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Study examines disaster impact on property values in Malaysia, indicating how hazard proximity and media coverage affect valuation.
Purpose This study investigates the impact of environmental disasters on residential property values, focusing on the Putra Heights gas pipeline explosion and the Sungai Kim Kim River industrial waste pollution in Malaysia. It aims to develop and test a spatially explicit valuation framework that captures both tangible and perception-driven effects, enabling more accurate post-disaster property assessments. Design/methodology/approach An extended hedonic pricing model, integrated with spatial econometric techniques – the spatial lag model (SLM) and spatial error model (SEM) – was applied to property transaction data before and after the disasters. Variables included structural and locational characteristics as well as disaster-specific factors such as hazard proximity, insurance accessibility, public perception indices and media coverage intensity. Geographic Information Systems (GIS) were used to quantify spatial spillover effects. Findings Environmental disasters caused both direct and indirect devaluation of properties, with average losses per property ranging from RM 13,500 to RM 60,500, and total market losses in high-impact zones reaching RM 12–18 m. Spillover effects extended up to 800 m from hazard sites. Elevation and structural resilience attracted value premiums, while proximity to hazards, constrained insurance access and negative media coverage contributed to persistent value suppression. Buyer preferences shifted towards safer, more resilient housing designs. Originality/value By integrating spatial econometric modelling with perception-based variables such as media coverage intensity, this research extends conventional valuation models. It bridges international valuation standards with Malaysian market conditions, offering practical tools for valuers, policymakers, insurers and developers to improve risk-adjusted pricing, compensation and recovery planning in disaster-prone property markets.
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Razali et al. (2025) studied this question.
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