The Simulation of Housing price in Tehran: An Spatial Agent Based Approach
The housing sector has always played a crucial role in the economy, with its fluctuations exerting significant effects on various economies. Prior to the 2007 financial crisis, standard models were commonly employed to explain price changes. These models assumed that agents were rational and well-informed, disregarding factors like irrationality and the heterogeneity of individuals that could contribute to such crises. However, agent-based models offer a different perspective, viewing the economy as a complex system with heterogeneous agents possessing limited information, engaging in interactions with each other. As a result, this study aims to evaluate a spatial agent-based model, specifically developed to analyze the housing market in Tehran. The simulation's results over an eleven-year period revealed that the growing demand from young households with limited savings for residential units under 100 square meters significantly drove up the prices of these particular units, outpacing other residential properties. Moreover, the findings indicated the higher growth of housing prices in the central areas of the city, primarily triggered by the influx of young households into these regions, seeking investment opportunities.
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