Earthquake Risk Embedded in Property Prices: Evidence From Five Japanese Cities

Abstract

A c c e p t e d M a n u s c r i p tWe analyze the impact of short-run (90 days) and long-run (30 years) earthquake risk on real estate transaction prices in five Japanese cities (Tokyo, Osaka, Nagoya, Fukuoka, and Sapporo), using quarterly data over the period 2006-2015. We exploit a rich panel data set (331,343 observations) with property characteristics, ward attractiveness information, macroeconomic variables, and longrun seismic hazard data, supplemented with short-run earthquake probabilities generated from a seismic excitation model using historical earthquake occurrences. We design a hedonic property price model that allows for subjective probability weighting, employ a multivariate error components structure, and develop associated maximum likelihood estimation and variance computation procedures. Our approach enables us to identify the total compensation for earthquake risk embedded in property prices, to decompose this into pieces stemming from short-run and long-run risk, and to distinguish between objective and subjectively weighted ('distorted') earthquake probabilities. We find that objective long-run earthquake probabilities have a statistically significant negative impact on property prices, whereas short-run earthquake probabilities become statistically significant only when we allow them to be distorted. The total compensation for earthquake risk amounts to an average -2.0% of log property prices, slightly more than the annual income of a middle-income Japanese household.

A multi-level modeling approach for predicting real-estate dynamics

“…Li and Brown used this approach in 1980 to evaluate house prices using neighborhood attributes (Li and Brown, 1980). The hedonic price model was effective in determining the price of a house based on proximity to public transportation (Chen et al , 2022), schools (Huang and Dall’erba, 2021), noise (Tsao and Lu, 2022) and environmental hazards (Ikefuji et al , 2022). A drawback of this approach was its inability to predict short-term and long-term trends in the housing market.…”