Early Warning System Of China's Real Estate Market Research

During the last global financial crisis that originated in the United States, people onceagain realized that the shocks caused by the housing market crisis not only seriously damagedthe entire economy of the United States, the world's biggest economy, but also had impactsall around the world. That is, in today's globalized economy, the serious instability andshocks of a nation's housing market can affect the entire world. Considering that the worldhas not fully recovered from the shocks of the global financial crisis and European fiscalcrisis yet, there is a huge possibility that global economy will face a serious situation that willmake recovery even harder if the housing market in China, which has risen to the secondbiggest economy in the world, falls in danger. That is why so many countries and researchinstitutions are paying attention to the movements of China's housing market. The timedesperately calls for a need to set up an early warning system for the housing marketappropriate for China's situation.In fact, many Chinese scholars have long tried to establish a housing market earlywarning system for China in various ways, but there is no housing market early warningsystem that is universally accepted yet. Many of the previous studies focused on setting up ahousing market early warning system centered around certain regions. Thus this study set outto establish a nationwide housing market early warning system for China with twoapproaches that had not yet been applied to the country, namely the Signal Approach Modeland Probit Model. Based on those two models, the investigator set up a housing market earlywarning system for China by making use of the quarterly macroeconomic indexes and realestate market indexes from the first quarter of1999to the third quarter of2010.The paper consists of a total of six parts: Chapter1is the introduction. Chapter2offers atheoretical consideration of house pricing models and connections between house prices andmacroeconomy. Chapter3examined relations between house prices and macro-and micro-economic factors with the Correlation Test and Granger Causality Test. Chapter4analyzedrelations and trends of mutual influence among China's three major house pricing indexeswith Granger Causality Test and VECM Model's impulse response analysis and variancedecomposition. Chapter5investigatedthe factors affecting house prices in macroeconomic factors and real estate market factorsseparately with VAR analysis and compared the results. Finally, Chapter6set up a housingmarket early warning system for China with the Signal Approach Model and Probit Model based on the results from the previous chapters, as well as tested its predictability.Unlike most of the previous studies that were carried out in sample forecast tests to testpredictability rather than out of sample forecast tests, the study divided Chapter6into twosections: Section1set up a housing market early warning system proper for the uniquesituations of China with the Signal Approach Model and Probit Model, compared it with thepast risk sections of China's housing market, and tested the system's predictability andresponsiveness to the old risks. In a word, Section1conducted an in sample forecast test.Section2conducted an out of sample forecast test with the established housing market earlywarning system.The results of the in sample forecast test show that the Signal Approach Model-based housingmarket early warning system recorded93%accuracy in predicting a risk one year prior torisk occurrence and that the Probit Model-based housing market early warning systemrecorded88.3%accuracy in predicting a risk one year prior to risk occurrence. The results ofthe out of sample forecast test reveal that the Signal Approach Model-based housing marketearly warning system recorded90%accuracy in predicting a risk one year prior to riskoccurrence and that the Probit Model-based housing market early warning system recorded80%accuracy in predicting a risk one year prior to risk occurrence.It is inevitable that the data and information used to set up a housing market earlywarning system had limitations, given that China's housing market has a short history andlimits to usable data. Thus it is difficult to say that the housing market early warning systemestablished in the study will record as high accuracy as the study in predicting other futurerisks. It is required to make ongoing observations of changes to the housing market,determine a leading composite index of housing market early warning systems according tochanges, and make proper adjustments to the threshold and weight.Since there was no logical deficiency or artificial manipulation in the methods andprocesses of setting up a housing market early warning system and testing its predictability inthe study, the housing market early warning system will be able to serve valid and meaningfulpurposes as a nationwide housing market early warning system in China and provide theChinese government with rational and scientific grounds for deciding a housing market policy.