Advancing Agenda 2063 by Improving Mortgage Access in Greater Kampala: A Logistic Regression Analysis of Eligibility and Developer Challenges

Abstract

This study aims to model strategies for improving mortgage financing accessibility in the Greater Kampala Metropolitan Area (GKMA) using logistic regression modelling. By investigating how mortgage eligibility criteria impact the challenges faced by potential mortgagors, the study collected quantitative data through self-administered questionnaires to assess developers’ perspectives on mortgage requirements. The findings reveal that a 2% mortgage processing fee significantly increases the likelihood of securing a mortgage (odds ratio = 2.011). At the same time, the requirement for verifiable income sources decreases the odds (odds ratio = 0.591), with property valuation and income verification showing minimal effects. The model demonstrates a good fit with a chi-square value of 73.317 (p < 0.001) and an AUC of 0.7473 on the ROC curve, indicating reasonable predictive accuracy. This research offers valuable insights into the impact of processing fees and income verification on mortgage access, providing practical guidance for enhancing mortgage accessibility strategies and refining approval criteria. By addressing these challenges, the study contributes to a more inclusive housing finance system that aligns with the broader goals of sustainable development outlined in Africa’s Agenda 2063.