Chapter 9 Space-Time Exploration

While the primary focus of GeoDa is on the exploration of cross-sectional or static data, it also includes limited functionality to investigate space-time dynamics through the use of the Time Editor, Time Player and Averages Chart.

This allows for the evolution of a variable to be shown over time through maps and graphs, in a form of comparative statics. One limitation of this approach is that it is cross-section oriented. More precisely, the different time periods are considered as separate cross-sectional variables (one cross-section for each time period). While this results in quite a bit of flexibility when it comes to grouping variables, it also means there is no inherent time-awareness, nor a dedicated panel data structure.

After explaining the approach to space-time exploration through the Time Editor and Time Player, I revisit the use of the Averages Chart for treatment effect analysis. In contrast to the discussion in Chapter 7, here a dynamic analysis is possible, in that spatial structural change can be assessed at two points in time through a difference in difference approach.

To illustrate these methods, I continue to use the Oaxaca Development sample data set, particularly the variables from the Mexican census at three different points in time: 2000, 2010, and 2020.