Landowners may be unwilling to rent land to a farmer seeking to grow novel crops with the attendant long-term contract that typifies many biomass supply arrangements. Financial flexibility and access to credit may face similar limitations if lenders perceive that producers are unable to adequately manage the relatively higher risk inherent in the nascent bio-energy industry. A final risk management strategy traditionally used by producers is adjusting cultural practices, including tillage practices and input levels, to account for price and policy changes. This simple strategy may be limited in the biomass industry in at least two ways. First, crop attribute requirements and cultural practice obligations incorporated in biomass contracts may limit farmers’ ability to adjust methods. Second, the producers’ relative unfamiliarity with novel energy crops may limit knowledge of alternative production practices. Thus, many of the historical tools for farm risk management are largely diminished in the biomass context. This contributes to the high level of producer-perceived risk in the biomass industry and resulting reluctance to transition from commodity crop production to potentially more profitable dedicated bio-energy crops. But to the extent that biomass contracts between producer and end-user can recreate these traditional risk management tools, rolling benches perceived risks may decline and facilitate adoption at lower cost.
A second major tool in decreasing producer risk in the biomass context—learning and experience—arises from both rural sociology research on innovation adoption and economic risk minimization scholarship. The learning and experience process is a critical method to reduce risk and uncertainty, thereby encouraging adoption. The literature identifies the adoption of technology as a dynamic learning process, in which learning and experience decrease risk by reducing uncertainty, improving decision making, and enhancing skill. As producers gain knowledge and experience with the innovation, skills improve in adapting the crop to particular agronomic and operational situations, and thus decrease the chance of failure. This dynamic learning process includes several stages: awareness, non-trial evaluation, trial evaluation, adoption, and review/modification. From these categories one can see that learning occurs throughout—before trialing via information collection and continuing through post-adoption in the form of adaption to new production information. While the learning process heavily depends on the trialibility of the innovation, learning and experience is much broader, and can be derived from more sources and methods than those that depend on the trialibility characteristics of the innovation. Certification systems, such as private sustainability standards, can provide key avenues of learning as potential adopters work with individual certifiers to implement innovative practices. University-based demonstration farms and extension outreach services also provide proxies for trialibility by sharing information in an open, collaborative environment.
The implications of the learning/experience literature for designing biomass contracts are simple, but important. Because learning and experience is a major tool in reducing risk and uncertainty, contracts incorporating provisions to facilitate and reward learning, both before and after the contract is signed, would provide a non-monetary, yet important incentive for farmer acceptance. Moreover, as the learning process continues beyond adoption, contracts that allow for information sharing between third parties, such as knowledge and experience with growing and harvesting biomass, would provide similar incentives. Unfortunately, at this stage of the industry, secrecy is often the norm in production contracts. This secrecy increases the perceived risk for some potential adopters and warrants additional research on the benefits and costs of these non-disclosure terms in a developing industry. The literature on formal economic contract theory generally focuses on two contract functions: risk-sharing and cost minimization. These two functions contain significant overlap and often conflict, in part because costs can be so broadly defined as to encompass all concepts of risk. Many cost-minimizing principles and tools can be gleaned from the economic contract literature, discussed more fully in Part II.C. below. However, in this section we discuss aspects of economic contract theory to mitigate and share risk, and the tradeoff between minimizing risk and cost.Contracts can minimize both exogenous and endogenous producer risks in two ways: eliminating risk, and transferring risk to another party. Exogenous risk arises from factors outside the parties’ control, such as weather and policy changes. As such, parties to the contract cannot eliminate exogenous risk, but can transfer or share it amongst themselves.
On the other hand, endogenous risk arises from the actions of the parties, such as opportunistic behavior and default. Accordingly, parties can minimize endogenous risk by controlling or incentivizing certain actions within the contract framework. Although farmers usually bear exogenous production risk, some contracts for traditional agricultural commodities transfer this risk to the end-user. For example, yield risk—a function of, among other things, weather—can be transferred completely to the end-user by contracting for a set amount of acreage production, rather than a fixed volume.82 Parties also can eliminate price risk over the term of the contract by establishing constant unit prices or price floors and ceilings. Information asymmetry and incomplete contracts are two common sources of endogenous risks, which give rise to the risk of opportunistic behavior. To exemplify the endogenous risk minimization function of contracts, consider the following classic example addressing moral hazard from the end-user’s perspective. The risk of opportunism arising from moral hazard and adverse selection typically is addressed through the Principal-Agent Framework by providing incentives in the contracts to align the goals of the parties.84 Suppose an end-user would offer a producer an acreage based contract, where the producer delivers to the end-user whatever yield is produced off of a fixed number of acres, for a fixed price per acre. Because the producer’s income does not depend on yield, the producer may act opportunistically, such as by applying less than the optimal amount of fertilizer to the crops. Information asymmetry is present because the farmer knows more about production practices than the end-user. Upon delivery, the end-user cannot determine if the lower than optimal yield was because of the lack of producer effort or from exogenous factors, such as poor weather, and thus cannot justify penalizing the farmer for a poor yield. This is especially true with novel cropping systems, such as dedicated bio-energy crops, as there is neither a history of production/yield data nor comparable county average yields, such as those available for established commodities . Thus, in order to decrease the risk of opportunism, the end-user must provide incentives to align the goals of the producer with those of the end-user. One such method would be to offer a payment structure dependent solely on yield, such as a set price per tonnage. The end-user could also modify the acreage contract and provide a bonus payment for achieving a higher yield. By incentivizing the producer to maximize yield, these strategies decrease the risk of opportunism for the end-user, grow tray but at the cost of transferring exogenous yield risk to the producer. A key principle of economic contract theory and risk-sharing is that there is nearly always a tradeoff between risk and costs. Gaining information and experience also is costly. Similarly, transferring exogenous risk through contracting will usually incur a risk-transfer premium, as the party assuming risk must be compensated. This is identical in concept to insurance premiums for any traditional type of insurance, such as property or health insurance.
Minimizing endogenous risk also comes at a cost. Writing and enforcing more complete contracts is costly, and difficult to achieve, especially in novel markets. Incentive payments are problematic for both parties. The party creating the incentive incurs the costs of pay-for-performance incentives. The party accepting the incentive payment ends up assuming more risk, as is shown in the previous example. When the Agent is risk averse, the Agent will demand a risk premium to compensate for the additional risk created by the incentive payment.Economists traditionally model information asymmetry problems through the Principal-Agent Framework, where the uninformed Principal offers a contract to an informed Agent. For example, a bio-refinery may offer a standard form contract to a number of producers, of whom the end-users know little or nothing about. While this model does not perfectly fit every structure of the biomass industry , the Principal-Agent model remains useful in identifying and addressing information asymmetry issues. Adverse selection problems arise during the negotiation of the contract when the Agent knows more about personal tolerances and preferences than the Principal knows or can observe.96 For example, producers know their risk tolerance, opportunity cost, and minimum demand for compensation, whereas the end-user can only speculate as to an individual producer’s characteristics. Producers can then “use this private information as market power to extract information rents” from end-users, by negotiating for a payment higher than the minimum that would be necessary for them to accept the contract. For example, suppose there are two types of potential biomass producers, high-opportunity-cost producers and low opportunity-cost producers. In order for the biomass end-user to incentivize the producers to participate, he will have to pay the high-cost producer a higher compensation than the low-cost producer to overcome his greater costs. However, when the end user cannot observe the types of the producers, the low-cost producers have the opportunity and incentive to portray themselves in negotiation as high-cost producers to extract the additional rents necessary to attract high-cost producers. The result of the end-user’s inability to distinguish between producers is higher total input supply costs. Economic contract theorists have discovered several methods to address adverse selection in the complete contract literature—the general goal is isolation strategies to encourage producers to reveal their types without incurring prohibitive information rents. Within the Principal-Agent Framework, complete contract theory offers several possible solutions to adverse selection problems, including rationing, screening, signaling, and auctioning. These strategies constitute a set of tools for contracting parties to choose from in addressing adverse selection problems. To explain these concepts, consider again the example mentioned earlier in the “Principal-Agent” section. The low-cost producer can produce a ton of biomass for $4/ton, plus an initial start-up cost of $100, up to a maximum of 100 tons . The high-cost producer’s cost per ton increases exponentially starting from $1/ton, and he also incurs $100 in start-up costs, up to a maximum of 100 tons . To obtain the largest supply of biomass possible for the least cost, the end-user would seek to deal only with the low-cost producers. However, the end-user cannot limit engagement due to an inability to identify the low-cost producers and, more importantly, low-cost producers alone cannot satisfy total demand. Therefore, the end-user must contract with both high and low-cost producers. A relatively simple but problematic tool that Principals can use is termed rationing. Principals can use rationing to offer contracts that are only feasible for the “better” producers. In this way the end-user limits the amount of rents that the better producers can extract by claiming to be “worse” producers; because the end-user knows the worst producers cannot feasibly accept the contract, the producer cannot pretend to have their characteristics. In our example, the end-user could offer contracts that would only be feasible for the low-cost producers and for a limited amount of high-cost production. For example, the contractor could offer $50/ton for biomass. This scenario would create for the low-cost producer a profit of $2,700 producing a maximum of 100 tons, and would also make biomass production profitable for the high-cost producers up to a volume of 48 tons. The downside to this simple contract solution is that the number of producers that can participate is limited by rationing, both by decreasing the amount of supply an end-user can secure and by excluding potential high-cost producers from the biomass industry. Also, the low-cost producers still extract relatively high information rents, as they would be incentivized by a much lower price . Economists have discovered a more complicated but perhaps more efficient strategy to address adverse selection—screening. With a screening strategy, the Principal offers a menu of contracts designed so that each type of producer will prefer the contract designed for his type; the producer cannot be better off by choosing a contract designed for another type. In this way, end-users must design contracts not only to satisfy the producers’ participation constraints, but also the producers’ incentive compatibility constraints. In our example above of just two types of producers, the end-user could offer two contracts: Contract 1 offering $2,601 for 50 tons of biomass, and Contract 2 offering $2,802 for 100 tons of biomass.