Estimation of the preference heterogeneity within stated choice data using semiparametric varying-coefficient methods

This study proposes the use of semiparametric varying-coefficient methods to estimate the preference heterogeneity within stated choice data. Semiparametric varying-coefficient methods have the potential to overcome the disadvantages of conventional random parameter models and latent class models. For binary probit models with varying coefficients, in particular, this study proposes an easy-to-compute local iterative least squares (LILS) approach, based on the expectation–maximization algorithm. The finite sample properties of the LILS estimator are assessed using Monte Carlo experiments. In order to demonstrate the practical usefulness of semiparametric varying-coefficient methods, we present an empirical study, conducting an economic valuation of a landscape with dichotomous choice contingent valuations.     

Valuations of aircraft noise: experiments in stated preference

The aim of this paper is to report new evidence relating to residents’ valuations of aircraft noise in three countries with an emphasis on a comparison of the valuations obtained using two contrasting approaches. One might be regarded as a standard stated choice approach offering pairwise comparisons of two alternatives characterised by a limited number of attributes. The other choice format adopted is innovative in drawing inspiration from the priority evaluator approach to embed aircraft movements alongside a wide range of other local factors that impact on residents’ quality of life. The paper addresses the differences in the results of the two approaches and explores the possible explanations for these variations. Although not conclusive, there is a suspicion that strategic bias may have influenced the results and we urge further research regarding incentives to such bias.     

Indices of biotic integrity in stated preference valuation of aquatic ecosystem services

Stated preference surveys often give minimal attention to distinctions between intermediate and final ecosystem services, leading to the potential for welfare estimates that overlook, misrepresent or double count associated values. This paper illustrates potential mechanisms through which multimetric indexes of the type developed in the ecological literature, here an index of biotic integrity, can be used within stated preference survey scenarios to both improve the validity of survey responses and provide otherwise unavailable information on willingness to pay for intermediate and final ecosystem services. We illustrate the approach using a choice experiment application to the restoration of migratory fish in a Rhode Island watershed. Where assumptions of the model hold, results can allow transparent disentanglement and estimation of marginal values for both intermediate and final ecosystem services.     

Societal preferences for fertility treatment in Australia: a stated preference discrete choice experiment

Objective: To investigate preferences for fertility treatment from the Australian general population with the aims of calculating the willingness to pay in tax contribution for attributes (characteristics) that make up treatment and for an “ideal” fertility treatment program. We also assessed whether willingness-to-pay varies by the relationship status or sexual orientation of the patient.

Methods: A stated preference discrete choice experiment was administered to a panel of 801 individuals representative of the Australian general population. Seven attributes of fertility treatment under three broad categories were included: outcome, process, and cost. Attributes were identified through published literature, focus group discussions, expert knowledge, and a pilot study. A Bayesian fractional experimental design was used, and data analysis was performed using a generalized multinomial logit model. Further analyses included interaction terms and latent class modeling.

Results: Six of the seven attributes influenced the choice of a treatment program. Under process attributes, individuals preferred: continuity of care of clinic staff, where patients are seen by the same doctor but different nurses at each visit; “alternative” treatments being offered to all patients; and onsite clinic counseling and peer-support groups. Personalization and tailoring of the treatment journey were not important. Among outcome attributes, the improved success rate of having a baby per cycle and significant side-effects were considered important. Cost of treatment also influenced the choice of treatment program. Individual preferences for fertility treatment were not associated with patients’ relationship status or sexual orientation. Latent class modeling revealed sub-groups with distinct fertility treatment preferences.

Conclusion: This study provides important insights into the attributes that influence the preferences of fertility treatment in Australia. It also estimates socially-inclusive willingness-to-pay values in tax contributions for an “ideal” package of treatment. The results can inform economic evaluations of fertility treatment programs.     

Cost credibility and the stated preference analysis of public goods

Two recent stated preference studies include questions that explore participants’ beliefs regarding the cost amount stated in the valuation question in relation to the cost to them if the project were implemented. Results from these studies suggest that a significant proportion of people do not believe these stated cost amounts. This paper explores the implications of participants answering valuation questions that are not consistent with their beliefs regarding stated costs. As an example, the paper develops a response model for dichotomous choice stated preference questions. Participants gather project information through the stated preference experiment, form a prior distribution of costs, update the distribution of costs based on a survey's stated cost and then respond to the dichotomous choice stated preference question. The model suggests that participants will not generally respond truthfully in the sense that they may say no to a stated cost that is less than their willingness to pay for a project or yes to a stated cost that is more than their willingness to pay. While the model findings suggest potentially serious problems with stated preference estimation, the observed patterns of disbelief from the empirical studies result in downwardly biased estimates of mean willingness to pay.     

浅谈发出存货计价方法的选择

对存货计价问题的产生进行说明,详细介绍了5种发出存货计价方法,并且通过它们之间的比较,重点阐述了企业如何根据自己选择恰当的存货计价方法。这样,选择比较合理的发出存货计价方法,可以有效达到企业管理的目标。     

Cost thresholds,cut-offs and sensitivities in stated choice analysis: Identification and implications

Within the discrete choice literature, there is growing recognition that some respondents do not process all attributes when evaluating their choice outcomes. Worryingly, the cost attribute is often among those attributes that are likely to be ignored by respondents. We use probabilistic decision process models (similar in form to latent class models, but where we define the classes to describe specific heuristics) to facilitate situations where respondents adopt cost thresholds and cut-offs. We further develop this model to address the potential confounding between preference heterogeneity and processing heterogeneity by simultaneously allowing for a segmentation of respondents based on their sensitivities to cost. Results, based on an empirical dataset on the existence value of rare fish species in Ireland, provide further confirmation that a share of respondents did not attended to cost. Importantly, however, when heterogeneity to cost levels is accounted for the inferred incidence of complete non-attendance is markedly lower, to the extent that when cost thresholds and cut-offs are also accommodated it almost disappears. This modelling approach leads to significant gains in model fit and has important implications for welfare analysis.     

Preference uncertainty in stated preference studies: facts and artefacts

The ordinal scale and polychotomous choice methods are two widely used techniques for estimating preference uncertainty in stated preference studies. This article presents the results of two experiments that apply these estimation techniques. The first experiment was designed to compare and contrast the scores of the ordinal scale and polychotomous choice method. The second experiment was conducted to test a scale that combines verbal expressions with numerical and graphical interpretations: a composite scale. The results of the study can be summarized in three key findings. First, the polychotomous choice method generates a higher proportion of ‘yes’ responses than the conventional dichotomous choice elicitation format. Second, the composite scale generates a significantly higher proportion of certain responses. Finally, the ordinal scale performs poorly on the ground of construct validity.     

Using stated preference discrete choice modelling to inform health care decision-making: A pilot study of breast screening participation

This study was an important start to explore the feasibility of applying stated preference discrete choice modelling (SPDCM) for use in developing breast screening participation enhancement strategies. It needs to be followed by further research to establish model validity and authoritative results. In the meantime a random effects binary probit choice model was estimated using a main effects with selected 2-way interaction design and a convenience sample of Australian breast cancer screening participants. A response rate of 48% was obtained. Clear preferences for different service configurations were revealed and used to demonstrate how potential strategies to enhance future participation rates of women placed on routine recall could be identified. As anticipated accuracy of screening was the most important attribute of the service to influence the probability of uptake but others were screening time, travel time, information about screening benefits and the desire for privacy lending support to the view that benefit assessment goes beyond health factors. In summary, the SPDCM approach can be regarded as a judicious approach for helping decision-makers improve screening participation.     

Individual valuation,market valuation,and the preference reversal phenomenon

This article reports experiments dealing with individual subject valuation and preference over prospect pairs that are known to generate systematic intransitivities in choice behavior termed “preference reversals”. The authors examine whether alternative procedures to those previously employed for eliciting individual limit selling prices over prospects alters the incidence or dollar magnitude of preference reversals. It is found that when individual limit selling prices over prospects are elicited in a repetitive, second-price sealed Vickrey (1961) auction market framework, rather than under the traditional single response Becker, DeGroot, and Marshak (1964) procedure, that the dollar magnitude of preference reversals declines significantly. Initially, when opening Vickrey auction limit selling prices are combined with individual subject choices over prospects, previous results like those of Grether and Plott (1979) are obtained. When ending Vickrey auction limit selling prices are combined with individual subject choices over prospects, the dollar magnitude of reversals declines significantly. These results imply that markets can be efficient and yield market clearing prices under a given arrangement of property rights even if the behavior of some individuals is inconsistent with expected utility theory.     

A penny for your thoughts: Inducing truth-telling in stated preference elicitation

Contingent valuation often induces hypothetical bias. In a laboratory experiment, we test three calibration mechanisms: cheap-talk, consequentialism, and a new mechanism, the Bayesian truth serum (“BTS”). We apply the BTS in a “faith-based” format: subjects are informed about the purpose and potential efficacy of the BTS, but not its theoretical foundations. We find that real and hypothetical responses differ significantly; real and consequentialist responses are statistically indistinguishable; cheap-talk and the BTS eliminate bias inconsistently; subject characteristics interact significantly with treatment.     

Modeling self-censoring of polluter pays protest votes in stated preference research to support resource damage estimations in environmental liability

The identification and treatment of protest response in stated preference (SP) research such as contingent valuation is an underdeveloped area. Protest related to the polluter pays principle (PPP) is expected to pose an important hurdle to the application of SP research in environmental liability claims, for instance under the European Environmental Liability Directive. Our main objective is to test the effect of PPP induced protest votes on welfare measures for lost passive use value using different treatment procedures. We argue for a more reliable and defensible indicator of willingness to pay (WTP) in environmental liability litigation cases than current standard removal practices in cases where protest votes affect sample representativeness. Analyzing the impact of PPP-based protest response on WTP values with the help of a Full Information Maximum Likelihood sample selection model, a significant correlation is found between the decision to participate in the CV market and the WTP bids. Self-censoring biases average WTP and is correlated with factors such as respondent use of the resource and disposition towards its future protection. Simply removing protest response from the sample is indefensible and results in a biased estimation of WTP.     

Relating environmental attitudes and contingent values: how robust are methods for identifying preference heterogeneity?

We assess the importance and robustness of cluster analysis and latent class analysis as methods to account for unobserved heterogeneity. We provide a critique and comparison of both methods in the context of measuring environmental attitudes and a contingent valuation study involving endangered species. We find strong evidence of robustness for these methods: group characterization and assignment of individuals to groups are similar between methods, and willingness-to-pay estimates are consistent. In addition, there are significant differences in willingness-to-pay across environmental attitudinal groups, and we find that accounting for unobservable heterogeneity provides a significantly better fitting model.     

Self-control,revealed preference and consumption choice

We provide a time-consistent model that addresses the preference reversals that motivate the time-inconsistency literature. The model subsumes the behavior generated by the time-inconsistency approach in finite settings but, unlike the time-inconsistent models, allows for self-control. This paper provides a brief summary of theoretical results shown elsewhere [Gul and Pesendorfer, Econometrica 69 (2001) 1403; Econometrica, (2002), in press; Rev. Econ. Stud. (2002), in press] and contrasts the predictions and welfare implications of our model and the time-inconsistent β−δ model.     

Locational choice of AFDC recipients within California: a conditional logit analysis

This paper examines factors that influence migration of AFDC recipients within California. A county level conditional logit model is used to analyze the impact of cost adjusted benefits on intrastate moves during recipients’ first year of welfare participation. Costs of living, particularly housing costs, differ considerably across counties of California, yet the welfare benefit is set at the state level. This creates the potential for variation in the purchasing power of the welfare benefit if a family chooses to move. Variation in cost of living is shown to have a significant effect on migration patterns of AFDC recipients. Estimates suggest that a $150 decrease in fair market rent results in 15% more migration to the county. Recipients’ migration is more responsive to cost of living than migration of the general population.     

Stochastic preference and randomized strategies for consumer choice

In this article a stochastic model of choice is developed that is based on game theory. The model is developed to demonstrate that a basic stochastic model can yield results similar to phenomena discovered in consumer behavior. In particular, a definition of brand loyalty is developed along with a basis for rational intransitivity of preferences, which is noted by brand switching. A measurement approach is also presented along with an example. The basic intent is to demonstrate that stochastic approaches to choice do have a foundation in both theoretical development beside observations in empirical studies.     

Valuing water level changes in reservoirs using two stated preference approaches: An exploration of validity

The combination of travel cost (TCM) and contingent behaviour (CB) methods is a relatively new research avenue in the recreational valuation community. Contrary to simple TCM applications, TCM-CB facilitates the ex ante valuation of marginal welfare effects resulting from environmental quality or quantity changes, similar to the contingent valuation method (CV). Even though TCM-CB is highly policy relevant, i.e. to inform changes in management regimes at recreational sites, the validity of estimates has hardly received any attention and little is known about the performance of TCM-CB compared to CV. In this paper, TCM-CB and CV are explored with respect to several validity tests in a case study on the recreational effects of water level changes in a reservoir. Overall, the findings reveal that TCM-CB and CV perform equally well in terms of theoretical validity, but that the marginal recreational value varies significantly between the two methods. We also observe that both methods face similar internal difficulties with respect to the stability of values when the order of a set of valuation questions is changed.     

Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles

According to intuition and theories of diffusion, consumer preferences develop along with technological change. However, most economic models designed for policy simulation unrealistically assume static preferences. To improve the behavioral realism of an energy–economy policy model, this study investigates the “neighbor effect,” where a new technology becomes more desirable as its adoption becomes more widespread in the market. We measure this effect as a change in aggregated willingness to pay under different levels of technology penetration. Focusing on hybrid-electric vehicles (HEVs), an online survey experiment collected stated preference (SP) data from 535 Canadian and 408 Californian vehicle owners under different hypothetical market conditions.Revealed preference (RP) data was collected from the same respondents by eliciting the year, make and model of recent vehicle purchases from regions with different degrees of HEV popularity: Canada with 0.17% new market share, and California with 3.0% new market share. We compare choice models estimated from RP data only with three joint SP–RP estimation techniques, each assigning a different weight to the influence of SP and RP data in coefficient estimates. Statistically, models allowing more RP influence outperform SP influenced models. However, results suggest that because the RP data in this study is afflicted by multicollinearity, techniques that allow more SP influence in the beta estimates while maintaining RP data for calibrating vehicle class constraints produce more realistic estimates of willingness to pay. Furthermore, SP influenced coefficient estimates also translate to more realistic behavioral parameters for CIMS, allowing more sensitivity to policy simulations.