IDEAS home Printed from https://ideas.repec.org/a/oup/erevae/v43y2016i2p331-358..html
   My bibliography  Save this article

Somatic cell counts in dairy marketing: quantile regression for count data

Author

Listed:
  • Richard J. Volpe
  • Timothy A. Park
  • Fengxia Dong
  • Helen H. Jensen

Abstract

We study the determinants of somatic cell count (SCC) for farm milk among US dairies. We synthesise much of the work that has been done to model SCC determinants in order to identify the potential impacts of buyer-imposed penalties and incentives within the supply chain. Additionally, we estimate quantile regression for count data to measure impacts specifically for those operations with the highest SCC and to account for the statistical properties of the data. Premiums in particular have the potential to reduce SCC considerably where it is currently the highest. We draw implications for profitability in relation to SCC reduction.

Suggested Citation

  • Richard J. Volpe & Timothy A. Park & Fengxia Dong & Helen H. Jensen, 2016. "Somatic cell counts in dairy marketing: quantile regression for count data," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(2), pages 331-358.
    • Handle: RePEc:oup:erevae:v:43:y:2016:i:2:p:331-358.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/erae/jbv021
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Johannes Sauer & David Zilberman, 2012. "Sequential technology implementation, network externalities, and risk: the case of automatic milking systems," Agricultural Economics, International Association of Agricultural Economists, vol. 43(3), pages 233-252, May.
    2. Machado, Jose A.F. & Silva, J. M. C. Santos, 2005. "Quantiles for Counts," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1226-1237, December.
    3. Hsiao, Cheng & Nugent, Jeffrey & Perrigne, Isabelle & Qiu, Jicheng, 1998. "Shares versus Residual Claimant Contracts: The Case of Chinese TVEs," Journal of Comparative Economics, Elsevier, vol. 26(2), pages 317-337, June.
    4. Alfonso Miranda, 2008. "Planned fertility and family background: a quantile regression for counts analysis," Journal of Population Economics, Springer;European Society for Population Economics, vol. 21(1), pages 67-81, January.
    5. William D. McBride & Catherine Greene, 2009. "Costs of Organic Milk Production on U.S. Dairy Farms," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(4), pages 793-813, December.
    6. Joseph V. Balagtas & Aaron Smith & Daniel A. Sumner, 2007. "Effects of Milk Marketing Order Regulation on the Share of Fluid-Grade Milk in the United States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(4), pages 839-851.
    7. Richard Bennett, 2003. "The ‘Direct Costs’of Livestock Disease: The Development of a System of Models for the Analysis of 30 Endemic Livestock Diseases in Great Britain," Journal of Agricultural Economics, Wiley Blackwell, vol. 54(1), pages 55-71, March.
    8. D. F. Benoit & D. Van Den Poel, 2009. "Benefits of Quantile Regression for the Analysis of Customer Lifetime Value in a Contractual Setting: An Application in Financial Services," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/551, Ghent University, Faculty of Economics and Business Administration.
    9. Greene, Catherine R. & Dimitri, Carolyn & Lin, Biing-Hwan & McBride, William D. & Oberholtzer, Lydia & Smith, Travis A., 2009. "Emerging Issues in the U.S. Organic Industry," Economic Information Bulletin 58617, United States Department of Agriculture, Economic Research Service.
    10. Winkelmann, Rainer, 2006. "Reforming health care: Evidence from quantile regressions for counts," Journal of Health Economics, Elsevier, vol. 25(1), pages 131-145, January.
    11. Richard J. Sexton, 2013. "Market Power, Misconceptions, and Modern Agricultural Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 209-219.
    12. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    13. Arthur Lewbel, 1997. "Constructing Instruments for Regressions with Measurement Error when no Additional Data are Available, with an Application to Patents and R&D," Econometrica, Econometric Society, vol. 65(5), pages 1201-1214, September.
    14. Wayne H. Howard & Ravinderpal Gill & Kenneth E. Leslie & Kerry Lissemore, 1991. "Monitoring and Controlling Mastitis on Ontario Dairy Farms," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 39(2), pages 299-318, July.
    15. Daniel Muluwork Atsbeha & Dadi Kristofersson & Kyrre Rickertsen, 2012. "Animal Breeding and Productivity Growth of Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(4), pages 996-1012.
    16. Richard Bennett & Jos IJpelaar, 2005. "Updated Estimates of the Costs Associated with Thirty Four Endemic Livestock Diseases in Great Britain: A Note," Journal of Agricultural Economics, Wiley Blackwell, vol. 56(1), pages 135-144, March.
    17. MacDonald, James M. & O'Donoghue, Erik J. & McBride, William D. & Nehring, Richard F. & Sandretto, Carmen L. & Mosheim, Roberto, 2007. "Profits, Costs, and the Changing Structure of Dairy Farming," Economic Research Report 6704, United States Department of Agriculture, Economic Research Service.
    18. Dong, Fengxia & Hennessy, David A. & Jensen, Helen H., 2012. "Factors determining milk quality and implications for production structure under somatic cell count standard modification," Staff General Research Papers Archive 35608, Iowa State University, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Doris Läpple & Garth Holloway & Donald J Lacombe & Cathal O’Donoghue, 2017. "Sustainable technology adoption: a spatial analysis of the Irish Dairy Sector," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(5), pages 810-835.

    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. Popp, David & Santen, Nidhi & Fisher-Vanden, Karen & Webster, Mort, 2013. "Technology variation vs. R&D uncertainty: What matters most for energy patent success?," Resource and Energy Economics, Elsevier, vol. 35(4), pages 505-533.
    2. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    3. Moreira S & Pita Barros P, 2009. "Double coverage and demand for health care: Evidence from quantile regression," Health, Econometrics and Data Group (HEDG) Working Papers 09/21, HEDG, c/o Department of Economics, University of York.
    4. Viviana Carcaiso & Leonardo Grilli, 2023. "Quantile regression for count data: jittering versus regression coefficients modelling in the analysis of credits earned by university students after remote teaching," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(4), pages 1061-1082, October.
    5. Georgios Papadopoulos, 2013. "Immigration Status and Victimization: Evidence from the British Crime Survey," University of East Anglia Applied and Financial Economics Working Paper Series 042, School of Economics, University of East Anglia, Norwich, UK..
    6. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly & Kaspar Wüthrich, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 123-137, January.
    7. Gramig, Benjamin M. & Horan, Richard D., 2011. "Jointly determined livestock disease dynamics and decentralised economic behavior," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(3), pages 1-18, September.
    8. Munasib, Abdul B.A. & Jordan, Jeffrey L., 2011. "The Effect of Social Capital on the Choice to Use Sustainable Agricultural Practices," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 43(2), pages 213-227, May.
    9. Luke B. Smith & Brian J. Reich & Amy H. Herring & Peter H. Langlois & Montserrat Fuentes, 2015. "Multilevel quantile function modeling with application to birth outcomes," Biometrics, The International Biometric Society, vol. 71(2), pages 508-519, June.
    10. Clatworthy, Mark A. & Peel, Michael J., 2016. "The timeliness of UK private company financial reporting: Regulatory and economic influences," The British Accounting Review, Elsevier, vol. 48(3), pages 297-315.
    11. J. Jobu Babin & Haritima S. Chauhan, 2023. "Show no quarter: combating plausible lies with ex-ante honesty oaths," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 9(1), pages 66-76, June.
    12. Toni Mora, 2008. "The relevance of satisfaction with coverage for health care utilization: evidence from Catalonia," Hacienda Pública Española / Review of Public Economics, IEF, vol. 184(1), pages 99-116, April.
    13. Ireneous N Soyiri & Daniel D Reidpath, 2013. "The Use of Quantile Regression to Forecast Higher Than Expected Respiratory Deaths in a Daily Time Series: A Study of New York City Data 1987-2000," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-1, October.
    14. Alguacil, Maite & Martí, Josep & Orts, Vicente, 2017. "Firm heterogeneity and the market scope of European multinational activity," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 645-659.
    15. Alyson S Barratt & Matthieu H Arnoult & Bouda Vosough Ahmadi & Karl M Rich & George J Gunn & Alistair W Stott, 2018. "A framework for estimating society's economic welfare following the introduction of an animal disease: The case of Johne's disease," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-26, June.
    16. Fuzi, Mohd Fadzli Mohd & Jemain, Abdul Aziz & Ismail, Noriszura, 2016. "Bayesian quantile regression model for claim count data," Insurance: Mathematics and Economics, Elsevier, vol. 66(C), pages 124-137.
    17. Meager, Rachael & Sturdy, Jennifer, 2017. "Aggregating Distributional Treatment Effects: A Bayesian Hierarchical Analysis of the Microcredit Literature," MetaArXiv 7tkvm, Center for Open Science.
    18. Mußhoff, Oliver & Grüner, Sven & Hirschauer, Norbert, 2014. "Muss man begrenzte Rationalität und heuristisches Entscheiden bei der Erklärung für die Verbreitung von Wetterindexversicherungen in der Landwirtschaft berücksichtigen? – Eine Untersuchung auf der Bas," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 63(02), pages 1-14, March.
    19. Maximilian Koppenberg, 2023. "Markups, organic agriculture and downstream concentration at the example of European dairy farmers," Agricultural Economics, International Association of Agricultural Economists, vol. 54(2), pages 161-178, March.
    20. Nemet, Gregory F., 2012. "Inter-technology knowledge spillovers for energy technologies," Energy Economics, Elsevier, vol. 34(5), pages 1259-1270.

    More about this item

    JEL classification:

    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

    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:oup:erevae:v:43:y:2016:i:2:p:331-358.. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.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.