45 research outputs found

    A comparison of approaches to estimating confidence intervals for willingness to pay measures

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    This paper describes three approaches to estimating confidence intervals for willingness to pay measures, the delta, Krinsky and Robb and bootstrap methods. The accuracy of the various methods is compared using a number of simulated datasets. In the majority of the scenarios considered all three methods are found to be reasonably accurate as well as yielding similar results. The delta method is the most accurate when the data is well-conditioned, while the bootstrap is more robust to noisy data and misspecification of the model. These conclusions are illustrated by empirical data from a study of willingness to pay for a reduction in waiting time for a general practitioner appointment in which all the methods produce fairly similar confidence intervals.willingness to pay, confidence interval, delta method, boot-strap

    Small-sample properties of tests for heteroscedasticity in the conditional logit model

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    This paper compares the small-sample properties of several asymptotically equivalent tests for heteroscedasticity in the conditional logit model. While no test outperforms the others in all of the experiments conducted, the likelihood ratio test and a particular variety of the Wald test are found to have good properties in moderate samples as well as being relatively powerful.

    Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment.

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    Different approaches to modelling the distribution of WTP are compared using stated preference data on Tanzanian Clinical Officers’ job choices and mixed logit models. The standard approach of specifying the distributions of the coefficients and deriving WTP as the ratio of two coefficients estimation in preference space) is compared to specifying the distributions for WTP directly at the estimation stage (estimation in WTP space). The models in preference space fit the data better than the corresponding models in WTP space although the difference between the best fitting models in the two estimation regimes is minimal. Moreover, the willingness to pay estimates derived from the preference space models turn out to be unrealistically high for many of the job attributes. The results suggest that sensitivity testing using a variety of model specifications, including estimation in WTP space, is recommended when using mixed logit models to estimate willingness to pay distributions.WTP space; Stated preference methods; Discrete choice; Mixed logit; Willingness to pay*

    Tests for the consistency of three-level nested logit models with utility maximization.

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    This paper provides necessary conditions for testing the local consistency of three-level nested logit models with random utility maximization. We find that for a model with two sub-nests per nest the conditions can lead to a substantial increase in the range of acceptable dissimilarity parameters, irrespective of the number of alternatives per sub-nest.Nested logit, Discrete choice, Random utility maximization

    GPs' implicit prioritization through clinical choices – evidence from three national health services

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    Acknowledgments The authors are grateful for valuable comments and inputs from participants at a series of seminars and conferences as well as to our three anonymous referees.Peer reviewedPostprin

    Valuation of small and multiple health risks: A critical analysis of SP data applied to food and water safety

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    This study elicits individual preferences for reducing morbidity and mortality risk in the context of an infectious disease (campylobacter) using choice experiments. Respondents are in the survey asked to choose between different policies that, in addition to the two health risks, also vary with respect to source of disease being targeted (food or water), when the policy takes place (in time), and the monetary cost. Our results in our baseline model are in line with expectations; respondents prefer the benefits of the program sooner than later, programs that reduce both the mortality and morbidity risk, and less costly programs. Moreover, our results suggest that respondents prefer water- compared with food-safety programs. However, a main objective of this study is to examine scope sensitivity of mortality risk reductions using a novel approach. Our results from a split-sample design suggest that the value of the mortality risk reduction, defined as the value of a statistical life, is SEK 3 177 (USD 483 million) and SEK 50 million (USD 8 million), respectively, in our two sub-samples. This result cast doubt on the standard scope sensitivity tests in choice experiments, and the results also cast doubt on the validity and reliability of VSL estimates based on stated preference (and revealed preference) studies in general. This is important due to the large empirical literature on non-market evaluation and the elicited values’ central role in policy making, such as benefit-cost analysis
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