Akademik Veri Yönetim Sistemi
INTERNATIONAL JOURNAL OF HOUSING MARKETS AND ANALYSIS, 2025 (ESCI, Scopus)
Purpose-This study aims to examine the affordability of state-led housing projects in Istanbul, focusing on whether initiatives implemented by Housing Development Administration (TOKI) and its subsidiary Emlak Konut Real Estate Investment Company (EKGYO) effectively meet the housing needs of lower-middle-income households within an increasingly commodified urban market. Design/methodology/approach-Utilizing a five-stage methodological framework, the research integrates geospatial mapping of completed housing projects, district level price-to-income ratio modeling, and land cost sensitivity analysis. Unit prices from 98 state-led developments are benchmarked against local market averages. Affordability is assessed using a standardized 120-month payment model and the widely recognized 30% income to housing cost threshold. A multi-scalar affordability index is developed by combining web-scraped sales data with official statistical sources. The study also incorporates multivariate regression and Random Forest modelling to examine the relative influence of district-level land costs, household income, and private market housing prices on project-level pricing. Findings-The majority of publicly supported housing units in Istanbul are priced above the average market rates in their respective districts, contradicting their intended social function. A strong and statistically significant positive correlation is found between land costs and sales prices in public housing projects, indicating that land value plays a major role in shaping housing affordability. While EKGYO's developments predominantly target higher-income groups, even TOKI's projects fail to offer economic accessibility for their intended lower-middle-income demographics. Only the districts of Tuzla and Silivri meet the defined affordability criteria. To refine the empirical analysis, a multivariate regression revealed that household income is a significant predictor of project pricing, while land costs and market prices showed weaker effects. A Random Forest model confirmed that private market prices exert the strongest influence, followed by income and land value. These results highlight how market forces shape even state-led housing, challenging the assumption that such projects are insulated from speculative pressures. Research limitations/implications-The study is limited to completed housing projects within Istanbul and does not encompass developments currently under construction or those located in other regions of Turkey. In addition, while the research incorporates advanced statistical and machine learning methods, the scope of variables was constrained by the availability of public data sources at the district level. Future research could expand the model to include more granular, neighborhood-level variables and temporal dynamics. Originality/value-This research offers a novel interdisciplinary perspective by integrating spatial, economic, and institutional analyses to assess housing affordability under state intervention. The study employs multivariate regression and machine learning-based Random Forest modeling to systematically evaluate the relative influence of household income, land costs, and market housing prices on the pricing of publicly supported housing units. The findings highlight a structural gap between the stated goals of public housing policies and their implementation in practice, providing evidence-based implications for more effective and equitable housing policy design.