Economic Computation and Economic Cybernetics Studies and Research, cilt.57, sa.2, ss.235-252, 2023 (SCI-Expanded)
In this study, sociodemographic factors affecting the homeownership were investigated using data from the 2017 Household Budget Survey conducted by the TURKSTAT. To logistic regression analysis, it was confirmed that sociodemographic variables such as gender, age, household type, annual disposable income, household size, education level, marital status, employment status and activity status have an impact on homeownership. As a distinction from the literature, canonical correlation analysis with optimal scaling was implemented to examine the interactions between the sub-categories related to these variables. When the positions of the variables were examined, the main variables with the highest load value are ownership type, housing type, and income. In addition, the secondarily effective variables with the highest load value are age and education. On the basis of subgroups, it was seen that being a home owner/tenant was correlated with subcategories of age and working status, while preference for housing type was correlated with subcategories of education and household size. The results of sub-categories may provide guidance for future housing projects and policies.