Econometrics is the application of statistical methods to economic data that gives empirical content to economic relations. Much of Econometrics is based on analytics based on theory, observation and inference. Spatial econometrics is the field where spatial analytics concepts are embedded into econometrics analysis – either the theoretical model involves interactions between different spatial entities, or the data observations are not truly independent and amenable to spatial auto-correlation or neighborhood analysis etc. When data has a locational component – spatial dependence becomes important to understand and spatial heterogeneity occurs in the relationships. These can substantially enhance econometric models as spatial dependency and heterogentiy basically cross-off traditional Gauss-Markov assumptions that variables are fixed in repeated sampling – whihc is not the case when spatial context is added. In fact, relationship varies within the spatial data sample and thus alternative modelling and estimation procedures are needed to successfully model this type of variation and draw appropriate inferences. This is where Spatial Econometrics becomes important.
Spatial Econometrics is applied in political economy, urban growth, real estate pricing structure, trade analysis and economic growth analysis, region expenditure analysis and many other new areas of knowledge in economics.
C-SAG is building specialised Spatial Econometrics models and tools with experts associated in economy, urban planning and political science.