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Record W4385807954 · doi:10.1080/00036846.2023.2244255

It’s all relative: consistent marginal effects with willingness to pay and willingness to accept framing in experimental auctions

2023· article· en· W4385807954 on OpenAlexaff
Tongzhe Li, Laura A. Paul, Kent D. Messer, Harry M. Kaiser

Bibliographic record

VenueApplied Economics · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsWillingness to payWillingness to acceptEconomicsContingent valuationCommon value auctionFraming effectIncentive compatibilityFraming (construction)IncentiveMicroeconomicsEconometricsSocial psychologyPersuasionPsychology

Abstract

fetched live from OpenAlex

When eliciting consumer preferences for controversial products – an increasing number of which exist due to increasing demographic diversity and political polarization – conventional assumptions that all individuals derive positive marginal utility from consumption are challenged. It is relatively easy to adjust hypothetical stated preference questionnaires to include negative willingness to pay (WTP), but few studies on controversial products investigate how individuals behave using incentive-compatible revealed preference techniques. Using a framed field experiment with 292 adult subjects, we fill this gap by comparing the differences and similarities between a set of results that arise from the Becker-DeGroot-Marschak (BDM) mechanism between WTP versus willingness to accept (WTA) elicitation methods. This study has two main findings. First, in economic experiments eliciting preferences for controversial products, neither the WTP nor the WTA method fully discovers the true valuation range across all participants. Second, despite framing effects that give rise to different bid distributions, relative revealed preferences for the examined products are consistent under various interventions, indicating that WTP and WTA estimates have consistent policy implications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.234
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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