Agent-based joint model of residential location choice and real estate price for land use and transport model
Authored by Chengxiang Zhuge, Chunfu Shao, Jian Gao, Chunjiao Dong, Hui Zhang
Date Published: 2016
DOI: 10.1016/j.compenvurbsys.2016.02.001
Sponsors:
Chinese National Natural Science Foundation
National Basic Research Program of China
Fundamental Research Funds for the Central Universities
Platforms:
MATSim
Model Documentation:
Other Narrative
Flow charts
Mathematical description
Model Code URLs:
Model code not found
Abstract
Residential location choice (RLC) and real estate price (REP) models are
traditional and key components of land use and transport model. In this
study, an agent-based joint model of RLC and REP (RLC-REP model) was
proposed for SelfSim, an agent-based dynamic evolution of land use and
transport model. The RLC-REP model is capable of simulating the
negotiation between the active household agents (buyers) and owner
agents (sellers) using agent-based modeling. In particular, both utility
maximization theory and prospect theory were used to develop a utility
function to simulate the location choice behavior of active household
agents. The utility function incorporates only two variables: house
price and accessibility. The latter variable is calculated using MATSim, an activity-based model. The asking price behavior of owner agents is
based on three specific rules. The residential location choices of
household agents and house prices can be obtained by negotiation.
Finally, genetic algorithm was used to estimate the parameters of the
RLC-REP model. The calibrated model was tested in Baoding, a
medium-sized city in China, and historical validation was performed to
assess its performance. The results suggest that the forecasting ability
of the RLC-REP model in terms of real estate price is satisfactory. (C)
2016 Elsevier Ltd. All rights reserved.
Tags
Simulation
behavior
accessibility
Urban-development
Hybrid genetic algorithm
Property-values
Loss aversion
Parameter-estimation
Metropolitan-area
Kinetic-models