Towards a New Urban Economics: Traditional Models, Complexity, Big Data and AI

Daniel Czamanski analyzes the transition of urban economics from historical methods to contemporary inductive reasoning. Evaluating this change across the field's early evolution to modern data-driven approaches, he builds on key concepts to explore complexity theory and artificial intelligence.Outlining central topics, including land use patterns, housing markets, transportation systems and environmental impact, Czamanski provides inductive responses which rely on empirical evidence as the basis for explaining urban growth. Moving past traditional, deductive-centric approaches, chapters emphasize the need to leverage advanced modelling techniques and data analysis to address complex challenges, such as spatial inequality and climate change. The book highlights the importance of understanding cities as nuanced, interconnected systems where macro patterns emerge from micro-level decisions, advocating for integrated and adaptable approaches to urban development and policymaking.Towards a New Urban Economics is an essential resource for scholars and students of economics, finance and disruptive technologies. City planners and government regulators will similarly benefit from its actionable insights into the future of urban spaces.