Abstract: One of the potential measures suggested to cope with the changes induced by Climate Change (CC) is the construction of rainwater harvesting reservoirs (Bozzola and Swanson, n.d.). The literature has focused mostly on the water allocation management but it overlooks at the structure of the investment decision. We analyse the investment decision in water storage facilities, for different farming specialization and under different climatic scenarios to assess the option value of the investment. We take an interdisciplinary approach integrating climate, agronomic and economic models. CC effects are assessed by a downscale of the A1B scenario of the IPCC (Tomozeiu et al., 2010). The resulting estimated temperatures and rainfall levels are then introduced in an agronomic model, which determines the irrigation water quantity and timing for a number of crops. Finally all these elements are included in a farm level economics model, DHYMORA (Viaggi et al., 2010). The model is applied to typical farm specializations in eastern Emilia-Romagna, including both annual and perennial crops.

Abstract: Climate-induced uncertainty in crop yields is introduced in the Norwegian sector model Jordmod. The model is comprised of a supply module in which profits for more than 300 regional farms are maximized and a market module which maximizes social welfare in the agricultural sector. In the supply module, farmers determine their plant decisions and crop input levels (N-fertilizer) subject to a discrete number of weather outcomes affecting crop yields. After that, a specific weather distribution is chosen determining crop yields. The resulting input-output mix at farm level makes up the supply side of the commodity markets which together with linear demand functions determine equilibrium levels. The procedure is repeated for each discrete weather outcome. Note that plant decisions and crop input levels remain the same for all weather outcomes as farmers face the same uncertainty during all repetitions, but crop yield will vary. Hence, equilibrium prices and quantities will vary as well allowing their representation as stochastic distributions. In a preliminary empirical application, the stochastic results are contrasted with the deterministic results based on the mean values of the weather outcomes. This comparison will shed light on the potential error made by neglecting uncertainty at the farm level.

Abstract: This paper builds a benchmark framework to study optimal land use, encompassing land use activities and environmental degradation. We focus on the spatial externalities of land use as drivers of spatial patterns: land is immobile by nature, but location’s actions affect the whole space since pollution flows across locations resulting in both local and global damages. We prove that the decision maker problem has a solution, and characterize the corresponding social optimum trajectories by means of the Pontryagin conditions. We also show that the existence and uniqueness of steady-state solutions are not straightforward. Finally, a global dynamic algorithm is proposed in order to illustrate the spatial-dynamic richness of the model. We find that our simple set-up already reproduces a great variety of spatial patterns related to the interaction between land use activities and the environment. In particular, abatement technology turns out to play a central role as pollution stabilizer, allowing the economy to achieve stable steady-states that are spatially heterogeneous.