Managing housing supply system gap through subsidy optimization: evidence from the Addis Ababa condominium housing program

Addis Ababa’s condominium housing program has long faced allegations of unaffordability for low-income households and fiscal strain due to generous subsidies. Globally, studies on ownership-based subsidized housing often overlook empirical assessments of subsidy targeting and the trade-offs between affordability and fiscal efficiency. This study addresses these gaps by modeling an income-based affordability rule, filling only the portion of the mortgage that exceeds a defined household cost-to-income ratio. The problem was implemented as a multi-objective optimization: maximizing housing consumption welfare of lower-incomes vis-à-vis minimizing total subsidies using Non-Dominated Sorting Genetic Algorithm. Results show that: (i) affordability of all flat challenge the widespread unaffordability claim; (ii) larger flats benefiting disproportionately from the subsidy package while smaller units receive less; (iii) optimal subsidy allocation could increase floor areas for the smaller units by at least 11.3%, balance the affordability threshold across flat types, and reduce total subsidies by 48%. Collectively, the results illustrate that the core challenge of the Addis Ababa condominium housing program, and elsewhere with similar situation, lies in inefficient subsidy targeting rather than absolute unaffordability that signify a gap in the management of the housing supply system instead of the housing policy.