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Methods of Change and Financial Performance of Dairy Farms Before and After a Switch to Management Intensive Grazing

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  • Taylor, Philip Eugene

Abstract

Interest in Management Intensive Grazing (MIG) of dairy cattle has increased during the last 2 decades. Most dairy producers utilizing MIG were former confinement or non-intensive pasture operations while the others started their operation with MIG. While research publications tout the financial and other benefits of MIG, often comparing them to non-MIG dairies, and anecdotal evidence in popular farm press has shown MIG in a favorable light, comparing a MIG dairy farm to itself before and after the management switch has not been a subject of research scrutiny. Knowing the potential impact of a switch to MIG prior to making a management decision to do so would be a significant piece of information for a dairy farm to understand if contemplating such a management change. Which farms are candidates for success following a switch? What changes in labor, cost of production, and herd health might be expected? These and other questions were investigated by examining 29 MIG dairy farms in Michigan. These farms experienced similar milk production levels per cow, reduced feed and hired labor cost significantly, reduced the acres of row crops grown, and experienced improved herd health resulting in much lower herd health costs. They did not build farm acres, but rather grew cattle numbers and improved management of pasture forage. Research work remains to be done that will more accurately measure true economic progress and further find management techniques that prove successful for MIG farms.

Suggested Citation

  • Taylor, Philip Eugene, 2009. "Methods of Change and Financial Performance of Dairy Farms Before and After a Switch to Management Intensive Grazing," Graduate Research Masters Degree Plan B Papers 56008, Michigan State University, Department of Agricultural, Food, and Resource Economics.
  • Handle: RePEc:ags:midagr:56008
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    File URL: http://purl.umn.edu/56008
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    1. Timmins, Christopher & Murdock, Jennifer, 2007. "A revealed preference approach to the measurement of congestion in travel cost models," Journal of Environmental Economics and Management, Elsevier, vol. 53(2), pages 230-249, March.
    2. Haab, Timothy C. & Hicks, Robert L., 1997. "Accounting for Choice Set Endogeneity in Random Utility Models of Recreation Demand," Journal of Environmental Economics and Management, Elsevier, vol. 34(2), pages 127-147, October.
    3. Kling, Catherine L., 1988. "Comparing welfare estimates of environmental quality changes from recreation demand models," Journal of Environmental Economics and Management, Elsevier, vol. 15(3), pages 331-340, September.
    4. von Haefen, Roger H. & Phaneuf, Daniel J., 2008. "Identifying demand parameters in the presence of unobservables: A combined revealed and stated preference approach," Journal of Environmental Economics and Management, Elsevier, vol. 56(1), pages 19-32, July.
    5. Sha Yang & Yuxin Chen & Greg Allenby, 2003. "Bayesian Analysis of Simultaneous Demand and Supply," Quantitative Marketing and Economics (QME), Springer, vol. 1(3), pages 251-275, September.
    6. Dhar, Tirtha & Chavas, Jean-Paul & Gould, Brian W., 2002. "An Empirical Assessment of Endogeneity Issues in Demand Analysis for Differentiated Products," Working Papers 201561, University of Wisconsin-Madison, Department of Agricultural and Applied Economics, Food System Research Group.
    7. Murdock, Jennifer, 2006. "Handling unobserved site characteristics in random utility models of recreation demand," Journal of Environmental Economics and Management, Elsevier, vol. 51(1), pages 1-25, January.
    8. Lew, Daniel K. & Larson, Douglas M., 2005. "Accounting for stochastic shadow values of time in discrete-choice recreation demand models," Journal of Environmental Economics and Management, Elsevier, vol. 50(2), pages 341-361, September.
    9. Brian W. Gould, 2003. "An Empirical Assessment of Endogeneity Issues in Demand Analysis for Differentiated Products," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(3), pages 605-617.
    10. Wetzel, James N., 1977. "Estimating the benefits of recreation under conditions of congestion," Journal of Environmental Economics and Management, Elsevier, vol. 4(3), pages 239-246, September.
    11. W. Bowman Cutter & Linwood Pendleton & J. R. DeShazo, 2007. "Activities in Models of Recreational Demand," Land Economics, University of Wisconsin Press, vol. 83(3), pages 370-381.
    12. Roger H. von Haefen & D. Matthew Massey & Wiktor L. Adamowicz, 2005. "Serial Nonparticipation in Repeated Discrete Choice Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1061-1076.
    13. McConnell, K. E. & Duff, Virginia A., 1976. "Estimating net benefits of recreation under conditions of excess demand," Journal of Environmental Economics and Management, Elsevier, vol. 2(3), pages 224-230, February.
    14. Chia-Yu Yeh & Timothy Haab & Brent Sohngen, 2006. "Modeling Multiple-Objective Recreation Trips with Choices Over Trip Duration and Alternative Sites," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(2), pages 189-209, June.
    15. P. Geoffrey Allen & Thomas H. Stevens & Scott A. Barrett, 1981. "The Effects of Variable Omission in the Travel Cost Technique," Land Economics, University of Wisconsin Press, vol. 57(2), pages 173-180.
    16. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
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    More about this item

    Keywords

    Dairy; Grazing; Economics; Pasture; Management; Farm; Farm Management; Livestock Production/Industries; Production Economics; Q10; Q12; Q19;

    JEL classification:

    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q19 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Other

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