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