| Abstract: | Certain complex processes are most effectively modeled not on the macro-scale, but from the bottom-up, by simulating the decisions of individual entities, or agents. This study uses an agent-based modeling (ABM) approach to simulate residential dynamics in an area of Boston that has increasingly experienced gentrification in the past decades. The model is instantiated using basic empirical data and uses simple decision-making rules, differentiated into four classes, to simulate the process of residential dynamics. The model employs the consumption explanation of the cause of gentrification, which emphasizes the choices of individuals drawn to urban amenities, while testing the production explanation, which suggests that major investments from the public and private sphere attract and explain gentrification. Verification shows that the processes in the model work according to its construction, simulates complexity and emergent phenomena, and may be a valuable explanatory tool for understanding and learning about some processes underlying gentrification. |
