In this paper, we investigate the nexus between urban air pollution and residents’ preferences for greenspace. We first provide a theoretical discussion on three potential mechanisms that link these two environmental issues. To start with, where people choose to locate in a city, as reflected by their exposure to air pollution, may indicate their preferences for greenspace through a residential sorting effect: residents of heavily polluted neighbourhoods may have a lower appreciation of environmental amenities in general, including greenspace. Further, air pollution may have direct implications for the use value of greenspace. On the one hand, people tend to reduce outdoor activities in severe pollution as an avoidance behaviour, which may lead to reduced visits to and hence lower use value of greenspace. On the other hand, residents of severely polluted areas may derive additional benefits from greenspace, as trees are able to enhance air quality. To empirically test these mechanisms, we undertook choice experiment surveys in Beijing to elicit the public’s willingness to pay (WTP) for greenspace. We purposefully valued three types of greenspace: a neighbourhood park near respondents' homes; a city park in central Beijing; and a national park in an outlying location. We use realtime pollution data to help explain the spatial and temporal variation in WTP, whilst controlling for other possible influencing factors. Neighbourhood parks are likely to provide direct air purification services for communities nearby, and our results indeed suggest that respondents exposed to higher levels of annual pollution are willing to pay more for an additional neighbourhood park. In contrast, WTP for the city park and national park is more likely to be linked with pollution levels via the residential sorting and reduced visits mechanisms. Yet our results find no evidence for such connections.
In this article we utilize the time respondents require to answer a self-administered online stated preference survey. While the effects of response time have been previously explored, this article proposes a different approach that explicitly recognizes the highly equivocal relationship between response time and respondents' choices. In particular, we attempt to disentangle preference, variance and processing heterogeneity and explore whether response time helps to explain these three types of heterogeneity. For this, we divide the data (ordered by response time) into approximately equal-sized subsets, and then derive different class membership probabilities for each subset. We estimate a large number of candidate models and subsequently conduct a frequentist-based model averaging approach using information criteria to derive weights of evidence for each model. Our findings show a clear link between response time and utility coefficients, error variance and processing strategies. Our results thus emphasize the importance of considering response time when modeling stated choice data.
Integrated Multi-Trophic Aquaculture (IMTA) has been put forward as a potential sustainable alternative to single fin fish species aquaculture. In IMTA, several species are combined in the production process. Integrating species has a conceivable dual advantage; the environmental impact can be lowered through nutrient cycling and from an economic perspective there is potential for increased efficiency, product diversification and a higher willingness to pay for more environmentally friendly produced salmon. This paper presents the results from a choice experiment which examines whether the Irish public is willing to pay a premium for “sustainably produced” farmed salmon from an IMTA process. Uniquely, an ecolabel was used in the design, based on familiar energy rating labels, to communicate the environmental pressure of fish farming to respondents. The experiment demonstrates that the Irish public has a willingness to pay a price premium for sustainability in salmon farming and for locally produced salmon.