No abstract

No abstract

No abstract

No abstract

No abstract

A stochastic dual model of investment under uncertainty is used to investigate structural adjustment in the Finnish hog industry. Value function restrictions are found to be comparable to those in existing dual models assuming deterministic state variables. The model also allows for an asymmetry in investment response during capital expansion and contraction phases. Empirical results show that investments respond negatively to increased uncertainty and that labor adjusts more slowly during contraction phases than during expansions. Results on economies of size, uncertainty effects, and adjustment rigidities have important implications for hog industry response to Finland's entry into the EU.

This article explores long-term land improvement (lime application) under land tenure insecurity on leased land. The dynamic optimisation problem is solved by a stochastic dynamic programming routine with known parameters for one-period returns and transition equations. The model parameters represent Finnish soil quality and production conditions. The farmer's decision rules are solved for alternative likelihood scenarios over the continuation of the fixed term lease contract. The results suggest that, as the probability for non-renewal of the lease contract increases, farmers quickly decrease investments in irreversible land improvement and, thereafter, yields decline gradually. The estimated decision rules are a part of larger set of farmer's decision rules to be taken care when land leasing and environmental legislation is renewed.

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.