Natural and Environmental Amenities: A Review of Definitions, Measures and Issues

Schaeffer, Yves; Dissart, Jean-Christophe

doi:10.1016/j.ecolecon.2017.12.001

Cited by 28 publications

(24 citation statements)

References 45 publications

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“…Based on research from various sciences, they claim that urban rivers, streams and riverine environs are "the most influential natural components and defining features of many cities." This is also to some extent confirmed in the meta-analysis of Schaeffer and Dissart (2018) in the sense that they find that water-related indicators are present in a large proportion of the reviewed papers. Chen et al (2019) identify two main research lines.…”

Section: Studies Of Individual Amenitiessupporting

confidence: 59%

“…Second, their impacts are local and subjective in nature, and also mainly important for people in contrast to firms. Moreover, Schaeffer and Dissart (2018) identify 16 classes of environmental amenities. Our paper includes amenities, which could belong to six of these classes, depending on how they are mutually defined.…”

Section: Environmental Amenities Some General Aspectsmentioning

confidence: 99%

“…However, our definition is also broader than that. In line with recent research, we also include more urban public-type of service facilities in our definition (Schaeffer & Dissart, 2018). Hence, we define environmental amenities as perceived local place-based attributes to be included in consumers' utility functions and in the production functions of suppliers.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, we define environmental amenities as perceived local place-based attributes to be included in consumers' utility functions and in the production functions of suppliers. According to Schaeffer and Dissart (2018), this definition is typical for the economic literature.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

House price valuation of environmental amenities: An application of GIS‐derived data

Osland

Östh

Nordvik

2022

Regional Science Policy & Practice

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Hedonic house price models are frequently used to improve our understanding of local housing markets. In recent years, rich registers containing details about home-qualities and neighbourhood characteristics have successfully been coupled with spatial qualities such as job-accessibility or distances to transport. Additional data sources provided by Open data communities, NGOs, data created by governmental agencies on regional national and international level has the potential of being very useful for analysing housing prices. However, the recent methodological advances in GIS and spatial analysis have not been extensively applied. We expand the hedonic price modelling toolbox with geo-coded free data on environmental amenities. We specifically include local measures describing the view-shed, and more varied specifications of access or dominance of green and blue amenities, in addition to urban public-type service and sport facilities. The GIS-derived data is used to study how the variables should be specified and to study their ability to improve even well specified hedonic price models. To our knowledge, this paper is the first to combine all the listed environmental properties in a hedonic model, and at the same time controlling for a large number of other important local neighbourhood characteristics.

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Section: Studies Of Individual Amenitiessupporting

confidence: 59%

Section: Environmental Amenities Some General Aspectsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

House price valuation of environmental amenities: An application of GIS‐derived data

Osland

Östh

Nordvik

2022

Regional Science Policy & Practice

View full text Add to dashboard Cite

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“…Willingness-to-pay (WTP) is another method to examine and compare alternatives. WTP calculations are conditional on the behavioral framework used and have been frequently used to determine valuation of environmental amenities [e.g., ( 68 )], food attributes [e.g., ( 69 )], and reductions in risk [e.g., ( 70 )]. Under the RUM framework in Equation 1 where all the non-cost and cost attributes enter the utility function, WTP estimates can be estimated as:

where t represents any non-cost attribute and c is the cost attribute.…”

Section: Resultsmentioning

confidence: 99%

Consumer Reactions to E. Coli and Antibiotic Residue Recalls: Utility Maximization vs. Regret Minimization

Dennis¹,

Ajewole²,

Bergtold³

et al. 2020

Front. Vet. Sci.

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Food safety remains a major issue to many consumers. Previous studies examining the economic impact of food safety recalls have focused on Class I recalls. Antibiotic residue in meat products, a Class II recall, has increased in consumer importance yet little is known about how much research and development expenditure should be allocated to reduce antibiotic residue pre-and post-harvest. This study compares demand elasticities and the decrease in willingness to pay in response to either an E. coli (Class I) or antibiotic residue (Class II) recall. We compare and contrast two competing behavioral frameworks, Random Utility and Regret Minimizing. Modeling behavior using the random regret framework is found to be more powerful for assessing consumer responses. In addition, we explore if different groups of consumers exist that either maximize utility or minimize regret. Consumer devaluations of E. coli (Class I) are 40-65% larger than antibiotic residue (Class II). Approximately 60% of consumers are identified as regret minimizers and 40% were identified as utility maximizers. While industry response and government policy recommendations differed conditional on modeling framework, the regret minimizing framework required smaller price discounts than regret minimizing to maintain the same level of market share.

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Multidimensional assessment of regional inequality toward sustainable development

Yang

Zhu

et al. 2023

Sustainable Development

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Considering various challenges and complexity in sustainable development, there is a need to enhance our understanding of the multidimensionality of spatial inequality (SI). This study proposed a multidimensional equality development index and empirically examined this using a case study of China. The dominant mode of SI has gradually changed from coastal–inland inequality to core–marginal inequality. The five dimensions of SI—economic vitality, innovation capacity, green growth capacity, social amenities, and inclusion and natural amenity—are correlated, and inequality in innovation capacity and economic vitality are major contributors to overall SI in China. A catching‐up effect in development exists across cities. The multidimensional inequalities are rooted in a geographical context and related to size, leading to differentiated evolutionary paths and trends. The proposed multidimensional assessment framework can be applied to other countries to reveal the complexity of inequality and enable the identification and management of barriers.

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Natural and Environmental Amenities: A Review of Definitions, Measures and Issues

Cited by 28 publications

References 45 publications

House price valuation of environmental amenities: An application of GIS‐derived data

House price valuation of environmental amenities: An application of GIS‐derived data

Consumer Reactions to E. Coli and Antibiotic Residue Recalls: Utility Maximization vs. Regret Minimization

Multidimensional assessment of regional inequality toward sustainable development

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