Spatial Seemingly Unrelated Regression Models
Generation of a random dataset with a spatial SUR structure.
Direct, indirect and total effects estimated for a spatial SUR model
Testing for the presence of spatial effects in Seemingly Unrelated Reg...
Likelihood ratio for testing homogeneity constraints on beta coefficie...
Methods for class spsur
Homicides in U.S. counties
Print method for objects of class summary.spsur.
Spain geometry
Spatial Seemingly Unrelated Regression Models.
Three Stages Least Squares estimation,3sls, of spatial SUR models.
General Spatial 3SLS for systems of spatial equations.
Maximum likelihood estimation of spatial SUR model.
Estimation of SUR models for simple spatial panels (G=1).
Summary of estimated objects of class spsur.
Wald tests on the beta coefficients
Wald tests for spatial parameters coefficients.
Spatial weight matrix for South-West Ohio Counties to estimate Spatial...
A collection of functions to test and estimate Seemingly Unrelated Regression (usually called SUR) models, with spatial structure, by maximum likelihood and three-stage least squares. The package estimates the most common spatial specifications, that is, SUR with Spatial Lag of X regressors (called SUR-SLX), SUR with Spatial Lag Model (called SUR-SLM), SUR with Spatial Error Model (called SUR-SEM), SUR with Spatial Durbin Model (called SUR-SDM), SUR with Spatial Durbin Error Model (called SUR-SDEM), SUR with Spatial Autoregressive terms and Spatial Autoregressive Disturbances (called SUR-SARAR), SUR-SARAR with Spatial Lag of X regressors (called SUR-GNM) and SUR with Spatially Independent Model (called SUR-SIM). The methodology of these models can be found in next references Minguez, R., Lopez, F.A., and Mur, J. (2022) <doi:10.18637/jss.v104.i11> Mur, J., Lopez, F.A., and Herrera, M. (2010) <doi:10.1080/17421772.2010.516443> Lopez, F.A., Mur, J., and Angulo, A. (2014) <doi:10.1007/s00168-014-0624-2>.