Abstract
We present a new bilateral agent-based land market model, which moves beyond previous work by explicitly modeling behavioral drivers of land-market transactions on both the buyer and seller sides; formation of bid prices (of buyers) and ask prices (of sellers); and the relative division of the gains from trade from the market transactions. We analyze model output using a series of macro-scale economic and landscape pattern measures, including land rent gradients estimated using simple regression models. We first demonstrate that our model replicates relevant theoretical results of the traditional Alonso/Von Thünen model (structural validation). We then explore how urban morphology and land rents change as the relative market power of buyers and sellers changes (i.e., we move from a 'sellers' market' to a 'buyers' market'). We demonstrate that these strategic price dynamics have differential effects on land rents, but both lead to increased urban expansion.
| Original language | Undefined |
|---|---|
| Pages (from-to) | 1-30 |
| Journal | Journal of artificial societies and social simulation |
| Volume | 12 |
| Issue number | 1,3 |
| Publication status | Published - 2009 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Agent-Based Computational Economics
- Location Choice
- Urban Land Market
- IR-61113
- Land Use
- Spatial Simulation
- METIS-249416
- Land Rent Gradient
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