Valuing water resources in Switzerland using a hedonic price model

Abstract

In this paper, linear and spatial hedonic price models are applied to the housing market in Switzerland, covering all 26 cantons in the country over the period 2005-2010. Besides structural house, neighborhood and socioeconomic characteristics, we include a wide variety of new environmental characteristics related to water to examine their role in explaining variation in sales prices. These include water abundance, different types of water bodies, the recreational function of water, and water disamenity. Significant spatial autocorrelation is found in the estimated models, as well as nonlinear effects for distances to the nearest lake and large river. Significant effects are furthermore found for water abundance and the distance to large rivers, but not to small rivers. Although in both linear and spatial models water related variables explain less than 1% of the price variation, the distance to the nearest bathing site has a larger marginal contribution than many neighborhood-related distance variables. The housing market shows to differentiate between different water related resources in terms of relative contribution to house prices, which could help the housing development industry make more geographically targeted planning activities. Key Points:Most variation in house prices is explained by structural house characteristics Significant effects are found for water abundance and the distance to large rivers The distance to the nearest bathing site has the largest marginal contribution

Calculation of Water Resource Value in Nanjing Based on a Fuzzy Mathematical Model

“…The water resource value is a complex and fuzzy system, and the factors that affect it can be broadly divided into 3 categories: quantity of water resources, quality of water resources and socioeconomic factors [12].…”

Determinants of the Price of Housing in the Province of Alicante (Spain): Analysis Using Quantile Regression

“…Smith et al [10] (pp. [34][35][36][37][38][39][40][41] assumed that housing is composed of a series of special characteristics such as: durability, heterogeneity, spatial fixation and government involvement. Sirmans et al [5] analysed one hundred and twenty-five articles that used hedonic models, collecting the variables that are significant to determine the price and its sign, comparing the coefficients by geographic location and examining the relationship between the price of housing and amount of time on the market.…”

“…Dwelling characteristics (A) Dwelling typology [11][12][13][14][15][16][17][18][19][20][21][22][23][24] Age of the dwelling [12,16, Dwelling surface area [11,13,15,16,18,[20][21][22][23][24][26][27][28][29][30][31][33][34][35][36][37][38][39][41][42][43][44][45][46][48][49][50][51][52][53][54]…”

“…Stetler et al [48] analysed the effect of the proximity of dwellings to forest fires in Montana. Other documents focus their attention on the ecological, scenic and entertainment value that housing in proximity to bodies of water has [32,35,47], or analyse how the price of housing is affected by proximity to landfill sites [42], train stops [28] or subway stations [49]. Wen et al [40] analysed how school quality affects the price of housing.…”

Transforming Abandoned Rail Corridors into Multi-purpose Trails: Applying a Spatial Hedonic Approach to Estimating the Economic Benefits of the Little Miami Scenic Trail in Cincinnati, Ohio, USA

“…The list of public goods that potential home buyers take into account when looking for a new home is as long as the list of hedonic studies. Besides structural housing characteristics, hedonic studies usually include neighborhood and locational characteristics, such as the quality of the school district [18,19], the availability of public transportation infrastructure [20,21], and the distances to lakes and/or rivers [22,23]. Other studies include crime [24,25] and the close proximity to brownfields [26,27].…”