This research first took root in the Information and Communication Technologies (ICT) in Urban Planning PhD course led by Prof. Dr Kerem Koramaz. Exploring his collaborative research with Prof. Dr Elif Alkay on land and house price variances in Istanbul prompted me to consider how these spatial patterns might be viewed through the lens of rent-gap theory. Alkay and Koramaz (2010) used Geographically Weighted Regression (GWR) in Geographical Information Systems (GIS) to investigate whether land prices contribute to the variance in house prices in Istanbul. While Prof. Dr Koramaz was showing us the maps they have produced, I raised a question to him, like, "We can conduct an analysis by using Neil Smith's the rent-gap theory to explore the urban regeneration pattern of Istanbul from investors' perspective."

Now, when I talk about an 'investor’s perspective', I’m looking at the stark gap between what urban regeneration should be and what it has actually become. In an ideal world, urban regeneration serves as a vital strategic tool to mitigate natural disaster risks and upgrade ageing infrastructure in vulnerable regions like Istanbul. However, regeneration areas in Istanbul are determined according to the profitability of developers rather than physical necessity. Instead of prioritising neighbourhoods with the highest structural risk, developers naturally gravitate towards areas where the gap between current housing prices and potential land value offers the fattest returns.

Here, Neil Smith's (1979) rent-gap theory explains the same. He wrote that "the rent gap is the disparity between the potential ground rent level and the actual ground rent capitalised under the present land use" (Smith, 1979). Although Smith (1979) used rent-gap to explain the gentrification process, the framework is equally instrumental in understanding urban regeneration as a process primarily driven by the movement of capital rather than the needs of the community. Developers start urban regeneration initiatives when a situation arises where they can buy houses at the lowest price and maximise their profits; that is, the rent gap is maximised. If I rewrite by using Smith's terms, it can be said that if the land price curve (potential land value) exceeds the house price curve (exaggerated actual land value) at any point, it signifies the presence of a rent gap. This creates a stark spatial disparity. Whilst high-value districts undergo rapid redevelopment, residents in lower-value, high-risk settlements are often overlooked. It appears that under free-market conditions, investment potential frequently takes precedence over urban resilience.

Objectives and Methodology: Decoding the Urban Fabric

This research aims to model Istanbul’s urban regeneration patterns at the neighbourhood level to identify areas where socioeconomic shifts might occur unexpectedly. To achieve this, I utilised a quantitative approach, comparing two distinct spatial methodologies: the rent-gap ratio and GWR analysis. While the rent-gap ratio offers a clear economic 'snapshot', GWR provides the necessary spatial granularity to show where and how these variables interact locally.

To operationalise Neil Smith’s theory within the context of Istanbul, I utilised a specific rent-gap ratio as a primary diagnostic tool. I calculated this ratio by dividing the average housing prices by the land values for each neighbourhood. 

To explain what GWR analysis is, it is essentially a spatial regression technique based on the understanding that the relationship between variables (such as land value and housing prices) can vary significantly from one location to another. Unlike traditional regression models that apply a single average result to the entire city, GWR generates local coefficients for each specific neighbourhood by weighting neighbouring data points based on their distance. This approach allows us to visualise how the influence of land value on housing shifts spatially, providing a far more precise prediction of which areas are truly targeted for transformation.

Both metrics effectively assess the degree to which existing housing stock corresponds to underlying land values. The analytical logic remains consistent; whilst lower rent-gap ratios or standard residuals derived from the GWR model signal imminent urban regeneration due to housing prices failing to meet potential land value, higher figures indicate that property prices are already aligned with land values.

Through the integration of geographic information technology with spatial data on housing prices and land values from March 2024, the study aims to pinpoint exactly where developers operating under free-market conditions find the highest potential for capital accumulation.

Key Findings: Profitability Over Physical Risk

Findings indicate that urban regeneration in Istanbul is predominantly driven by market-driven profitability rather than physical necessity or structural risk. Regeneration is concentrated in neighbourhoods where structurally ageing housing sits on strategically valuable land, typically situated near major transport arteries or central business districts. In these high-potential zones, the rent gap is maximised, as the potential land value significantly surpasses the actual capitalised value of the current property.

Furthermore, nearly all neighbourhoods predicted to undergo rapid regeneration are situated in the immediate vicinity of recently completed or ongoing large-scale investment projects. These flagship developments serve as economic catalysts, artificially inflating potential land rent and signalling profitable reinvestment opportunities for developers. Ultimately, this profit-orientated mechanism results in the rapid regeneration of high-value districts while leaving residents in lower-value, high-risk settlements in precarious conditions.

Methodological Comparison: Whilst both methodologies pointed to the same general locations and sub-regions, they did not identify identical neighbourhoods. Essentially, both analyses highlighted the same locations but at different levels of granularity and spatial detail.

Implications and Future Horizons

These findings highlight the urgent necessity for data-driven spatial governance to ensure that urban regeneration is not entirely surrendered to market forces. By utilising ICT to anticipate these shifts, urban planners can develop proactive strategies to protect disadvantaged groups and mitigate negative socio-economic outcomes, such as exclusionary displacement. Future research could further refine these models by incorporating longitudinal housing price data and official government records to ensure more robust local interventions.

Lastly, I would like to thank you in advance for your comments and further suggestions.

Please note that any data from this study has been intentionally excluded because the research is currently being developed into a formal journal article. I kindly request that the information written here be used ethically and with respect for academic integrity, as this work is still undergoing the publication process.

Cansu Çiçek Aydın(1), Elif Alkay(2), Turgay Kerem Koramaz(3)

About me: I (Cansu CICEK-AYDIN) am both a PhD student and research assistant at Istanbul Technical University (ITU), Department of Urban and Regional Planning. My ongoing PhD research focuses on the drivers behind inconsistencies between Türkiye's housing policy and planning practices in Istanbul and its resulting consequences for the city's physical, social, and economic structures from an institutional economic perspective.

My research interest focuses on housing policy, housing markets and urban regeneration. If you'd like to contact me or discuss more about my research, please email: [email protected]


References

Alkay, E., Koramaz, T.K. (2010). Urban Transformation Measures: Interpolation of Land and House Prices in Istanbul. Proceedings of 14th IPHS Conference Urban Controversies, Transformation: Contrasts and Challenges Conference Volume 2.  International Planning History Society and ITU Urban and Environmental Planning and Research Centre: Istanbul, Turkey. 671 - 706. 

Smith, N. (1979). Toward a Theory of Gentrification A Back to the City Movement by Capital, not People. Journal of the American Planning Association, 45(4), 538-548