Housing Sources of Second‐Tier Urban Residents Based on Multivariate Correspondence

Abstract

To explore the relationship between different housing sources and individual attributes in second-tier cities, finding the key point of contradiction between supply and demand in the real estate market is important. Multivariate correspondence analysis (MCA) is a powerful method to solve the complex problem of the relationship between classified variables. Also known as corresponding analysis, it is a multivariate statistical analysis method that aims to describe the relationship between two classification variables in a corresponding table in a low-dimensional space. MCA has unique advantages when dealing with categorical variable data. It combines the advantages of factor analysis and multidimensional scaling. On the basis of combining and analysing the existing literature, this paper makes an analysis of the data obtained from a housing questionnaire survey collected in Jinan, Shandong Province, in 2017. The research results show that the housing sources of second-tier urban residents are closely related to age, annual family income, marriage, education level, and individual characteristics of the permanent family population but not to gender.