Grower Response to Contracts and Risk in Genetically Modified (GM) Crops

Article excerpt

Contract strategies can resolve some of the challenges that exist for property rights conformance of genetically modified (GM) crops. The purpose of this research is to determine how contract terms impact adoption decisions related to GM grain production and marketing. A simulation model was developed for prospective GM introduction in hard red spring (HRS) wheat, and distributions of net returns for growers were analyzed using stochastic dominance and stochastic efficiency. Results illustrate that contracts can be designed to induce desired behavior. Technology fees, probabilities of detection, and the level of non-GM premiums were the most notable factors influencing adoption decisions. In addition, point-of-delivery pricing and premiums for non-GM production impact adoption decisions.

Key words: adoption risk, GM crops, incentives contracting, stochastic dominance


Agbiotechnology companies use contracts in numerous crops to protect their intellectual property and earn a return from their research. Contracts for genetically modified (GM) crops normally include terms for technology user fees, seed planting, and replanting restrictions (e.g., growers cannot keep seed for the following year for replanting purposes). Contract provisions allow monitoring of acres planted, and stewardship guidelines provide growers with agronomic recommendations and requirements for technology use. In response, growers can choose from a range of alternatives including adoption and complying or not complying with the contract terms, adopting it illegally, or not adopting the technology.

The purpose of this research is to examine how contract terms and pricing strategies impact adoption decisions related to GM grain production and marketing, in this case wheat. The analysis determines how technology agreements impact incentives to conform to contract terms, the size of non-GM premiums to discourage adoption, and point-of-delivery pricing. Stochastic dominance and stochastic efficiency are used to identify how contract terms affect efficient choice sets for growers and risk-efficient adoption strategies. This article contributes to the growing literature on contracting strategies, risk, and GM crops marketing.

Background and Previous Literature

There has been an escalation in research on contracts in the economics literature (e.g., as discussed in Dutta, 1999; Laffont and Martimort, 2002; Molho, 1997; Rasmusen, 1994; and Salanié, 1997; among others). In agriculture, there has been an increase in the use of contracts to govern production and marketing in agriculture (MacDonald et al., 2004; Key and MacDonald, 2006). However, in grains (and small grains in particular), use of contracts has not been common, comprising only about 12% of the production.

Contracts are more critical for GM crops. The contracts examined here would be considered production contracts in the paradigm of MacDonald et al. (2004). Production contracts detail specific farmer and contractor responsibilities and typically specify particular inputs and production guidelines, and allow the contractor to give technical advice and make field visits. Sykuta and Parcell (2003) describe the terms of the agbiotechnology contract used by DuPont, and the contract terms used by a broad spectrum of agbiotechnology firms are discussed by Maxwell, Wilson, and Dahl (2004). With increased use of agbiotechnology in crop production, undoubtedly there has been an increase in use of production contracts (e.g., as analyzed in Hurley, Mitchell, and Rice, 2004). Further, as GM output traits are developed, the need for contracting will become essential (Riley and Hoffman, 1999; Shoemaker et al., 2001).

Contracts define fees, agronomic stewardship recommendations,1 penalties, incentives, and premiums. The agbiotechnology firm establishes the technology fee, but must consider the tradeoff between higher fees versus the disincentive they provide growers to adopt the technology and/or comply with contract terms. …