Valuing Urban Landscape Using Subjective Well-Being Data: Empirical Evidence from Dalian, China
Erda Wang (),
Nannan Kang () and
Yang Yu ()
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Erda Wang: Faculty of Management and Economics, Dalian University of Technology, Dalian 116023, China
Nannan Kang: Faculty of Management and Economics, Dalian University of Technology, Dalian 116023, China
Yang Yu: School of Economics and management, Dalian Ocean University, Dalian 116023, China
Sustainability, 2017, vol. 10, issue 1, 1-20
It has been well recognized that the urban landscape ecosystem is able to make a great contribution to the quality of life for people who live in the city and beyond, thus it can potentially accrue a significant economic value to the human well-being. However, due to its public good nature, it is difficult to monetizing its values in a systematic manner. In this paper, we attempt to assess the economic value of the urban landscape through people’s life satisfaction approach utilizing a large sample of dataset complied from the general public survey in Dalian City which is one of the well-known tourism cities in China. The results indicate that most of the urban landscape attributes impose significant effects on people’s life satisfaction, thus accruing a considerable amount of value to the local residents. Taking a 10-point ranking scale for the urban landscape quality as an example, the household willingness to pay on average reaches ¥24,579 per annum for one point of ranking level increase. Relative to the low level of household income, those high-income households are much keener to the changes of the landscape quality. If the urban landscape quality is disaggregated into five levels, household’s marginal willingness-to-pay diminishes as the urban landscape’s rank level is improved.
Keywords: life satisfaction approach; economic valuation; landscape sustainability; human well-being (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:10:y:2017:i:1:p:36-:d:124218
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