IDEAS home Printed from https://ideas.repec.org/p/ags/eaae14/182781.html
   My bibliography  Save this paper

Is animal welfare better on small farms? Evidence from veterinary inspections on Swedish farms

Author

Listed:
  • Hess, Sebastian
  • Bolos, Laura A.
  • Hoffmann, Ruben
  • Surry, Yves

Abstract

Structural change towards more ‘industrialised’ pig farming is widely criticised for having adverse effects on farm animal welfare (FAW). This criticism implies that larger farms might be less concerned with animal welfare than smaller, more diversified farms, e.g. since small farmers would value FAW more. Based on data from veterinary pig farm inspections, various aspects of this standard criticism were empirically tested. The results showed that FAW violations were less frequent on larger farms and more frequent on pig farms with dairy cows. Violations were no less frequent in areas with more organic production, but on average less severe.

Suggested Citation

  • Hess, Sebastian & Bolos, Laura A. & Hoffmann, Ruben & Surry, Yves, 2014. "Is animal welfare better on small farms? Evidence from veterinary inspections on Swedish farms," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182781, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae14:182781
    DOI: 10.22004/ag.econ.182781
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/182781/files/EAAE_Is_animal_welfare_better_on_small_farms_uploadEAAE.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.182781?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. Carl Johan Lagerkvist & Helena Hansson & Sebastian Hess & Ruben Hoffman, 2011. "Provision of Farm Animal Welfare: Integrating Productivity and Non-Use Values," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(4), pages 484-509.
    2. Zeileis, Achim & Kleiber, Christian & Jackman, Simon, 2008. "Regression Models for Count Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i08).
    3. Ben B. Hansen, 2004. "Full Matching in an Observational Study of Coaching for the SAT," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 609-618, January.
    4. Rakhal Sarker & Yves Surry, 2004. "The Fast Decay Process in Outdoor Recreational Activities and the Use of Alternative Count Data Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(3), pages 701-715.
    5. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(3), pages 199-236, July.
    6. Rakhal Sarker & Yves Surry, 2004. "The fast decay process in recreational demand activities and the use of alternative count data models," Post-Print hal-02682254, HAL.
    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. Arne Henningsen & Tomasz Gerard Czekaj & Björn Forkman & Mogens Lund & Aske Schou Nielsen, 2018. "The Relationship between Animal Welfare and Economic Performance at Farm Level: A Quantitative Study of Danish Pig Producers," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(1), pages 142-162, February.
    2. Danne, Michael & Mußhoff, Oliver, 2018. "Producers' valuation of animal welfare practices: Does herd size matter?," DARE Discussion Papers 1801, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).

    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. Lenis, David & Ackerman, Benjamin & Stuart, Elizabeth A., 2018. "Measuring model misspecification: Application to propensity score methods with complex survey data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 48-57.
    2. Katsuhito Nohara & Masaki Narukawa, 2015. "Measuring lost recreational benefits in Fukushima due to harmful rumors using a Poisson-inverse Gaussian regression?," ERSA conference papers ersa15p344, European Regional Science Association.
    3. Iacus, Stefano & Porro, Giuseppe, 2008. "Invariant and Metric Free Proximities for Data Matching: An R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i11).
    4. Jason Lyall, 2008. "Does Indiscriminate Violence Incite Insurgent Attacks? Evidence from a Natural Experiment," HiCN Working Papers 44, Households in Conflict Network.
    5. Casey A. Klofstad & Benjamin G. Bishin, 2014. "Do Social Ties Encourage Immigrant Voters to Participate in Other Campaign Activities?," Social Science Quarterly, Southwestern Social Science Association, vol. 95(2), pages 295-310, June.
    6. Cousineau, Martin & Verter, Vedat & Murphy, Susan A. & Pineau, Joelle, 2023. "Estimating causal effects with optimization-based methods: A review and empirical comparison," European Journal of Operational Research, Elsevier, vol. 304(2), pages 367-380.
    7. Ghosh, Debashis, 2011. "Propensity score modelling in observational studies using dimension reduction methods," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 813-820, July.
    8. Jennings, Wesley G. & Richards, Tara N. & Dwayne Smith, M. & Bjerregaard, Beth & Fogel, Sondra J., 2014. "A Critical Examination of the “White Victim Effect” and Death Penalty Decision-Making from a Propensity Score Matching Approach: The North Carolina Experience," Journal of Criminal Justice, Elsevier, vol. 42(5), pages 384-398.
    9. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
    10. Gerrie‐Cor Herber & Maarten Schipper & Marc Koopmanschap & Karin Proper & Fons van der Lucht & Hendriek Boshuizen & Johan Polder & Ellen Uiters, 2020. "Health expenditure of employees versus self‐employed individuals; a 5 year study," Health Economics, John Wiley & Sons, Ltd., vol. 29(12), pages 1606-1619, December.
    11. Glazer Amanda K. & Pimentel Samuel D., 2023. "Robust inference for matching under rolling enrollment," Journal of Causal Inference, De Gruyter, vol. 11(1), pages 1-19, January.
    12. Boulding, Carew & Wampler, Brian, 2010. "Voice, Votes, and Resources: Evaluating the Effect of Participatory Democracy on Well-being," World Development, Elsevier, vol. 38(1), pages 125-135, January.
    13. Martin Cousineau & Vedat Verter & Susan A. Murphy & Joelle Pineau, 2022. "Estimating causal effects with optimization-based methods: A review and empirical comparison," Papers 2203.00097, arXiv.org.
    14. Phuong Nguyen-Hoang, 2012. "Fiscal effects of budget referendums: evidence from New York school districts," Public Choice, Springer, vol. 150(1), pages 77-95, January.
    15. Nakatani, Tomoaki & Sato, Kazuo, 2005. "Truncation and Endogenous Stratification in Various Count Data Models for Recreation Demand Analysis," SSE/EFI Working Paper Series in Economics and Finance 615, Stockholm School of Economics.
    16. Gonzalez-Ramirez, Maria Jimena & Kling, Catherine L. & Arbuckle, J. Gordon Jr., 2015. "Cost-share Effectiveness in the Adoption of Cover Crops in Iowa," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205876, Agricultural and Applied Economics Association.
    17. Richard Aviles-Lopez & Juan de Dios Luna del Castillo & Miguel Ángel Montero-Alonso, 2023. "Exploratory Matching Model Search Algorithm (EMMSA) for Causal Analysis: Application to the Cardboard Industry," Mathematics, MDPI, vol. 11(21), pages 1-34, October.
    18. Liu, Yan & Chen, Xi & Yan, Zhijun, 2019. "Depression in the House: The Effects of Household Air Pollution from Solid Fuel Use in China," IZA Discussion Papers 12654, Institute of Labor Economics (IZA).
    19. Noemi Kreif & Richard Grieve & Rosalba Radice & Zia Sadique & Roland Ramsahai & Jasjeet S. Sekhon, 2012. "Methods for Estimating Subgroup Effects in Cost-Effectiveness Analyses That Use Observational Data," Medical Decision Making, , vol. 32(6), pages 750-763, November.
    20. Do, Manh Hung & Nguyen, Trung Thanh & Grote, Ulrike, 2023. "Land consolidation, rice production, and agricultural transformation: Evidence from household panel data for Vietnam," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 157-173.

    More about this item

    Keywords

    Health Economics and Policy;

    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:eaae14:182781. 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/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.