Discrete choice experiment

Does attribute order influence attribute-information processing in discrete choice experiments?

The existing empirical evidence shows that both contingent valuation and discrete choice experiment (DCE) methods are susceptible to various ordering effects. However, very few studies have analysed attribute-ordering effects in DCEs, and no study has investigated their potential influence on information-processing strategies, such as attribute non-attendance (ANA). This paper tests for attribute-ordering effects and examines whether the order of attributes describing the alternatives affects respondents’ propensity to attend to or ignore an attribute. A split-sample approach is used, where one sample received a DCE version in which the positions of the first and last non-monetary attributes are switched across the sequence of choice tasks compared with the other sample. The results show that attribute order does not affect welfare estimates in a significant way under the standard assumption of full attribute attendance, thus rejecting the notion of procedural bias. However, the welfare estimates for the attributes whose order was reversed and the share of respondents who ignored them differ significantly between the two attribute-ordering treatments once ANA behaviour is accounted for in the estimated choice models. These results highlight the important role of information-processing strategies in the design and evaluation of DCEs.

Using geographically weighted choice models to account for the spatial heterogeneity of preferences

In this paper, we investigate the use of geographically weighted choice models for modelling spatially clustered preferences. We argue that this is a useful way of generating highly‐detailed spatial maps of willingness to pay for environmental conservation, given the costs of collecting data. The data used in this study come from a discrete choice experiment survey of public preferences for the implementation of a new national forest management and protection programme in Poland. We combine these with high‐resolution spatial data related to local forest characteristics. Using locally estimated discrete choice models we obtain location‐specific estimates of willingness to pay (WTP). Variation in these estimates is explained by characteristics of the forests close to where respondents live. These results are compared with those obtained from a more typical, two stage procedure which uses Bayesian posterior means of the mixed logit model random parameters to calculate location‐specific estimates of WTP. We find that there are indeed strong spatial patterns to the benefits of changes to the management to national forests. People living in areas with more species‐rich forests and those living nearer bigger areas of mixed forests have significantly different WTP values than those living in other locations. This kind of information potentially enables a better distributional analysis of the gains and losses from changes to natural resource management, and better targeting of investments in forest quality.

Spatial heterogeneity of willingness to pay for forest management

The paper investigates the spatial heterogeneity of public's preferences for the implementation of a new country-wide forest management and protection program in Poland. Spatial econometric methods and high resolution geographical information system data related to forest characteristics are used to explain the variation in individual-specific willingness to pay (WTP) values, derived from a discrete choice experiment study. We find that respondents' WTP is higher the closer they live to their nearest forest, and the scarcer forests are in the area where they live. Interestingly, the higher the ecological value of forests in respondents' area, the more people prefer extending areas of national forest protection. We also investigate spatial patterns in individual-specific WTP scores and in latent class membership probabilities, finding that preferences are indeed spatially clustered. We argue that this clustering should be taken into account in forest management and policy-making.

Disentangling the influence of knowledge on attribute non-attendance

We seek to disentangle the effect of knowledge about an environmental good on respondents' propensity to ignore one or more attributes on the choice cards in a discrete choice experiment eliciting people's preferences for increased protection of cold-water corals in Norway. We hypothesize that a respondent's level of knowledge influences the degree to which she ignores attributes. Respondents participated in a quiz on cold-water coral prior to the valuation task and we use the result of the quiz as an ex-ante measure of their knowledge. Our results suggests that a high level of knowledge, measured by a high quiz score, is associated with higher probabilities of attendance to the three non-cost attributes, although this effect is only significant for one of them. A higher quiz score is also associated with a significantly lower probability of attending to the cost attribute. Furthermore, although being told your score has mixed directional effects on attribute non-attendance, it does not significantly affect the probability of attending to any of the attributes. Finally, allowing for attribute non-attendance leads to substantially lower conditional willingness-to-pay estimates. This highlights the importance of measuring how much people know about the goods over which they are choosing, and underlines that more research is needed to understand how information influences the degree to which respondents ignore attributes.

Informing management strategies for a reserve: Results from a discrete choice experiment survey

It is well-known that operating within the boundaries of a national park provides commercial actors with the opportunity to charge a price premium, though this has to a lesser degree been demonstrated for marine protected areas. We estimate national tourists' willingness-to-pay a price premium for boat trips in the Nha Trang Bay Marine Protected Area, Vietnam, using a discrete choice experiment. Our results show that tourists are willing to pay an average price premium of 18 USD per trip for a large improvement in environmental quality, and that avoiding the loss of jobs for local fishermen is of minor importance. Furthermore, the economic benefits generated from management scenarios that combine biodiversity restoration and environmental quality improvement within the reserve sufficient to cover additional costs of such improvements.

Motivations matter: Behavioural determinants of preferences for remote and unfamiliar environmental goods

Discrete choice experiments (DCE) are one of the main methods for the valuation of non-market environmental goods. However, concerns regarding the validity of choice responses obtained in such surveys remain, particularly in surveys dealing with environmental goods remote from and unfamiliar to respondents. This study assesses behavioural determinants of preferences for conservation benefits of a marine protected area on the Dogger Bank, a shallow sandbank in the southern North Sea in an attempt to assess construct validity of survey responses. The Theory of Planned Behavior (TPB) and the Norm Activation Model (NAM) are employed to empirically measure constructs that predict stated choices. The study finds that identified protest respondents score significantly lower on most TPB and NAM components than non-protesters. Results further show that components of both the TPB and the NAM robustly predict choice behaviour. The inclusion of the TPB components improves the predictive power of the estimation model more than the NAM components. In an additional latent class logit model, TPB and NAM components plausibly explain different patterns of WTP for conservation benefits of an offshore marine protected area. These findings support construct validity of stated choice data regarding the valuation of remote and unfamiliar environmental goods.