The impact of soil-liquefaction information disclosures on housing prices: evidence from Kaohsiung, Taiwan

Abstract

Do housing markets appropriately assess disaster-resistant structures located in high-potential areas following information shocks? This study considers the disclosure of the potential for soil liquefaction released by the Taiwanese government and discusses the effects of the disclosures on housing prices in Kaohsiung. We find that the influence of this disclosure on the house prices in high-potential areas varies, depending on whether the property is in a high-rise building, and on whether the property was designed in compliance with building regulations amended in 1999, the point in time when soil liquefaction potential was prioritized as important elements of housing construction and maintenance. Our findings imply that information disclosure helps properties to be properly assessed on markets.

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Fig. 1

Notes

  1. 1.

    Both parties did not know the risk prior to the date of disclosure, and both can search on the website after disclosure.

  2. 2.

    See the website at: https://lvr.land.moi.gov.tw/homePage.action (in Chinese). Accessed 17 May 2020.

  3. 3.

    Other types of structures in the database include "factory", "store", "warehouse", "farmhouse", "industrial office", "commercial office" and "others".

  4. 4.

    See the website at: https://www.liquid.net.tw/cgs/public/ (in Chinese). Accessed 17 May 2020.

  5. 5.

    In addition to green, yellow, and red tiles, the other tiles are areas without soil liquefaction information in 2016: non-liquefied area or the areas whose information will be released after 2019.

  6. 6.

    See the soil liquefaction prevention website at: https://www.cpami.gov.tw/chinese/index.php?option=com_content&view=article&id=19652&Itemid=53 (in Chinese). Accessed 20 May 2019.

  7. 7.

    In addition to the CPA, the Central Geological Survey (CGS), and the Public Works Bureau (PWB), Kaohsiung City Government emphasized this point. The explanation website operated by CGS is available at: https://www.liquid.net.tw/cgs/public/QA01.html (in Chinese). Accessed 17 May 2020. The PWB’s soil liquefaction website is available at: https://soil.kcg.gov.tw/k62c0316g8269/ (in Chinese). Accessed 17 May 2020.

  8. 8.

    Transaction records from RETD are expressed using the TWD97 coordinate system (commonly applied in Taiwan), whereas soil liquefaction potential maps are expressed in the WGS84 coordinate system. Using the "WGS84_TM2" tool from Academia Sinica GIS Application Kits, we convert TWD97 latitude and longitude to the coordinates from the WGS84 system. The application kits were developed with the financial support from "National Science and Technology for e-learning and Digital Archives Program: Sub Program for Encouraging Humanistic, Social, Economic and Industrial Developments". These application kits are available at: https://gis.rchss.sinica.edu.tw/ISTIS/tools (in Chinese). Accessed 17 May 2020.

  9. 9.

    We applied to the Fiscal Information Agency, Ministry of Finance for the mean and standard deviation of annual taxable income of households in each urban-village.

  10. 10.

    The dengue fever data are collected from "DATA.GOV.TW," and specifically, the daily number of confirmed cases since 1998 is available at: https://data.gov.tw/node/21025 (in Chinese). Accessed 17 May 2020.

  11. 11.

    The population density data for all districts of Kaohsiung City can be found on the website operated by Urban Development Bureau, Kaohsiung City Government at: https://housing.kcg.gov.tw/LFA/ (in Chinese). Accessed 17 May 2020.

  12. 12.

    Macroeconomic variables, such as unemployment rates and interest rates, are not considered in the empirical model. However, macroeconomic conditions or other unobserved month-specific events are addressed by the month fixed effects (Pope 2008b). Moreover, the estimates for the period specific fixed effects in this hedonic model (γ3) can be used to calculate hedonic price indexes (Hill 2011).

  13. 13.

    Moreover, quantile regression can provide estimates not only for the conditional median, but also for other conditional percentiles, such as the 25th percentile or the 75th percentile. We can thereby observe how different points in the distribution of the dependent variable (for instance, high-priced or low-priced properties) respond to changes in the explanatory variables.

  14. 14.

    For the 25th percentile of prices or the 75th percentile of prices, the information disclosure had similar effects (the results are not reported here). Interestingly, the impact on the price difference between properties in high potential areas and those in areas without information is stronger for the 25th percentile of prices than what is found for median prices or the 75th percentile of prices.

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Acknowledgements

This paper has benefited from the detailed comments provided by Chun-Hua Tang and Ming-Chi Chen. Sincere gratitude is also extended to the anonymous referees for helpful suggestions. The usual disclaimer applies.

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Correspondence to Chien-Yuan Sher.

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Sher, CY., Chen, NW., Liu, YH. et al. The impact of soil-liquefaction information disclosures on housing prices: evidence from Kaohsiung, Taiwan. JER 72, 217–241 (2021). https://doi.org/10.1007/s42973-020-00048-6

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JEL Classification

  • R21
  • D82
  • D83