This study provides the first systematic analysis of the relationship between population aging and housing demand in an Iranian intermediate city (Shahin Shahr). This study aims to quantitatively model how demographic factors influence demand and to forecast the housing shortage through 2037. The main goal is to address the important issue of how to reduce the mismatch between housing supply and demand for the elderly in high-migration cities. Ultimately, this research intends to suggest practical, localized policy solutions to promote a more equitable urban future.
This study uses a quantitative-analytical approach, using Spectrum software (version 6.1) to project the future population of Shahin Shahr until 2037. Data were gathered from official sources, including population and housing censuses, health network records and municipal statistical yearbooks. After validating the demographic model with an acceptable margin of error of 2.1%, an exponential growth model was used to convert population estimates into household projections and assess housing demand. The statistical significance of the population aging trend was confirmed through a proportions test (p < 0.001).
This study forecasts Shahin Shahr’s population will grow from 202,163 in 2022 to 311,882 in 2037, with a total fertility rate (TFR) of 1.3. The share of elderly residents (65+) increases from 9.13% to 11.63% (p < 0.001), driven by declining fertility (1.1 in 2023), decreasing household size (to 2.91), rising life expectancy and migration (accounting for 78% of growth). Housing demand rises sharply, creating a cumulative shortage of 81,040 units by 2037, with an annual deficit of 2,114 units, amid 666% increase in housing prices. Persistent mismatch between supply and demand favors larger units (>100 m²) over smaller, senior-friendly options, worsening spatial exclusion.
Limitations: This study relies on secondary data, which restricts a deeper understanding of the elderly’s personal preferences and subjective needs. In addition, the predictive models used are vulnerable to unforeseen economic or political shocks. Implications: The findings highlight the structural inefficiencies of the housing market and emphasize the need for targeted interventions. A five-pillar policy framework has been proposed to encourage spatial justice and sustainable development. This research offers a model for new cities in the Global South, focusing on socioeconomic and design-oriented approaches.
This study presents an integrated analytical framework to address the elderly housing crisis by combining theories of spatial justice (Fainstein, 2010), the right to the city (Lefebvre, 1991), the age-friendly city (WHO, 2007) and the life-cycle approach (Li and Zhao, 2011). Its dual-layer model examines both structural causes – such as housing commodification and land speculation – and human impacts, including spatial discrimination. The study proposes policies like land value taxation (LVT), strategic land distribution, preferential loans for small housing units (<75 m²), accessibility improvements and the formation of local councils. This model offers a transferable solution for medium-sized cities in developing countries.
The housing crisis in Shahin Shahr has caused spatial discrimination and excluded the elderly from adequate housing, leading to increased domestic risks such as falls and health threats. Rising intergenerational inequality has pushed younger people out of the housing market, increasing their reliance on parental support – causing delayed marriages, lower fertility rates and greater economic dependence. This trend has divided society into “insiders” and “outsiders,” deepening the social isolation of the elderly and undermining both the right to the city and spatial justice. Without action, these social inequalities are likely to continue.
By presenting an integrated analytical framework, this study offers the first systematic analysis of the relationship between population aging and housing demand in medium-sized Iranian cities. By combining Marxist, Georgist and spatial justice theories, it addresses spatial, methodological and theoretical gaps within Iranian scholarship. Focusing on Shahin Shahr as a natural laboratory, the study provides transferable insights for developing cities. Quantitative modeling using the Spectrum software, along with the proposal of a practical policy package – such as LVT – enhances its applied relevance and offers equity-focused and sustainable solutions to the elderly housing crisis.
