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Research On Influence Factors And Prediction Of Commodity Residential Market Demand In Wuhan

Posted on:2018-06-09Degree:MasterType:Thesis
Country:ChinaCandidate:B W YangFull Text:PDF
GTID:2439330605953606Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
The transaction volume of commercial housing is running at record levels driven by the strong demand in recent years in Wuhan,and the newly-built commercial housing sales area has achieved first in the country in 2016.The development of Wuhan commercial housing market has a close relation to the social,economic and other factors.Study on the status of Wuhan commercial housing market and the demand forming mechanism,on this basis,forecast the future market demand can make us accurately understand the characteristics of the market and grasp the market changes and development trend.Thus policy advice and reference could be provided to real estate developers,government departments and residents.The article first reviews the related concepts and theories of housing market and housing market demand,summarizes the development process and characteristics of Wuhan commercial housing market from several different aspects.Then the Grey Relational analysis is used to find out the the degree of relevance between Wuhan commercial housing market demand and various factors that affecting the demand and then the multiple linear regression model is built to analyze the main factors influencing the demand.Finally,through the combination of GM(1,1)model and multiple regression model,the commercial housing demand of Wuhan during the 13 th Five-Year Plan period is forecasted.Based on researches above,the article points out that the economic growth,urbanization process and improvement of urban infrastructure have great effect on housing demand of Wuhan,there is a huge potential demand in Wuhan commercial housing market,and the current implementation of the purchase limit credit policy is difficult to fundamentally change the long-term trend of market demand.
Keywords/Search Tags:Commodity housing demand, Grey relational analysis, Multiple Linear regression, GM(1,1) Model, Combination forecasting
PDF Full Text Request
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