A spatio-temporal analysis of house prices in Brunei Darussalam

This paper presents the first spatio-temporal analysis of property prices in Brunei Darussalam, a small, resource-rich economy with distinct housing market characteristics. Despite global interest in quantitative housing market analyses, Brunei’s market remains underexplored, with prior studies predominantly qualitative. Addressing this gap, $$N=3763$$ N = 3763 residential transactions from 2015 to 2023 were analysed using Conditional Autoregressive (CAR) priors to model spatial dependencies and temporal trends in house prices accounting for other price determinants. Emerging Hotspot Analysis was then employed to classify price clustering across time. Key findings revealed significant spatial autocorrelation ( $$\rho = 0.43$$ ρ = 0.43 ) and temporal persistence best modeled by an autoregressive structure of order two, indicating that market reactions to changes can extend up to 6 months. The results demonstrate the critical role of spatial and temporal factors in shaping property prices, providing actionable insights for policy interventions and real estate market analysis, particularly in addressing disparities between urban and rural housing markets.