A Random Coefficients Model of Seafood Demand: Implications for Consumer Preferences and Substitution Patterns

Ray, Kevin D.; Lew, Daniel K.; Kosaka, Rosemary

doi:10.1086/723730

i

A Random Coefficients Model of Seafood Demand: Implications for Consumer Preferences and Substitution Patterns

2023
By Ray, Kevin D. ; Lew, Daniel K. ; Kosaka, Rosemary

Details

Journal Title:

Marine Resource Economics
Personal Author:

Ray, Kevin D. ; Lew, Daniel K. ; Kosaka, Rosemary
NOAA Program & Office:

NMFS (National Marine Fisheries Service) ; AFSC (Alaska Fisheries Science Center) ; SWFSC (Southwest Fisheries Science Center)
Description:

Discrete choice models of demand are growing in popularity for understanding markets for seafood, but have thus far been limited to applications using individual-level choice data. The random coefficients logit model is a discrete choice demand model designed for aggregate sales data and imparts a number of theoretical and empirical advantages. Instrumental variables account for price endogeneity, which can arise when there are unobserved product characteristics. Furthermore, correlated preferences can be accommodated in the random coefficients as well as through demographic interactions, which is especially important for seafood where product characteristics are primarily qualitative. We estimate this model for salmon fillets using four years of county-level seafood sales in California, and demonstrate the insights that can be drawn regarding consumer preferences and substitution patterns. Although the model is computationally burdensome, it offers considerable potential for further seafood demand analysis.
Keywords:

Economics And Econometrics Geography, Planning And Development Management, Monitoring, Policy And Law Oceanography Economics And Econometrics Geography, Planning And Development Management, Monitoring, Policy And Law Economics And Econometrics Geography, Planning And Development Management, Monitoring, Policy And Law
Source:

Marine Resource Economics, 38(2), 113-133
DOI:

https://doi.org/10.1086/723730
ISSN:

0738-1360 ; 2334-5985
Format:

PDF
Publisher:

University of Chicago Press
Document Type:

Journal Article
License:

https://creativecommons.org/publicdomain/zero/1.0/
Rights Information:

CC0 Public Domain
Compliance:

Submitted
Main Document Checksum:

urn:sha256:10bc5c52b61fed7e194103d38c4bc63a1373029d5e2b59705f20e19d5f50367b
Download URL:

https://repository.library.noaa.gov/view/noaa/49759/noaa_49759_DS1.pdf
File Type:

[PDF - 312.42 KB ]

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