Spatial econometrics studies how geography affects statistical data analysis using regression analysis to build models and predict future events. It has applications in real estate, politics, public health, and criminology.
Spatial econometrics is an interdisciplinary field of study that divides into statistics, economics, regional science, and econometrics. The field originally evolved from econometrics, which mixes statistics and mathematics with economics. The spatial aspect of econometrics leads to a study of how spatial relationships, or geography, affect the study of statistical data analysis by providing a geographically centered interpretation of a data set.
Regression analysis is used by spatial econometrics professionals, who use this approach to build statistical models and tests. With regression analysis, researchers look at one dependent variable and one or more independent variables. When the value of the dependent variable changes, researchers try to predict how the change will affect the values of the independent variables. These variables involve spatial relationships, such as what part of a city that different people included in a statistical model call home, or how proximity to certain geographic features affects prices for homes in different parts of a country.
Those who use spatial econometrics to study relationships between various variables do so differently than spatial statistics. Rather than just focusing on the relationships between the data collected by the researchers, the researchers focus on a theoretical model to understand how changes in the data through regression analysis are affected by geography. This focus on theoretical models also determines which variables in a dataset are of interest to someone using spatial econometrics. The limits of a theoretical model are estimated by researchers using regression analysis.
The ultimate goal of spatial econometrics is not only to understand what has occurred, but also to make educated predictions about future events. Researchers focus on how the spatial relationships between these variables affect the final outcomes of various events. Using the results of such predictions, many organizations can more fully prepare for otherwise unpredictable space events.
The application of spatial econometrics cuts across a wide variety of fields. Real estate appraisers, real estate investors, and other professions that need to measure and predict price trends in the real estate industry rely on spatial econometrics. Political scientists use data to study the effect of which neighborhood a person lives in and how they vote in elections. Public health administrators use the demographic data collected by spatial econometricians to better understand how disease spreads throughout the population. Criminologists can use similar information to study factors that contribute to specific types of criminal activity in different geographic areas.
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