固定效应模型的估计原理说明

1、最新资料推荐 / 23固定效应模型的估计原理说明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相同的，则称此模型为固定效应模 型。固定效应模型分为三类：1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：K儿=4+工0內+冷=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 均是相同的，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

2、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：（RRSS-URSS）/F= F（N-1,NK + 1）/（NT-N-K + i）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：已知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（“，不变价格）居民，利用数据（1）建立面板数据（panel data）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（

3、income）数据以及消费者价格指数（p）分别见表1, 2和3。表1 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（元）数据人均消费1996199719981999200020012002CONSUMEAH3607.433693.553777.413901.814232.984517.654736.52CONSUMEBJ5729.526531.816970.837498.488493.498922.7210284.6CONSUMEFJ4248.474935.955181.455266.695638.746015.116631.68CONSUMEHB3424.3540

4、03.713834.43402634348.474479.755069.28CONSUMEHLJ3110.923213.423303.153481.743824.444192.364462.08CONSUMEJL3037.323408.033449.743661.684020.874337.224973.88CONSUMEJS4057.54533.574889.435010.915323.185532.746042.6CONSUMEJX2942.113199.613266.813482333623.563894.514549.32CONSUMELN3493.023719.913890.7439

5、89.934356.064654.425342.64CONSUMENMG2767.843032.33105.743468.993927.754195.624859.88CONSUMESD3770.994040.634143.964515.0550225252.415596.32CONSUMESH6763.126819.946866.418247.698868.199336.110464CONSUMESX3035.593228.713267.73492.983941.874123.014710.96CONSUMETJ4679.615204.155471.015851.536121.046987.

6、227191.96CONSUMEZ,!5764.276170.146217.936521.547020.227952.398713.08表2 1996-2002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1996199719981999200020012002INCOMEAH4512.774599.274770.475064.65293555668.86032.4INCOMEBJ7332.017813.168471.989182.7610349.6911577.7812463.92INCOMEFJ5172.936143.646485.636859.817432.26

7、8313.08918936INCOMEHB4442.814958.675084.645365.035661.165984.826679.68INCOMEHLJ3768314090.724268.54595.144912.885425.876100.56INCOMEJL3805.534190.584206.644480.0148105340.466260.16INCOMEJS5185.795765.26017.856538.26800.237375.18177.64INCOMEJX3780.24071.324251.424720.585103.585506.026335.64INCOMELN42

8、07.234518.14617.244898.615357.795797.016524.52INCOMENMG3431.813944.674353.024770.535129.055535.896051INCOMESD4890.285190.795380.085808.966489.977101.087614.36INCOMESH8178.488438.898773.110931.6411718.0112883.4613249.8INCOMESX3702.693989.924098.734342.614724.115391.05623436INCOMETJ5967.716608.397110.

9、547649.838140.58958.79337.56INCOMES6955.797358.727836.768427.959279.1610464.6711715.6表3 1996-2002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19961997199819992(MH)20012002PAH109.9101.310097.8100.7100.599PBJ111.6105.3102.4100.6103.5103.198.2PFJ105.9101.799.799.1102.19&799.5PHB107.1103.598.49&199.7100.599PHLJ107.110

10、4.4100.496.898.3100.8993PJL107.2103.799.29898.6101.399.5PJS109.3101.799.49&7100.1100.899.2PJX108.41021019&6100.399.5100.1PLN107.9103.199.39&699.91009&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

11、.199.598.999.6101.299.6PZJ107.9102.899.79&810199.899.1二输入操作：步骤：(1) FileNewVVorkfllej File j Edit Object View Proc Quick Options Add-ins Window HelpHewWorkfile.Ctrl+NO.penDatabase.SaveCtrl+SProgramSave As.Text FileCloseImport步骤：(2) Start dateEnd date K步骤：(3) ObjectNew ObjectFile Edit Object View Proc

12、 Quick Options Add-ins Window HelpNew Object.Gen erate Seri es.Manaqe Links & Formulae.Fetch from DB.Update s-elected from DB.Store selected to DB.| VieiCopy selected.Show | Fetch | Store | Delete | RaiSarRename selected.F20Delete selectedP.rint Selected步骤：(4) T pe of objectPoolB Workfile: New Objec

13、tview proc| ObjRange: 1996Sample: 1996Type of objectNanne for objectc residPoolEquationFactorGraphGroupLogLMatrix-Vector-CoefModelpoolmodclGenr| Sample |Filler:t Zcrne Freeze E.timCe J Define PooGenr She et AHBJ rj HD HUT JL JS JX LNNMG SDPool EstimationSPcci fica tJonO pti or5Dependent variable .；o

14、XReQiessors and ARO terms；, ,tc UoEmon co effici entsxSHSXEstimauon mettiodFixecd and Random EffectsCrss sect! on: ZorovPeriod:INonoWoiightc: No weights匸Eatimtion flQttinga oMot hod LS - Loact Squaroc (and AR)Sample;1996 2002CO-section specific coeWce?nt;Period specific coefficients:I .Balance Sampl

15、e-itt左对话框说明Specification OptionsEsticriation settingsMethod： LS - L&ast Squares (and AR)Regressors and WlO terms Cofnmon.vBiLince SampleSample 1996 2002| 确定琨消 Dependent variable:解释变豊 Common：系数相同部分Cross-section specific:截面系数不同部分步骤：(2)将截距项选择区选Fixed effects (固定效应)Cross-section： FixedPool EstimationSpec

16、ificationOptionsDependent variade，:匸consume?Estimatio n method It-,JRxed and Random EffectsCross-section:Period:V/eights: No weightsvCommon coefficients:c income?Cross-section specific coeffiaents:FixedvPeriod specific coefficients:Estimobon settingsMethod LS Least Squares (and AR)Sample: 1996 2002B

17、alance Sample取消得到如下输出结果:Dependent Variable: CONSUME?Method: Pooled Least SquaresDate: 07/16/14 Time: 11:06Sample: 1996 2002Included observations: 7Cross-sections included 15Total pool (balanced) observations: 105VariableCoefficientStd. Errort-StatisticProb.C596.504989.845046.6392630.0000INCOME?0.686

18、2320.01385049.548620.0000Fixed Effects (Cross)AHC-53.23597BJC592.4387FJ-C-4175884HB-C-169.6295HUC-192.0354-JL-C0.493915JSC-36.60391JX-C-341.5000LNC88.76802NMG-C-230.184-0SDC-140.3215SHC327.1060SX-C-95.13180TJ-C6143642ZJ-C230.1580Effects SpecificationCross-s e ction fixed (du mmy variabl e s)R-square

19、d0.992490Mean dependentvar4981.017Adjusted R-squared0.991225S.D. depen de nt var1700.985S.E. of regression159.3436Akaike info criterion13.11944Sum squared res id2259743.Schwarz criterion13.52385Log likelihood-672.7706Hannan-Quinn enter.13.28332F-statistic784.1521Durbin-Watson stat1.624146Prob(F-stat

20、istic)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。仇：模型中不同个体的截距相同（真实模型为混合回归模型）。耳:模型中不同个体的截距项e不同（真实模型为个体固定效应回归模型）。对模型进行检验:(RRSS - URSS)/ (4965275-2259743)/=7.69 (14,90)=1.8023 =力51URSS/一 225974V7W-N-K + 1)790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 = 596.50 + 0.69Incomeit -53.

21、23 + 592.44)2 +. + 230.16DI5(6.64)(49.55)F=099,SSQ. =2259743其中虚拟变量几的定义是:1,如果属于第个个体M = 12,150,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 北京市居民的自发性消费明显高于其他地区。2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 距是相同的，那么应该建立时点固定效应模型：K儿二久+工0血+作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

22、择 区选Period： Fixed （时间固定效应）得到如下结果:Depen dent Varia&ie: CONSUME Method: Pooled Least Squares Date： 07f21/14 Timo： 11：08Sample: 1996 2002 included observations: 7 cross-5 ecoons mdudea 15Tolal pool (balanced) obser/ations 105Van ableCoefficientSid. ErrorStat)5licProb.C2.53022568.563820.0383620.9695INCO

23、ME?0.78000500102S475 996950 0000Fixed EfTGCts (Period1996-C114 02501997-C137.50061998-C53.936191999-C38641272O0D-C-9.0450032001 -C-160 02642O02-C9774908Ettecis SpecificationPenoafixed (dummy*/anaoiesR-squared0.986439Mean depondent var4981.017Adjusted R-squared0 985460SO depends nt var1700 985S.E. of

24、 regression205.1087Akaike info criterion13.55809sum squared resid4080749.scnv/arzcritenon13.76030Log likelihood-703 7997Hann 合 n-Ouinn criter13.64003F-siatisiic1007.948DufDin-.Yaison stat0.786995Proo(F-5tat)3lic)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,=ao模型中不同个体的截距相同（真实模型为混合回归模型）。耳：模型中不同个体

25、的截距项不同（真实模型为时间固定效应回归模型）。对模型进行检验:(RRSS - URSS)/ (4965275-4080749)/二354吒肋(6, 98)=2.19 二/7-1URSS/一4080749/7(NT-T-K + )/98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 + 0.78/ + 114D, +137.5D? +.-97.7Z)7(76.0)/?2 = 0.986, SSE = 4080749其中虚拟变量口几、？的定义是：小1,如果属于第t个截面，t=1996,., 2002D

26、=10,其他3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相同，那么应该建立时点个体固定效应模型：K儿二&+齐+工0內+叫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）Pool Estimationconsume?SpcdficoonOptionsDapendentvariaHe-Estimation me

27、thod mdComm on coefficients：c income?Fixed and Random EffectsI BalanceSampleCrosssection specific coefficients:Period specific coefficients:Estimation settingsMethod LS Least Squares (and AR)Sample: 1996 2002得到结果如下:Dependent Variable: CONSUME?Method: Pooled Least SquaresDate: 07/21/14 Time: 15:44Sam

28、ple: 1996 2002Included observations: 7Cross-sections included: 15Total pool (balanced) observations: 105VariableCoefficientStd. Errort-StatisticProb.C806.6751221.21433.6465780.0005INCOME?0.6533380.03454118.915040.0000Fixed Effects (Cross)AH-C-94.50854BJ-C698.0132FJC18.86465HB-C-200.3997HLJ-C-246.371

29、2JL-C-54.16421JS-C31.26919JX-C392.9844LN-C47.39508NMG-C-284.2660SD-C-150.8912SH-C465.4906SX-C-152.6560TJ-C103.9569ZJ-C311.5193Fixed Effects (Period)1996-C59.123731997-C17.954691998-C31.455641999-C57.240422000-C36.243822001-C29.264152002-C122.8854Effects SpecificationCross-section fixed (dummy variab

30、les) Period fixed (dummy variables)R-squared0.993278Mean dependent var4981.017Adjusted R-squared0.991577SD.dependent var1700.985S.E. of regression156.1067Akaike info criterion13.12288Sum squared resid2022652Schwarz criterion13.67895Log likelihood-666.9514Hannan-Quinn criter.13.34821F-statistic584.04

31、06Durbin-Watso n stat1.455623Prob(F-statistic)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。人=易二 = 4i和人=了2=冷= -对模型进行检验:=5.83f；)o5(20, 83 )=1.7uR%s 20226%醐卩皿% * w _力严65275-2022652煖2所以推翻原假设，可以建立个体时点固定效应回归模型D个体随机效应回归模型估计截距项选择Random effects （个体随机效应）得到如下部分输出结果：Dependent Variable: CP?Method: Pooled EGLS (Cr

32、oss-section random effects)Date: 07/02/08 Time: 15:06Sample: 1996 2002Included observations: 7Cross-seciions included: 15Total pool (balanced) observations: 105Swamy and Arora estimator of component variancesVariableCoelficientStd. Errort-StatisticProb.C345.179575.472174.5735990.0000IP?07245690.0105

33、7268.538140.0000Random Effects (Cross)AH-C-2.553433BJ-C367.0439FJ-C-54.24006HB-C-104.8367HU-C-1017680JL-C54.90671JS-C-32.27868JX-C-223.9519LN-C112.1152NMG-C-133.1377SD-C-100.8713SH-C126.1820SX-C-22.79189TJ-C10.08794ZJ-C106.0939相应的表达式是:CPlt =3452 + 072/巳-2.6 +367.0D2 +. + 106.1D15（68.5）R2 = 0.9& SSE

34、= 2979246其中虚拟变量9,Q，,卩5的定义是：小 仏如果属于第i个个体,i=l, 2,., 15 鬥0,其他接下来利用Hausman统计量检验应该建立个体随机效应回归模型还是个体固定 效应回归模型。H。：个体效应与回归变量（圮）无关（个体随机效应回归模型）个体效应与回归变量（/）相关（个体固定效应回归模型）分析过程如下:ZoEViers - Pool: POOL02 Torkfile: CASE13: :Casel3 3 File gdit Object View Proc Quick Options Window Help 社EjlProcobject Print|Ndme|Free

35、ze Estimate|阮fine|PoolG而sheetrandom effects)Cross Section IdenCoefficient TestsFixed/Random Effects TestingRedundant Fixed Eects - Likelihood RatioSpreadsheet (stacked data) Descriptive Statistics 血it root test.LabelCorreia ted Random Effec ts - Hausman Tes t75.472174.5735990.00000.01057268.538140.0

36、000Repr esentat i onsEstimation OutputResidualsCoef Covariance MatrixMilVZ.OOOHO.JBJ-C367.0439FJ-C54.24006HB-C-104.8367HU-C-101.7680JL-C54.90671JS-C32.27868JX-C223.9519LN-C112.1152MMP-.n件伯77l_lFath = c： documents and settinszhuyix:imy documents DB = none WF = casel3得到如下检验结果:Correlated Random Effects

37、 Hausman TestPool: POOL02Test cross-section random effectsTest SummaryChi-Sq. StatisticChi-Sq. d.f.Prob.Cross-section random1478756310.0001Cross-section random effects testcomparisons:VariableFixedRandomV3r(Diff.)Prob.IP?0.69756107245690.0000490.0001由检验输出结果的上半部分可以看出，Hausman统计量的值是14.79,相对应的 概率是0.000b

38、即拒接原假设，应该建立个体固定效应模型。检验结果的下半部分是Hausman检验中间结果比较。个体固定效应模型对参数 的估计值为0.697561,随机效应模型对参数的估计值为0.724569。两个参数的估 计量的分布方差的差为0.000049。综上分析，1996-2002年中国东北.华北、华东15个省级地区的居民家庭 人均消费和人金收入问题应该建立个体固定效应回归模型。人均消费平均占人 均收入的70%o随地区不同，自发消费(截距项)存在显著性差异。(4)面板单位根检验以cp序列为例。首先在工作文件窗口中打开cp变量的15个数据组。单位根检验过程如下:纣新资料推荐 / 23EVievs - Gro

39、up: UHTITLED lorkfile: CASE13:Casel33 File Edit Object View ProcQuick Options Window Help-aXyiewProcobject PrintName(Freeze| Defaultv iSort(Transpose(Edit+/-Smpl+/-lnsDel (TitleSarnpie)GroupMembersBJCPFJCPHBCPHUCPJL|CPSpreadsheet3764011.7753197.3392904.6872833.321371 Dated Data TableMS4853.4413868.3

40、193077.9893236.432445；Graph515197.0413896.7783289.9903477.560491(Muitinl Gr anks巧75314.5214104.2813596.8393736.408507(2715522.7624361.5553890.5804077.961531；Descriptive Stats336094.3364457.4634159.0874281.560548(Testsof Equality.126665.0055120.4854493.5354998.874609-N-Way Tabulati on.CorreiationsCov

41、ari ancesPrincipal Components.-=Correlogram (1)CrossCorreiation (2)Coi.ntegration TestJUnit Root Test.=Granger Causal ity.LabelIr.Fath = c： docwnents and settingszhuyiximy documentsDB=none WF =casel3 Group Unit Root TestTest typeSummorxL&g length() kutomatic selectiSchwarzMaximuni(* indi cates autom

42、atic selection, cf maxinrum lags)O Esr specificInclude in test equa.tioa Indi vi dual i rti erIitdi vidual trend and int_; NorteSpectral estimationKernelBartlettVEandwidltli selectionOptions21 Use balanced smpl*) Automatic：Vsr gecifiOK Cancel得到如下检验结果:最新资料推荐 / 23Group unit mol lest SummaryDate: 07/D2

43、/U8 Time: 15:40Sample: 1996 2002Series: CPAH. CPBJ. CPFJ. CPHB, CPHU. CPJL. CPJS, CPJX.CPLN, CPNMG, CPSD. CPSH. CPSX. CPTJ, CPZJExogenous variables: Individual effectsAutomatic selection of maximum lagsAutomatic selection of lags based on SIC: 0 to 1Newey-West bandwidth selection using Bartlett kern

44、elMeihodStatisticProb.*CrosssectionsObsNull; Unit root (assumes common unit rooi process)Levin. Lin & Chu t*9.697781.00001584Null: Unit root (assumes individual unit root process)Im, Pesaran and Shin W-stat6.463801.00001584ADF Fisher Chi-square3.049971.00001584PP - Fisher Chi-square5.243351.00001590

45、Null: No unit root (assumes common unit root process)Hadri Z-stat7.583830.000015106k Probabilities for Fisher tests are computed using an asympotic Chi -square distribution. All other-tests assume asymptotic normality.从上面的检验结果可以看出来，6种检验方法的结论都认为15个cp序列存在单 位根。选择IPS检验方法进行单位根检验。检验结果如下：Null Hypothesis: U

46、nit root (individual unit root process)Date: 07/U2；08 Time: 15:44Sample: 1996 2002Series: CPAH. CPBJ, CPFJ. CPHB. CPHU. CPJL, CPJS. CPJX.CPLN, CPNMG, CPSD. CPSH. CPSX. CPTJ. CPZJExogenous variables: Individual effectsAutomatic selection of maximum lagsAutomatic selection of lags based on SIC: 0 to 1

47、Total number of observations 84-Cross-sections included: 16MethodStatisticProb.*Im. Pesaran and Shin W-stat6.463801.0000* Probabilities are computed assuming asympotic normalityIntermediate ADF test resultsMaxSeriest-StatProb. E(t)E(Var)LaqLaqObsCPAH5.55420.9999 -1.5582.643115CPBJ0.56130.9695 -1.547

48、2.332016CPFJ-0.69690.7711 -1.5472.332016CPHB-0.53040.8U9 -1.5472.332016CPHU2.65880.9991 -1.5472.332016CPJL0.63240.9732 -1.5472.332016CPJS-1.35320.5305 -1.5472.332016CPJX0.53560.9631 -1.5472.332016CPLN1.12760.9893 -1.5472.332016CPNMG3.07650.9992 -1.5582.643115CPSD-0.33890.8450 -1.5582.643115CPSH0.787

49、10.9754 -1.5582.643115CPSX2.11120.9980 -1.5472.332016CPTJ-0.15460.8827 -1.5582.643115CPZJ2.00920.9966 -1.5582.643115Average1.0653-1.5522.459从上面的结果可以看出，cp面板存在单位根，同时每个个体都存在单位根。2收集中国2000-2005年各地区城镇居民人均可支配收入X和消费指出Y统计 数据如表9.4。数据是6年的，每一年都有32组数据，共192组观测值。人均可支配收入和消费支出数拯（单位：元）200020012002200320042005可支可支可支可支

50、可支可支地配收消费配收消费配收消费配收消费配收消费配收消费区入支出入支出入支出入支出入支出入支出XYXYXYXYXYXY全6279.949986859.553097702.860298472.265109421.6718210493.7942国8.008.010880.941003.88北10349.849311577.892212463.102813882.111215637.122017652.1324京69.4978.72924.60623.84840.40954.20天8140.561218958.769879337.5719110312.786711467.88021263&9653

51、津0.040.226.9691.5316.4455.26河5661.143485984.844796679.650697239.054397951358199107.06699北6.472.758.286.77189.67山4724.139415391.041236234.347107005.051057902.856548913.96342西fit1.875.016.963.38651.63内 蒙5129.039275535.841956051.048597012.954198122.962199136.76928古5.759.620.88049.269.60辽5357.743565797.

52、046546524.553427240.560778007.565439107.57369宁9.061.422.648.926.285.27吉4810.040205340.44337626049737005.154927840.660688690.66794林m0.876.226.88701.997.71龙4912.838245425.841926100.544626678.950157470.755678272.56178江8.447.366.08091.531.01上11718.886812883.933613249.104614867.110416682.126318645.1377海0

53、19460804.00490.34821.03033.41江6800.253237375.155328177.660429262.4670810481.733212318.8621苏380.744.606.5893.2657.82浙9279702010464.795211715.871313179.971214546.106316293.1225江6.2267.3960.0853.893864773.74安5293.542325668.845176032.447366778.050647511.457118470.66367徽5.980.650.523.343338.67福7432.25638

54、8313.060159189.366319999.5735611175.8161123218794建6.748.116.684.2637531.41江5103.536235506.038946335.645496901.449147559.653378619.66109西8.562.514322.554.846.39山6489.950227101.052527614355968399.960699437.8667310744.7457东7.008.416321.350.7579.31河4766.238305267.441106245.44504692649417704.952948667.96

55、038南6.712.170.682.60097.02湖5524.546445855.948046788.556087321.959638022.763988785.96736北4.508.792.928.255.524.56湖6218.752186780.555466958.555747674.260828617.468849523.97504南3.796.226.720.628.617.99广9761.5801610415809911137.898812380.963613627.1069147691180东7.9119.6320.4843.27654.79949.87广5834.44852

56、6665.752247315.354137785.057638689.964459286.77032西3.313.732.444.509.730.80海5358340825838.843676822.754597259.255027735.758028123.95928南2.564.852.645.438.404.79重6275.955696721.058737238.063608093.671189220.9797310243.8623庆8.849.694.247.066.0546.29四5894.248556360.451766610.854137041.857597709.8637183

57、85.96891川7.787.170.087.21746.27贵5122.242785451.942735944.045986569.249487322.0549481516159州1.281.908.283.985.453.29云6324.651856797.752527240.558277643.560238870.868379265.96996南4.311.606.927.568.010.90西7426355547869.15994807969528765.480459106.083389431.18617藏2.426.392.445.347.21811陕5124.242765483.7

58、46376330.853786806.356667492.462338272.06656西4.673.744.045.547.072.46甘4916.241265382.944206151.450646657.252987376.759378086.86529肃5.471.314.244914.307.20青5169.941855853.746986170.550426745.354007319.657588057.86245海6.732.592.522.247.955.26宁4912.44200554445956067.451046530.453307217.858218093.66404复

59、0.507.404.928.347.384.31新5644.844226395.049316899.656367173.555407503.457737990.162076.934.404.404.612.625.52回国首先建立工作文件，打开工作文件后，过程如下: Torkfile: U1TTITLEDprint|Saw |Detaik47： |站0内|7|宝0佗 |DeletE |Genr&mplE |Range: Sample;C0 residNew Obj ect.Generate Series.Eredk Links.Display Filter: *Fetch Fr帅 DB.Upd

60、ate selected, from DU.Store selected to DB.Copy sel-ectedRenaniQ selectGd.Delete selected.Print SelectedC； Untitled X New Page /建立面板数据库，并命名为XY输入不同省市（包括全国）的标识，如下:EVie- Pool: XTTorkfile: UHTITLED:Untitled File Edit Object ViewProc Quick Opti ons Window Help.axView |Procobject | (Print |Name (Freeze |