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Investment and the Dynamic Cost of Income Uncertainty: the Case of Diminishing Expectations in Agriculture

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  • Heikkinen, Tiina
  • Pietola, Kyosti

Abstract

This paper studies optimal investment and the dynamic cost of income uncertainty, applying a stochastic programming approach. The motivation is given by a case study in Finnish agriculture. Investment decision is modelled as a Markov decision process, extended to account for risk. A numerical framework for studying the dynamic uncertainty cost is presented, modifying the classical expected value of perfect information to a dynamic setting. The uncertainty cost depends on the volatility of income; e.g. with stationary income, the dynamic uncertainty cost corresponds to a dynamic option value of postponing investment. The numerical investment model also yields the optimal investment behavior of a representative farm. The model can be applied e.g. in planning investment subsidies for maintaining target investments. In the case study, the investment decision is sensitive to risk.

Suggested Citation

  • Heikkinen, Tiina & Pietola, Kyosti, 2006. "Investment and the Dynamic Cost of Income Uncertainty: the Case of Diminishing Expectations in Agriculture," Discussion Papers 11868, MTT Agrifood Research Finland.
  • Handle: RePEc:ags:mttfdp:11868
    DOI: 10.22004/ag.econ.11868
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    1. Tauer, Loren W., 2006. "When to Get In and Out of Dairy Farming: A Real Option Analysis," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 35(2), pages 1-9, October.
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    Cited by:

    1. Irawan, Denny & Okimoto, Tatsuyoshi, 2021. "Overinvestment and macroeconomic uncertainty: Evidence from renewable and non-renewable resource firms," Journal of Economic Dynamics and Control, Elsevier, vol. 126(C).
    2. Heikkinen, T. & Pietola, K., 2009. "Investment and the dynamic cost of income uncertainty: The case of diminishing expectations in agriculture," European Journal of Operational Research, Elsevier, vol. 192(2), pages 634-646, January.
    3. Assa, Hirbod & Sharifi, Hossein & Lyons, Andrew, 2021. "An examination of the role of price insurance products in stimulating investment in agriculture supply chains for sustained productivity," European Journal of Operational Research, Elsevier, vol. 288(3), pages 918-934.
    4. Trigeorgis, Lenos & Tsekrekos, Andrianos E., 2018. "Real Options in Operations Research: A Review," European Journal of Operational Research, Elsevier, vol. 270(1), pages 1-24.
    5. Mittenzwei, Klaus & Bullock, David S. & Salhofer, Klaus & Kola, Jukka, 2011. "Towards a Theory of Policy Making," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114639, European Association of Agricultural Economists.
    6. Viaggi, Davide & Raggi, Meri & Gomez y Paloma, Sergio, 2010. "An integer programming dynamic farm-household model to evaluate the impact of agricultural policy reforms on farm investment behaviour," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1130-1139, December.
    7. Reidsma, Pytrik & Janssen, Sander & Jansen, Jacques & van Ittersum, Martin K., 2018. "On the development and use of farm models for policy impact assessment in the European Union – A review," Agricultural Systems, Elsevier, vol. 159(C), pages 111-125.
    8. Borodin, Valeria & Bourtembourg, Jean & Hnaien, Faicel & Labadie, Nacima, 2016. "Handling uncertainty in agricultural supply chain management: A state of the art," European Journal of Operational Research, Elsevier, vol. 254(2), pages 348-359.
    9. Dowson, Oscar & Philpott, Andy & Mason, Andrew & Downward, Anthony, 2019. "A multi-stage stochastic optimization model of a pastoral dairy farm," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1077-1089.

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