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Enhancing Farm Profitability through Portfolio Analysis: The Case of Spatial Rice Variety Selection

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  • Nalley, Lawton Lanier
  • Barkely, Andrew
  • Watkins, Brad
  • Hignight, Jeffrey A.

Abstract

This study applies portfolio theory to rice varietal selection decisions to find profit maximizing and risk minimizing outcomes. Results based on data from six counties in the Arkansas Delta for the period 1999–2006 suggest that sowing a portfolio of rice varieties could have increased profits from 3 to 26% (depending on the location) for rice producers in the Arkansas Delta. The major implication of this research is that data and statistical tools are available for rice producers to improve the choice of rice varieties to plant each year in specific locations. Specifically, there are large potential gains from combining varieties that are characterized by inverse yield responses to growing conditions such as drought, pest infestation, or the presence of a specific disease.

Suggested Citation

  • Nalley, Lawton Lanier & Barkely, Andrew & Watkins, Brad & Hignight, Jeffrey A., 2009. "Enhancing Farm Profitability through Portfolio Analysis: The Case of Spatial Rice Variety Selection," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 41(3), pages 1-12, December.
    • Handle: RePEc:ags:joaaec:56650
    DOI: 10.22004/ag.econ.56650
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    References listed on IDEAS

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    1. Andrew P. Barkley & Lori L. Porter, 1996. "The Determinants of Wheat Variety Selection in Kansas, 1974 to 1993," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(1), pages 202-211.
    2. Barkley, Andrew P. & Peterson, Hikaru Hanawa, 2008. "Wheat Variety Selection: An Application of Portfolio Theory to Improve Returns," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37597, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    3. Brennan, John P., 1984. "Measuring the Contribution of New Varieties to Increasing Wheat Yields," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 52(03), pages 1-21, December.
    4. Annou, Mamane Malam & Thomsen, Michael R. & Hansen, James M. & Wailes, Eric J. & Cramer, Gail L., 2001. "Implications Of Rice Biotechnology On Optimal Rice Crop Rotation In The Mississippi River Delta Region," Staff Papers 15774, University of Arkansas, Department of Agricultural Economics and Agribusiness.
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    Cited by:

    1. Codjo, O.S. & Fiamohe, R. & Kpenavoun, S. & Acclassato, D. & Biaou, G., 2018. "Application of Portfolio and Stochastic Simulation Analysis for a Decision of Governance Structures Choice of Benin s Rice Producers," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277145, International Association of Agricultural Economists.
    2. Steven C. Blank & Danny Klinefelter, 2012. "Keeping ARMS relevant: increasing its usability," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 72(2), pages 222-232, July.
    3. Alulu, Joseph & Muendo, Kavoi & Mbeche, Robert & Mithöfer, Dagmar, 2024. "Seed innovations and performance of African indigenous vegetables producers: Evidence from Kenya," IAAE 2024 Conference, August 2-7, 2024, New Delhi, India 344235, International Association of Agricultural Economists (IAAE).
    4. Bodin, P. & Olin, S. & Pugh, T.A.M. & Arneth, A., 2016. "Accounting for interannual variability in agricultural intensification: The potential of crop selection in Sub-Saharan Africa," Agricultural Systems, Elsevier, vol. 148(C), pages 159-168.
    5. Watkins, K. Bradley & Henry, Chris G. & Hardke, Jarrod T. & Mane, Ranjitsinh U. & Mazzanti, Ralph & Baker, Ron, 2021. "Non-radial technical efficiency measurement of irrigation water relative to other inputs used in Arkansas rice production," Agricultural Water Management, Elsevier, vol. 244(C).
    6. Watkins, K. Bradley & Henry, Christopher G. & Mazzanti, Ralph & Schmidt, Lance & Hardke, Jarrod T., 2014. "Non-Radial Technical Efficiency of Water and Nitrogen Usage in Arkansas Rice Production," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162593, Southern Agricultural Economics Association.
    7. Mishenin, Yevhen & Marekha, Iryna & Yarova, Inessa & Kovalova, Olha & Pizniak, Tetiana, 2022. "Optimizing a portfolio of agri-environmental investments," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 8(1), March.
    8. Mortenson, Ryan & Parsons, Jay & Pendell, Dustin L. & Haley, Scott D., 2012. "Wheat Variety Selection: An Application of Portfolio Theory in Colorado," Western Economics Forum, Western Agricultural Economics Association, vol. 11(2), pages 1-12.
    9. Watkins, K. Bradley & Hristovska, Tatjana & Mazzanti, Ralph & Wilson, Charles E., Jr., "undated". "Measuring Technical, Allocative, and Economic Efficiency of Rice Production in Arkansas using Data Envelopment Analysis," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 142962, Southern Agricultural Economics Association.
    10. Diersen, Matthew & Gurung, Pratik & Fausti, Scott, 2015. "Optimal Allocation of Index Insurance Intervals for Commodities," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196793, Southern Agricultural Economics Association.

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    More about this item

    Keywords

    Agribusiness; Crop Production/Industries; Farm Management; Production Economics; Productivity Analysis; Risk and Uncertainty;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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