Rural investment and the dynamic cost of income uncertainty

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 model for computing the dynamic uncertainty cost is presented, applying the classical expected value of perfect information. The uncertainty cost depends on the volatility of income; e.g. with stationary income, the dynamic uncertainty cost is equivalent to a dynamic option value of postponing investment. In the case study, the investment decision is sensitive to risk. The model can be applied e.g. in planning investment subsidies for maintaining target investments.