夜雨聆风
空间计量软件代码资源集锦(Matlab/R/Python/SAS/Stata), 不再因空间效应而感到孤独
凡是搞计量经济的，都关注这个号了
邮箱：econometrics666@sina.cn
所有计量经济圈方法论丛的do文件, 微观数据库和各种软件都放在社群里.建议到空间计量研究小组交流访问.计量经济圈空间计量研究小组@陈鑫—同济大学在读博士.
空间计量研究小组推荐
咱们空间计量研究小组已经聚集了一大批空间计量专业学者。今天，将给圈友们分享一些空间计量软件代码资源集锦，通过这些资源能够对空间计量有一个整体的把握。如果对空间计量感兴趣且有一些专业基础知识，欢迎到空间计量研究小组交流访问(文后“阅读原文”)。
空间计量百科全书式的使用指南百科指南
1）Matalb 代码资源：
Elhorst J.P.:
https://spatial-panels.com/software/
James P. LeSage:
https://www.spatial-econometrics.com/
Donald J. Lacombe:
http://myweb.ttu.edu/dolacomb/matlab.html
2）R代码资源：
CRAN Task View:
https://cran.r-project.org/web/views/Spatial.html
3）Python代码资源：
PySAL:
https://pysal.readthedocs.io/en/latest/users/tutorials/index.html
4）Stata代码资源：具体操作详见计量经济圈里的《空间计量的46页Notes, 区经相关学者可参阅》：
创建空间权重矩阵
l spmat –Create and manage spatial-weighting matrix objects [Author: Drukker et.al,2013]
l spatwmat—Spatial weights matrices for spatial data analysis [Author: Pisati ,2012]
l spwmatrix— Generates, imports, and exports spatial weights [Author: Jeanty, updated 2014.03.15]
l spwmatfill —Assigns first nearest neighbors to observations with no contiguous neighbors. [Author: Jeanty, 2010]
l spweight — Module to compute Cross-Section and Panel SpatialWeight Matrix [Author: Shehata, 2013]
l spweightxt– Module to compute Cross-Section and Panel Spatial Weight Matrix [Author: Shehata,2013]
l spweightcs —Module to computeCross Section Spatial Weight Matrix [Author: Shehata, 2013]
l spcs2xt—Module to Convert Cross Section to Panel Spatial Weight Matrix [Author: Shehata, 2012]
l shp2dta —Module to converts shape boundary files to Stata datasets [Author: Crow, 2013]
空间自相关检验
l spautoc –Stata modules to calculate spatial autocorrelation [Author: Nicholas Cox et.al,2006]
l spatgsa –Measures of global spatial autocorrelation [Author: Maurizio Pisati, 2001]
l spatlsa –Measures of local spatial autocorrelation [Author: Maurizio Pisati, 2001]
l spatcorr –Stata modules to compute and plot spatial autocorrelation [Author: Maurizio Pisati, 2001]
l spatdiag –Diagnostic tests for spatial dependence in OLS regression [Author: Maurizio Pisati, 2001]
l anketest–Moduleto perform diagnostic tests for spatial autocorrelation in the residuals ofOLS, SAR, IV, and IV-SAR models
l splagvar-Moduleto generate spatially lagged variables, construct the Moran Scatter plot, andcalculate Moran’s I statistics
空间截面回归
l spatreg- Moduleto estimate the spatial lag and the spatial error regression models by maximumlikelihood.
l spmlreg–Moduleto estimate the spatial lag, the spatial error, the spatial durbin, and thegeneral spatial models by maximum likelihood
l spautoreg–Moduleto estimate Spatial Cross Sections Regression (Lag-Error-Durbin-SAC-SPGKS-SPGSAR-GS2SLS-GS3SLS-SPML-SPGS-SPIVREG-IVTobit)
l sppack–Modulefor cross-section spatial-autoregressive models
l gs2sls-Moduleto estimate Generalized Spatial Two Stage Least Squares Cross Sections Regression
l gs2slsar–Module to estimate GeneralizedSpatial Autoregressive Two Stage Least Squares Cross Sections Regression
l gs3sls–Moduleto estimate Generalized Spatial Three Stage Least Squares Cross SectionsRegression (3SLS)
l gs3slsar–Module to estimate GeneralizedSpatial Autoregressive Three Stage Least Squares (3SLS) Cross SectionsRegression
l spgmm–Moduleto estimate Spatial Autoregressive Generalized Method of Moments Cross SectionsRegression
l spregsac–Module to estimate Maximum Likelihood Estimation AutoCorrelation (SAC) CrossSection Regression
l spregsar–Moduleto estimate Maximum Likelihood Estimation Spatial Lag Cross Sections Regression
l spregsdm–Moduleto Estimate Maximum Likelihood Estimation Spatial Durbin Cross SectionsRegression
l spregsem–Module to Estimate Maximum LikelihoodEstimation Spatial Error Cross Sections Regression
l spmstard–Moduleto Eestimate Multiparametric Spatio Temporal AutoRegressive Regression SpatialDurbin Cross Sections Models
l spmstar–Moduleto Estimate (m-STAR) Spatial Multiparametric Spatio Temporal AutoRegressiveRegression Models
l spmstardh–Moduleto Estimate (m-STAR) Spatial Multiparametric Spatio Temporal AutoRegressiveRegression: Spatial Durbin Multiplicative
Heteroscedasticity Cross SectionsModels
l spmstarh–Moduleto Estimate (m-STAR) Spatial Multiparametric Spatio Temporal AutoRegressiveRegression: Spatial Lag Multiplicative Heteroscedasticity Cross Sections Models
l sptobitmstar–Moduleto Estimate Tobit (m-STAR) Spatial Multiparametric Spatio TemporalAutoRegressive Regression: Spatial Lag Cross Sections Models
l sptobitmstard–Moduleto Estimate Tobit (m-STAR) Spatial Multiparametric Spatio TemporalAutoRegressive Regression: Spatial Durbin Cross Sections Models
l sptobitmstardh–Moduleto Estimate Tobit (m-STAR) Spatial Multiparametric Spatio TemporalAutoRegressive Regression: Spatial Durbin Multiplicative HeteroscedasticityCross Sections Models
l sptobitmstarh–Moduleto Estimate Tobit (m-STAR) Spatial Multiparametric Spatio TemporalAutoRegressive Regression: Spatial Lag Multiplicative Heteroscedasticity CrossSections Models
l sptobitsar–Moduleto Estimate Tobit MLE Spatial Lag Cross Sections Regression
l sptobitsem–Moduleto Estimate Tobit MLE Spatial Error Cross Sections Regression
l sptobitsdm–Moduleto Estimate Tobit MLE Spatial Durbin Cross Sections Regression
l sptobitsac–Moduleto Estimate Tobit MLE Spatial Autocorrelation Cross Sections Regression
空间面板回归
l xsmle –Stata modules to calculate spatial Panel Regression [Author: Belotti et.al, 2014]
l spglsxt–Moduleto estimate Spatial Panel Autoregressive Generalized Least Squares Regression
l spregsdmxt:Maximum Likelihood Estimation Spatial Durbin Panel Regression [Author: Shehataet.al, 2014]
l gs2slsarxt–Moduleto estimate Generalized Spatial Panel Autoregressive Two Stage Least SquaresRegression
l gs2slsxt–Moduleto estimate Generalized Spatial Panel Autoregressive Two-Stage Least SquaresRegression
l spgmmxt–Moduleto estimate Spatial Panel Autoregressive Generalized Method of MomentsRegression
l spmstardhxt–Moduleto estimate (m-STAR) Spatial Multiparametric Spatio Temporal AutoRegressiveRegression: Spatial Durbin Multiplicative Heteroscedasticity Panel Models
l spmstardxt–Moduleto Estimate (m-STAR) Spatial Multiparametric Spatio Temporal AutoRegressiveRegression: Spatial Durbin Panel Models
l spmstarhxt–Moduleto Estimate (m-STAR) Spatial Multiparametric Spatio Temporal AutoRegressiveRegression: Spatial Lag Multiplicative Heteroscedasticity Panel Models
l spmstarxt–Moduleto Estimate (m-STAR) Spatial Panel Multiparametric Spatio TemporalAutoRegressive Regression Models
l spregdhp–Module to estimate Spatial PanelHan-Philips Linear Dynamic Regression: Lag & Durbin Models
l spregdpd–Module to estimate Spatial PanelArellano-Bond Linear Dynamic Regression: Lag & Durbin Models
l spregfext–Module to compute Spatial Panel FixedEffects Regression: Lag and Durbin Models
l spreghetxt–Module to Estimate Spatial PanelRandom-Effects Multiplicative Heteroscedasticity Regression: Lag and DurbinModels
l spregrext–Module to compute Spatial PanelRandom Effects Regression: Lag and Durbin Models
l spregsacxt–Module to Estimate Maximum LikelihoodEstimation Spatial AutoCorrelation (SAC) Panel Regression
l spregsarxt–Module to Estimate Maximum LikelihoodEstimation Spatial Lag Panel Regression
l spregsdmxt–Module to Estimate Maximum LikelihoodEstimation Spatial Panel Durbin Regression
l spregsemxt–Module to Estimate Maximum LikelihoodEstimation Spatial Error Panel Regression
l Spregxt—New Stata Module Econometric Toolkitto Estimate Spatial Panel Regression Models
l spxttobit–Moduleto estimate Tobit Spatial Panel Autoregressive
广义最小二乘法GLS回归
l sptobitmstardhxt–Moduleto Estimate Tobit (m-STAR) Spatial Multiparametric Spatio TemporalAutoRegressive Regression: Spatial Durbin Multiplicative HeteroscedasticityPanel Models
l sptobitmstardxt–Moduleto estimate Tobit (m-STAR) Spatial Multiparametric Spatio TemporalAutoRegressive Regression: Spatial Durbin Panel Models
l sptobitmstarhxt–Moduleto estimate Tobit (m-STAR) Spatial Multiparametric Spatio TemporalAutoRegressive Regression: Spatial Lag Multiplicative Heteroscedasticity PanelModels
l sptobitmstarxt–Moduleto estimate Tobit (m-STAR) Spatial Multiparametric Spatio TemporalAutoRegressive Regression: Spatial Lag Panel Models
l sptobitsemxt–Moduleto estimate Tobit MLE Spatial Error Panel Regression
l sptobitsacxt–Moduleto estimate Tobit MLE Spatial AutoCorrelation (SAC) Panel Regression
l sptobitsarxt– Module to estimate Tobit MLE Spatial Lag Panel Regression
l sptobitsdmxt–Moduleto estimate Tobit MLE Spatial Panel Durbin Regression
其他程序
l china_spatdwm–Moduleto provide spatial distance matrices for Chinese provinces and cities
l usswm–Moduleto provide US state and county spatial weight (contiguity) matrices
l spmap–Moduleto visualize spatial data
l spseudor2–Module to calculate goodness-of-fit measures in spatial autoregressive models
l spagg–Moduleto create aggregate source or target contagion spatial effect variable fordirected dyadic data
l spspc–Module to create specific source or target contagion spatial effect variablefor directed dyadic data
l spdir–Moduleto create directed dyad contagion spatial effect variable
l spundir–Moduleto create directed dyad contagion spatial effect variable
l spmon–Moduleto create spatial effect variable for monadic data
l spgrid–Moduleto generate two-dimensional grids for spatial data analysis
l spkde -Moduleto perform kernel estimation of density and intensity functions fortwo-dimensional spatial point patterns
5）SAS代码资源：
The SPATIALREGProcedure：
https://support.sas.com/rnd/app/ … ets_spatialreg.html
6) 相关论坛
Github: https://github.com/
如果对空间计量感兴趣且有一些专业基础知识，欢迎到空间计量研究小组交流访问(文后“阅读原文”)。
可以到计量经济圈社群进一步访问交流各种学术问题，这年头，我们不能强调一个人的英雄主义，需要多多汲取他人的经验教训来让自己少走弯路。
计量经济圈当前有几个阵地，他们分别是如下4个matrix：
①小鹅社群：数据软件书籍等所有资料(最多且更新频繁)，
②微信群：服务于计量经济圈社群群友(最活跃)，
③研究小组：因果推断, 空间计量, 面板数据(最专业)，
④QQ群：2000人大群服务于社群群友(最大)。
计量经济圈是中国计量第一大社区，我们致力于推动中国计量理论和实证技能的提升，圈子以海内外高校研究生和教师为主。计量经济圈绝对六多精神：社科资料最多、社科数据最多、科研牛人最多、海外名校最多、热情互助最多、前沿趋势最多。如果你热爱计量并希望长见识，那欢迎你加入到咱们这个大家庭(戳这里)，要不然你只能去其他那些Open access圈子了。注意：进去之后一定要看小鹅社群“群公告”，不然接收不了群息，也不知道怎么进入咱们独一无二的微信群和QQ群。在规则框架下社群交流讨论无时间限制。
只有进去之后才能够看见这个群公告
