Regulatory Actions under Adjustment Costs and the Resolution of Scientific Uncertainty

Food system regulators often decide whether to ban existing practices or approve new technologies without conclusive scientific evidence on possible damage and knowing that resolution is likely in the future. In a model with three decision points and stochastic resolution of uncertainty, we study interactions between expected losses due to regulation and information availability when a regulator is deciding on an early reversible ban and on a later reversible ban. Adjustment costs create inertia concerning intermediate signals such that earlier decisions are not overturned, and also a bias against imposing an early ban. The prospect of more later-stage information can increase or decrease the incentive to ban early, but research decreases the incentive to ban early.     

Geographical Indications and the Competitive Provision of Quality in Agricultural Markets

The economics of geographical indications (GIs) is assessed within a vertical product differentiation framework that is consistent with the competitive structure of agriculture. It is assumed that certification costs are needed for GIs to serve as (collective) credible quality certification devices, and production of high-quality product is endogenously determined. We find that GIs can support a competitive provision of quality and lead to clear welfare gains, although they fall short of delivering the (constrained) first best. The main beneficiaries are consumers. Producers may also accrue some benefit if production of the high-quality products draws on scarce factors that they own.     

On the Segregation of Genetically Modified,Conventional and Organic Products in European Agriculture: A Multi‐market Equilibrium Analysis

Evaluating the possible benefits of the introduction of genetically modified (GM) crops must address the issue of consumer resistance as well as the complex regulation that has ensued. In the European Union (EU), this regulation envisions the co‐existence of GM food with conventional and quality‐enhanced products, mandates the labelling and traceability of GM products and allows only a stringent adventitious presence of GM content in other products. All these elements are brought together within a partial equilibrium model of the EU agricultural food sector. The model comprises conventional, GM and organic food. Demand is modelled in a novel fashion, whereby organic and conventional products are treated as horizontally differentiated but GM products are vertically differentiated (weakly inferior) relative to conventional ones. Supply accounts explicitly for the land constraint at the sector level and for the need for additional resources to produce organic food. Model calibration and simulation allow insights into the qualitative and quantitative effects of the large‐scale introduction of GM products in the EU market. We find that the introduction of GM food reduces overall EU welfare, mostly because of the associated need for costly segregation of non‐GM products, but the producers of quality‐enhanced products actually benefit.     

Genetically Modified Crops and Product Differentiation: Trade and Welfare Effects in the Soybean Complex

A partial equilibrium four-region world trade model for the soybean complex is developed in which Roundup Ready (RR) products are weakly inferior substitutes to conventional ones, RR seeds are priced at a premium, and costly segregation is necessary to separate conventional and biotech products. Solution of the calibrated model illustrates how incomplete adoption of RR technology arises in equilibrium. The United States, Argentina, Brazil, and the Rest of the World (ROW) all gain from the introduction of RR soybeans, although some groups may lose. The impacts of RR production or import bans by the ROW or Brazil are analyzed. U.S. price support helps U.S. farmers, despite hurting the United States and has the potential to improve world efficiency.     

Production risk and the estimation of ex-ante cost functions

Cost function estimation under production uncertainty is problematic because the relevant cost is conditional on unobservable expected output. If input demand functions are also stochastic, then a nonlinear errors-in-variables model is obtained and standard estimation procedures typically fail to attain consistency. But by exploiting the full implications of the expected profit maximization hypothesis that gives rise to ex-ante cost functions, it is shown that the errors-in-variables problem can be effectively removed, and consistent estimation of the parameters of interest achieved. A Monte Carlo experiment illustrates the advantages of the proposed procedure as well as the pitfalls of other existing estimators.