IDEAS home Printed from https://ideas.repec.org/a/wly/ajagec/v106y2024i1p286-305.html
   My bibliography  Save this article

The role of animal breeding in productivity growth: Evidence from Wisconsin dairy farms

Author

Listed:
  • Jared Hutchins
  • Yating Gong
  • Xiaodong Du

Abstract

We examine the relationship between investments in animal breeding and productivity growth on Wisconsin dairy farms using a control function approach. We incorporate farm‐level annual investment in breeding and genetics into the law of motion of productivity as in De Loecker (2013) to test the relationship between these investments and realized productivity. Our unique dataset also allows us to look at the effect of choosing bulls with high milk yield potential on productivity. Our results indicate that breeding investments made 3 years prior are associated with higher productivity of the current cohort. However, the farms with the highest level of productivity reap the lowest benefits from breeding investments, suggesting that there are diminishing returns to investing in genetics. When milk output is not quality adjusted, the contribution of breeding to productivity is undetectable, suggesting that breeding and investments in milk quality are related. We conclude that investments in breeding and genetics significantly contribute to dairy farm productivity, especially in terms of milk quality.

Suggested Citation

  • Jared Hutchins & Yating Gong & Xiaodong Du, 2024. "The role of animal breeding in productivity growth: Evidence from Wisconsin dairy farms," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(1), pages 286-305, January.
  • Handle: RePEc:wly:ajagec:v:106:y:2024:i:1:p:286-305
    DOI: 10.1111/ajae.12374
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ajae.12374
    Download Restriction: no

    File URL: https://libkey.io/10.1111/ajae.12374?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. Jan De Loecker, 2011. "Product Differentiation, Multiproduct Firms, and Estimating the Impact of Trade Liberalization on Productivity," Econometrica, Econometric Society, vol. 79(5), pages 1407-1451, September.
    2. Deep Mukherjee & Boris E. Bravo-Ureta & Albert De Vries, 2013. "Dairy productivity and climatic conditions: econometric evidence from South-eastern United States," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(1), pages 123-140, January.
    3. Barrett E. Kirwan & Shinsuke Uchida & T. Kirk White, 2012. "Aggregate and Farm-Level Productivity Growth in Tobacco: Before and After the Quota Buyout," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(4), pages 838-853.
    4. Paul L. E. Grieco & Shengyu Li & Hongsong Zhang, 2016. "Production Function Estimation With Unobserved Input Price Dispersion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57, pages 665-690, May.
    5. Hall, Robert E, 1988. "The Relation between Price and Marginal Cost in U.S. Industry," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 921-947, October.
    6. repec:zwi:journl:v:57:y:2013:i:1:p:123-140 is not listed on IDEAS
    7. 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.
    8. Fabian Frick & Johannes Sauer, 2018. "Deregulation and Productivity: Empirical Evidence on Dairy Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(1), pages 354-378.
    9. Heesun Jang & Xiaodong Du, 2019. "Evolving techniques in production function identification illustrated in the case of the US dairy," Applied Economics, Taylor & Francis Journals, vol. 51(14), pages 1463-1477, March.
    10. Paul L. E. Grieco & Shengyu Li & Hongsong Zhang, 2016. "Production Function Estimation With Unobserved Input Price Dispersion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 665-690, May.
    11. Townsend, Robert & Thirtle, Colin, 2001. "Is livestock research unproductive?: Separating health maintenance from improvement research," Agricultural Economics, Blackwell, vol. 25(2-3), pages 177-189, September.
    12. Hutchins, Jared & Hueth, Brent, 2021. "Supply Response in Dairy Farming: Evidence from Monthly, Animal-Level Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 47(1), January.
    13. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    14. Eric Njuki & Boris E Bravo-Ureta & Víctor E Cabrera, 2020. "Climatic effects and total factor productivity: econometric evidence for Wisconsin dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(3), pages 1276-1301.
    15. Eric Njuki & Boris E Bravo-Ureta & Víctor E Cabrera, 2020. "Corrigendum: Climatic effects and total factor productivity: econometric evidence for Wisconsin dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(2), pages 848-848.
    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. Kritikos, Alexander S. & Schiersch, Alexander & Stiel, Caroline, 2021. "The Productivity Puzzle in Business Services," IZA Discussion Papers 14610, Institute of Labor Economics (IZA).
    3. Alexander S. Kritikos & Alexander Schiersch & Caroline Stiel, 2022. "The productivity shock in business services," Small Business Economics, Springer, vol. 59(3), pages 1273-1299, October.
    4. Geoffrey Barrows & Hélène Ollivier & Ariell Reshef, 2023. "Production Function Estimation with Multi-Destination Firms," CESifo Working Paper Series 10716, CESifo.
    5. Hutchins, Jared P. & Nolan, Derek & Skidmore, Marin, 2023. "Extreme Heat and Livestock Production: Costs and Adaptation in the US Dairy Sector," 2023 Annual Meeting, July 23-25, Washington D.C. 335579, Agricultural and Applied Economics Association.
    6. van Heuvelen, Gerrit Hugo & Bettendorf, Leon & Meijerink, Gerdien, 2021. "Markups in a dual labour market: The case of the Netherlands," International Journal of Industrial Organization, Elsevier, vol. 77(C).
    7. Emir Malikov & Shunan Zhao & Jingfang Zhang, 2024. "A System Approach to Structural Identification of Production Functions with Multi-Dimensional Productivity," Advances in Econometrics, in: Essays in Honor of Subal Kumbhakar, volume 46, pages 211-263, Emerald Group Publishing Limited.
    8. Doris Läpple & Colin A. Carter & Cathal Buckley, 2022. "EU milk quota abolition, dairy expansion, and greenhouse gas emissions," Agricultural Economics, International Association of Agricultural Economists, vol. 53(1), pages 125-142, January.
    9. Shunan Zhao & Bing Qian & Subal C. Kumbhakar, 2020. "Estimation of productivity and markups with price dispersion: Evidence from Chinese manufacturing during economic transition," Southern Economic Journal, John Wiley & Sons, vol. 87(2), pages 666-699, October.
    10. Emir Malikov & Jingfang Zhang & Shunan Zhao & Subal C. Kumbhakar, 2023. "Accounting for Cross-Location Technological Heterogeneity in the Measurement of Operations Efficiency and Productivity," Papers 2302.13430, arXiv.org.
    11. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Cédric Duprez & Glenn Magerman & Marijn Verschelde, 2021. "Structural Identification of Productivity under Biased Technological Change∗," Working Papers ECARES 2021-28, ULB -- Universite Libre de Bruxelles.
    12. Flora Bellone & Patrick Musso & Lionel Nesta & Frederic Warzynski, 2016. "International trade and firm-level markups when location and quality matter," Journal of Economic Geography, Oxford University Press, vol. 16(1), pages 67-91.
    13. Mauro Caselli & Arpita Chatterjee & Shengyu Li, 2023. "Productivity and Quality of Multi-product Firms," Discussion Papers 2023-10, School of Economics, The University of New South Wales.
    14. Dobbelaere, Sabien & Kiyota, Kozo & Mairesse, Jacques, 2015. "Product and labor market imperfections and scale economies: Micro-evidence on France, Japan and the Netherlands," Journal of Comparative Economics, Elsevier, vol. 43(2), pages 290-322.
    15. Amoroso, S., 2013. "Heterogeneity of innovative, collaborative, and productive firm-level processes," Other publications TiSEM f5784a49-7053-401d-855d-1, Tilburg University, School of Economics and Management.
    16. Jonathan Hambur, 2023. "Product Market Competition and its Implications for the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 99(324), pages 32-57, March.
    17. Jan De Loecker & Frederic Warzynski, 2012. "Markups and Firm-Level Export Status," American Economic Review, American Economic Association, vol. 102(6), pages 2437-2471, October.
    18. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    19. Jan De Loecker & Pinelopi K. Goldberg & Amit K. Khandelwal & Nina Pavcnik, 2016. "Prices, Markups, and Trade Reform," Econometrica, Econometric Society, vol. 84, pages 445-510, March.
    20. Florin Maican & Matilda Orth, 2017. "Productivity Dynamics and the Role of ‘Big-Box’ Entrants in Retailing," Journal of Industrial Economics, Wiley Blackwell, vol. 65(2), pages 397-438, June.

    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:wly:ajagec:v:106:y:2024:i:1:p:286-305. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1467-8276 .

    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.