EViews60在面板数据模型估计中的操作

1、EViews 6.0在面板数据模型估计中的实验操作1、进入工作目录cd d:nklx3,在指定的路径下工作是一个良好的习惯2、建立面板数据工作文件workfile（1）最好不要选择EViews默认的blanaced panel类型Moren_panel（2）按照要求建立简单的满足时期周期和长度要求的时期型工作文件3、建立pool对象(1)新建对象(2)选择新建对象类型并命名(3)为新建pool对象设置截面单元的表示名称 在此提示下(Cross Section Identifiers: (Enter identifiers below this line )输入截面单元名称。建议采用汉语拼 音，

2、例如29个省市区的汉语拼音，建议在拼音名前加一个下划线”，如图关闭建立的pool对象，它就出现在当前工作文件中。4、在pool对象中建立面板数据序列 双击pool对象，打开pool对象窗口，在菜单view的下拉项中选择spreedsheet（展开表）在打开的序列列表窗口中输入你要建立的序列名称，如果是面板数据序列必须在序列名后添加“？”。例如，输入GDP?，在GDP后的?的作用是各个截面单元的 占位符，生成了 29个省市区的GDP的序列名，即GDP后接截面单元名，再在接时期，就表示出面板数据的3维数据结构（1变量2截面单元3时期）了。请看工作文件窗口中的序列名。展开表（类似exce 1）中等待

3、你输入、贴入数据。5、贴入数据（1）打开编辑（edit）窗口(2)贴入数据(3)关闭pool窗口，赶快存盘见好就收6、在pool窗口对各个序列进行单位根检验选择单位根检验设置单位根检验单位根检验结果Pool Unit Root Test on K?Pool unit root test: SummarySeries: K_BEIJING, K_TIANJIN, K_HEBEI, K_SHANXI_D, K_NEIMENG, K_LiAONING, KjjiLIN, K_HLJIANG, K_SHANGHAI, K.JIANGSU, K_ZHEJIANG, K_ANHUI, KFUJIAN, K

4、_JIANGXI, K_SHANDONG, K_HENAN, K_HUBEI, K_HUNAN, K_GUANGDONG, K_GUANGXI, KHAINAN, fCsiCHUArT K_GUIZHOU, K_YUNNAN, jCsHANXX, KGANSU, KQINGHAI, K项INGXIA, K_XINJIANG一 一Date: 05/24/07 Time: 19:57 一一Sample: 1986 2005Exogenous variables: Individual effectsAutomatic selection of maximum lagsAutomatic selec

5、tion of lags based on SIC: 0 to 4Newey-West bandwidth selection using Bartlett kernelCross-MethodStatistic Prob.*sectionsObsNull: Unit root (assumes common unit root process)Levin, Lin & Chu t*-2.660530.003929526Null: Unit root (assumes individual unit root process)Im, Pesaran and Shin W-stat4.26701

6、1.000029526ADF - Fisher Chi-square19.30851.000029526PP - Fisher Chi-square14.51641.000029551* Probabilities for Fisher tests are computed using an asymptotic Chi -square distribution. All other tests assume asymptotic normality.注意检验方法和两种检验的零假设:Null: Unit root (assumes common unit root process)各截面有相同

7、的单位根Null: Unit root (assumes individual unit root process)允许各截面有不同单位根其中，Levin, Lin & Chu t*检验拒绝含有单位根的零假设，即拒绝非平稳 7、在pool窗口对面板数据组合进行协整检验选择进行协整检验-! x| Pool： FAZHANMOXI Workfile: SHSH02:yongxiifa，h.LNK?LNDH?LNXH?RepresentationsEstimation OutputResidualsCoef Covariance MatrixCoefficient TestsFixed/Random

8、 Effects Testing 35.0006768.1583392.00568I*25.2814238.3201552.02725!75.4350218.3888582.04838：5.6846398.4576492.06907II5.7038898.5389732.08933I)5.7148758.6090242.10920：Spreadsheet (stacked data).,. Descriptive Statistics ,.Unit Root Test.5.9679888.6426182.1286836.3524608.6473672.1477836.7073698.70008

9、22.16653，17.0477068.7005222.18493Cointegration Test.16.9501428.7032892.20300*Label7.0506948.7185902.22075IBEIJING-19987.598307.1768528.6765072.238191BEIJING-19997.G72G877.2620738.6882852.25533BEIJING-20007.7964137.2490708.7030532.27218!BEIJING-2001恒秘|Proc|Object| Print| Name |Freeze | Edit+/-1 Order

10、+/-1 Smpl+/-1Format Title | Estimate |Define| PoolGenr| SCross Section Identifiers协整检验设置对话框，注意有3种检验方法(test type)协整检验结果，同样要注意两种假定(含有AR，即含有单位根，非协整)，两 种零假设都是非协整，小概率事件发生拒绝非协整。本例题检验的4个序列时协整的，特别提示还要看各个序列的单位根检验是否是 同阶单整的，否则单凭协整检验的结果根据不足。Pedroni Residual Cointegration TestSeries: LNY? LNK? LNDH? LNXH?Date: 0

11、5/24/07 Time: 20:14Sample: 1986 2005Included observations: 20Cross-sections included: 29Null Hypothesis: No cointegrationTrend assumption: No deterministic trendLag selection: fixed at 1Newey-West bandwidth selection with Bartlett kernelAlternative hypothesis: common AR coefs. (within-dimension)Weig

12、htedProb.StatisticProb.StatisticPanel v-Statistic1.4150600.14661.5389000.1221Panel rho-Statistic1.8843370.06761.6258930.1064Panel PP-Statistic0.0473930.3985-0.3684740.3728Panel ADF-Statistic-3.2473110.0020-3.2811550.0018Alternative hypothesis: individual AR coefs. (between-dimension)StatisticProb.Gr

13、oup rho-Statistic3.8269590.0003Group PP-Statistic0.1998720.3911Group ADF-Statistic-3.6546000.0005Cross section specific resultsPhillips-Peron results (non-parametric)Cross IDARVariance HAC Bandwidth Obs8、建立混合模型在pool对象窗口的proc （过程）的下拉式菜单中选择估计打开模型设置窗口。混合模型的设置混合模型的结果Dependent Variable: LNY?Method: Poole

14、d Least SquaresDate: 05/24/07 Time: 20:30Sample: 1986 2005Included observations: 20Cross-sections included: 29Total pool (balanced) observations: 580VariableCoefficientStd. Errort-StatisticProb.C-0.8602430.121396-7.0862770.0000LNK?0.8291890.01305963.495910.0000LNDH?0.2613960.01200521.773960.0000LNXH

15、?0.2377270.0556284.2734790.0000LNNE1?-0.1452770.063819-2.2763740.0232LNCE1?0.0901580.0561431.6058730.1089R-squared0.986459Mean dependent var7.086138Adjusted R-squared0.986341S.D. dependent var1.240231F nfn1AAQA7infn rrit&rinn-1 nidRnq9、建立变系数模型这里只建立一次变一个变量且在截面维的变系数模型。当然也可是在时间维的变 系数。而且可以一次不止变一个变量的系数。变

16、系数模型的设置变系数模型的估计结果Dependent Variable: LNY?Method: Pooled Least SquaresDate: 05/24/07 Time: 20:37Sample: 1986 2005Included observations: 20Cross-sections included: 29Total pool (balanced) observations: 580VariableCoefficientStd. Errort-StatisticProb.C-1.0909600.215765-5.0562320.0000LNDH?0.3031280.0260

17、9311.617090.0000LNXH?0.1917570.1201801.5955750.1112LNNE1?-0.2482310.075168-3.3023300.0010LNCE1?0.6448430.0814977.9124580.0000BEIJING-LNKBEIJING0.7414960.02224433.334790.0000TIANJIN-LNKTIANJIN0.7727700.02240234.496290.0000HEBEI-LNKHEBEI0.7493170.01875839.947250.0000SHANXI_D-LNKSHANXI_D0.7416180.02142

18、234.619030.0000NEIMENG-LNKNEIMENG0.7436640.02129534.921500.0000LIAONING-LNKLIAONING0.7869310.01974639.852630.0000JILIN-LNKJILIN0.7658240.02165935.358240.0000HLJIANG-LNKHLJIANG0.7833390.02071837.808940.000010、建立截距维的固定效应模型，并检验模型的冗余性（是否比混合模型优？） 截面维固定效应模型的设置截面维固定效应模型的估计结果Dependent Variable: LNY?Method:

19、Pooled Least SquaresDate: 05/24/07 Time: 20:42Sample: 1986 2005Included observations: 20Cross-sections included: 29_ |口|乂|Total pool (balanced) observations: 580VariableCoefficientStd. Errort-StatisticProb.C-0.7852040.267649-2.9337080.0035LNK?0.6907670.02006434.427310.0000LNDH?0.1038980.0385402.6958

20、280.0072LNXH?1.3497620.1780527.5807240.0000LNNE1?-0.1652170.072697-2.2726610.0234LNCE1?0.3528760.0828214.2606880.0000Fixed Effects (Cross)BEIJING-C-0.614424TIANJIN-C-0.436907HEBEI-C0.113717SHANXI_D-C-0.207641NEIMENG-C-0.209332LIAONING-C0.095655截面维固定效应模型的冗余性检验，首先在pool模型的view中选择似然比的检 验菜单选项 Pool: FAZHA

21、NMOXI Workfile: SHSH02:yongxufazhanmoxi矶虱 Pr匚|Obje匚t|Estimate|Dmfinm|PwlGeE|ShmmtCross Section IdentifiersRepresentationsEstimation OutputResidualsCoef Covariance MatrixCoefficient TestsFixed/Random Effects Testing Redundant Fixed Effects - Likelihood RatioSpreadsheet (stacked data) .Descriptive Sta

22、tistics .Unit Root Test.Co integration Test.Correlated Random Effects - Hausman TestLabelLNNE1?LNCE1?D437 98 32 -0.165217 0.3528760.2676490.0200640.0385400.1780520.0726970.082821-2.93370834.427312.6958287.580724-2.2726614.2606880.00350.00000.00720.00000.02340.0000似然比检验的结果，零假设固定效应模型是冗余的，小概率事件发生，拒绝冗余，

23、 于是摒弃混合模型：Redundant Fixed Effects TestsPool: FAZHANMOXITest cross-section fixed effectsEffects TestStatisticd.f.Prob.Cross-section F18.205856(28,546)0.0000Cross-section Chi-square382.452544280.0000Cross-section fixed effects test equation: Dependent Variable: LNY?Method: Panel Least SquaresDate: 05/

24、24/07 Time: 20:47Sample: 1986 2005Included observations: 20Cross-sections included: 29Total pool (balanced) observations: 580CoefficientStd. Errort-StatisticProb.C-0.8602430.121396-7.0862770.0000LNK?0.8291890.01305963.495910.000011、建立截距维的随机效应模型，并进行Hausman检验，确定是选择随机效应 亦或是固定效应模型，零假设：随机效应模型成立。截面维随机效应模型

25、的设置截面维随机效应模型的估计结果Dependent Variable: LNY?Method: Pooled EGLS (Cross-section random effects)Date: 05/24/07 Time: 20:56Sample: 1986 2005Included observations: 20Cross-sections included: 29Total pool (balanced) observations: 580Swamy and Arora estimator of component variancesVariableCoefficientStd. Err

26、ort-StatisticProb.C-1.2662660.199089-6.3603000.0000LNK?0.7567330.01631446.386370.0000LNDH?0.2780840.02008213.847110.0000LNXH?0.4885100.0988494.9420000.0000LNNE1?-0.1295320.067090-1.9307220.0540LNCE1?0.3901600.0711465.4839100.0000Random Effects (Cross)BEIJING-C-0.243423TIANJIN-C-0.042283HEBEI-C-0.043

27、812SHANXI_D-C-0.113288NEIMENG-C-0.073589截面维随机效应模型的Hausman检验菜单项的选择画 Pool: FAZHANMOXI Workfile: SHSH02=y(mgxiifazhanmoxiHi旬履 I Pr 匚 |。切日匚 t| Print | Na me Freeze Estimate Define PoolGenr Sheet: Cross Section IdentifiersRepresentationsEstimation OutputResidualsCoef Covariance Matrixaction random effect

28、s)Coefficient Testsn：- AAfl|Fixed/Random Effects Testing |Redundant Eixed Effects - Likelihood RatioSpreadsheet (stacked data) .-Descriptive Statistics .Correlated Random Effects - Hausman Test*nt Std. Error t-Statistic Prob.Unit Root Test.Co integration Test.560.199089-6.3603000.0000330.01631446.38

29、6370.0000Label340.02008213.847110.0000截面维随机效应模型Hausman检验的结果:Hausman检验的零假设是应当选择随机效应模型，小概率事件发生拒绝零假设， 选择固定效应模型Correlated Random Effects - Hausman TestPool: FAZHANMOXITest cross-section random effectsTest SummaryChi-Sq. StatisticChi-Sq. d.f.Prob.Cross-section random53.39400450.0000Cross-section random e

30、ffects test comparisons:VariableFixedRandomVar(Diff.)Prob.LNK?0.6907670.7567330.0001360.0000LNDH?0.1038980.2780840.0010820.0000LNXH?1.3497620.4885100.0219310.0000LNNE1?-0.165217-0.1295320.0007840.2025LNCE1?0.3528760.3901600.0017980.379212、13在时间维重复10、和11、的工作，确定数据适合采用何种模型?14、建立截面变截距模型，分析没有观察的截面单元因素的影响

31、截面变截距模型的设置截面变截距模型的估计结果Dependent Variable: LNY?Method: Pooled Least SquaresDate: 05/24/07 Time: 21:05Sample: 1986 2005Included observations: 20Cross-sections included: 29Total pool (balanced) observations: 580VariableCoefficientStd. Errort-StatisticProb.C-0.7852040.267649-2.9337080.0035LNK?0.6907670.

32、02006434.427310.0000LNDH?0.1038980.0385402.6958280.0072LNXH?1.3497620.1780527.5807240.0000LNNE1?-0.1652170.072697-2.2726610.0234LNCE1?0.3528760.0828214.2606880.0000Fixed Effects (Cross)BEIJING-C-0.614424TIANJIN-C-0.436907HEBEI-C0.113717SHANXI_D-C-0.207641NEIMENG-C-0.209332LIAONING-C0.09565515、建立时期变截

33、距模型，分析没有观察的时期因素的影响时期变截距模型的设置时期变截距模型的估计结果Dependent Variable: LNY?Method: Pooled Least SquaresDate: 05/24/07 Time: 21:08Sample: 1986 2005Included observations: 20Cross-sections included: 29Total pool (balanced) observations: 580VariableCoefficientStd. Errort-StatisticProb.C-0.6582070.117502-5.6016470.

34、0000LNK?0.7467130.01892639.453540.0000LNDH?0.3210070.01529420.989580.0000LNXH?0.2479490.0528904.6879810.0000LNNE1?0.0872650.0856731.0185830.3088LNCE1?-0.4359990.080745-5.3997150.0000Fixed Effects (Period)1986-C-0.1907931987-C-0.1966561988-C-0.1490011989-C-0.1469821990-C-0.1120041991-C-0.10882016、在整个

35、估计、检验构成中养成使用冻结和命名保存的习惯，以便撰写报告时 调用。Table: UNTITLED Workfile: SHSH02=y(mgxiifa-hanm.View Fr匚gbjaztl Print|Nmme| Edit+/-匚ellFmt Grid+/- Title 匚口0101寸门垸+/-|ABCDE1 1Dependent Variable: LNY?I 2Method: Pooled Least SquaresI 3Date: 05/24/07 Time: 21:08I 4Sample: 1986 2005I 5Included observations: 201 6Cross

36、-sections included: 29Total pool (balanced) observations:580十VariableCoefficientStd. Errort-StatisticProb.1 11C-0.6582070.117502-5.6016470.0000I 12LNK?0.7467130.01892639.453540.0000I 13LNDH?0.3210070.01529420.989580.0000I 14LNXH?0.2479490.0528904.6879810.00001 15LNNE1?0.0872650.0856731.0185830.30881 16LNCE1?-0.4359990.080745-5.3997150.00001 17Fixed Effects (Period)18KI I17、工作中注意使用工作文件窗口顶部的显示过滤器，简化你的窗口，以免眼花 缭乱。过虑前Workfile: SIHSH02 - (e:newdatash.|旦Xf Fnzi匚 | Qbjm匚t| Print SaveEtails+/-1 ShowFetchStoreDelete Genr |SampleRange: 198