IDEAS home Printed from https://ideas.repec.org/p/ags/iaae18/275957.html
   My bibliography  Save this paper

Consumer preferences and willingness to pay for Aflatoxin- Free Milk in Pakistan

Author

Listed:
  • Abedullah, A.
  • Kouser, S.
  • Ibrahim, M.

Abstract

Aflatoxins are highly toxic compounds in milk and pose serious risks to human health. Past studies have observed high concentration of aflatoxin in raw milk of Pakistan. Nonetheless, this study contributes by investigating consumers’ demand for aflatoxin-free raw milk. For this purpose, we conducted a discrete choice experiment with a random sample of 360 households drawn from three mega cities of Punjab province. Random parameter logit and latent class models are used to incorporate preference heterogeneity in the stated choice analysis. Empirical findings suggest that consumers want to pay a highest premium for milk having low concentration of aflatoxin. Based on these findings, we suggest that there is considerable scope for the rapid development of aflatoxin-free raw milk, even though it is marketed at prices that are significantly higher than current milk prices.

Suggested Citation

  • Abedullah, A. & Kouser, S. & Ibrahim, M., 2018. "Consumer preferences and willingness to pay for Aflatoxin- Free Milk in Pakistan," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275957, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae18:275957
    DOI: 10.22004/ag.econ.275957
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/275957/files/2383.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.275957?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. Ward, Patrick S. & Ortega, David L. & Spielman, David J. & Singh, Vartika, 2014. "Heterogeneous Demand for Drought-Tolerant Rice: Evidence from Bihar, India," World Development, Elsevier, vol. 64(C), pages 125-139.
    2. Shahzad Kouser & Matin Qaim, 2013. "Valuing financial, health, and environmental benefits of Bt cotton in Pakistan," Agricultural Economics, International Association of Agricultural Economists, vol. 44(3), pages 323-335, May.
    3. Junyi Shen & Yusuke Sakata & Yoshizo Hashimoto, 2006. "A Comparison between Latent Class Model and Mixed Logit Model for Transport Mode Choice: Evidences from Two Datasets of Japan," Discussion Papers in Economics and Business 06-05, Osaka University, Graduate School of Economics.
    4. Unknown, 2010. "Demand for livestock products in developing countries with a focus on quality and safety attributes: Evidence from case studies," Research Reports 97973, International Livestock Research Institute.
    5. Islam, S.M. Fakhrul & Jabbar, Mohammad A., 2010. "Consumer preferences and demand for livestock products in urban Bangladesh," Research Reports 97972, International Livestock Research Institute.
    6. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    8. Dalton, Timothy J. & Yesuf, Mahmud & Muhammad, Lutta, 2011. "Demand for Drought Tolerance in Africa: Selection of Drought Tolerant Maize Seed using Framed Field Experiments," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103712, Agricultural and Applied Economics Association.
    9. Banerji, A. & Chowdhury, Shyamal K. & de Groote, Hugo & Meenakshi, Jonnalagadda V. & Haleegoah, Joyce & Ewoo, Manfred, 2013. "Using elicitation mechanisms to estimate the demand for nutritious maize: Evidence from experiments in rural Ghana," HarvestPlus working papers 10, International Food Policy Research Institute (IFPRI).
    10. Walke, Maria & Mtimet, Nadhem & Baker, Derek & Lindahl, Johanna & Hartmann, Monika & Grace, Delia, 2014. "Kenyan perceptions of aflatoxin: an analysis of raw milk consumption," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182729, European Association of Agricultural Economists.
    11. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    12. Milon, J. Walter & Scrogin, David, 2006. "Latent preferences and valuation of wetland ecosystem restoration," Ecological Economics, Elsevier, vol. 56(2), pages 162-175, February.
    13. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
    14. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D., 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, September.
    15. Jayson L. Lusk & Jutta Roosen & John A. Fox, 2003. "Demand for Beef from Cattle Administered Growth Hormones or Fed Genetically Modified Corn: A Comparison of Consumers in France, Germany, the United Kingdom, and the United States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 16-29.
    16. Enoch M. Kikulwe & Ekin Birol & Justus Wesseler & José Falck‐Zepeda, 2011. "A latent class approach to investigating demand for genetically modified banana in Uganda," Agricultural Economics, International Association of Agricultural Economists, vol. 42(5), pages 547-560, September.
    17. Eric Ruto & Guy Garrod & Riccardo Scarpa, 2008. "Valuing animal genetic resources: a choice modeling application to indigenous cattle in Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 89-98, January.
    18. Dan Rigby & Michael Burton, 2005. "Preference heterogeneity and GM food in the UK," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 32(2), pages 269-288, June.
    19. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    20. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
    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. Sergio Colombo & Nick Hanley & Jordan Louviere, 2009. "Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 307-322, May.
    2. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    3. H. Holly Wang & Lu Liu & David L. Ortega & Yu Jiang & Qiujie Zheng, 2020. "Are smallholder farmers willing to pay for different types of crop insurance? An application of labelled choice experiments to Chinese corn growers," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(1), pages 86-110, January.
    4. Jae Eun You & Jong Woo Choi, 2022. "An analysis of food culture and technology acceptance for youth: Using a choice experiment and a latent class model," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(2), pages 510-522, March.
    5. Angel Bujosa & Antoni Riera & Robert Hicks, 2010. "Combining Discrete and Continuous Representations of Preference Heterogeneity: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 47(4), pages 477-493, December.
    6. Kikulwe, Enoch & Birol, Ekin & Wesseler, Justus & Falck-Zepeda, José, 2009. "A latent class approach to investigating consumer demand for genetically modified staple food in a developing country: The case of GM bananas in Uganda," IFPRI discussion papers 938, International Food Policy Research Institute (IFPRI).
    7. Eric Ruto & Riccardo Scarpa, 2010. "Using Choice Experiments to Investigate Preferences for Cattle Traits in Kenya," Chapters, in: Jeff Bennett & Ekin Birol (ed.), Choice Experiments in Developing Countries, chapter 14, Edward Elgar Publishing.
    8. Ortega, David L. & Wang, H. Holly & Wu, Laping & Olynk, Nicole J., 2011. "Modeling heterogeneity in consumer preferences for select food safety attributes in China," Food Policy, Elsevier, vol. 36(2), pages 318-324, April.
    9. Tonsor, Glynn T. & Olynk, Nicole & Wolf, Christopher, 2009. "Consumer Preferences for Animal Welfare Attributes: The Case of Gestation Crates," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(3), pages 713-730, December.
    10. Sarfo, Yaw & Musshoff, Oliver & Weber, Ron & Danne, Michael, 2021. "Farmers’ Willingness to Pay for Digital Credit: Evidence from a Discrete Choice Experiment in Madagascar," 2021 Conference, August 17-31, 2021, Virtual 315029, International Association of Agricultural Economists.
    11. Shijiu Yin & Shanshan Lv & Yusheng Chen & Linhai Wu & Mo Chen & Jiang Yan, 2018. "Consumer preference for infant milk‐based formula with select food safety information attributes: Evidence from a choice experiment in China," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 66(4), pages 557-569, December.
    12. Kikulwe, Enoch M. & Birol, Ekin & Wesseler, Justus & Falck-Zepeda, Jose Benjamin, 2013. "Benefits, costs, and consumer perceptions of the potential introduction of a fungus-resistant banana in Uganda and policy implications," IFPRI book chapters, in: Falck-Zepeda, Jose Benjamin & Gruère, Guillaume P. & Sithole-Niang, Idah (ed.), Genetically modified crops in Africa: Economic and policy lessons from countries south of the Sahara, chapter 4, pages 99-141, International Food Policy Research Institute (IFPRI).
    13. Yanling Peng & Yuansheng Jiang & Yu Hong, 2022. "Heterogeneous Preferences for Selecting Attributes of Farmland Management Right Mortgages in Western China: A Demand Perspective," Land, MDPI, vol. 11(8), pages 1-14, July.
    14. Birol, Ekin & Asare-Marfo, Dorene & Karandikar,Bhushana & Roy, Devesh, 2011. "A latent class approach to investigating farmer demand for biofortified staple food crops in developing countries: The case of high-iron pearl millet in Maharashtra, India," HarvestPlus working papers 7, International Food Policy Research Institute (IFPRI).
    15. Wang, Shuxian & Wu, Linhai & Zhu, Dian & Wang, Hongsha & Xu, Lingling, 2014. "Chinese consumers’ preferences and willingness to pay for traceable food attributes: The case of pork," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 165639, Agricultural and Applied Economics Association.
    16. Benoit Chèze & Charles Collet & Anthony Paris, 2021. "Estimating discrete choice experiments : theoretical fundamentals," CIRED Working Papers hal-03262187, HAL.
    17. Faustin, Vidogbèna & Adégbidi, Anselme A. & Garnett, Stephen T. & Koudandé, Delphin O. & Agbo, Valentin & Zander, Kerstin K., 2010. "Peace, health or fortune?: Preferences for chicken traits in rural Benin," Ecological Economics, Elsevier, vol. 69(9), pages 1848-1857, July.
    18. Andy S. Choi & Kelly S. Fielding, 2016. "Cultural Attitudes as WTP Determinants: A Revised Cultural Worldview Scale," Sustainability, MDPI, vol. 8(6), pages 1-18, June.
    19. Wu, Linhai & Wang, Shuxian & Zhu, Dian & Hu, Wuyang & Wang, Hongsha, 2015. "Chinese consumers’ preferences and willingness to pay for traceable food quality and safety attributes: The case of pork," China Economic Review, Elsevier, vol. 35(C), pages 121-136.
    20. Sardaro, Ruggiero & Faccilongo, Nicola & Roselli, Luigi, 2019. "Wind farms, farmland occupation and compensation: Evidences from landowners’ preferences through a stated choice survey in Italy," Energy Policy, Elsevier, vol. 133(C).

    More about this item

    Keywords

    Agricultural and Food Policy; International Development; Livestock Production/Industries;
    All these 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:iaae18:275957. 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/iaaeeea.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.