IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0223436.html
   My bibliography  Save this article

Bull efficiency using dairy genetic traits

Author

Listed:
  • Christine E Whitt
  • Loren W Tauer
  • Heather Huson

Abstract

Dairy bulls are evaluated using progeny data and genomic testing to determine the quantity of specific traits that they will pass to their daughters. Some bulls excel in some traits but not others. Specifying these various traits as outputs, with the single input of insemination, technical, revenue, allocative, and profit efficiency of bulls available for artificial insemination are estimated using Free Disposal Hull. Although bulls generally are highly technically efficient, because only high performing bull semen is offered for sale, bulls are less revenue, allocative and profit efficient. These efficiencies are relative to peer bulls and can be updated as new bulls become available.

Suggested Citation

  • Christine E Whitt & Loren W Tauer & Heather Huson, 2019. "Bull efficiency using dairy genetic traits," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-14, November.
    • Handle: RePEc:plo:pone00:0223436
    DOI: 10.1371/journal.pone.0223436
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223436
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0223436&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0223436?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. Lawton L. Nalley & Andrew P. Barkley & Allen M. Featherstone, 2010. "The genetic and economic impact of the CIMMYT wheat breeding program on local producers in the Yaqui Valley, Sonora Mexico," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 453-462, September.
    2. Loren Tauer, 2001. "Input aggregation and computed technical efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 8(5), pages 295-297.
    3. Edward C. Jaenicke & Laura L. Lengnick, 1999. "A Soil-Quality Index and Its Relationship to Efficiency and Productivity Growth Measures: Two Decompositions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 881-893.
    4. Bruce A. Babcock & William E. Foster, 1991. "Measuring the Potential Contribution of Plant Breeding to Crop Yields: Flue-Cured Tobacco, 1954–87," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(3), pages 850-859.
    5. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    6. Kerr, William A., 1984. "Selective Breeding, Heritable Characteristics And Genetic-Based Technological Change In The Canadian Beef Cattle Industry," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 9(01), pages 1-15, July.
    7. Daniel Atsbeha & Dadi Kristofersson & Kyrre Rickertsen, 2015. "Broad breeding goals and production costs in dairy farming," Journal of Productivity Analysis, Springer, vol. 43(3), pages 403-415, June.
    8. Timothy J. Richards & Scott R. Jeffrey, 1996. "Establishing Indices of Genetic Merit Using Hedonic Pricing: An Application to Dairy Bulls in Alberta," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 44(3), pages 251-264, November.
    9. Taciana Mareth & Antônio Márcio Tavares Thomé & Luiz Felipe Scavarda & Fernando Luiz Cyrino Oliveira, 2017. "Technical efficiency in dairy farms," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 66(3), pages 380-404, March.
    10. 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.
    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. Hutchins, Jared P. & Gong, Yating & Du, Xiaodong, 2021. "The Role of Animal Breeding in Productivity Growth: Evidence from Wisconsin Dairy Farms," 2021 Annual Meeting, August 1-3, Austin, Texas 313882, Agricultural and Applied Economics Association.
    2. Ali, Beshir M. & de Mey, Yann & Oude Lansink, Alfons G.J.M., 2021. "The effect of farm genetics expenses on dynamic productivity growth," European Journal of Operational Research, Elsevier, vol. 290(2), pages 701-717.
    3. 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.
    4. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
    5. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, August.
    6. Kerstin Enflo & Per Hjertstrand, 2009. "Relative Sources of European Regional Productivity Convergence: A Bootstrap Frontier Approach," Regional Studies, Taylor & Francis Journals, vol. 43(5), pages 643-659.
    7. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    8. H Fukuyama & W L Weber, 2009. "Estimating indirect allocative inefficiency and productivity change," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1594-1608, November.
    9. María Victoria Uribe‐Bohorquez & Jennifer Martínez‐Ferrero & Isabel‐María García‐Sánchez, 2019. "Women on boards and efficiency in a business‐orientated environment," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 26(1), pages 82-96, January.
    10. Oleg Badunenko & Daniel Henderson & Romain Houssa, 2014. "Significant drivers of growth in Africa," Journal of Productivity Analysis, Springer, vol. 42(3), pages 339-354, December.
    11. Esso-Hanam Atake, 2017. "Sustaining Gains in Health Programs: Technical Efficiency and its Determinants in Malaria Programs in Sub-Saharan Africa," Applied Health Economics and Health Policy, Springer, vol. 15(2), pages 249-259, April.
    12. Alfred A. Haug & Vincent C. Blackburn, 2017. "Government secondary school finances in New South Wales: accounting for students’ prior achievements in a two-stage DEA at the school level," Journal of Productivity Analysis, Springer, vol. 48(1), pages 69-83, August.
    13. Fadzlan Sufian & Fakarudin Kamarudin, 2014. "The impact of ownership structure on bank productivity and efficiency: Evidence from semi-parametric Malmquist Productivity Index," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-27, December.
    14. Alessandra Cepparulo & Gilles Mourre, 2020. "How and How Much? The Growth-Friendliness of Public Spending through the Lens," European Economy - Discussion Papers 132, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    15. Lyman, Nathaniel & Nalley, Lawton Lanier, 2013. "Stochastic Valuation of Hybrid Rice Technology in Arkansas," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 142505, Southern Agricultural Economics Association.
    16. Nguyen, Bao Hoang & Simar, Léopold & Zelenyuk, Valentin, 2022. "Data sharpening for improving central limit theorem approximations for data envelopment analysis–type efficiency estimators," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1469-1480.
    17. I. Fraser & W. Horrace, 2003. "Technical Efficiency of Australian Wool Production: Point and Confidence Interval Estimates," Journal of Productivity Analysis, Springer, vol. 20(2), pages 169-190, September.
    18. Daniel Adelman, 2020. "An Efficient Frontier Approach to Scoring and Ranking Hospital Performance," Operations Research, INFORMS, vol. 68(3), pages 762-792, May.
    19. Nolwenn Roudaut & Anne Vanhems, 2012. "Explaining firms efficiency in the Ivorian manufacturing sector: a robust nonparametric approach," Journal of Productivity Analysis, Springer, vol. 37(2), pages 155-169, April.
    20. Isabel-María García-Sánchez & Luis Rodríguez-Domínguez & Javier Parra-Domínguez, 2013. "Yearly evolution of police efficiency in Spain and explanatory factors," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(1), pages 31-62, January.

    More about this item

    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:plo:pone00:0223436. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.