Crastes dit Sourd, R orcid.org/0000-0003-4506-2910 (2023) A new empirical approach for mitigating exploding implicit prices in mixed multinomial logit models. American Journal of Agricultural Economics. ISSN 0002-9092
Abstract
This paper introduces a new shifted negative log-normal distribution for the price parameter in mixed multinomial logit models. The new distribution, labeled as the μ-shifted negative log-normal distribution, has desirable properties for welfare analysis and in particular a point mass that is further away from zero than the negative log-normal distribution. This contributes to mitigating the “exploding” implicit prices issue commonly found when the price parameter is specified as negative log-normal and the model is in preference space. The new distribution is tested on five stated preference datasets. Comparisons are made with standard alternative approaches such as the willingness-to-pay (WTP) space approach. It is found that the μ-shifted distribution yields substantially lower mean marginal WTP estimates compared to the negative log-normal specification and similar to the values derived from models estimated in WTP-space with flexible distributions, while at the same time fitting the data as well as the negative log-normal specification.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) |
Keywords: | choice modeling, mixed logit, non-market valuation, random utility,utility in WTP-space |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Management Division Decision Research (LUBS) |
Depositing User: | Symplectic Publications |
Date Deposited: | 01 Feb 2023 11:14 |
Last Modified: | 01 Feb 2023 11:14 |
Published Version: | http://dx.doi.org/10.1111/ajae.12367 |
Status: | Published online |
Publisher: | Wiley |
Identification Number: | 10.1111/ajae.12367 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:195800 |