GeoDaSpace

The GeoDa Center for Geospatial Analysis and Computation at Arizona State University has developed a powerful tool for spatial data analysis called GeoDaSpace.

GeoDaSpace is a user-friendly software that offers a range of spatial econometric techniques to analyze various types of spatial data. It allows users to visualize and explore data patterns, estimate spatial models, generate forecasts, and produce maps and visualizations.

With a clean and intuitive interface, users can easily input their own datasets, specify model parameters, and interpret results. GeoDaSpace supports a range of spatial regression models, including Spatial Lag Models (SLMs), Spatial Error Models (SEMs), and Spatial Durbin Models (SDMs).

• SLMs: used to investigate the dependence among observations based on their neighbors.
• SEMs: used to investigate the effects of omitted variables on spatial dependence.
• SDMs: used to address simultaneous autoregressive effects in panel data settings.

GeoDaSpace also offers diagnostic tools to assess the adequacy of model assumptions and identify potential outliers. The software is widely used by economists, geographers, sociologists, political scientists, and urban planners to examine the role of space in their research questions.

GeoDaSpace is a valuable tool for those seeking to understand spatial dependencies and patterns in their data. Its user-friendly interface and wide range of techniques make it accessible to researchers with different levels of experience in spatial data analysis.