Identification Of Abnormal Fluctuation In Urban Housing Prices And The Influencing Factors

Controlling house price fluctuations in a reasonable range is necessary to defend the bottom line of regional and systemic financial risks,and it is also a major challenge for the Chinese government in the economic field.China's real estate industry has reached a critical period for maintaining price stability.The key concern is no longer proving whether a bubble exists or how large the bubble is,but rather how to prevent abnormal fluctuations in house prices.Therefore,it is particularly important to accurately identify abnormal fluctuations in house prices and to effectively control them.However,little research has examined what drives abnormal fluctuations in urban housing prices.Studies that have done so have primarily employed synthetic index systems of influencing factors,which are subjective and one-sided.Based on the above realistic needs and theoretical background,this paper defines the abnormal fluctuations in housing prices,and clarifies the difference between abnormal price fluctuations,price fluctuations,and housing price bubbles.Subsequently,on the basis of extensive reading of the literature,the method of identifying abnormal fluctuations in house prices is summarized as peak-valley detection trigonometry,dynamic mean-line migration method and recursive HP filtering method.At the same time,based on the 35 large-and medium-sized cities' quarterly data from 2005 to 2017,this study analyzes the overall,individual,and spatial characteristics of abnormal housing price fluctuations in new residential buildings and second-hand residential.Finally,the nonparametric test and MNL model are employed to analyze the influencing factors.The findings are as follows:(1)The abnormal rise in urban housing prices was mainly concentrated in 2009,2013,and 2016;the period of abnormal decline was concentrated in 2008,2011,and 2014,and there was a close relationship between these periods.(2)The results of spectral clustering revealed that house price fluctuations between cities are transmitted from the first category to the third category and have a step-by-step weakening effect.(3)Increases in credit growth rate,household income,and commercial residential sales area increase the probability of a peak in housing prices;by contrast,increases in real estate investment and supply of homesteads are the key factors leading to an increased probability of falling house prices.