Fat Tails, Flat Tails, and Willingness to Pay: Kriström Revisited

This article explores the limitations of two commonly used nonparametric approaches: the Turnbull estimator and the Kriström estimator. Fat tails and flat tails in the distribution of bid responses can result in a large divergence in willingness-to-pay estimates across different estimation methods. Since it is extremely rare to capture the tail of the distribution, we highlight the merit of an alternative approach using 120 datasets drawn from the literature. We calculate four nonparametric estimates of willingness to pay for each dataset. Meta-analysis is used to help determine when the Turnbull and Kriström estimators diverge.

Publication Details

Journal
Project Muse (Johns Hopkins University)
Published
2024-10-06
Primary Topic
Magnetic confinement fusion research
Type
article
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article

Fat Tails, Flat Tails, and Willingness to Pay: Kriström Revisited

Project Muse (Johns Hopkins University)
Magnetic confinement fusion research
article

Fat Tails, Flat Tails, and Willingness to Pay: Kriström Revisited

article en

Abstract

This article explores the limitations of two commonly used nonparametric approaches: the Turnbull estimator and the Kriström estimator. Fat tails and flat tails in the distribution of bid responses can result in a large divergence in willingness-to-pay estimates across different estimation methods. Since it is extremely rare to capture the tail of the distribution, we highlight the merit of an alternative approach using 120 datasets drawn from the literature. We calculate four nonparametric estimates of willingness to pay for each dataset. Meta-analysis is used to help determine when the Turnbull and Kriström estimators diverge.

Project Muse (Johns Hopkins University)
Openalex Percentile: Top 75%
Magnetic confinement fusion research
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Fat Tails, Flat Tails, and Willingness to Pay: Kriström Revisited · Project Muse (Johns Hopkins University) (2024) | TGRS Research Map | TGRS