The objective of this study is to contribute to the understanding of price formations in housing markets through an agent-based simulation that conceptualizes insights from behavioral economics. For this purpose,… Click to show full abstract
The objective of this study is to contribute to the understanding of price formations in housing markets through an agent-based simulation that conceptualizes insights from behavioral economics. For this purpose, the study uses a prominent real estate market model as a benchmark and extends it to account for (1) behavioral heterogeneity and (2) dynamic agent interaction. The validation of the model is carried out by using real data from the Turkish housing market. The results show that the introduction of a fitness-based behavior-switching regime with myopic agents improves the extent to which the observed market behavior can be replicated, in comparison to the benchmark model.
Journal Title: Computational Economics
Year Published: 2018
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