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Modelling Production Risk in Small Scale Subsistence Agriculture


  • Asche, Frank
  • Guttormsen, Atle G.
  • Roll, Kristin H.


In this paper we are investigating how production risk may influence the way a risk averse producer like a subsistence farmer chooses optimal input levels. Risk averse producers will take into account both the mean and the variance of output, and therefore we expect them to choose input levels which differ form the optimal input level of risk neutral producers. Production risk is of particular importance in developing countries, since variance in production here may have grave consequences for the farmer and his family. To model the production decision problem under such circumstances we have made use of the fact that production risk can be treated as heteroskedasticity. Our analysis is based on a dataset obtained from a survey on smallholders in the Kilimanjaro region in Tanzania. Since evidence of output risk in inputs is found, we reestimate the mean and variance function using a maximum likelihood estimator, and correct the standard errors to provide valid inference.

Suggested Citation

  • Asche, Frank & Guttormsen, Atle G. & Roll, Kristin H., 2006. "Modelling Production Risk in Small Scale Subsistence Agriculture," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25574, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae06:25574

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    References listed on IDEAS

    1. Arne Hallam & Rashid M. Hassan & B. D'Silva, 1989. "Measuring Stochastic Technology for the Multi-product Firm: The Irrigated Farms of Sudan," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 37(3), pages 495-512, November.
    2. Asche, Frank & Tveteras, Ragnar, 1999. "Modeling Production Risk With A Two-Step Procedure," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(02), December.
    3. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-465, May.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
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    Cited by:

    1. Vorotnikova, Ekaterina & VanSickle, John J. & Borisova, Tatiana, 2012. "The Economic Value of the Precision Disease Management System for Anthracnose and Botrytis Fruit Rot for the Florida Strawberry Industry," 2012 Annual Meeting, February 4-7, 2012, Birmingham, Alabama 119791, Southern Agricultural Economics Association.
    2. Vorotnikova, Ekaterina & Borisova, Tatiana & VanSickle, John J., 2014. "Evaluation of the profitability of a new precision fungicide application system for strawberry production," Agricultural Systems, Elsevier, vol. 130(C), pages 77-88.
    3. Vorotnikova, Ekaterina & VanSickle, John J. & Borisova, Tatiana, 2013. "The Economic Value of Precision Management System for Fungicide Application in Florida Strawberry Industry," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143108, Southern Agricultural Economics Association.

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