Dynamic Spatial Time Series Models study how economic processes change over time and space. The researchers explore different ways to analyze these processes, focusing on spatial data that evolves dynamically. They discuss the importance of considering spatial differences in policies and cover various modeling techniques for analyzing spatial time series data. Key findings include the use of parametric and non-parametric models to capture linear and nonlinear relationships, as well as the identification of causal relationships in spatial time series settings.