Danny Campbell

Benefit Estimates for Landscape Improvements: Sequential Bayesian Design and Respondents’ Rationality in a Choice Experiment

A multi-attribute, stated-preference approach is used to value low and high impact actions on four major landscape components addressed by the Rural Environment Protection Scheme in Ireland. Several methodological issues are addressed: the use of prior beliefs on the relative magnitudes of parameters, standardized description of different levels of landscape improvements via image manipulation software, adoption of efficiency-increasing sequential experimental design, and sensitivity of benefit estimates to inclusion of responses from ‘‘irrational’’ respondents. Results suggest that Bayesian design updating delivers significant efficiency gains without loss in respondent efficiency, and estimates are upward-biased when irrational respondents are included. (JEL Q24, Q51)

Using choice experiments to explore the spatial distribution of willingness to pay for rural landscape improvements

We report findings from a choice experiment survey designed to estimate the economic benefits of policy measures to improve the rural landscape in the Republic of Ireland. Using a panel mixed logit specification to account for unobserved taste heterogeneity we derived individual-specific willingness-to-pay (WTP) estimates for each respondent in the sample. We subsequently investigated the spatial dependence of these estimates. Results suggest the existence of positive spatial autocorrelation for all rural landscape attributes. As a means of benefit transfer, kriging methods were employed to interpolate WTP estimates across the whole of the Republic of Ireland. The kriged WTP surfaces confirm the existence of spatial dependence and illustrate the implied spatial variation and regional disparities in WTP for all the rural landscape improvements investigated.

Heterogeneity in the WTP for recreational access: distributional aspects

In this study we have addressed appropriate modelling of heterogeneity in willingness to pay (WTP) for environmental goods, and have demonstrated its importance using a case of forest access in Denmark. We compared WTP distributions for four models: (1) a multinomial logit model, (2) a mixed logit model assuming a univariate Normal distribution, (3) or assuming a multivariate Normal distribution allowing for correlation across attributes, and (4) a mixture of two truncated Normal distributions, allowing for correlation among attributes. In the first two models mean WTP for enhanced access was negative. However, models accounting for preference heterogeneity found a positive mean WTP, but a large sub-group with negative WTP. Accounting for preference heterogeneity can alter overall conclusions, which highlights the importance of this for policy recommendations.

Lexicographic Preferences in Discrete Choice Experiments: Consequences on Individual-Specific Willingness to Pay Estimates

In discrete choice experiments respondents are generally assumed to consider all of the attributes across each of the alternatives, and to choose their most preferred. However, results in this paper indicate that many respondents employ simplified lexicographic decision-making rules, whereby they have a ranking of the attributes, but their choice of an alternative is based solely on the level of their most important attribute(s). Not accounting for these simple decision-making heuristics introduces systemic errors and leads to biased point estimates, as they are a violation of the continuity axiom and a departure from the use of compensatory decision-making. In this paper the implications of lexicographic preferences are examined. In particular, using a mixed logit specification this paper investigates the sensitivity of individual-specific willingness to pay (WTP) estimates conditional on whether lexicographic decision-making rules are accounted for in the modelling of discrete choice responses. Empirical results are obtained from a discrete choice experiment that was carried out to address the value of a number of rural landscape attributes in Ireland.

Using Discrete Choice Experiments to Derive Individual-Specific WTP Estimates for Landscape Improvements under Agri-Environmental Schemes: Evidence from the Rural Environment Protection Scheme in Ireland

Reported in this paper are the findings from two discrete choice experiments that were carried out to address the value of a number of farm landscape improvement measures within the Rural Environment Protection (REP) Scheme in Ireland. Image manipulation software is used to prepare photorealistic simulations representing the landscape attributes across three levels to accurately represent what is achievable within the Scheme. Using a mixed logit specification willingness to pay (WTP) distributions based on the parameter estimates obtained from the individual conditional distributions are derived. These estimates are subsequently adjusted and combined to account for baselines and levels of improvement resulting from the implementation of the REP Scheme. Individual-specific WTP estimates are thus obtained for the contribution of the Scheme to rural landscapes and are subsequently contrasted with the average cost of the Scheme across the Irish adult population. Results indicate that the Scheme contributes substantial benefits to rural landscapes.

Accounting for attribute-level non-attendance in a health choice experiment: does it matter?

An extensive literature has established that it is common for respondents to ignore attributes of the alternatives within choice experiments. In most of the studies on attribute non-attendance, it is assumed that respondents consciously (or unconsciously) ignore one or more attributes of the alternatives, regardless of their levels. In this paper, we present a new line of enquiry and approach for modelling non-attendance in the context of investigating preferences for health service innovations. This approach recognises that non-attendance may not just be associated with attributes but may also apply to the attributes levels. Our results show that respondents process each level of an attribute differently: while attending to the attribute, they ignore a subset of the attributes levels. In such cases, the usual approach of assuming that respondents either attend to the attribute or not, irrespective of its levels, is erroneous and could lead to misguided policy recommendations. Our results indicate that allowing for attribute-level non-attendance leads to substantial improvements in the model fit and has an impact on estimated marginal willingness to pay and choice predictions.

Estimating the welfare impacts of agricultural landscape change in Ireland: a choice experiment approach

In this paper we exploit a choice experiment modelling framework to estimate the potential non-market welfare impacts of a number of hypothetical rural Irish landscape types that could become real by the year 2030, depending both on future agricultural policy reform and changing land use demands. The results of a random parameters logit model demonstrate significant preference heterogeneity amongst the Irish population for the attributes of agricultural landscapes. The largest welfare gain for the population is found to be from the ‘agri-environmental landscape’ that protects traditional farm landscape features and enhances biodiversity.

Elimination and selection by aspects in health choice experiments: Prioritising health service innovations

Priorities for public health innovations are typically not considered equally by all members of the public. When faced with a choice between various innovation options, it is, therefore, possible that some respondents eliminate and/or select innovations based on certain characteristics. This paper proposes a flexible method for exploring and accommodating situations where respondents exhibit such behaviours, whilst addressing preference heterogeneity. We present an empirical case study on the publics preferences for health service innovations. We show that allowing for elimination-by-aspects and/or selection-by-aspects behavioural rules leads to substantial improvements in model fit and, importantly, has implications for willingness to pay estimates and scenario analysis.

Demand for safety and regional certification of food: Results from Great Britain and the Republic of Ireland

Purpose – This paper aims to explore the relationship between consumer demand for enhanced food safety features and regional identification of food amongst consumers across Great Britain and the Republic of Ireland. Design/methodology/approach – The paper uses the choice experiment method to determine preferences for food testing standards, traceability standards, health and welfare standards, region of origin and price. Findings – The results show that substantial differences exist in preferences for the features between consumers in both countries. In addition, while stark differences are apparent between the two countries, in their preferences for food originating from their local region, the results suggest that consumers perceive significant substitutability between the enhanced safety features and the local regional label in both countries. Originality/value – This paper provides a unique insight into preferences for a wide range of enhanced food safety features amongst consumers in these two countr...

Examining labelling effects within discrete choice experiments: An application to recreational site choice

Data from a discrete choice experiment aimed at eliciting the demand for recreational walking trails on farmland in Ireland is used to explore whether some respondents reach their choices solely on the basis of the alternatives label. To investigate this, this paper exploits a discrete mixtures approach that also encompasses continuous distributions to reflect the heterogeneity in preferences for the attributes and alternatives. We find evidence that a proportion of respondents choose on the basis of the label only and that differences emerge between rural and urban respondents. We provide a number of alternative explanations for why this may occur. Results highlight a large impact on welfare measures when we accommodate the fact that a proportion of respondents choose on the basis of the label only.