Homeownership affordability: data-driven methodology for effective housing policy

Purpose The purpose of this paper is to contribute to the development of practical housing policy tools by presenting an algorithm that, unlike most existing approaches, enables the evaluation of homeownership affordability gaps across a broader range of household groups and locations. Design/methodology/approach This paper presents the homeownership affordability matrix, which considers age-duration effects and various demographic characteristics, along with house prices and household incomes, within a single algorithm. It considers variations in housing size, matching the needs of different households, corresponding to loan terms, and examines the impact of mortgage duration on the affordability of mortgage payments across various age and income groups. Findings The findings indicate that applying the suggested algorithm facilitates informed policy decisions by helping to identify and target household groups and regions that most need assistance with accessing affordable homeownership. Based on Israeli data, this study reveals that large households and younger populations face ongoing challenges in obtaining mortgage financing and achieving homeownership, with a significant decline in homeownership affordability for various household groups between 2007 and 2017. In high-demand districts, affordability levels worsened for all households. Practical implications This approach provides policymakers with deeper insights and allows for the ex-post evaluation of the effectiveness of implemented policy decisions. Originality/value The proposed methodology offers a greater level of detail than existing approaches to assessing homeownership affordability gaps and can be adapted to various market conditions worldwide.