This web app offers a intuitive step-by-step process for estimation of spatial econometric models, including a basic spatial visualization, creating of spatial weighting matrix and spatial correlation tests. Currently, it is possible to estimate OLS, SAR, SEM, SAC, SLX, SDM and SDEM models, with maximum likelihood and GMM estimators. Estimates of impacts are provided, when applicable.

First, the user must upload a spatial file containing all variables needed for the modelling. We suggest the GML format, that can be easily exported by Quantum GIS (QGIS) and others GIS software. After uploading the spatial file, the user can check the validity of data and plot a map of a choosen variable. Spatial weights matrix can be created, being used in the spatial correlation tests (Moran'I, Geary's C, Gestis-Ord's G and G*) and LISA map. The same spatial weights matrix is used for the estimation of the spatial cross-section models. After estimating the models, the user can check the results and explore the residuals in a map.

This web app was entirely created with R using the Shiny library. Spatial data is handled by the RGDAL, cleangeo and leaflet libraries. Spatial dependence tests and spatial models are provided by the spdep library.

This is a prototype. All results must be checked and validated by the users.

Developers: Raphael Saldanha (Fiocruz); Eduardo Almeida (UFJF).

Spatial data file (Cross-section)

GML file

Load here your spatial data file including variables. Currently, we suggest the GML format.




Data table




Spatial Weights Matrix



Spatial Autocorrelation

Target variable

Spatial Models