IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v171y2019icp126-134.html
   My bibliography  Save this article

Profit stability of mixed dairy and beef production systems of the mountain area of southern Auvergne (France) in the face of price variations: Bioeconomic simulation

Author

Listed:
  • Diakité, Z.R.
  • Corson, M.S.
  • Brunschwig, G.
  • Baumont, R.
  • Mosnier, C.

Abstract

Mountain farmers face additional structural constraints (e.g., steep slopes, high elevations, fragmented fields) along with the regular risks inherent to agriculture, such as economic fluctuations. We thus hypothesized that simultaneously producing dairy and beef herds (i.e., “mixed cattle systems”) on mountain farms is a good compromise between a farm's expected profits and the variation in these profits. To explore the profit stability of mixed cattle systems in the face of price variations, we used the bioeconomic optimization model Orfee to simulate one farm strategy: adjusting the number of cattle. The model simulated three mixed cattle systems (dairy and beef herds) and two specialized cattle systems (dairy or beef herd) on two farms in southern Auvergne (France) that differed in agronomic potential, field configurations and animal productivity. A local sensitivity analysis of beef, milk and feed price was combined with a global sensitivity analysis based on metamodels. Results indicated that the number of cattle was adjusted as a function of resource availability, farm structure, and product prices on the market. Compared to specialized systems, mixed cattle systems usually seemed an effective strategy to manage economic risk, with good compromise between expected profits and variation in profits.

Suggested Citation

  • Diakité, Z.R. & Corson, M.S. & Brunschwig, G. & Baumont, R. & Mosnier, C., 2019. "Profit stability of mixed dairy and beef production systems of the mountain area of southern Auvergne (France) in the face of price variations: Bioeconomic simulation," Agricultural Systems, Elsevier, vol. 171(C), pages 126-134.
    • Handle: RePEc:eee:agisys:v:171:y:2019:i:c:p:126-134
    DOI: 10.1016/j.agsy.2019.01.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X18307960
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2019.01.012?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
    ---><---

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

    References listed on IDEAS

    as
    1. Kleijnen, J.P.C., 1995. "Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments," Other publications TiSEM 87ee6ee0-592c-4204-ac50-6, Tilburg University, School of Economics and Management.
    2. Jacquet, F. & Pluvinage, J., 1997. "Climatic uncertainty and farm policy: A discrete stochastic programming model for cereal-livestock farms in Glgeria," Agricultural Systems, Elsevier, vol. 53(4), pages 387-407, April.
    3. Emilio A. Laca, 2007. "Stochastic Rangeland Use under Capital Constraints," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(3), pages 805-817.
    4. Jean-Paul Chavas, 2008. "On the economics of agricultural production ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 52(4), pages 365-380, December.
    5. Mosnier, Claire & Duclos, Anne & Agabriel, Jacques & Gac, Armelle, 2017. "Orfee: A bio-economic model to simulate integrated and intensive management of mixed crop-livestock farms and their greenhouse gas emissions," Agricultural Systems, Elsevier, vol. 157(C), pages 202-215.
    6. Cariboni, J. & Gatelli, D. & Liska, R. & Saltelli, A., 2007. "The role of sensitivity analysis in ecological modelling," Ecological Modelling, Elsevier, vol. 203(1), pages 167-182.
    7. Lambert, David K., 1989. "Calf Retention And Production Decisions Over Time," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 14(1), pages 1-11, July.
    8. Kobayashi, Mimako & Howitt, Richard E. & Jarvis, Lovell S. & Laca, Emilio A., 2007. "AJAE Appendix: Stochastic Rangeland Use Under Capital Constraints," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 89(3), pages 1-18, August.
    9. Olson, Kent D. & Mikesell, Chris L., 1988. "The Range Stocking Decision And Stochastic Forage Production," Staff Papers 13502, University of Minnesota, Department of Applied Economics.
    10. Aude Ridier & Florence Jacquet, 2002. "Decoupling Direct Payments and the Dynamics of Decisions under Price Risk in Cattle Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 53(3), pages 549-565, November.
    11. Kingwell, Ross S. & Pannell, David J. & Robinson, Stephen D., 1993. "Tactical responses to seasonal conditions in whole-farm planning in Western Australia," Agricultural Economics, Blackwell, vol. 8(3), pages 211-226, March.
    12. Kwansoo Kim & Jean-Paul Chavas & Bradford Barham & Jeremy Foltz, 2012. "Specialization, diversification, and productivity: a panel data analysis of rice farms in Korea," Agricultural Economics, International Association of Agricultural Economists, vol. 43(6), pages 687-700, November.
    13. Tibor F. Liska, 2007. "The Liska model," Society and Economy, Akadémiai Kiadó, Hungary, vol. 29(3), pages 363-381, December.
    14. Janssen, Sander & van Ittersum, Martin K., 2007. "Assessing farm innovations and responses to policies: A review of bio-economic farm models," Agricultural Systems, Elsevier, vol. 94(3), pages 622-636, June.
    15. Mosnier, C. & Agabriel, J. & Lherm, M. & Reynaud, A., 2009. "A dynamic bio-economic model to simulate optimal adjustments of suckler cow farm management to production and market shocks in France," Agricultural Systems, Elsevier, vol. 102(1-3), pages 77-88, October.
    16. Chavas, Jean-Paul & Aliber, Michael, 1993. "An Analysis Of Economic Efficiency In Agriculture: A Nonparametric Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(1), pages 1-16, July.
    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. Barnes, Andrew P. & Bevan, Kev & Moxey, Andrew & Grierson, Sascha & Toma, Luiza, 2023. "Identifying best practice in Less Favoured Area mixed livestock systems," Agricultural Systems, Elsevier, vol. 208(C).
    2. Bell, L.W. & Moore, A.D. & Thomas, D.T., 2021. "Diversified crop-livestock farms are risk-efficient in the face of price and production variability," Agricultural Systems, Elsevier, vol. 189(C).

    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. Rose, G. & Mulder, H.A. & Thompson, A.N. & van der Werf, J.H.J. & van Arendonk, J.A.M., 2014. "Varying pasture growth and commodity prices change the value of traits in sheep breeding objectives," Agricultural Systems, Elsevier, vol. 131(C), pages 94-104.
    2. Mosnier, C. & Agabriel, J. & Lherm, M. & Reynaud, A., 2009. "A dynamic bio-economic model to simulate optimal adjustments of suckler cow farm management to production and market shocks in France," Agricultural Systems, Elsevier, vol. 102(1-3), pages 77-88, October.
    3. Ridier, Aude & Chaib, Karim & Roussy, Caroline, 2016. "A Dynamic Stochastic Programming model of crop rotation choice to test the adoption of long rotation under price and production risks," European Journal of Operational Research, Elsevier, vol. 252(1), pages 270-279.
    4. Lescot, Jean-Marie & Rousset, Sylvain & Souville, Genevieve, 2011. "Assessing Investment in Precision Farming for Reducing Pesticide Use in French Viticulture," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114387, European Association of Agricultural Economists.
    5. Tsakiridis, Andreas & Breen, James & O'Donoghue, Cathal & Hanrahan, Kevin & Wallace, Michael & Crosson, Paul, 2016. "Flexibility of beef suckler cow systems under varying calf retention strategies," 90th Annual Conference, April 4-6, 2016, Warwick University, Coventry, UK 236289, Agricultural Economics Society.
    6. Robert, Marion & Thomas, Alban & Bergez, Jacques Eric, 2016. "Processes of adpatation in farm decision-making models. A review," TSE Working Papers 16-731, Toulouse School of Economics (TSE).
    7. Dieguez Cameroni, F.J. & Terra, R. & Tabarez, S. & Bommel, P. & Corral, J. & Bartaburu, D. & Pereira, M. & Montes, E. & Duarte, E. & Morales Grosskopf, H., 2014. "Virtual experiments using a participatory model to explore interactions between climatic variability and management decisions in extensive grazing systems in the basaltic region of Uruguay," Agricultural Systems, Elsevier, vol. 130(C), pages 89-104.
    8. Mosnier, Claire, 2014. "Would multi-peril grassland insurance improve French suckler cow farm sustainability?," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182786, European Association of Agricultural Economists.
    9. Francisco A. Buendia-Hernandez & Maria J. Ortiz Bevia & Francisco J. Alvarez-Garcia & Antonio Ruizde Elvira, 2022. "Sensitivity of a Dynamic Model of Air Traffic Emissions to Technological and Environmental Factors," IJERPH, MDPI, vol. 19(22), pages 1-17, November.
    10. Lorscheid, Iris & Meyer, Matthias, 2016. "Divide and conquer: Configuring submodels for valid and efficient analyses of complex simulation models," Ecological Modelling, Elsevier, vol. 326(C), pages 152-161.
    11. Kanapaux, William & Kiker, Gregory A., 2013. "Development and testing of an object-oriented model for adaptively managing human disturbance of least tern (Sternula antillarum) nesting habitat," Ecological Modelling, Elsevier, vol. 268(C), pages 64-77.
    12. Chu-Agor, M.L. & Muñoz-Carpena, R. & Kiker, G.A. & Aiello-Lammens, M.E. & Akçakaya, H.R. & Convertino, M. & Linkov, I., 2012. "Simulating the fate of Florida Snowy Plovers with sea-level rise: Exploring research and management priorities with a global uncertainty and sensitivity analysis perspective," Ecological Modelling, Elsevier, vol. 224(1), pages 33-47.
    13. Petropoulos, G. & Wooster, M.J. & Carlson, T.N. & Kennedy, M.C. & Scholze, M., 2009. "A global Bayesian sensitivity analysis of the 1d SimSphere soil–vegetation–atmospheric transfer (SVAT) model using Gaussian model emulation," Ecological Modelling, Elsevier, vol. 220(19), pages 2427-2440.
    14. Soraya Tanure & Carlos Nabinger & João Luiz Becker, 2015. "Bioeconomic Model of Decision Support System for Farm Management: Proposal of a Mathematical Model," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(6), pages 658-671, November.
    15. Gregory Hill & Steven Kolmes & Michael Humphreys & Rebecca McLain & Eric T. Jones, 2019. "Using decision support tools in multistakeholder environmental planning: restorative justice and subbasin planning in the Columbia River Basin," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 9(2), pages 170-186, June.
    16. Martin Fiszbein, 2017. "Agricultural Diversity, Structural Change and Long-run Development: Evidence from the U.S," NBER Working Papers 23183, National Bureau of Economic Research, Inc.
    17. Martin Fiszbein, 2022. "Agricultural Diversity, Structural Change, and Long-Run Development: Evidence from the United States," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(2), pages 1-43, April.
    18. Wernsdörfer, H. & Rossi, V. & Cornu, G. & Oddou-Muratorio, S. & Gourlet-Fleury, S., 2008. "Impact of uncertainty in tree mortality on the predictions of a tropical forest dynamics model," Ecological Modelling, Elsevier, vol. 218(3), pages 290-306.
    19. Rougier, Thibaud & Drouineau, Hilaire & Dumoulin, Nicolas & Faure, Thierry & Deffuant, Guillaume & Rochard, Eric & Lambert, Patrick, 2014. "The GR3D model, a tool to explore the Global Repositioning Dynamics of Diadromous fish Distribution," Ecological Modelling, Elsevier, vol. 283(C), pages 31-44.
    20. Mosnier, Claire & Duclos, Anne & Agabriel, Jacques & Gac, Armelle, 2017. "Orfee: A bio-economic model to simulate integrated and intensive management of mixed crop-livestock farms and their greenhouse gas emissions," Agricultural Systems, Elsevier, vol. 157(C), pages 202-215.

    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:eee:agisys:v:171:y:2019:i:c:p:126-134. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    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.