| Trading agents’ behaviors in the housing market have been a frontier topic in thefield of housing micro-economics in recent years. Since the urban housing systemreform in China, the controversy continues one after another over the ever-risinghousing prices, persistently high vacancy rate, successive failure of governmentalinterventions and so forth. In this context, considering the characteristic of tradingfrictions in the housing market, the explorations from the search-matching perspectiveon the trading agents’ behaviors behind the phenomena possess dual significance intheoretical meanings and practical values, which not only facilitate the micro-levelanalysis on the formation mechanism of the macro performance in China’s housingmarket, but also provide the basis for the formulation of housing intervention policies.On the basis of existing studies, the general research framework of the tradingagents’ behaviors in the housing market is proposed, respectively from the patterns ofthe trading agents’ search-matching behaviors, the influence of the search-matchingbehaviors on the housing market transactions, and the effect of the agent-orientedhousing market intervention policy. Within this framework, the dissertation firstlyincorporates the characteristics of China’s housing market, establishes a theoreticalmodel for the search-matching behaviors of buyers and sellers with the assistance of thebroker, and analyzes the trading agents’ behaviors and their influencing factorsquantitatively. Secondly, the multi-agent technology is introduced to define the tradingagents’ behavioral functions of China’s housing market, and the dynamic simulation ofhousing prices, trading volume and liquidity is implemented on the NetLogo platform,which upgrades the micro-level static analysis to the macro-level dynamic simulation.Finally, the search-matching behaviors of trading agents under the home-purchase limitpolicy are modeled, and the simulation is conducted to describe the process that housingprices and rent prices respond to the demand shock under the home-purchase limit.The conclusions include:(1) On the micro level, the trading agents’ behaviorsrepresented by search intensity and search duration are influenced by the marketenvironment, the search cost and the broker commissions to different degrees. Theresponse of the seller to the change in the market environment is not as sensitive as thebuyer, indicating that the seller has lagged responses to the variations in the market environment. The commission levied by the broker if exceeding a certain level could bedetrimental to the benefits of trading agents, and finally squeezes the sellers out of thetransaction.(2) On the macro level, the acceleration of new housing supply can reducethe search duration and direct buyers transfer to the new housing market. Higher searchintensities can increase the trading volumes in resale housing market, but inhibit thenew housing sales, and result in the longer time on market for new houses.(3) In termsof the policy evaluation, the home-purchase limit policy leads to a sharp rise in rents ina short time, and further conducts to the housing price through the rental return insubsequent periods. The housing market liquidity denoted by the time on market showsextraordinary volatility more than housing price and trading volume, but eventuallyreturns to its original equilibrium level.The suggestions include:(1) Fundamentally improving the land supply and themarket information efficiency to speed up the matching process for trading agents andto relax the constraints of the land supply imposed on the housing market.(2) Fasteningthe transition of the mandatory purchase limit policy to market-based housingintervention tools, in order to direct the Chinese households to the rational tenure choice.(3) Utilizing the property taxes, publicized housing information and rent control toincrease the holding costs of vacant houses, so as to improve the position of theinformation disadvantage on the demand side.
|
PDF Full Text Request