336.110464CONSUMESX3035.593228.713267.73492.983941.874123.014710.96CONSUMETJ4679.615204.155471.015851.536121.046987.227191.96CONSUMEZJ5764.276170.146217.936521.547020.227952.398713.08表21996—2002年中国东北、华北、华东15个省级地区的居民家庭人均收入〔元〕数据人均收入1996199719981999200020012002INEAH4512.774599.274770.475064.65293.555668.86032.4INEBJ7332.017813.168471.989182.7610349.6911577.7812463.92INEFJ5172.936143.646485.636859.817432.268313.089189.36INEHB4442.814958.675084.645365.035661.165984.826679.68INEHLJ3768.314090.724268.54595.144912.885425.876100.56INEJL3805.534190.584206.644480.0148105340.466260.16INEJS5185.795765.26017.856538.26800.237375.18177.64INEJX3780.24071.324251.424720.585103.585506.026335.64INELN4207.234518.14617.244898.615357.795797.016524.52INENMG3431.813944.674353.024770.535129.055535.896051INESD4890.285190.795380.085808.966489.977101.087614.36INESH8178.488438.898773.110931.6411718.0112883.4613249.8INESX3702.693989.924098.734342.614724.115391.056234.36INETJ5967.716608.397110.547649.838140.58958.79337.56INEZJ6955.797358.727836.768427.959279.1610464.6711715.6表31996—2002年中国东北、华北、华东15个省级地区的消费者物价指数物价指数1996199719981999200020012002PAH109.9101.310097.8100.7100.599PBJ111.6105.3102.4100.6103.5103.198.2PFJ105.9101.799.799.1102.198.799.5PHB107.1103.598.498.199.7100.599PHLJ107.1104.4100.496.898.3100.899.3PJL107.2103.799.29898.6101.399.5PJS109.3101.799.498.7100.1100.899.2PJX108.410210198.6100.399.5100.1PLN107.9103.199.398.699.910098.9PNMG107.6104.599.399.8101.3100.6100.2PSD109.6102.899.499.3100.2101.899.3PSH109.2102.8100101.5102.5100100.5PSX107.9103.198.699.6103.999.898.4PTJ109103.199.598.999.6101.299.6PZJ107.9102.899.798.810199.899.1二、1.输入操作：步骤：〔1〕File——New——Workfile0FileEditObjectViewPro-匚QuickOptionsAdd-insWindowHelpflewWorLcfile...匚trl+N.0_penDatabase...Ctrl+5frogramSaveAs...TertFileClose|Irriport卜步骤：〔2〕StartdateEnddateK

步骤：〔3〕ObjectNewObject步骤：〔4〕TypeofobjectPool步骤：〔5〕输入所有序列名称EPool:POOLMODELWorkfile:UNTITLIED::Untitled\-nView!ProcObjectPrintNameFreezeEstimateD-efinePooLGenrSheetCrossSectidn.Identifierz：tinieridentiEiers"belowthisline)AHBJFJHBHLJJLJ-SJXL忖NMGSDSHsxTJZJ步骤：〔6〕定义各变量点击shee—输入consume?ine?p?回Pool;POOLMODELWorkfile;UNTITLED;:Untitled\-已sc步骤：〔7〕将表1、2、3中的数据复制到Eviews中2.估计操作：obsCONSUME?INCOME?P?obsCONSUME?INCOME?P?AH-199E3607.430451Z77D109.9000AH-19973693.5504599.27D101.3000AH-19983777.410477(1.470100.0000AH--iggg3901.8105064.60097.80000AH-20004232.9805291550100.7000AH-20014517.6505663.800100.5000AH-2002斗736.5206032400gg.QoaooBJ-19965729.5207332.010111.6000BJ-19976531.8107313.1BD105.3000BJ-19986970.8303471.9SO102.4000BJ-iggg7498.4809132.760100.6000BJ-20003493.4901034969103.5000步骤：〔1〕点击poolmodel——Estimate对话框说明Dependentvariable:被解释变量；mon:系数一样局部Cross-sectionspecific:截面系数不同局部步骤：〔2〕将截距项选择区选Fixedeffects〔固定效应〕Cross-section:Fixed得到如下输出结果：DependentVariable:CONSUME?Method:PooledLeastSquares□ate:07/16/14Time:11:06S-ample:19962002Includedobservations:7Cross-sectionsincluded:15Totalpool(^balanced)observations:105VariableCoefficientStd.Errort-statisticProb.C596.504989.94504-6.839263o.ooaciINCOME?0.6862^20.013S5049.&48B2o.ooaaFiicedEffects(CroesiAH-C-53.23597BJ-C592.4387FJ-C-41.75834HB^C-189.6295.HU-C-192.0^54」L_U0.4-9391&-^6.60391」X—C-^41.5000LN-C.76302NMG-C-230.1840SD-C-140.3215SH-C227.1060SX-C-9&.131S0TJ-C61.43642ZJ-C230.1580EffectsSpecificationCross-sectionfixed(duinmyvariable^jR-squared0.992490Meand&pendentyar4931.017AdjustedR-squared0.99122&■S.D.dependentvar1700.985S.E.ofregression159.34^6Akaikeinfocriterion1211944Sumsquaredresid2259743.■Schwarzcriterion13.52385Loglikelihood-672.7706Hannan-Quinneriter.13.28332F-statistie754.1521□urbin-Watsonstat1.624146Prob[F-statistic)o.oaaooo接下来用F统计量检验是应该建立混合回归模型，还是个体固定效应回归模型。H:S。模型中不同个体的截距一样〔真实模型为混合回归模型〕0iH:模型中不同个体的截距项«不同〔真实模型为个体固定效应回归模型〕1i对模型进展检验:(RRSS-URSS)/(4965275-2259743)/'F=URSS(NT-N-KI)=—22597439。口曲9F0(14,90)=1W3所以推翻原假设，建立个体固定效应回归模型更合理。RRSS求法请参见Eview面板数据之混合回归模型相应的表达式为：Consume二596.50+0.69Income-53.23D+592.44D+...+230.16Ditit1215(6.64)(49.55)R2二0.99,SSE二2259743r其中虚拟变量D,D，…,D的定义是：1215[1,如果属于第个个体,i=1,2,...,15i[0,其他15个省级地区的城镇人均指出平均占收入68.62%。从上面的结果可以看出市居民的自发性消费明显高于其他地区。时点固定效应模型时点固定效应模型就是对于不同的截面〔时点〕有不同截距的模型。如果确知对于不同的截面，模型的截距显著不同，但是对于不同的时间序列〔个体〕截距是一样的，那么应该建立时点固定效应模型：y=丫+*卩x+uittkkitit(2)k=2时点固定效应模型与个体固定效应模型的操作区别在于步骤〔2〕，将时间项选择区选Period:Fixed〔时间固定效应〕PoolEstimation£<™firalKr>Options,Esbmnhon理tfriRiyaMethodIS-LeaitSquares(andAR)BalancePoolEstimation£<™firalKr>Options,Esbmnhon理tfriRiyaMethodIS-LeaitSquares(andAR)BalanceDepie*Sample:19^62DD2得到如下结果:DepensentVariable:CONSUME'?Melhad:PaaledlLE^stSquaresDaita:Q7f2i/14TirTie:n：oaSample:19962002lndudl9dob^$rvaUon£：7Crosseecuonsmdude<F15Taialpool{balanced);□bservztiDns105VanableCoefficientSid.Errorl-StaU5ticProb.c-2.63D22560.5&332■0.D3B3520.9695INCOME?0.7300050.0102^47599695a0000FixedEiredts(Period)1986--C11402601997-C137.5006igge-c53.93619-I599-C・30.641272O0D-C-9.0450®2O01-C■16002642Q02-C・97.74908EiiedsSp^dfic^tionPenddflxed(dummyvanR-squared0.93M39制軸ndepgriMil泊r4981.017MustedR-squared0.985460S.Dctependenlvar1700905S.E.nfregression205.1087月kaikeinfacriierian13.55809sumsquaredresid4000749.Sctiwarzcritennn13.7B030Laglikelihood-7017997Hannan-Ouinn亡『廿皂「13.64003F-sla11sllc1007.9^3Durbln-Walson£tatD.736995Pro-Stanslic)0.000000接下来用F统计量检验是应该建立混合回归模型，还是个体固定效应回归模型。h:a=a。模型中不同个体的截距一样〔真实模型为混合回归模型〕。0iH:模型中不同个体的截距项a不同〔真实模型为时间固定效应回归模型〕。1t对模型进展检验:(RRSS-(RRSS-URSS)F=T一1URSS/(NT-T-K+1)=3.54>F0(56‘98)=219所以推翻原假设，可以建立时点固定效应回归模型RRSS求法请参见Eview面板数据之混合回归模型相应的表达式为:Consume=—2.6+0.78IP+114D+137.5D+...—97.7Ditit127(76.0)R2=0.986,SSE=4080749其中虚拟变量D,D，…,D的定义是：127f1,如果属于第t个截面，t=1996,...,2002D=2t[o,其他时点个体固定效应模型时点个体固定效应模型就是对于不同的截面〔时点〕、不同的时间序列〔个体〕都有不同截距模型。如果确知对于不同的截面、不同的时间序列〔个体〕模型的截距都显著地不一样，那么应该建立时点个体固定效应模型：y=九+丫+丫卩x+u(3)itttkkitit(3)k=2时点固定效应模型与个体固定效应模型的操作区别在于步骤〔2〕，将截距项选择区域：Cross-section:fixed〔个体固定效应〕，时间项选择区选Period:Fixed〔时间固定效应〕PoolEstimationSpEdficaiionPoolEstimationSpEdficaiionOptions得到结果如下:DependentVariable:CONSUME?Method:PooledLeastSquarest-StatisticProb.t-StatisticProb..word.zl..word.zl.Date:07/21/14Time:15:44Sample:19962002Includedobservations:7Cross-sectionsincluded:15Totalpool(balanced)observations:105VariableCoefficientStd.ErrorC806.6751221.2143INE?0.6533380.034541FixedEffects(Cross)AH--C-94.50854BJ--C698.0132FJ--C-18.86465HB--C-200.3997HLJ--C-246.3712JL--C-54.16421JS--C-31.26919JX--C-392