Dynamic Learning and Context-Dependence in Sequential, Attribute-Based, Stated-Preference Valuation Questions

Holmes, Thomas P.; Boyle, Kevin J.

doi:10.3368/le.81.1.114

Cited by 94 publications

(70 citation statements)

References 27 publications

(26 reference statements)

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“…In previous studies either the number of attributes or the number of choice tasks are considerably higher. In terms of choice tasks, our study is closest to the one conducted by Holmes and Boyle (2005). They use eight attributes of which seven are statistically significant at the 10% level in the context of forest management, which may have been an important driving force behind the preference structure dynamics found in their study.…”

Section: Discussionmentioning

confidence: 85%

“…2 If the scale increases, variance decreases: that is, people are making a more accurate choice between the presented alternatives. Obtaining estimates for the scale parameter therefore provides more insight into preference refinement during a choice sequence (Holmes and Boyle 2005). Our first hypothesis of preference refinement predicts an increase in the scale parameter over the choice sequence, while our second hypothesis concerns the stability of the preference parameters.…”

Section: Econometric Modeling Of Preference Refinement In Choice Expementioning

confidence: 99%

“…However, the use of CE to test preference learning, preference stability and choice consistency is limited (e.g. Brazell and Louviere 1998;Dellaert et al 1999;DeShazo and Fermo 2002;Holmes and Boyle 2005;Ladenburg and Olsen 2008;Savage and Waldman 2008;Rose et al 2009). …”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Preference learning can also be measured through the stochastic term as making more precise choices reduces the variance of the stochastic term. Highly uncertain respondents are expected to make random choices, reflected by widely distributed utility functions (Holmes and Boyle 2005). The main objective of this study is to examine how repeated choice affects preference learning.…”

mentioning

confidence: 99%

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Choice Certainty and Consistency in Repeated Choice Experiments

Brouwer

Dekker

Rolfe

et al. 2009

Environ Resource Econ

118

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The main objective of this study is to examine how repeated choice affects preference learning in stated preference experiments. We test different hypotheses related to preference learning by analyzing response patterns and asking respondents in a choice experiment to report their experienced certainty when going through the choice tasks. In a split-sample test, we show that follow-up choice certainty questions are procedural invariant. The self-reported certainty results indicate that learning occurs, but econometric testing procedures do not identify any significant impact of learning effects on parameter estimates or variance across choice tasks. Additional tests of choice consistency suggest that preferences in the choice experiment are stable and coherent.

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Section: Discussionmentioning

confidence: 85%

Section: Econometric Modeling Of Preference Refinement In Choice Expementioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

mentioning

confidence: 99%

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Choice Certainty and Consistency in Repeated Choice Experiments

Brouwer

Dekker

Rolfe

et al. 2009

Environ Resource Econ

118

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“…2 Differences in scale between both the test and the retest might be caused by effects such as learning, fatigue, complexity and consistency as various studies have shown (e.g. Breffle and Rowe 2002;Holmes and Boyle 2005;Campbell et al 2008;Carlsson et al 2012). In the present case a learning effect might occur as respondents face the same choice sets a second time.…”

Section: Parametric Analysis and Willingness-to-pay Estimatesmentioning

confidence: 89%

Test–Retest Reliability of Choice Experiments in Environmental Valuation

Liebe

Meyerhoff

Hartje

2012

Environ Resource Econ

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The paper presents the results of the first test-retest study on choice experiments in environmental valuation. In a survey concerning landscape externalities of onshore wind power in central Germany, respondents answered the same five choice sets at two different points in time. Each choice set comprised three alternatives described by five attributes, and the time interval between the test and the retest was eleven months. The analysis takes place at three different levels, investigating choice consistency at the choice task level and repeatability of the latent construct utility at the level of parametric models as well as at the level of willingness-to-pay estimates. At the choice task level we observed 59 % identical choices. The parametric analysis shows that the test and retest estimates are not equal, even when we control for scale, that is, differences in the error variance. However, comparing the marginal willingness-to-pay estimates among test and retest reveals only a statistically significant difference for one of the attributes. Overall, this indicates a moderate test-retest reliability taking into account that consistency at the choice task level overlooks the stochastic nature of the process underlying discrete choice experiments.

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Performance-based Labeling

Hicks

2007

New Frontiers in Environmental and Social Labeling

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Dynamic Learning and Context-Dependence in Sequential, Attribute-Based, Stated-Preference Valuation Questions

Cited by 94 publications

References 27 publications

Choice Certainty and Consistency in Repeated Choice Experiments

Choice Certainty and Consistency in Repeated Choice Experiments

Test–Retest Reliability of Choice Experiments in Environmental Valuation

Performance-based Labeling

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