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This paper aims to analyze and compare housing tenure and model housing price index (HPI) in Saudi Arabia with selected Organization for Economic Cooperation Development (OECD) countries.

The research uses quantitative data from the Saudi 2022 Statistical Census and OECD sources. Analytical methods include polynomial regression modeling for housing price trends and analysis of variance (ANOVA) to explore the relationship between housing variables, alongside descriptive and inferential statistics.

The polynomial regression analysis reveals distinct HPI trends across the studied countries, indicating stability and growth. Countries like Australia, France and the US are projected to see substantial HPI increases by 2026, reaching values around 175, signaling strong market recovery and growth. Greece’s trajectory is marked by fluctuations, recovering modestly post-2020, while Saudi Arabia’s market shows stability with a slight increase forecasted to 92.8 by 2026. The ANOVA analysis for Saudi Arabia highlights significant regional differences in housing tenure, with economic conditions and housing types significantly impacting tenure patterns.

This study fills a void in research by offering a comparative analysis of housing tenure and HPI, shedding light on how economic and demographic factors influence housing trends. The findings are crucial for policymakers to develop targeted strategies that address affordability and stability, catering to diverse demographic needs.

This study aims to explore and analyze the disparities in the distribution of housing types and characteristics among households in Saudi Arabia, taking into consideration the regional perspective.

This study uses quantitative data obtained from the General Authority for Statistics, specifically from the Saudi 2022 Statistical Census. The data were analyzed using descriptive statistics (percentages) as well as inferential statistics, including correlation analysis (Pearson correlation) and t-tests.

The study found a distinct preference among Saudis for villas, with 85.3% choosing this housing type, while only 14.7% of non-Saudis opted for villas. The statistical analysis confirmed the significance of housing type for Saudi citizens (t = 2.561, p = 0.037), while non-Saudis did not show a statistically significant preference (t = 1.703, p = 0.132). The Pearson correlation results revealed a moderate positive correlation (r = 0.641, p = 0.009) between regional landmass and the number of houses, and a very strong positive relationship (r = 0.984) between population and the number of houses across the 13 regions. As expected, with increasing population, there was a significant increase in the number of houses (p = 0.001).

This study fills a research gap by investigating regional disparities in housing characteristics in Saudi Arabia. The findings are valuable for policymakers, housing developers and the housing market in understanding these disparities. The insights from this research can inform decision-making to promote equitable access to housing types and foster social inclusivity in the housing sector.