Research On Influencing Factors Of Second-Hand Housing Prices

As the second home market continues to expand,more and more residents are choosing second homes as their first home purchase.As a result,the operation of the second home market and its development pattern will have a great impact on China’s real estate industry in the years and decades to come.There are numerous factors that affect the price of second homes,including the price of commercial properties,the environment of the neighbourhood,the location,the supporting facilities and policies.Taking the city of Hefei as an example,although there is still a big gap between Hefei and traditional first-tier cities such as Beijing and Shanghai in various aspects at this stage,as a new first-tier city,it is important to explore the trend of the development of the second-hand property market in Hefei,which is of great practical significance to the development of the second-hand property market in Hefei and other new first-tier cities.Firstly,the transaction data of the second-hand property prices in Hefei city in the past five years were obtained from the Chain Home website through crawler data collection,which included 34 micro variables such as the floor area of the house,the decoration situation,the property service and the environmental facilities of the district,followed by the combination of latitude and longitude using Baidu map to obtain the data of the surrounding supporting information of each property.Then the macro-influencing factors that affect the price of second-hand properties were filtered through the literature of previous years.The macro influencing factors were urbanisation rate,real estate investment amount,GDP per capita,regional GDP,urban disposable income per capita and urban consumer price index.Considering that the micro data are continuous monthly data and the macro data are annual data for the past 5 years,different models were developed for the macro and micro data to study the factors affecting the prices of second-hand properties.After cleaning and processing the collected data,the influencing factors were screened using the embedding method,wraparound selection method and grey correlation analysis to determine the final30 micro variables that entered the model.Using the micro-data set to build the characteristic price model,the logit model was first determined to have the highest explanatory power for the characteristic price influencing factors of second-hand properties in Hefei City through significance testing and goodness-of-fit judgement.Using Hefei city as the research sample,the overall data sample was explored in addition to the influence of the overall data sample on the price of second-hand properties.The overall Hefei city was further divided into two categorical samples,A and B,based on the division of GDP and per capita disposable income of each district in Hefei city,to explore the differences between the overall influencing factors and the influencing factors of the categorical samples.Finally,a random forest model was constructed to explore the influence of macro-influencing factors on second-hand property prices.Based on two regressions of the characteristic price model,the differences in the influencing factors on the prices of second-hand properties in Hefei for the overall sample and the categorical sample(Zone A and Zone B)respectively yielded that the influencing factors of whether the neighborhood is equipped with an underground had the most significant effect on the overall sample and the Zone A sample,and the floor area of secondhand properties had the most significant effect on the Zone B sample.The economic significance of building area,equipped lift,property price,number of bedrooms,decoration condition and amenities is stronger for the overall sample and the sample from Area A,and the effect on the model is not significant for the sample from Area B.In the analysis of the degree of influence of macro factors on second home prices under the random forest model,it was found that under the year-on-year growth rate of the urban consumer price index was the most influential macro influence on the second home price transaction index.By comparing the results of existing studies,it can be seen that each characteristic has a different impact on second home prices at different time stages.The findings of this paper suggest that at this stage,the government can focus primarily on consumer income and investment when regulating house prices,while home buyers can take into account factors such as floor area and surrounding transport facilities when evaluating the price of their chosen home.Figure [10] table [18] reference [79]...