Abstract: The state-contingent approach developed by Chambers and Quiggin (2000) constitutes an attractive blend of a theory of production analysis under uncertainty and a theory of decision-making under uncertainty.One of the goals of this contribution is to introduce the reader to the approach by outlining its contents while comparing and contrasting it to related theories. With respect to production analysis: an emphasis is made on the ability of the approach to deliver well defined cost functions corresponding to stochastic production technologies. With respect to decision-making under uncertainty: the comparison with other theories consistent with a rational agent emphasizes the production theoretical basis of the state-contingent approach.It is the author’s belief that appropriately categorizing the state-contingent approach serves the primary goal of this work: to explore its usefulness as a basis for economic modeling. Some challenges regarding an empirical implementation are discussed: challenges in estimating the parameters of a state-contingent technology representation in general, as well as challenges arising from the fact that the approach is constructed around the argument pioneered by Leonard J Savage: that probabilities underlying economic decision-making are inherently subjective.(The financial support of ScienceCampus Halle is gratefully acknowledged.) No Label

Abstract: The main objective of CAP Direct payments (DP) has been to increase and stabilise farm income together with a large number of additional goals (Gardner, 1991). Despite its importance, there are limited empirical evidences on farm income variability over time at farm level apart Vrolijk and Poppe (2008) and Vrolijk, de Bont, van der Veen, and Poppe (2009). The analysis focuses of the following research questions:•     What is the amount of the support provided by DP? How the income of Italian farms will be affected by reductions of DP levels?•     What is the extent of farm income variability over time? Is it the same in all types of farms?•     Where is this variability coming from?•     Do CAP direct payments reduce farm income variability? How do DP affect it? Are DP targeted to stabilise the income of those farms facing larger income variability? The analysis has been developed on the individual farms belonging to the whole Italian sample of the EU FADN farms during all years of the decade 2003-2012. The variability of farm income (FI) is assessed by calculating variance and Coefficient of Variation (CV) over the 10 year period for each farm for each relevant income component. The role of DP on income stabilisation is assessed by means of variance decomposition by income sources (Burt and Finley, 1968; El Benni and Finger, 2013; Mishra and El-Osta, 2001).The presence of DP allows for a reduction of the variability of farm income: the variability of FI when DP are not accounted for is higher than that of the whole FI. Finally, DP seem to be not targeted to those farms facing the highest level of market income variability. These results support the hypothesis that there is a potentially large room for better design the DP policy to reduce income variability. No Label

Abstract: The paper addresses future climate and policy uncertainty for agricultural production and food security in Norway. The two crop simulation models, CSM-CERES-Wheat and, the LINGRA model, were used to determine the impact of climate change on grain yield of spring wheat, and harvest security and biomass yield of timothy, an important forage grass in Northern Europe, respectively. Harvestable yield distributions from the crop models were fed into a stochastic version of the economic sector model Jordmod. Distributions of the rates of agricultural subsidies rates were assessed based on past policy changes and prospective reforms. The model was used to assess the effects of both climate and policy uncertainty on agricultural production, land use, and national food security. Jordmod is comprised of a supply module in which stochastic profits for more than 300 regional farms are maximized and a deterministic market module which maximizes social welfare in the agricultural sector. Socio-economic scenarios were developed around the level of ambition of Norwegian agricultural policy makers. The model results were contrasted with the deterministic results based on average yield and payment rates. The innovation of this paper lays in assessing the combined effects of future climate and policy uncertainty for the agricultural sector in Norway. It also highlights the potential errors made by neglecting these types of uncertainty in economic modelling. No Label