Stated Preference Studies Research Articles

Comparing offshore and onshore wind development considering acceptance costs

Cost efficient deployment of wind energy is in focus for reaching ambitious targets for renewable energy and transforming the energy supply to one based on renewables. However, as more wind is being deployed the available sites onshore become less attractive in terms of wind conditions and capacity factor and more resistance from population groups affected in the deployment areas results in a reduction of areas that can be developed. We consider three different methods for estimating acceptance costs, one based on compensation and property purchase costs, one based on property value loss near wind turbines, and one based on willingness to pay calculated from a stated preference study. Utilising these methods, we provide an estimation of Levelised Cost of Energy (LCOE) for an expansion of 12 GW onshore or offshore wind capacity in Denmark. We find that the three methods provide similar estimates for local acceptance, but that a high range of uncertainty exists in the upper bound of acceptance costs. Onshore does not have a clear-cut cost advantage over offshore when considering substantial amounts of wind capacity expansion and using high estimates for nation-wide acceptance costs. Moderate onshore wind expansion considering only local acceptance has a cost advantage.

A comparison of bus passengers’ and car drivers’ valuation of casualty risk reductions in their routes

IntroductionThe economic value of safety represents an important guide to transport policy, and more studies on individuals’ valuation of road safety are called for. This paper presents a stated preference study of the value of preventing fatal and serious injuries involving bus passengers and car drivers in road accidents. ObjectivesFormer valuation studies based on travel behaviour and route choice have involved primarily car drivers. Our study also included bus passengers, thus providing a comparison of two types of transport mode users. Moreover, the comparison was based on two different valuation methods. MethodologyAbout 600 bus passengers and nearly 2300 car users from different areas of Norway reported a recent trip, described by its distance and travel cost. Then they answered stated choice tasks that took a reference in the reported trip and involved trade-offs among travel time, fatal and seriously injured victims and travel costs. Afterwards, they faced a simple trade-off between travel costs, and fatal and seriously injured victims. FindingsPooling the data from the two stated preference formats, we derived values of a statistical life and of a statistical seriously injured victim. Regarding the value of statistical life, our point estimates were NOK 45.5 million and NOK 58.3 million for bus users and car users respectively. DiscussionThe point estimates for bus passengers and car users were not statistically different given their confidence intervals. Thus, we recommend the use of a single value, identical for both modes of transport, for the prevention of a statistical fatality as well as for a statistical injury

The Income Elasticity of Global Values of a Statistical Life: Stated Preference Evidence

Examination of estimates of the income elasticity of the value of a statistical life based on international stated preference studies yields an average between 0.94 and 1.05 overall and 0.65 and 0.80 after controlling for covariates. Quantile regression estimates indicate that the income elasticity is about 0.55 for more affluent counties and 1.0 for lower income nations, i.e., those countries that have estimates of the value of a statistical life below $2 million or per capita income levels below $3,212. The estimates distinguish the values of the income elasticity across country either by income level or by the value of a statistical life. These elasticities are similar to those found in revealed preference labor market studies. The estimates are robust, controlling for possible sample selection bias and the influence of covariates, such as the type of risk.

Discounting future payments in stated preference choice experiments

When costs are presented as a series of recurring payments in stated preference choice experiment (CE) questions, how respondents discount future payments is important in explaining choices and in the measurement of the present value of willingness to pay. In this paper, alternative discounting approaches are compared to examine their effect on measuring preferences and values using data from a survey examining public preferences for the protection of an endangered species. Exponential and hyperbolic discounting assumptions lead to very similar results in terms of both model fit and welfare. All estimated models suggest future payments are discounted at a very high rate. Several factors likely influencing the magnitude of these estimated discount rates are discussed, and then an argument is made for using payment vehicles in stated preference studies that employ a single lump sum payment rather than a series of future payments.

The role of driving range in consumers' purchasing decision for electric cars in Italy

The paper reports the results of a stated preference study, carried out in Italy in 2017, on consumers' preferences between an electric car (EC) and a petrol car. The focus is on the role of driving range. We find that the linear specification leads to lower willingness to pay (WTP) estimate for the driving range than the logarithmic, quadratic and EC-specific ones. The estimation of a mixed logit model leads to a coefficient of the EC-specific range attribute six times larger than the coefficient of the non-EC one. The jointly statistically significant covariates explaining the heterogeneity of the coefficient of the EC-specific driving range attribute are gender, number of cars owned by the family, and knowledge of cars. The implied WTP varies from 37 to 106 €/km, depending on the socio-economic characteristics of the respondent. Simulative analysis shows that very relevant increases in the probability of buying an electric car (ranging from 28% to 68%) over a petrol one require jointly improvements in the fast charging network, driving range and financial incentives.

What is the causal impact of information and knowledge in stated preference studies?

This paper reports the results of a stated preference experiment designed to test how information about a good’s attributes provided in a survey affects knowledge, and how knowledge affects preferences for that good. A novel experimental design allows us to elicit subjects’ ex ante knowledge levels about a public good’s attributes, exogenously vary how much new objective information about these attributes we provide to subjects, elicit subjects’ valuation for the good, and elicit posterior knowledge states about the same attributes. We find evidence of incomplete learning and fatigue: as subjects are told more information, their marginal learning rates decrease. Consistent with previous work, ex ante knowledge does affect stated willingness to pay. However, we find no significant marginal impact of knowledge on the mean nor the variance of willingness to pay for changes in the environmental good conditional on ex ante knowledge. Our results are consistent with a number of conceptual models of information processing and preferences, including confirmation bias, costly search, and timing differences in learning and preference formation.

Stated Preferences for Conservation Policies Under Uncertainty: Insights on the Effect of Individuals\u2019 Risk Attitudes in the Environmental Domain

The outcome of a conservation policy is often subject to uncertainty. In stated preference valuation, it is increasingly recognised that uncertainty affects preferences for the outcomes of environmental policies. However, there is also agreement that the effect of uncertainty and people’s attitudes towards risk need to be better understood. To shed more light on the impact of risk, we designed a discrete choice experiment to compare preferences for environmental outcomes under climate change across two split samples. Each sample was confronted with a scenario where results were presented as certain or uncertain, but were otherwise associated with the same expected values. We found significant differences between the certain and the uncertain treatment, with uncertain outcomes being associated with more extreme utility levels and willingness to pay, in absolute terms. This finding was confirmed irrespective of whether gains or losses were considered and despite sensitivity to uncertainty—specific to the socio-demographic profile. Our results suggest that individuals are not risk neutral in the presence of uncertainty around environmental outcomes. These findings are crucial to better understand stated preferences for conservation policies in risky contexts. Our results reinforce the idea that uncertainty should be explicitly incorporated in the design of stated preference studies to better inform policy.

Demand effects in stated preference surveys

We argue that demand effects in stated preference studies are understudied. By demand effects, we mean anything in the survey that unintentionally influences respondents' beliefs about appropriate behavior, which in turn might affect their responses in the survey. We implement two methods for measuring and implicitly reducing the influence of demand effects. The first approach—random selection of good to be valued—does not have any effect on respondent behavior. The second approach—a demand script and a control question with feedback—has a sizable and statistically significant effect on respondent behavior. In particular, estimated marginal willingness to pay for improvements in water quality are substantially (around 50 percent) lower than a control treatment; we attribute this decrease to a reduced demand effect. Our results suggest that stated preference methods tend to lead to biased willingness-to-pay estimates due to demand effects, but that the bias can be reduced using simple measures.

Understanding peak avoidance commuting by subway: an empirical study in Beijing

ABSTRACTCongestion is a major problem for peak-hour commuters in the Beijing subway system, as it leads to long queuing times and overcrowded vehicles. This paper explores to what extent peak travel can be reduced by providing incentives for peak avoidance. In a stated preference study, travellers’ responses to two financial and two non-financial incentives were measured, and factors increasing or limiting the response were identified. Our results suggest that all four incentives can be reasonably effective tools and the financial incentives seem to have a slightly stronger effect than the services and credit-for-gifts-based scenarios. Ordered logit models indicate that various factors influence people’s receptiveness of incentives for peak avoidance which relate to the ease of change or presence of alternatives and receptiveness to incentives. Both theoretical and policy implications are concluded that the proposed factors and incentive system can help solving the subway congestion in Beijing.

Preferences for Offshore-Onshore Wind Power Development in Denmark Accounting for Spatial Data

Wind energy installed capacity has been increasing steadily all over the world and is expected to continue to do so in the future, following lowering costs of technology as well as increased renewable energy goals by governments. Nonetheless, public opposition has been increasing, and the discussion regarding siting wind turbines onshore or offshore is constantly present on public discourse. By combining a stated preference study with spatial data processed utilising GIS (Geographic Information System), we explore preferences for onshore and offshore wind turbines, considering their visual impact, costs, as well as socioeconomic and spatial attributes of the respondents. Results show that in general respondents show strong preferences towards offshore wind turbines as opposed to onshore. Furthermore, spatial data is found to be significant in regards to the preferences of the respondents, particularly the respondents’ distance to the coast and potential offshore wind farms and the number of wind turbines seen from the residence. In the same line, socioeconomic indicators such as age and income prove significant to respondents’ preferences in line with previous research.

Modeling Distance Decay Within Valuation Meta-Analysis

Environmental benefit transfers increasingly rely on welfare estimates generated using meta-regression models (MRMs) of non-market willingness to pay (WTP). Theory and intuition suggest that these estimates should generally be sensitive to spatial dimensions. A common spatial pattern found in primary valuation studies is distance decay, in which WTP for environmental improvements diminishes as a function of distance to affected areas. Despite the potential importance of distance decay for benefit transfer accuracy, no valuation MRM in the published literature has developed an explicit mechanism to account for it. This paper outlines an approach to model the systematic effect of distance within valuation MRMs. The approach is illustrated using a meta-analysis of WTP for quality improvements in US water bodies. The metadata are drawn from stated preference studies that estimate per household WTP for water quality changes, and combine primary study information with external geospatial data. Results demonstrate statistically significant and intuitive influences of distance and other spatial factors on WTP. The resulting benefit transfers are more accurate than otherwise identical transfers that cannot account for spatial variations.

Using structural restrictions to achieve theoretical consistency in benefit transfers

Analysts often extrapolate estimates of the value of environmental improvements reported in prior studies to evaluate new policy proposals, a practice sometimes referred to as "benefit transfer." Benefit transfer functions are frequently specified based on statistical considerations alone. However, such a purely statistical approach can lead to willingness-to-pay functions that fail to satisfy some aspects of theoretical consistency that may be especially important for policy evaluations. In this paper, we examine several previous meta-analyses of nonmarket valuation studies in light of the adding-up condition, which is one important aspect of theoretical validity. We then use meta-regression to estimate a new willingness-to-pay function for surface water quality improvements intended to be used for benefit transfers. We estimate the meta-regression model using summary results from 51 previously published stated preference studies. An important feature of our approach is that we develop the meta-regression estimating equation to ensure that the resulting benefit transfer function will necessarily comply with the adding-up condition. This is achieved by first specifying a marginal willingness-to-pay function and then deriving an expression for total willingness-to-pay. This leads to a non-linear estimating equation, so we estimate the parameters of the model using non-linear least squares. We discuss the advantages and disadvantages of our approach relative to other structural approaches, and we compare our empirical results to a more traditional nonstructural meta-regression model. Finally, we examine the quantitative importance of imposing the adding-up condition in our case study by performing some illustrative calculations of willingness-to-pay for hypothetical water quality improvements using both structural and non-structural models.

A Systematic Review of Discrete-Choice Experiments and Conjoint Analysis Studies in People with Multiple Sclerosis

Multiple sclerosis (MS) is a chronic disabling, inflammatory, and degenerative disease of the central nervous system that, in most cases, requires long-term disease-modifying treatment (DMT). The drugs used vary in efficacy and adverse effect profiles. Several studies have used attribute-based stated-preference methods, primarily to investigate patient preferences for initiating or escalating DMT. To conduct a systematic review of attribute-based stated-preference studies in people with MS to identify common methods employed and to assess study quality, with reference to the specific challenges of this disease area. We conducted a systematic search for studies related to attribute-based stated-preference and MS in multiple databases, including Cochrane and MEDLINE. Studies were included if they were published in a peer-reviewed journal, were on the topic of MS, and used a survey methodology that measured stated preferences for attributes of a whole. Analysis was conducted using narrative synthesis and summary statistics. Study quality was judged against the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) conjoint analysis checklist. We identified 16 relevant articles reporting 17 separate studies, all but one focusing on DMTs. Most studies were discrete-choice experiments. Study quality was generally high, but we recommend the following: (1) that consideration of sample sizes be improved, (2) that survey design choices be justified and documented, (3) that qualitative approaches for attribute and level selection be incorporated to better involve patients, and (4) that reporting of experimental practice be improved. The effects of DMTs on reproduction and the impact of how risk and uncertainty are presented were identified as neglected research topics. The ISPOR conjoint analysis checklist was found to be unsuitable for the assessment of study quality. Attribute-based stated preference is a useful method with which to examine the preferences of people with MS in their choice of DMT. However, further research embracing the methodological recommendations identified, particularly greater use of qualitative methods in attribute development, is needed.

The Income Elasticity of Global Values of a Statistical Life: Stated Preference Evidence

Examination of estimates of the income elasticity of the value of a statistical life based on international stated preference studies yields an average between 0.94 and 1.05 overall and 0.65 and 0.80 after controlling for covariates. Quantile regression estimates indicate that the income elasticity is about 0.55 for more affluent countries and 1.0 for lower income nations, i.e., those countries that have estimates of the value of a statistical life below $2 million or per capita income levels below $3212. The estimates distinguish the values of the income elasticity across country either by income level or by the value of a statistical life. These elasticities are similar to those found in revealed preference labor market studies. The estimates are robust, controlling for possible sample selection bias and the influence of covariates, such as the type of risk.

Appropriate Payment Vehicles in Stated Preference Studies in Developing Economies

Selecting appropriate payment vehicles is critical for the perceived consequentiality and incentive compatibility of stated preferences surveys. We analyze the performance of three different payment vehicles in a Malaysian case of valuing wetland conservation. Two are well-known: voluntary donations and income taxes. The third is new: reductions in government subsidies for daily consumer goods. Using donations is common, but this payment vehicle is prone to issues of free-riding. An income tax usually has favorable properties and is commonly used in environmental valuation. However, in Malaysia as well as in many other low- to middle-income economies, large proportions of people do not pay income taxes, putting the validity of this payment vehicle into question. Instead, citizens in Malaysia and many other countries benefit from subsidies for a range of consumer goods. We find that price sensitivity is higher and the unexplained variance smaller when using subsidies rather than donations or income taxes. Importantly, this approach translates into completely different conclusions concerning policy advice. Our results suggest that in developing countries, using reduced subsidies as a payment vehicle may have favorable properties in terms of improved payment consequentiality compared to alternative payment vehicles, thus enhancing the external validity of stated preference surveys.

Individual Trade-Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma.

The objectives of this study were to elicit the preferences of patients with multiple myeloma regarding the possible benefits and risks of cancer treatments and to illustrate how such data may be used to estimate patients' acceptance of new treatments. Patients with multiple myeloma from the cancer charity Myeloma UK were invited to participate in an online survey based on multicriteria decision analysis and swing weighting to elicit individual stated preferences for the following attributes: (a) 1-year progression-free survival (PFS, ranging from 50% to 90%), (b) mild or moderate toxicity for 2 months or longer (ranging from 85% to 45%), and (c) severe or life-threatening toxicity (ranging from 80% to 20%). A total of 560 participants completed the survey. The average weight given to PFS was 0.54, followed by 0.32 for severe or life-threatening toxicity and 0.14 for mild or moderate chronic toxicity. Participants who ranked severe or life-threatening toxicity above mild or moderate chronic toxicity (56%) were more frequently younger, working, and looking after dependent family members and had more frequently experienced severe or life-threatening side effects. The amount of weight given to PFS did not depend on any of the collected covariates. The feasibility of using the collected preference data to estimate the patients' acceptance of specific multiple myeloma treatments was demonstrated in a subsequent decision analysis example. Stated preference studies provide a systematic approach to gain knowledge about the distribution of preferences in the population and about what this implies for patients' acceptance of specific treatments. This study demonstrated how quantitative preference statements from a large group of participants can be collected through an online survey and how such information may be used to explore the acceptability of specific treatments based on the attributes studied. Results from such studies have the potential to become an important new tool for gathering patient views and studying heterogeneity in preferences in a systematic way, along with other methods, such as focus groups and expert opinions.

Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review.

Latent class analysis (LCA) has been increasingly used to explore preference heterogeneity, but the literature has not been systematically explored and hence best practices are not understood. We sought to document all applications of LCA in the stated-preference literature in health and to inform future studies by identifying current norms in published applications. We conducted a systematic review of the MEDLINE, EMBASE, EconLit, Web of Science, and PsycINFO databases. We included stated-preference studies that used LCA to explore preference heterogeneity in healthcare or public health. Two co-authors independently evaluated titles, abstracts, and full-text articles. Abstracted key outcomes included segmentation methods, preference elicitation methods, number of attributes and levels, sample size, model selection criteria, number of classes reported, and hypotheses tests. Study data quality and validity were assessed with the Purpose, Respondents, Explanation, Findings, and Significance (PREFS) quality checklist. We identified 2560 titles, 99 of which met the inclusion criteria for the review. Two-thirds of the studies focused on the preferences of patients and the general population. In total, 80% of the studies used discrete choice experiments. Studies used between three and 20 attributes, most commonly four to six. Sample size in LCAs ranged from 47 to 2068, with one-third between 100 and 300. Over 90% of the studies used latent class logit models for segmentation. Bayesian information criterion (BIC), Akaike information criterion (AIC), and log-likelihood (LL) were commonly used for model selection, and class size and interpretability were also considered in some studies. About 80% of studies reported two to three classes. The number of classes reported was not correlated with any study characteristics or study population characteristics (p>0.05). Only 30% of the studies reported using statistical tests to detect significant variations in preferences between classes. Less than half of the studies reported that individual characteristics were included in the segmentation models, and 30% reported that post-estimation analyses were conducted to examine class characteristics. While a higher percentage of studies discussed clinical implications of the segmentation results, an increasing number of studies proposed policy recommendations based on segmentation results since 2010. LCA is increasingly used to study preference heterogeneity in health and support decision-making. However, there is little consensus on best practices as its application in health is relatively new. With an increasing demand to study preference heterogeneity, guidance is needed to improve the quality of applications of segmentation methods in health to support policy development and clinical practice.

Social Benefits From Controlling Invasive Asian Tiger and Native Mosquitoes: A Stated Preference Study in Athens, Greece

The economic aspects of the problem of invasive mosquitoes present a new challenge to science. The impacts of mosquitoes on humans are intensifying in many regions as several factors – such as climate change and increased transport – create favorable conditions for the entry of invasive mosquitoes. At the same time budget constraints limit public prevention measures and demand clear justification of additional costs for controlling invasive mosquitoes. Consequently, the benefits arising from preventive policies should be clearly articulated and included in the evaluation process. The present study evaluates the potential benefits of alternative prevention measures in the metropolitan area of Athens, Greece, representative of the geographically and climatically vulnerable Mediterranean cities. The study differentiates the health and nuisance costs associated with invasive mosquito species from those associated with native mosquito species. In contrast to other findings in the literature, the benefits from controlling health impacts were found to be higher than those of avoiding nuisance. This is mainly related to the high health risk induced by new invasive species. Another important finding is that the expected benefits of mosquito control programs clearly outweigh the respective costs.

The Adding-Up Test in an Incentivized Value Elicitation Mechanism: The Role of the Income Effect

In the context of testing the construct validity of stated preference studies, some researchers advocate the use of an “adding-up test” designed to gauge whether elicited values are sufficiently sensitive to a change in the scope (i.e. size) of a good. Crucial to the applicability of this test in practice, which relies on endowing a subsample of respondents with a good free of charge, is that the income effects due to endowment are negligible. In this study, we apply the adding-up test in an experimental value elicitation format to examine the potential effect of endowment as part of the test design on the adding-up property of elicited values. The results show that the adding-up property can be affected by free provision of part of the bundle.

Conducting a Discrete-Choice Experiment Study Following Recommendations for Good Research Practices: An Application for Eliciting Patient Preferences for Diabetes Treatments

ObjectivesTo consolidate and illustrate good research practices in health care to the application and reporting of a study measuring patient preferences for type 2 diabetes mellitus medications, given recent methodological advances in stated-preference methods. MethodsThe International Society for Pharmacoeconomics and Outcomes Research good research practices and other recommendations were used to conduct a discrete-choice experiment. Members of a US online panel with type 2 diabetes mellitus completed a Web-enabled, self-administered survey that elicited choices between treatment pairs with six attributes at three possible levels each. A D-efficient experimental design blocked 48 choice tasks into three 16-task surveys. Preference estimates were obtained using mixed logit estimation and were used to calculate choice probabilities. ResultsA total of 552 participants (51% males) completed the survey. Avoiding 90 minutes of nausea was valued the highest (mean −10.00; 95% confidence interval [CI] −10.53 to −9.47). Participants wanted to avoid low blood glucose during the day and/or night (mean −3.87; 95% CI −4.32 to −3.42) or one pill and one injection per day (mean −7.04; 95% CI −7.63 to −6.45). Participants preferred stable blood glucose 6 d/wk (mean 4.63; 95% CI 4.15 to 5.12) and a 1% decrease in glycated hemoglobin (mean 5.74; 95% CI 5.22 to 6.25). If cost increased by $1, the probability that a treatment profile would be chosen decreased by 1%. ConclusionsThese results are consistent with the idea that people have strong preferences for immediate consequences of medication. Despite efforts to produce recommendations, ambiguity surrounding good practices remains and various judgments need to be made when conducting stated-preference studies. To ensure transparency, these judgments should be described and justified.