AM-31 - Principles of spatial econometrics

Learning Objectives: 
  • Explain how spatial dependence and spatial heterogeneity violate the Gauss-Markov assumptions of regression used in traditional econometrics
  • Demonstrate how the spatial weights matrix is fundamental in spatial econometrics models
  • Demonstrate why spatial autocorrelation among regression residuals can be an indication that spatial variables have been omitted from the models
  • Demonstrate how spatially lagged, trend surface, or dummy spatial variables can be used to create the spatial component variables missing in a standard regression analysis
  • Describe the general types of spatial econometric models