Computational Model Library

Displaying 10 of 21 results Housing clear filters

Exploring Urban Shrinkage

Andrew Crooks | Published Thursday, March 19, 2020

While the world’s total urban population continues to grow, this growth is not equal. Some cities are declining, resulting in urban shrinkage which is now a global phenomenon. Many problems emerge due to urban shrinkage including population loss, economic depression, vacant properties and the contraction of housing markets. To explore this issue, this paper presents an agent-based model stylized on spatially explicit data of Detroit Tri-county area, an area witnessing urban shrinkage. Specifically, the model examines how micro-level housing trades impact urban shrinkage by capturing interactions between sellers and buyers within different sub-housing markets. The stylized model results highlight not only how we can simulate housing transactions but the aggregate market conditions relating to urban shrinkage (i.e., the contraction of housing markets). To this end, the paper demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test polices to alleviate this issue.

The PARSO_demo Model

Davide Secchi | Published Tuesday, November 05, 2019

This model explores different aspects of the formation of urban neighbourhoods where residents believe in values distant from those dominant in society. Or, at least, this is what the Danish government beliefs when they discuss their politics about parallel societies. This simulation is set to understand (a) whether these alternative values areas form and what determines their formation, (b) if they are linked to low or no income residents, and (c) what happens if they disappear from the map. All these three points are part of the Danish government policy. This agent-based model is set to understand the boundaries and effects of this policy.

An economic agent-based model of Coupled Housing and Land Markets (CHALMS) simulates the location choices, insurance purchasing decisions, and risk perceptions of coastal residents, and how coastal risks are capitalized (or not) into coastal housing and land markets.

RHEA aims to provide a methodological platform to simulate the aggregated impact of households’ residential location choice and dynamic risk perceptions in response to flooding on urban land markets. It integrates adaptive behaviour into the spatial landscape using behavioural theories and empirical data sources. The platform can be used to assess: how changes in households’ preferences or risk perceptions capitalize in property values, how price dynamics in the housing market affect spatial demographics in hazard-prone urban areas, how structural non-marginal shifts in land markets emerge from the bottom up, and how economic land use systems react to climate change. RHEA allows direct modelling of interactions of many heterogeneous agents in a land market over a heterogeneous spatial landscape. As other ABMs of markets it helps to understand how aggregated patterns and economic indices result from many individual interactions of economic agents.
The model could be used by scientists to explore the impact of climate change and increased flood risk on urban resilience, and the effect of various behavioural assumptions on the choices that people make in response to flood risk. It can be used by policy-makers to explore the aggregated impact of climate adaptation policies aimed at minimizing flood damages and the social costs of flood risk.

The model represents empirically observed recycling behaviour of Chinese citizens, based on the theory of reasoned action (TRA), the theory of planned behaviour (TPB) and the theory of planned behaviour extended with situational factors (TPB+).

Next generation of the CHALMS model applied to a coastal setting to investigate the effects of subjective risk perception and salience decision-making on adaptive behavior by residents.

Endogenous Dynamics of Housing Market Cycles

Birnur Özbaş Onur Özgün Yaman Barlas | Published Monday, September 09, 2013 | Last modified Wednesday, January 08, 2014

The purpose of this model is to analyze the dynamics of endogenously created oscillations in housing prices using a system dynamics simulation model, built from the perspective of construction companies.

Coupled Housing and Land Markets (CHALMS)

Nicholas Magliocca Virginia Mcconnell Margaret Walls | Published Friday, November 02, 2012 | Last modified Monday, October 27, 2014

CHALMS simulates housing and land market interactions between housing consumers, developers, and farmers in a growing ex-urban area.

Income and Expenditure

Tony Lawson | Published Thursday, October 06, 2011 | Last modified Saturday, April 27, 2013

How do households alter their spending patterns when they experience changes in income? This model answers this question using a random assignment scheme where spending patterns are copied from a household in the new income bracket.

ABODE - Agent Based Model of Origin Destination Estimation

D Levinson | Published Monday, August 29, 2011 | Last modified Saturday, April 27, 2013

The agent based model matches origins and destinations using employment search methods at the individual level.

Displaying 10 of 21 results Housing clear filters

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