使用Eviews進行面板數據操作(有圖有真相)

1、Eviews面板數據上機操作2011年4月26日、建立兩種eviewsl作文件(1) 建立混合數據型工作文件1 建立一個年度工作文件(1996-2002) . (file:) filenewworkfileobjectnew objectpoolOKWorkfile CreateWorkfile structure typeD-ated - regular frequency Irregular Dated and Panel workfiles may be made from Un structured workfiles by later specifying date and/or o

2、ther iden tifier series Date specification! OK J I CancelNames (optional)WF；Page:在彈出的對話框中輸入截面?zhèn)€體的名稱縮寫一一點擊sheet,輸入變量名 （注意：在面板數據中，變量名的后面要加上“？ ”，表示不同個體）。r13k在彈出的右圖對話框中點擊Edit鍵 輸入數據，點擊order鍵可以在“按 個體進行排序”和“按時間進行排 序”之間進行切換。生成新的序列打開原始數據（在變量列表中雙擊poolOl即可打開），點擊工具欄倒數第二個的“poolGenr”鍵，或者選擇quickgenerate series,在彈出的

3、對話框中輸入要生成的公式，如:cp?=consume?/p?, ip?=income?/p? Pool: POOLOl Workfile: PANEL DATA:UntitledrView Proc Object Print Name Freeze ：Edit4-/- Order+/- Smpl4-/- Format Title Estimate Define PoolGenr SampleobsCONSUME? |INCOME?P?BJ-19965729.5207332.010111.60004ZZZ)VBJ-19976531.8107813.160105.3000BJ-19986970.8

4、308471.980102.4000BJ-19997498.4809182.760100.6000BJ-20008493.49010349.69103.5000BJ-20018922.72011577.78103.1000BJ-200210284.6012463.9298.20000TJ-19964679.6105967710109.0000TJ-19975204.1506608.390103.1000TJ-19985471.0107110.54099.50000TJ-19995851.5307649.83098.90000TJ-20006121.04081 40.50099.60000TJ-

5、20016987.2208958700101.2000TJ-20027191.9609337.56099.60000HB-19963424.3504442.810107.1000HB-19974003.7104958.670103.5000HB-19983834.4305084.64098.40000HB-1999dn?6 mririmnqa wnnnHR-9nnn4L卜(2) 建立面板數據型工作文件1 建立一個年度工作文件(1996-2002) . (file:)file new workfile 在彈出的對話框的左邊選擇Balance panel 并輸入起始時間，在截面數據選項中輸入T5”

6、 一一OKobjectnew objectpoolOK(2) objectnew objectquickempty group,后面步驟 的和截面數據的操作一樣。Workfile CreateObject View ProcQuickOQtions Win dow HelpBalanced P曰 nelIrregul-ar Dated and Panel workfiles may be made from Unstructured workfiles by later specifying date and/or other identifier series Panel specifica

7、tionNumber of cross sections:15Workfile:Names (opti onS)WF；Page:Range: 1996Sample: 1996 ismebscrossid daieid resid ser01 ser02Sample.Generate Series.Show .Graph Empty Group (Edit Series)Series Statistics Group Statistics Estimate Equati on. Estimate VAR.注意：由于無法輸入個體名稱, 容易產生混亂，因此不建議使用二、畫個體符號不同的散點圖方法一:

8、在變量截面中按住Ctrl鍵，依次選擇每個個體的因變量和自變量，點擊右鍵, 選擇openas group,在打開的數據窗口中選擇viewgraphconsumehbOpenconsumejs consume consumeln& cpnmg Kcpsd2S cpshcpsx Scptj & cpzj0pln0pnmg EpoolOI0psdGroup: UNTITLED Workfile: PAPas Groupcon sume nmgconsumesh consumes0 income? 0 incomet Hincomef 0 incomet 0 incomer 0incom

9、ej Hincomej 0incomej;CopyPastePaste Special.Manage Links & Formulae.Fetch from DB.Store to DB.Object copy as Equation.as Factor.as VAR. asSystem.as Multiple seriesE3両5 Print Item© 険甸 Group Members Spreadsheet Dated Data TableGraph.,Descriptive StatsCovarianize Analysis.N-Way Tabulation.Test

10、s of Equality.Principal Comp on ents.IPAH .06251 i.40247 .70470 .78528 .56753 .40597 .93333ah切 Bhbhlj卩.)s p p p p p p p c c c c c c c slslslsls曲Is0 incomel0 incomer0 incomes Hincomesn HincomesxRename.Delete0incometj0incomezjH I S X I - Z /- - -C w- p p P在彈出的對話框中選擇scatter在multiple中選擇single graph-XY p

11、airsOK便可得如下的散點圖o (CPAH.IPAH) i' (CPFJJPFJ) x (CPHU.IFHLJ) (CPJSJPJS) x (CPLN.IPLN)(CPSD.IPSD)(cpsx.ipsxiI- (CPZJJPZ (CPBJ.IP0J) (CPHBJPHB) + (CPJL.IPJL) (CPJX.IPJX) a (CPNMG.IPNMG)(CPSH.IPSH) (CPTJJPTJ)方法二（個人認為該方法較麻煩）：新建立一個截面數據文件夾filenewworkfile,在彈出的對話框左側選擇unstructured/undated,右邊輸入 1 05OKobjectn

12、ewobjectseries,在右邊變量名的對話框中輸入變量名cp_l 996 （這里一定要輸入，否則不會出現該變量）一一0K雙擊變量名cp_1996,在彈出的 對話框的第1 -1 5個空格中輸入數據。Workfile CreateWorkfib structure typeUnstructured / Undated D-ata r-angeObservations: 105Irregular Dated and Panel workfiles may be made from Un structured workfiles by later specifying date and/or o

13、ther identifier series CancelView Proc Object Properties113282.46625133.97834011.77543197.33952904.68762833.32173712.26082714.12493237.275102572.342113440.684126193.333132813.336144293.220155342.23416NA按照以上方法依次建立變量cp_1997、cp_1998，并輸入數據，在輸入 數據時cp_l 997要在第1 6-30個空格中輸入，cp_l 998要在第31-45個空 格中輸入，依次類推。然后再建

14、立變量cp_iah、cpbj、cp.ifj方法同上建立一個以所有的因變量值()為橫坐標的變量ipSeries: CP IBJ Workfile:View Proc Object Properties PrintSeries: CP_1997 % Series: CP_20Q2 VVorkfile: UNTIView ProcObject Properties Print NamefView ProcObject ； Properties Print Name115NA89NA163646.1 5090NA176203.048914784.364184853.441921 0473.1 2193

15、868.31 9936665.005203077.9899451 20.485213286.432954493.535224457.788964998.8742331 36.873976091.331243608.060984544.775252901.722995402.063263930.5741004850.1 80276634.1 831015635.770283131.62910210411.94295047.6721034787.561306002.0821047220.84331hJQ1058792.21 0qq6NA7NA85133.97896203.048106807.451

16、117453 757128206.271138654.4331410473.1215NA16NAView Proc | Object Properties90NA91NA924293.220935047.672945498.503955916.613966145.622976904.368987220.84399NA Series: CPJTJ Wori 建立以所有的因變量值()為橫坐標的變量ip和ip_t,其中ip是按個體排序的 1 05個ip值，ip_t是按時間排序的1 05個ip值。 按Ctrl鍵，分別按順序點擊ip_t,cp_l 996,cp_l 997,cp_l 998一一右鍵 op

17、en as a group(或者show),此時打開的數據為階箱型，其中第一列為全 部105個ip值,后面分別為1996年、1997年.的cp值。1006038.9221017668.03610213183.881036335.7321049375.06010511822.001S? EViews Group: UNTITLED Workfile: SANDIANTUUntitled口 File Edit Object View Proc Quick Options Window HelpView | Proc| Object Print | Name | Freeze | | Def sui

18、t Sort | Transpose | Edit-t-/-1 Smpl+/-1 InsCobsIP TCP 1996CP 1997CP 1996CP 1999133431.5942813.336NANANA145474.9634293.220NANANA156446.6155342.234NANANA164540.247NA3646.150NAMA177419.905NA6203.048NANA186040.944NA4853.441NANA194790.986NA3868.319NANA203918.314NA3077.989NANA214041.061NA3286.432NANA2256

19、68.830NA4457788NAMA233991.490NA3136.873NANA244382.250NA3608.060NANA253774.804NA2901.722NANA265049.407NA3930.574NANA278209.037NA6634.183NANA283869.952NA3131.629NANA296409.690NA5047.672NANA307158.288NA6Q02.082NANA314770.470NANA3777.410NA328273.418NANA6807.451MA336505.145NANA5197.041NA345167.317NANA389

20、6.778NA354251.494NANA3289.990NA364240.565NANA3477.560NA374°在打開的數據組中點擊viewgraphscattersimple scatter 便可得到不同時間的散點圖。同理，按Ctrl鍵，分別選擇ip_i, ip_ah,l p_bj, ip_hb便可得到不同個體 的散點圖。11000-10000-9000-8000-7000-6000-5000-4000-3000-6 7 89 9 99 9 9 1 -1 di _ _ _ ppp c c c9 0 0 12 2 p p P c c Co CPAH+ CP.JJL CP.JSD

21、 CP IBJ CPUSq CPJSH» CP IFJo CPIJXO CPISX* CPHB CPILN CP.JTJ:CPHLJA CPINMG0 CP.IZJ20002000 4000 6000 8000 10000 12000 14000IPJ由貓讒嚨豔洛泊三、配回歸直線（file： 7panelO5食品支出）按住Ctrl,選擇要畫回歸線的兩個變量，在本例中按住Ctrl,選擇fl和il openas group在打開的數據對話框中選擇viewgraph在graph type選項中選擇scatter在對畫框右邊點擊option選項Group: UNTITLED Workfile

22、: UNTGroup MembersSpreadsheetDated Data TableMi60.950062.6800i83.4400i95.3000Graph.Descriptive Stats Covariance Analysis. N-Way Tabulation. Tests of Equality. Principal Components. i30.7500i33.8500i40.7700iSO.OOOOi67.5500i76.6400Correlogram (1).Cross Correlation (2) Unit Root Test.Cointegration Test

23、.Qranger Causality.i82.2700834500；95.0000'04.1 600'04.3000'1 7.7000Label29.840033.3100Option選項對話框中有多種選擇（具體圖形在下頁）:a. x選inverse表示倒數模型b. x選log表示對數模型c. x、y都選log表示雙對數模型d. x選power 2表示是只有平方項的模型e. x選polynomial 2表示既有平方項又有一次方項的模型倒數模型20.000-f雙對數模型有一次方的二次項模型F1對數模型從這幾個圖形來看，雙對數模型和 二次多項式模型擬合的較好，但是 圖形越來

24、越分散，說明存在異方差, 可以用下一頁的方法來克服異方差。無一次方的二次項樓型(3) 克服二次多項式模型的異方差：按Ctrl選擇fl ,il show在對話框中輸Alog(fl) log(il)打開數據窗 口viewgraphscatteroption在x transformation中選擇polynomialOK,便可得無異方差的散點圖。obsLOG(F1)LOG )15.6266856.32963225.7143606.33271135.6617106.36894245.5691086.38906555.712U76.44691065.7780246.45181275.7567546.46

25、2671|vigw|Pro.cobject Piint |rtam4|Fre©zg| | Default |10.09.5-9.0-8.5-8.0-6.5-7.06.06.56.05.5£0017.0-LOG(F1)9.0四、畫擬合曲線點擊之前所做的估計結果的名稱（這里為pool02,每次做出結果后最好保存, 便于以后隨時打開），在打開的結果窗口中點擊procmake model在彈出的對話框中點擊solve在彈出的Model solution對話框的左邊中 間部分選擇Static solution此時原始的變量窗口會多岀cpah_0> cpbj_O

26、等，這是個體變量的擬合值。tlPool: P00L02 Workfile: 5PANEL02PaneView?rdq| Object 1 Print 1 NameFreezeEstimateDefiModel: UNTITLED Workfile: 5PANEL02PanMigyv|Proc|obj&:t| Print|N3mg|FreeN&| Solw | EqMtions|SaveDel：3ils4/-| ShowI H ICro Tot?Li礙EstimateMMMake ResidualsMake Group.Make Period Stats series.1 Mak

27、e ModelMake System.Update Coefs from PoolGenerate Pool series. Delete Pool series.R-sAdjiS.EP馬Store Pool series (DB).Fetch Pool series (DB).Import Pool data (ASCILXLS.WK?).Export Pool datJ (ASCII,XLS,WK?).I Equati on s: 15E POOL02Eq1.DyTiAmic solution Static solutioni,r Fi t static - no eq inteStruc

28、tural (ignore AJobsobs0 consumetj 0 consumezj EElcp0 cpah0 cpah_O0 cpbjS cpbj_O0 cpflS cpij_O0 cphbS cphb_OS cphlj0 cphljJD3ISDIK K n n.w.wd.d.c c c c按住Ctrl,選擇cpah和cpah.Oopen as a group在彈出的數據對話框中選擇viewgraphline便可得到由原始值和擬合值曲線構成的圖。如果想在圖形中出現散點，可以雙擊圖形, 在彈出的對話框中選擇line&symbol,便可 出現帶有散點圖的圖形。Line attrib

29、utes五、面板數據的估計和檢驗(file :5panelO2)1.面板數據的估計 建立面板數據文件夾，具體步驟參考第一部分 打開數據窗口，點擊estimate,彈出pool estimate對話框，如下頁所示。V填入因變量選擇None表示混合 模型，選擇fixed表 示個體固定效應模型, 選擇random表示個 體隨機效應模型選擇None表示混合 模型，選擇fixeH表 示時間固定效應標型, 選擇random表示時 間隨機效應模型GLS權重，通過加權可以克服異方差變參模 型V下面為個體固定效應的結果。點擊viewrepresentation可以顯示具體的回歸方程式。Pool: POOL02

30、Workfile: 5PAN邁鐵 I Prod Object | Print Namere 述 | _E Cross Section IdentifiersRepresentationsS? EViews - Pool: POOL02 Workfile: 5PANEL02Panel02口 File Edit Object View 臼cc Quick Options WindowView | Pfoc | Object|Estirate | Define PoolGenr | Sheet |VariableCoefficie ntStd Errort-StatisticC533440369.3

31、47727.692266IP?0.6947360.01086363.95600Fixed Effects (Cross)AH-C-3977133BJ-C546.0966FJ-C-45.58037HB-C-156.7460HU-C-174.2270JL-C19.93251JS-C-34.68271Estimation OutputResidualsCoef Covariance MatrixConfidence Ellipse.Wald Coefficient Tests.View | Proc object | Print Name Freeze | Estimate | Define | P

32、oolGenr | Sheet | buDstituted uoetticierrts:CPAH = -39.77133443 + 533.440323 + 0.6947364855*IPAH:PBJ = 546.0965643 + 533.440323 十 0.6947364855*IPBJCPFJ = -45.58037043 + 533.440323 + 0.6947364855*IPFJCPHB = -156.7459542 十 533.440323 + 0.6947364855*IPHBCPHLJ 二-174.2269943 十 533.440323 十 0. 6947364855*

33、IPHLJCPJL = 19.93250903 + 533.440323 + 0.6947364855*IPJL2.面板數據的檢驗Hausman檢驗（要在隨機效應結果窗口中進行）對數據進行隨機效應模型估計，在估計結果窗口點擊viewFixed/RandomEffects testingCorrelated Random Effect-Hausman Test （6.0以上白勺版本才可以）Pool: POOL02 Workfile: 5PANE：Pool: POOL02 Workfile: 5PANEL02:Panel02計磴yy Proc Object Print Name Freeze Es

34、timate Define PoolGenr SheetCross Section IdentifiersC345.1795IP?0.724569Random Effects (Cross)AH-C-2.553433BJ-C367.0439FJ-C-54.24006HB-C-104.8367HU-C-101.7680JL-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站如Ptxobj&d:

35、 print加皂總対 EsQ芒iiV七PU巧【Hi亡仃iFtearesentationsEstimation OutputResidualsCoef CovariancE MatrixCoeffi匚ient TestsFixed/Randorn Effects TestingSpreadsheet (stacked data). Descriptive Statistics .Unit Root Test.Cointegration Test.Label)5lent variancesStd. Error 1Statistic Prob.Redundant Fixed Effects - Li

36、kelihood RatioCorrelated Random Effects Hausman Test注意：只有在隨機效應估計窗口中才能 進行Hausman檢驗，只有在固定效應估 計窗口中才能進行似然比檢驗Pool: P00L02 Workfile: 5PANEL02:Panel02Yi 胡Object|Piint|NameFr88ze Estimatepefin&poolGend品estTest SummaryChi-Sq. StatisticChi-Sq. d.f.Prob.Cross-section random14.78756310.0001Correlated Random

37、 Effects HausmanTostPool: POOL02Test cross-section random effectsHausman檢驗的原假設是個體效 應與回歸變量無關，應建立隨機效 應模型，因此當Hausman值較大， 其對應的P值遠小于0.05時，拒絕 原假設，應建立個體固定效應模型。似然比檢驗方法同上，只是要在個體固定效應模型的輸出結果下進行檢驗*liPool: POOL02 Workfile: 5PANEL02:Panel02F曰View |PrQcj ObjectPrint|Nane| 屁 ©e 乙 eEstimate Define jP OQlGenr ：

38、Sh eetEffects TestStatisticd.f.Prob.Cross-section F7.151832(14.89)0.0000Cross-section Chi-square79.146400140.0000Redundant Fixed Effects TestsPool: POOL02Test cross-sectionfbcod effects該檢驗的原假設是勺相等，應建 立混合效應模型，當F值較大，P 值遠小于0.05時，拒絕原假設， 應建立個體固定效應模型。兩個檢驗的結果都是要建立個體固定效應模型, 因此這組數據應建立個體固定效應模型。 其他功能點擊 viewRes

39、idualTable,Graphs, Covarianee Matrix, Correlation Matrix可以分別得到 按個體計算的殘差序列表、殘差序 列圖、殘差序列的方差協方差矩陣、 殘差序列的相關系數矩陣。在估計結果中點擊procMakeModel可以出現估計結果的聯立方 程形式，進一步點擊Solve鍵可以 在彈出的對話框中進行動態(tài)和靜態(tài) 預測。DeFSar Incl CroTote Poof: P00L02 Workfile: 5PANEL02Panel02迅議| Proc|Object| Print) Name|Freeze; Estimate Define|Pool«

40、Genr |SheetCross Section IdentifiersRearese ntationsEstimation OutputaResiduals 1TableCoef C ovariance Matrix Confiden 匚 e Ellipse. Wald Coefficient Tests.GraphsCovariance MatrixCorrelation MatrixSpreadsheet (stacked data) .Descriptive Statistics .Unit root test.ValueStd. Err.Label514.9142 81.59665R

41、estrictions are linear in coefficients.Pool: P00L02 Workfile: 5PANEL02Panel0View >?rdg| Object Print Name Freeze Estimate DefineEstimateMake ResidualsMake Group.Make Period Stats series.Make ModelMake System.Update Coefs from PoolGenerate Pool series.Delete Pool series.Store Pool series (DB).Fetch Pool series (DB).Import Pool data (ASCII,XLSUWK?).Export Pool data (ASCII,XLS,WK?).五、面板數據的單位根檢驗在估計結果或原始的面包數據窗口中