Purpose – This paper seeks to investigate the impact of socioeconomic factors of homebuyers such as gender, age, marital status, education, economic status and race on home ownership and loan decisions in urban China. Design/methodology/approach – This paper employs logistic regression to investigate the socioeconomic factors affecting the consumers' house purchase decision in urban China and the factors affecting the housing loan application. Findings – Using a structured questionnaire to collect relevant data from household residents (both homeowners and non‐home owners) in Nanjing in 2010, the findings document that male respondents who are non‐minorities and have higher levels of education are more likely to purchase a house. The results also show that race, educational attainment, size of household and credit card ownership are significantly related to rejection for a housing loan. Research limitations/implications – The findings in this paper provide homebuyers with a better understanding of factors affecting the housing loans and their decision to purchase a house. Homebuyers can accurately assess their financial ability and improve the use of their credit to purchase a house. In addition, Chinese homebuyers should be encouraged to save since savings serve as a step in building their credit worthiness; therefore, their accessibility to housing loans can be improved and the rate of homeownership will be increased as well. Originality/value – This research would benefit both lender and borrowers. The research findings provide banks with a better understanding of homebuyers' characteristics that influence their accessibilities to housing loans. Homeownership requires affordable housing financing. Banks should consider repackaging their home loan products to make them more attractive to those with limited means. Such products should focus on making loans more affordable in real terms. First‐time homebuyers are almost always young and earn low incomes.
Journal of Asia Business Studies – Emerald Publishing
Published: Dec 20, 2013
Keywords: House price; Loans; Logistic regression; Home ownership