Abstract
In the paradigm of the search theory, we established the search model applicable to the characteristics of China's resale housing market, by modeling the search behavior for buyer and seller, respectively. Setting the parameters based on the Beijing housing market survey in August 2012, we implemented agent-based simulation to study the dynamics of the search behavior measured by search intensity and search time. Sensitivity test was also used to analyze the determinants of the search behavior for trading agents. The simulation results validate the idiosyncratic feature of the agent's search behavior, which is consistent with theoretical analysis. The increase of matching efficiency promotes the agents' search intensities, but the higher unit search cost can reduce the agents' search intensities. The buyer's search behavior is more sensitive to the change in the market tightness ratio. Brokerage service lowers the transaction price and lessens the agents' search intensities. Sensitivity test further reveals that, the matching efficiency and the market tightness ratio play very important role in improving housing market liquidity. The changes in the search cost and the broker commission rate can reduce the agents' search intensities significantly and there are critical turning points at which the abrupt change occurs.
Highlights
1.1 Housing market is a typical market with trading frictions
Thinking, at the constant unit search cost, when the search intensities of trading participants are promoted in the resale housing market, the number of successful matches and the total search costs will increase, the economic phenomenon will emerge on the macro level, such as the overshooting of housing price and trading volume, or the fluctuations of the market liquidity measured by the average time to sell for vacant houses
5.1 In this article, we build a theoretical search model applicable to the characteristics of China's housing market by modeling the behavioral functions of sellers and buyers, and simulate the agents' search behaviors on NetLogo based on the survey data of resale housing market in Beijing
Summary
1.1 Housing market is a typical market with trading frictions. Within a certain period, considerable vacant houses and home buyers co-exist as unmatched at the same time, so the housing market is inconsistent with the condition of market clearance. With the application of the theoretical model, we use the survey data of China's housing market to set the model parameters, and simulate the dynamic process of the agent's search behavior and its influencing factors. Compared with the past research, this article makes substantial contributions as follows: 1) by addressing the characteristics of China's resale housing market, this article is the first to investigate the micro-level behavior of the housing market participants in the context of a transitional economy; 2) by introducing the intermediary brokerage service commonly seen in China's resale housing market, we attempt to build a theoretical search model with the joint participation of buyers, sellers and brokers; 3) by applying the multi-agent technique, we simulate the search behavior of trading http://jasss.soc.surrey.ac.uk/17/1/18.html. 16/10/2015 agents, and conduct the sensitivity analysis for its determinants based on the micro data obtained from the housing market survey
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