2016
DOI: 10.1016/j.regsciurbeco.2016.06.005
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Flood hazards impact on neighborhood house prices: A spatial quantile regression analysis

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Cited by 88 publications
(52 citation statements)
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“…As a useful supplement to OLS regression, quantile regression produces a complete description of the impact across the entire distribution of housing prices and is robust to non-normal random errors [59,60]. This method has been widely used in the field of social sciences and some scholars have recently tried introducing it into the field of real estate [61][62][63][64][65]. For example, Kang and Liu [66] investigated the influence of the 2008 financial crisis on housing prices at different quantiles of the price distribution in Taiwan.…”
Section: Of 23mentioning
confidence: 99%
“…As a useful supplement to OLS regression, quantile regression produces a complete description of the impact across the entire distribution of housing prices and is robust to non-normal random errors [59,60]. This method has been widely used in the field of social sciences and some scholars have recently tried introducing it into the field of real estate [61][62][63][64][65]. For example, Kang and Liu [66] investigated the influence of the 2008 financial crisis on housing prices at different quantiles of the price distribution in Taiwan.…”
Section: Of 23mentioning
confidence: 99%
“…These authors find that internal remittances from long-distance labor migrants is the most important coping mechanism. Zhang (2016) provides evidence that being located on the floodplain has a negative impact on the price of house sales using data for the metropolitan area of Fargo-Moorhead. This study also reports that, following a major flood in 2009, home prices fell temporarily but quickly recovered, but his study does not employ property-level damage estimates.…”
Section: Literaturementioning
confidence: 99%
“…The results confirmed that risk was underestimated before the event and overestimated after the event, which means that houses in high-risk areas were not sold at cheaper prices than others before the earthquake; afterwards, risk awareness increased, causing house-price differentials to widen. Drops in house prices can also be observed right after floods, but they are usually followed by a fast recovery in the following years (Atreya et al 2013, Zhang 2016, indicating that the memory of the flood tends to fade away. Su et al (2015) analysed the difference in risk awareness before and after a rainstorm disaster in Beijing in 2012: public risk perception significantly increased after the disaster, with double the amount of people adopting prevention measures.…”
Section: Introductionmentioning
confidence: 99%