IDEAS home Printed from https://ideas.repec.org/p/ags/aaea26/404502.html

Meat Taxes and Protein Substitution in Digital Food Retail: Evidence from a Multi-Country Experiment

Author

Listed:
  • Sariman, Sevval Buse
  • Caputo, Vincenzina

Abstract

No abstract is available for this item.

Suggested Citation

  • Sariman, Sevval Buse & Caputo, Vincenzina, 2026. "Meat Taxes and Protein Substitution in Digital Food Retail: Evidence from a Multi-Country Experiment," 2026 Annual Meeting, July 26 - 28, 2026, Kansas City, Missouri 404502, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea26:404502
    DOI: 10.22004/ag.econ.404502
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/404502/files/177534_193561_115232_AAEA_paper_protein.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.404502?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Cerutti, Alessandro K. & Contu, Simone & Ardente, Fulvio & Donno, Dario & Beccaro, Gabriele L., 2016. "Carbon footprint in green public procurement: Policy evaluation from a case study in the food sector," Food Policy, Elsevier, vol. 58(C), pages 82-93.
    2. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    3. Marco Springmann & Daniel Mason-D’Croz & Sherman Robinson & Keith Wiebe & H Charles J Godfray & Mike Rayner & Peter Scarborough, 2018. "Health-motivated taxes on red and processed meat: A modelling study on optimal tax levels and associated health impacts," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-16, November.
    4. Caputo, Vincenzina & Lusk, Jayson L., 2022. "The Basket-Based Choice Experiment: A Method for Food Demand Policy Analysis," Food Policy, Elsevier, vol. 109(C).
    5. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Neill, Clinton L. & Lahne, Jacob, 2022. "Matching reality: A basket and expenditure based choice experiment with sensory preferences," Journal of choice modelling, Elsevier, vol. 44(C).
    2. Franceschinis, Cristiano & Scarpa, Riccardo & Thiene, Mara, 2024. "Nudging consumers’ choices for niche milk: A real purchase experiment," Food Policy, Elsevier, vol. 128(C).
    3. Clinton L. Neill & Logan L. Britton, 2026. "Are all meats substitutes? A basket‐and‐expenditure‐based approach," Agribusiness, John Wiley & Sons, Ltd., vol. 42(3), pages 954-974, July.
    4. Tobias Börger & Danny Campbell & Jürgen Meyerhoff & Malte Welling, 2026. "Preferences for Biodiversity-Promoting Private Garden Designs: A Basket-Based Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 89(1), pages 1-32, January.
    5. Cristiano Franceschinis & Riccardo Scarpa & Mara Thiene & Roselinde Kessels, 2025. "Individual preferences for food items within couples: Validating choice experiments predictions with real purchases data," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 69(1), pages 7-24, January.
    6. Bhat, Chandra R. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Aarti C., 2020. "A multiple discrete extreme value choice model with grouped consumption data and unobserved budgets," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 196-222.
    7. Pellegrini, Andrea & Rose, John Matthew, 2025. "On allowing endogenous minimum consumption bounds in the multiple discrete continuous choice model: An application to expenditure patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 193(C).
    8. Fang, Hao Audrey, 2008. "A discrete-continuous model of households' vehicle choice and usage, with an application to the effects of residential density," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 736-758, November.
    9. Yu, Biying & Zhang, Junyi & Fujiwara, Akimasa, 2011. "Representing in-home and out-of-home energy consumption behavior in Beijing," Energy Policy, Elsevier, vol. 39(7), pages 4168-4177, July.
    10. Tapia, Rodrigo J. & de Jong, Gerard & Larranaga, Ana M. & Bettella Cybis, Helena B., 2020. "Application of MDCEV to infrastructure planning in regional freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 255-271.
    11. Kumar Dey, Bibhas & Anowar, Sabreena & Eluru, Naveen, 2021. "A framework for estimating bikeshare origin destination flows using a multiple discrete continuous system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 119-133.
    12. Wu, Guoqiang & Hong, Jinhyun, 2022. "An analysis of the role of residential location on the relationships between time spent online and non-mandatory activity-travel time use over time," Journal of Transport Geography, Elsevier, vol. 102(C).
    13. Bhat, Chandra R., 2018. "A new flexible multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 261-279.
    14. Jing Li & Edward C. Jaenicke & Tobenna D. Anekwe & Alessandro Bonanno, 2018. "Demand for ready‐to‐eat cereals with household‐level censored purchase data and nutrition label information: A distance metric approach," Agribusiness, John Wiley & Sons, Ltd., vol. 34(4), pages 687-713, October.
    15. Fenichel, Eli P. & Abbott, Joshua K., 2014. "Heterogeneity and the fragility of the first best: Putting the “micro” in bioeconomic models of recreational resources," Resource and Energy Economics, Elsevier, vol. 36(2), pages 351-369.
    16. Pellegrini, Andrea & Pinjari, Abdul Rawoof & Maggi, Rico, 2021. "A multiple discrete continuous model of time use that accommodates non-additively separable utility functions along with time and monetary budget constraints," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 37-53.
    17. Sikder, Sujan & Pinjari, Abdul Rawoof, 2013. "The benefits of allowing heteroscedastic stochastic distributions in multiple discrete-continuous choice models," Journal of choice modelling, Elsevier, vol. 9(C), pages 39-56.
    18. Liao, Fanchao & Dissanayake, Dilum & Homem de Almeida Correia, Gonçalo, 2024. "Modelling the complementarity and flexibility between different shared modes available in smart electric mobility hubs (eHUBS)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
    19. Khan, Mubassira & Machemehl, Randy, 2017. "Commercial vehicles time of day choice behavior in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 68-83.
    20. Khandker Habib, 2011. "A random utility maximization (RUM) based dynamic activity scheduling model: Application in weekend activity scheduling," Transportation, Springer, vol. 38(1), pages 123-151, January.

    More about this item

    Keywords

    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea26:404502. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.