Athanasios Petsakos

Calibration of agricultural risk programming models

Positive Mathematical Programming (PMP) is one of the most commonly used methods for calibrating activity programming models. In this article we consider PMP as a calibration method for risk programming models with a mean-variance (E-V) specification. We argue that the restrictive theoretical assumptions employed by typical linear E-V models limit their applicability in analyzing the effects of decoupled payments on agricultural production decisions. Furthermore, the requirement for eliciting a risk aversion coefficient renders such models incompatible with the PMP method. For this reason we propose a nonlinear E-V specification and develop a PMP-based procedure for its calibration which does not aim at introducing (further) nonlinearities in the objective function, but at recovering the “true” distribution of wealth that will allow the final model to reproduce base year observations. We also examine how our approach relates to the recent PMP developments on calibration against elasticity priors and we show how such priors can be used for the calibration of the nonlinear E-V model.

Evaluating the Efficiency of a Uniform N-Input Tax under Different Policy Scenarios at Different Scales

Nitrate pollution from agriculture is an important environmental externality, caused by the excessive use of fertilizers. The internalization of this problem, via a tax on mineral nitrogen, could lead to a second best solution, reducing nitrate emissions. Several authors suggest that a reduction in agricultural support could produce similar results. In this paper, we examine the effects of different levels of a uniformly implemented nitrogen tax in France under two policy scenarios, corresponding to post Agenda 2000 and 2003 Luxembourg reforms of European Union’s Common Agricultural Policy, in order to reveal the synergies and conflicts between the tax and the policy scenarios in terms of nitrate emissions abatement. The analysis is performed at different geographical scales, from the national to the regional and is based on a bioeconomic approach that involves the coupling of the economic model AROPAj with the crop model STICS. Results show that the efficiency of the N-tax varies according to the geographical scale of the analysis and the type of farming. Furthermore, we prove that a uniform implementation may lead to perverse effects that should always be taken into account when introducing second-best instruments.

Comparing modeling approaches for assessing priorities in international agricultural research

This article examines how the estimated impacts of crop technologies vary with alternate methods and assumptions, and also discusses the implications of these differences for the design of studies to inform research prioritization. Drawing on international potato research, we show how foresight scenarios, realized by a multi-period global multi-commodity equilibrium model, can affect the estimated magnitudes of welfare impacts and the ranking of different potato research options, as opposed to the static, single-commodity, and country assumptions of the economic surplus model which is commonly used in priority setting studies. Our results suggestthatthe ranking oftechnolo- gies is driven by the data used for their specification and is not affected by the foresight scenario examined. However, net benefits vary significantly in each scenario and are greatly overestimated when impacts on non-target countries are ignored. We also argue that the validity of the singlecommodity assumption underpinning the economic surplus model is case-specific and depends on the interventions examined and on the objectives and criteria included in a priority setting study.