Technological support system for macro-control of Shenzhen real estate market

Abstract

Real estate industry is one of the pillar industries in China. The healthy development of real estate industry plays an important role in economic growth, the adjustment of industrial structure, and the improvement of people's living level. With the continuous marketization and normalization of China real estate market (REM), the market mechanism has played an important role in the market regulation, but macro-control by the government is still an essential measure for the real estate market. How to improve the macro-control level and to make the macro-control policies and means effective but not to violate the market rule, are the important issues faced by the government in order to keep the real estate industry health development. This research taking Shenzhen real estate market as the example, constructs a synthetic technological support system including real estate warning systems (REWS), real estate confidence index systems (RECIS), and system simulation and policies experiment (SS&PE) for Shenzhen real estate market macro-control. Based on the domestic and overseas status of relevant research, this dissertation analyzes the mechanism, purposes, meanings and functions of constructing a technological support system for the real estate macro-control, and presents the contents and methods of establishing it. The focuses of the research are on real estate warning systems (REWS), real estate confidence index systems (RECIS), and system simulation and policies experiment (SS&PE). For the REWS, first of all, the research analyzes its effect on the technological support system for macro-control of REM and selects appropriate warning methods according to the characteristics of real estate industry. Then the warning situation is defined and warning factors are determined by considering the real situation of Shenzhen REM. And then it presents the criteria, procedure and methods to select indicators reflecting warning signs, and selects 9 indicators. For these indicators, their warning limits are determined based upon relevant methods and at the same time the methods adjusting warning accumulation are shown. After that, the methods of warning analysis are probed into, based on which the warning analysis of single indicator and composite indicator is done. Finally, the expression and analysis of warning signals are researched and relative questions needed paying attention to are put forward. With regard to the RECIS, at first its influence on the technological support system for macro-control of REM is discussed and key techniques of constructing the system are brought forward. Then through questionnaires investigation, the research discusses how to establish monomial indexes and composite index, which reflect efficient demand and supply (D&S), latent demand and latent supply, via adopting factor analysis methods, SPSS software, TRECI&BRE methods and index simulation methods. Thereby, a four-level RECIS is established, viz. a composite index, monomial indexes, sub-indexes and basic indexes, its functions are analyzed, and relevant models are founded by using weighted average methods, ratio methods, etc. At one time, the weight coefficients of indexes are determined with Delphi method. Otherwise, the predictive analysis of indexes at all levels is presented. Concerning the system simulation and policy experiments (SS&PE) of real estate, the first one is that its significance is analyzed. Then the dissertation constructs the theoretical model of system simulation and the conceptual model of system simulation of Shenzhen real estate, divides residential housing systems into four modules, namely land for housing, housing demand, housing supply, and housing price and presents the main DYNAMO equations for each of modules, in which relevant calculation and parameters are determined. According as these modules, an example is take and relevant results are analyzed. Based upon the model of system simulation constructed, the research makes some experiments on relative real estate policies and analyzes the approach for study on policies. In the end, based on the investigation and collection data for Shenzhen REM, an application of the technology support system for macro-control is done via adopt the relative models. The performance of the system is analyzed and measured, which ensures the practicability and effectiveness of the system for the macro-control of REM.