2019
DOI: 10.1016/j.ufug.2019.04.004
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A hedonic pricing method to estimate the value of waterfronts in the Gulf of Mexico

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Cited by 42 publications
(32 citation statements)
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“…They usually focus on coastal erosion, beaches, and their impacts on recreation and tourism [58][59][60][61][62]. For instance, coastal residents in Mexico placed their importance on proximity to waterfronts as one of the attributes when deciding a settlement and higher prices were paid for houses located near most waterfront types [63]. The results in the ML model (Table 5) estimated the WTP of coastal forest per 100 m to be JPY 695, with positive attitudes of nearly 60%; however, enlarging coastal forests may cause an overlap with residences in some locations.…”
Section: Discussionmentioning
confidence: 99%
“…They usually focus on coastal erosion, beaches, and their impacts on recreation and tourism [58][59][60][61][62]. For instance, coastal residents in Mexico placed their importance on proximity to waterfronts as one of the attributes when deciding a settlement and higher prices were paid for houses located near most waterfront types [63]. The results in the ML model (Table 5) estimated the WTP of coastal forest per 100 m to be JPY 695, with positive attitudes of nearly 60%; however, enlarging coastal forests may cause an overlap with residences in some locations.…”
Section: Discussionmentioning
confidence: 99%
“…Finally, exploring the wider socio-economic, and sometimes unintended, consequences of improving and managing freshwater blue spaces is of high importance. For example, access to water tends to increase house prices (Dahal et al, 2019) and consequently, increasing access to freshwater blue space may induce gentrification and the displacement of residents (Vert et al, 2019). The use of public participation geographic information systems (PPGIS) may be particularly useful in remediating these unintended consequences and developing inclusive freshwater blue-health strategies that can cater to the needs of a number of different water-users (Raymond et al, 2016).…”
Section: Promoting Freshwater Blue-health Opportunitiesmentioning
confidence: 99%
“…As well, Laszkiewicz et al (2019) analyzed the apartment market in Lodz (Poland) and pointed out that proximity to parks and forests exert a positive impact on apartment prices, whereas Fernandez and Bucaram (2019) highlighted for Auckland, New Zealand that beaches and volcanic parks may add price premiums or price discounts, depending on the price distribution. In the same vein, Dahal et al (2019) confirmed for real estate sales for the coastal Alabama, USA, that vicinity to bays, streams, and rivers is positively valued by inhabitants. Nevertheless, Liang et al (2018) argued that lakes should show a certain size or quality in order to reveal a positive impact on housing prices.…”
Section: Previous Literature Concerning Landscape Features and Housinmentioning
confidence: 70%
“…1. Hence we consider the sale price of the apartment, alongside several structural attributes similar to previous papers such as number of rooms (Keskin, 2008;Czembrowski and Kronenberg, 2016;Ligus andPeternek, 2016 Selim, 2009;Baranzini and Schaerer, 2011), house surface (Wilhelmsson, 2002;Jim and Chen, 2009;Selim, 2009;Chen and Jim, 2010;Hui et al, 2012;Ibeas et al, 2012;Efthymiou and Antoniou, 2013;Ooi et al, 2014;Zhang and Leonard, 2014;Kim et al, 2015;Czembrowski and Kronenberg, 2016;Ligus and Peternek, 2016;Tian et al, 2017;Wu et al, 2017;Brecard et al, 2018;McCord et al, 2018;Yuan et al, 2018;Dahal et al, 2019;Laszkiewicz et al, 2019;Yang et al, 2019), comfort, floor level (Keskin, 2008;Jim and Chen, 2009;Chen and Jim, 2010;Baranzini and Schaerer, 2011;Hui et al, 2012;Ibeas et al, 2012;Efthymiou and Antoniou, 2013;Ooi et al, 2014;Ligus and Peternek, 2016;Wu et al, 2017;Li et al, 2019), number of bathrooms (Conroy and Milosch, 2011;Ibeas et al, 2012;Larsen and Blair, 2014;Zhang and Leonard, 2014;…”
Section: Sample and Variablesmentioning
confidence: 99%
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