[AM9-1] Principles of spatial econometrics

Spatial econometrics uses spatial stochastic models to determine autocorrelation between interacting agents. The techniques involved are regression, the use of a spatial weights matrix, least squares, etc.

External resources

• Anselin, L. 1988. Spatial econometrics: Methods and models. Dordrecht: Kluwer.
  ISBN number: 9789024737352

Learning outcomes

• 282 - Describe the general types of spatial econometric model
  Describe the general types of spatial econometric model
• 283 - Explain how spatial dependence and spatial heterogeneity violate the Gauss-Markov assumptions of regression used in traditional econometrics
  Explain how spatial dependence and spatial heterogeneity violate the Gauss-Markov assumptions of regression used in traditional econometrics
• 284 - 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
  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
• 285 - Demonstrate how the spatial weights matrix is fundamental in spatial econometrics models
  Demonstrate how the spatial weights matrix is fundamental in spatial econometrics models
• 286 - Demonstrate why spatial autocorrelation among regression residuals can be an indication that spatial variables have been omitted from the models
  Demonstrate why spatial autocorrelation among regression residuals can be an indication that spatial variables have been omitted from the models

Self assessment

Outgoing relations

• [AM9-1] Principles of spatial econometrics subclassof [AM9] Spatial regression and econometrics

Contributors

• Rob Lemmens
  University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)
  https://research.utwente.nl/en/persons/rob-lemmens