Spatial Socio-Econometric Modeling

Catalog description

Despite the vast availability of data that can be linked to earth’s surface (AKA geo- referenced or geo-located), most research continue to ignore or omit the influence of location on the outcomes of interest. For example, assume one is interested in measuring the impact of an intervention taking place in some school districts across a given state. Assume further that a variety of school-level administrative indicators are readily available for model inclusion, whereas other place-based indicators require extra data gathering, management, and methods before they can be statistically accounted for. In scenarios like this, researchers typically proceed to model the intervention effects without considering other place-based variables that surely impact students’ performance over and above their within school experiences. That is, given that where individuals experiences life transcends school boundaries, the omission of out-of-school localized factors such as neighborhood-level poverty, crime, or unemployment levels, equates to ignoring and/or assuming that those factors bear no effect on such individuals’ prospects of success. The overarching purpose of this course is threefold. First, it discusses the most recent theories on neighborhood effects, equality of opportunity and environmental determinism as the foundations for the applications and methods covered in the course. Second, the course moves to introduce a survey of geolocated data sources that can be incorporated in traditional socio-econometric research. Third, the course provides participants with tools and methods to visualize and model datasets with spatial elements in order to reach conclusions and offer recommendations that consider the relevance of place and space. It is hoped that the incorporation of these place-based indicators may provide more robust and precise evidence, (as) compared to evidence…