SAR models for cross-sectional data

Linear models with autoregressive errors and spatial lags of the dependent and independent variables

Generalized method of moments estimator GS2SLS (generalized spatial two-stage least squares)

Spatial lags and autoregressive error terms given by one or more spatial weighting matrices

Heteroskedastic errors

Maximum-likelihood estimator

Robust standard errors

Constraints

Instrumental-variables spatial linear models

Moran test of residual correlation

 

SAR models for panel data

Fixed-effects maximum-likelihood linear models

Random-effects maximum-likelihood linear models

Model panel-level effects and normal i.i.d. or with the same autoregressive form as the time-level errors

 

Data management for spatial data

Capabilities for

Data with shapefiles

Data without shapefiles but including location information

Data without shapefiles or location information

Automatic translation of standard-format shapefiles

Set coordinates as

Planar

Latitude and longitude

Calculate distances

Automatic balancing of spatial panel data

Draw choropleth maps

Spatial weighting matrices for SAR models

Create and manage spatial weighting matrices that specify spatial lags

Nearest-neighbor weighting matrices

Inverse-distance weighting matrices

Custom weighting matrices from

Stata data

Mata programs

File import

Normalization of weighting matrices

Spectral (largest eigenvalue)

Min–max normalization

Row

Manage matrices

List

Summarize

Drop

Copy

Save and use

Add note

Import and export weighting matrices from text files

Use and save weighting matrices in Stata format

 

Predictions

Reduced-form mean

Direct mean

Indirect mean

Limited-information mean

Full-information mean

Linear prediction

Residuals

Uncorrelated residuals

 

Postestimation analysis

Direct and indirect (spillover) effects with standard errors

 

Postestimation Selector

View and run all postestimation features for your command

Automatically updated as estimation commands are run