互助問答125問動態(tài)空間計量模型的估計問題

1、您使用動態(tài)空間計量模型對問題進行估計時，同時使用的是矩估計的方法，如 何實現(xiàn)那個AR ( 1 )和AR (2)的檢驗?zāi)?？相?yīng)的代碼是什么?AR (1) , AR (2)是用來檢驗動態(tài)面板，如差分或系統(tǒng) GMM是否存在擾動項一階和 二階自相關(guān)的。動態(tài)空間計量模型的使用未見推廣的這些檢驗?？臻g計量中有SAF模型，即空間自相關(guān)(回歸)模型。動態(tài)空間計量，動態(tài)空間面板模型的構(gòu)建與檢驗仍然 處在前沿的研究階段，Elhost (2010)對Arrelano和bond的差分GMM估計量進 行擴 展，使其包括一個內(nèi)生交互效應(yīng)，且同時發(fā)現(xiàn)這種估計量仍然可能存在嚴重的偏誤，特 別是Wy的參數(shù)的估計。Kukenov

2、a andMonteiro (2009)、Jacobs et al (2009)同時研究了動態(tài)面板數(shù)據(jù) 模型 (Ym, Wy-i),并擴展了 Blu ndell and Bo nd ( 1998)的系統(tǒng) GMM& 計，使之 包含內(nèi)生交互效應(yīng)(Wy)，前者同時研究了內(nèi)生解釋變量乙，后者研究了誤差項的空間自相關(guān)W。他們發(fā)現(xiàn)系統(tǒng)GMM&計量要優(yōu)于差分GMM且減小了參數(shù)估計。動 態(tài)空間面板模型的stata程序如下：clear *清空 ssc in stall spregdpd (or spregdhp) * 安裝 spregdpd 或 spregdhp 動態(tài)空間面板 模板help spregdpd(o

3、r spregdhp) help 輸參閱幫助文件(有案例)岀：Title+spregdpd: Spatial Panel Arella noBond Lin ear Dyn amic Regressi on:Lag & Durbin Mo delsSyntax+spregdpd depvari ndepvars weight, n c(#) wmfile(weight_file) model(sar|sdm)r un( xtab on d|xtdhp|xtdpd|xtdpdsys) be fe re Imspac ImhetImno rmdiag tests stand inv inv2 mf

4、x(lin, log) no con sta nt predict(new_var)resid(new_var) inst(vars) diff(vars) en dog(vars) pre(vars)dgmmiv(varlist) collzero tolog two step level(#) vce(vcetype)Model Opti ons +1- model(sar) MLE Spatial Panel Lag Model (SAR)2- model(sdm) MLE Spatial Pa nel Durbin Model (SDM)Run Options+1-NEWHa n-Ph

5、ilips (2010) Lin ear Dy namic Panelrun( xtdhp)2- run( xtab ond) xtab on dArella no-Bond Lin ear Dyn amic PanelRegressi on3- run( xtdpd)xtdpdArella no-Bo nd (1991) Lin ear Dyn amic PanelRegressi on4- run( xtdpdsys) xtdpdsys Arellano-Bover/Blundell-Bond (1995, 1998)System LinearDynamic Panel Regressio

6、n Options+* nc(#) Number of Cross Sections Units Time series observationsmust be Balanced in each Cross Sectionwmfile(weight_file) OpenCROSS SECTION weight matrix file.testsdisplay ALLImh, Imn, Imsp, diag tests two-step estimate run(xtdpd)t 超卵詒fiV(varlist)DifferencedEquation run(xtdpd) inst(varlist)

7、Variablesrun(xtabond)length is lag(1)diff(varlist)ExogenousVariables run(xtabond) en dog(varlist)run(xtabond,xtdpdsys) pre(varlist)Variablesrun(xtabond, xtdpdsys)GMM Instruments forAdditional InstrumentalDependent Variable LagAlready DifferencedEn doge nous VariablesPredeterminedvce(vcetype) ols,rob

8、ust, cluster, bootstrap, jackknife, hc2, hc3 level(#)confide nee in tervals level; defaultislevel(95)Spatial Panel Aautocorrelation Tests+Imspac Spatial Panel Aautocorrelation Tests:* Ho: Error has NoSpatial AutoCorrelationHa: Error hasSpatial Autocorrelation* Spatial Econo metrics Regressi on Model

9、s: * (1) Spatial Panel Data Regressi on Models:spregxt Spatial Panel Regressi on Econo metric Models:StataModule Toolkitgs2slsxtGeneralized Spatial Panel 2SLS Regressiongs2slsarxt Generalized Spatial Panel Autoregressive 2SLS Regression spglsxt Spatial Panel Autoregressive Generalized LeastSquares R

10、egression spgmmxtSpatial Panel Autoregressive GeneralizedMethod ofMoments Regression spmstarxt (m-STAR) Spatial Lag Panel Models spmstardxt(m-STAR) Spatial Durbin Panel Modelsspmstardhxt(m-STAR) Spatial Durbin MultiplicativeHeteroscedasticityPanel Modelsspmstarhxt (m-STAR) Spatial Lag Multiplicative

11、HeteroscedasticityPanel ModelsspregdhpSpatial Panel Han-Philips Linear DynamicRegression: Lag& Durbin ModelsspregdpdSpatial Panel Arella noBond Lin ear Dyn amicRegression:Lag & Durbin ModelsspregfextDurbinModelsSpatial Panel Fixed Effects Regression: Lag &spregrextSpatial Panel Random Effects Regres

12、sion: Lag &Durbinspregsacxt spregsarxt spregsdmxt spregsemxtModelsMLE Spatial Autocorrelation Panel Regression (SAC)MLE Spatial Lag Panel Regression (SAR)MLE Spatial Durbin Panel Regression (SDM)MLE Spatial Error Panel Regression (SEM)* Spatial Cross Section Regression Models:spregcsSpatial Cross Se

13、ction Regression EconometricModels:Stata Module Toolkitgs2sls gs2slsar Regressi ongs3slsgs3slsarRegressionspautoregspgmmspmstarspmstardspmstardhGeneralized Spatial 2SLS Cross SectionsRegressionGeneralized Spatial Autoregressive 2SLS CrossSectionsGeneralized Spatial 3SLS Cross SectionsRegression Gene

14、ralized Spatial Autoregressive 3SLS CrossSectionsSpatial Cross Section Regression ModelsCross Sections Modelsspmstarh(m-STAR) Spatial Lag MultiplicativeHeteroscedasticityCross Sections ModelsMLE Spatial AutoCorrelation Cross SectionsRegressionSpatial Autoregressive GMM CrossSections Regression (m-ST

15、A旳 Spatial Lag Cross Sections Models (m-STA旳 Spatial Durbin Cross Sections Models (m STAR) Spatial Durbin MultiplicativeHeteroscedasticityspregsac(SAC) spregsar “l(fā)e Spatial Lag Cross Sections Regression(SAF?) spregsdmMLE Spatial Durbin Cross Sections Regression(SDM)spregsemMLE Spatial Error Cross Se

16、ctions Regression(SEM)* (3) Tobit Spatial Regression Models:* (3-1) Tobit Spatial Panel Data Regression Models: sptobitgmmxt Tobit Spatial GMM Panel Regression sptobitmstarxtTobit (m-STAR) Spatial Lag Panel Models sptobitmstardxtTobit (m-STAR) Spatial Durbin Panel Models sptobitmstardhxtTobit (m- ST

17、AR) Spatial Durbin Multiplicative HeteroscedasticityPanel Models sptobitmstarhxtTobit (m-STAR) Spatial Lag Multiplicative HeteroscedasticityPanelModelssptobitsacxt Tobit MLE Spatial Autocorrelation (SAC) Panel Regression sptobitsarxt Tobit MLE Spatial Lag Panel Regression sptobitsdmxt Tobit MLE Spat

18、ial Panel Durbin Regression sptobitsemxt Tobit MLE Spatial Error Panel Regression spxttobit Tobit Spatial Panel Autoregressive GLS Regression * (3-2) Tobit Spatial Cross Section Regression Models: sptobitgmm Tobit Spatial GMM Cross Sections Regressionsptobitmstar Tobit (m-STAR) Spatial Lag Cross Sec

19、tions Models sptobitmstardTobit (m- STAR) Spatial Durbin Cross Sections Models sptobitmstardhTobit (m-STAR) Spatial Durbin Multiplicative HeteroscedasticityCross Sections sptobitmstarhTobit (m-STAR) Spatial Lag Multiplicative Heteroscedasticity CrossSections sptobitsac Tobit MLE AutoCorrelation (SAC) Cross Sections Regress