Discrete choice experiments

Using stated preference valuation in the offshore environment to support marine planning

This study presents valuations of components of marine natural capital that have hitherto been overlooked by the valuation literature. Using a discrete choice experiment, it values a set of ecosystem services linked to seabed natural capital in the UK section of the North Sea. The study focuses on offshore seabed habitats, using Good Environmental Status as a measure of seabed health, thus linking directly to management targets under the EU Marine Strategy Framework Directive. It considers how changing pressures on seabed habitats could affect marine industries and other ecosystems through trade-offs with (1) the contribution that exploitation of these habitats makes to the maritime cultural heritage; and (2) changes to the health of seabird populations. For seabed habitats and seabirds, the elicited values mainly represent non-use values for changes in the condition of natural capital assets. For maritime cultural heritage the valuation refers to the changed provision of this cultural ecosystem service. Results show that the public in England hold significant, strongly correlated, values for changes in the condition of offshore seabeds and seabird populations. Projected losses in maritime cultural heritage are found to lead to expected welfare decreases. Implications of these findings for marine planning and decision-making are discussed.

Non-monetary numeraires: varying the payment vehicle in a choice experiment for health interventions in Uganda

Schistosomiasis is a serious health problem in many parts of Africa which is linked to poor water quality and limited sanitation resources. We administered a discrete choice experiment on water access and health education in rural Uganda, focussing on interventions designed to reduce cases of the disease. Unlike previous studies, we included a payment vehicle of both labour hours supplied per week and money paid per month within each choice set. We were thus able to elicit both willingness to pay and willingness to work for alternative interventions. Respondents exhibit high demand for new water sources. From the random parameter model, only households with knowledge about water-borne parasites are price sensitive and exhibit willingness to pay values. Through a latent class model specification, higher income respondents exhibit higher willingness to pay values for all programme attributes; however, lower income participants have higher willingness to work values for certain new water sources. We found a shadow wage rate of labour that is between 15 and 55% of the market wage rate.

Including opt-out options in discrete choice experiments: Issues to consider

Providing an opt-out alternative in discrete choice experiments can often be considered to be important for presenting real-life choice situations in different contexts, including health. However, insufficient attention has been given to how best to address choice behaviours relating to this opt-out alternative when modelling discrete choice experiments, particularly in health studies. The objective of this paper is to demonstrate how to account for different opt-out effects in choice models. We aim to contribute to a better understanding of how to model opt-out choices and show the consequences of addressing the effects in an incorrect fashion. We present our code written in the R statistical language so that others can explore these issues in their own data. In this practical guideline, we generate synthetic data on medication choice and use Monte Carlo simulation. We consider three different definitions for the opt-out alternative and four candidate models for each definition. We apply a frequentist-based multimodel inference approach and use performance indicators to assess the relative suitability of each candidate model in a range of settings. We show that misspecifying the opt-out effect has repercussions for marginal willingness to pay estimation and the forecasting of market shares. Our findings also suggest a number of key recommendations for DCE practitioners interested in exploring these issues. There is no unique best way to analyse data collected from discrete choice experiments. Researchers should consider several models so that the relative support for different hypotheses of opt-out effects can be explored.

Strategic bias in discrete choice experiments

An induced value laboratory experiment is conducted to explore the vulnerability of discrete choice experiments to strategic misrepresentation of preferences. We consider strategic behaviour to arise when an agent: (i) believes the choice experiment will be used to determine a provision decision over a discrete set of alternatives; and (ii) has expectations about the relative likelihood of those alternatives being selected and delivered. In the experiment, agents receive induced values for the discrete set of provisioning alternatives. In treatments where agents receive information that their first best outcome is unlikely to win, we investigate the extent to which their choices change, in a manner consistent with them seeking to deliver their second best outcome in the provisioning decision. We find that 27% of respondents misrepresent their preferences and reveal evidence of strategic bias. We find that this behaviour is sufficient to change inferences about preferred provision at the aggregate level.

The role of interdisciplinary collaboration for stated preference methods to value marine environmental goods and ecosystem services

With the increasing use of environmental valuation methods in coastal, marine and deep-sea settings, there is a growing need for the collaboration of natural scientists and environmental economists. Stated preference valuation methods in particular need to be based on sound natural science information and translate such information to be used in social surveys. This paper uses three applications to make explicit the flow of information between different disciplines in the preparation and implementation of stated preference studies. One approach for facilitating this flow is to increase knowledge and understanding of natural scientists on these methods. To address this, this paper highlights key opportunities and pitfalls and demonstrates those in the context of three case studies. It therefore provides guidance on stated preference valuation for natural scientists rather than for economists.