Offered the choice of these two contracts, the high-cost producer will choose Contract 1, as he will profit $1, and cannot profit from Contract 2, as his costs outweigh the compensation for 100 tons. The lowcost producer will always choose Contract 2. Although he could profit $2,301 under Contract 1, Contract 2 is designed to allow the low-cost producer to profit $2,302 and produce the maximum of 100 tons. This menu of contracts thus satisfies both producers’ participation and compatibility constraints, and incentivizes both parties to reveal their types by their contract choice. Note that offering this menu of contracts results in higher production at lower costs than rationing . Note also that the end-user still must pay the low-cost producers’ information rents in order to incentivize acceptance of the contract designed for the low-cost producer. Screening thus decreases, but does not eliminate, the rents low-cost producers can extract from private information. The amount of biomass that the high-cost producers can contract is also limited in order to make the high cost contract less desirable for the low-cost producer. Additionally, screening may limit producer participation. Screening presents another significant challenge for Principals. In order to design a menu of contracts to satisfy both the participation constraints and incentive compatibility constraints of producers, the Principal must have detailed knowledge of the characteristics and distribution of each type of producer. To the extent that an end-user’s understanding of producers is lacking, especially in a fledgling industry such as energy biomass, trimming cannabis the value and feasibility of screening may be limited severely. A third method to address adverse selection is through the use of auctions, specifically procurement auctions. In a procurement auction the buyer invites bids from suppliers for a specific contract. 

In auctioning, the lower-cost producers can still extract information rents from the end-user, as they must only offer a price just below the next lowest bidder, a strategy called bid shading. Therefore, they always offer a bid higher than their minimum bid, extracting the difference as information rent. The lower-cost the producer, the higher the information rent they can extract, while the highest-cost producer again cannot extract any information rent. While auctions again only minimize and do not eliminate information rents, auctions provide several advantages over other methods, such as screening or rationing. In theory, auctions can reduce the information rents without limiting production . For example, while rationing uses fixed prices and screening limits to decrease the attractiveness to low-cost producers, auctioning uses competitive bidding to achieve the same purpose. Finally, auctions dispense with the need of the end-user to know the cost distribution of different types of producers, and reveal changes in this cost distribution over time. On the other hand, auctions present some unique challenges. They require a critical mass of bidders to ensure competitive bidding, and create more uncertainty for the buyer , as they offer fewer predictions of producer responses. In addition, auctions can be costly and complicated to design and administer. A final strategy to address adverse selection is signaling, where the informed party acts first to reveal their private information to gain an advantage. This strategy has direct implications for both Principals and Agents. In a simple form of signaling, the Principal gathers information on observable characteristics of producers that are correlated with opportunity cost or other hidden information variables. Based on this information, the Principal can create minimum eligibility requirements for contracting. However, to prevent low-cost producers from masquerading as high-cost producers, the observable characteristics must be costly to fake. Also, information collection can be costly, and “the ability of this information to reduce information rents without distorting [production supply] will only be as good as the strength of the correlation between the characteristics and [producer types.]” 

Some producers, may also find it in their best interest to take the initiative to use signals to reveal their private information . End-users can increase supply while limiting the potential for information rents by contracting with high-cost producers that effectively signal their type. By requiring signals that are impossible or costly to mask , the end-user can obtain the added production from high-cost producers without the risk of paying increased information rents from low-cost producers masquerading as high-cost producers.While adverse selection problems arise during contract negotiation, moral hazard emerges after the contract is signed. Moral hazard exists where the Agent makes a decision that affects the utility of both the Agent and the Principal, the Principal can only observe the outcome of the decision, which is an imperfect indication of the action, and the action that the Agent would take to maximize his utility does not simultaneously maximize the utility of the Principal . Information asymmetry in this case again gives rise to opportunistic behavior on behalf of the informed party, as they may shirk their effort. Literature from sociology and economic contract theory has developed several tools to address moral hazard problems. To model this problem, we offer a second simple example in which an end-user has contracted with a producer to produce and deliver biomass. Assume that a producer’s yield depends on two variables: his effort , which is costly to the farmer; and the weather. The end-user and producer have signed an acreage-based supply contract, where the farmer is to deliver the entire crop from 50 acres of land to the end-user for a fixed price per acre. This scenario gives rise to moral hazard, as the farmer has an incentive to slough off, a decision that conflicts with the interest of the end-user seeking to maximize yield from the land under production. Perhaps the most powerful tool available to address moral hazard is incentive contracting, developed in complete contracts literature. However, incentive contracting also creates the trade-off between risk and cost discussed earlier in the Risk Minimizing Perspective. 

The economic contract literature assumes that only the outcome of the Agent’s decision is observable, and thus the Principal can only influence the choice the Agent makes by conditioning the Agent’s utility on the outcome. However, because the outcome is imperfectly correlated to the Agent’s actions due to the variability of weather, basing the Agent’s utility on outcome imposes risk for the Agent. Once again using mechanism design, the Principal must maximize his utility subject to the producer participation constraints and incentive compatibility constraints. The incentive compatibility constraints imply that the contract must provide enough incentive that the producer prefers to put forth effort. For example, the producer must profit more from applying fertilizer than from failing to apply it. In our example above, where the end-user can only observe yield, the end-user can only base incentives on yield. Because application of fertilizer positively correlates with yield , the end-user could modify the contract to award a bonus for achieving a certain threshold of yield. If the end-user can renegotiate the current contract, he might desire a price-per-ton contract over an acreage contract, to tie the Agent’s utility to outcome . The proposition is quite a simple one: the end user will give the Agent a higher payment when the end-user can infer from the outcome that the Agent made a favorable decision, and vice versa. While both these solutions may satisfy incentive compatibility constraints by incentivizing the farmer to put forth effort, they also increase risk, which serves to tighten a producer’s participation constraints. In order to incentivize the producer to accept the incentive contract, the end-user must also satisfy the producer’s participation constraints. Participation constraints may include a host of factors, economic and non-economic, and the producer’s aversion to risk. Therefore, cannabis drying rack as risk is passed to the producer to satisfy incentive compatibility constraints, end-users must provide larger payments to satisfy the producer’s participation constraints. The extra compensation that the Principal must pay is an information rent that arises from the asymmetric information between the parties. Within this general theory, several important principles emerge. First, the smaller the expected difference between outcome of a favorable Agent action and an unfavorable one, the larger the incentive must be to motivate the Agent to act. The reason is because it becomes more difficult to distinguish between the Agent’s action and inaction. Also, the optimal strength of incentives is dependent on several factors. Second, the greater the value of any additional producer effort and the greater effect the incentive will have on the producer’s behavior, the stronger the incentive should be. Finally, the tradeoff between risk and incentive implies that weaker incentives should be given to more risk-averse producers. A more difficult problem arises, however, when a Principal has multiple objectives to maximize, and a producer’s single action affects both objectives. When a producer’s action supports one goal and opposes the other, incentive conflicts arise. The optimal balance will occur where the marginal benefit gained from incentivizing the producer to act to support one objective is equal to the marginal cost of the detriment to the conflicting objective. The value of incentive contracting is limited by more than the risk-cost tradeoff. Incentive contracts assume that outcome, and only outcome, is observable, and the Principal cannot gather additional information. Incentive contracts also assume that the Principal has no way to force the Agent to act.

While in some scenarios these two assumptions hold true, the agricultural context provides unique opportunities to employ additional tools to manage incentives.Incentive contracts rely on “quality measurement,” an observation limited by numerous factors, including the above mentioned inability to distinguish between quality arising from producer effort and quality arising from fortuitous circumstances . While yield is fairly easy to measure, other crop/production characteristics are more difficult to assess at delivery, such as moisture and ash content; carbon footprint; and other sustainability attributes . Large crop volumes, high costs of measurement technology, limited time, and logistical complexities further limit measurement ability. Also, when measurements are controlled by a single party, the risk of opportunistic behavior arises from measurement errors or fraud. Parties can address this risk, although at a cost, by employing third-party verification or allowing the other party to re-test. These terms refer to measurement characteristics of a transaction that reflect both the asymmetry of information and the costs of monitoring or verifying individual performance. Separability refers to the “ability to evaluate an Agent’s effort just by observing output,” or “how much of the quality/quantity of the product is measurably attributable to the producer’s management efforts[.]” Programmability refers to “how closely output is tied to specific input decisions and observable management practices.” Production processes that are highly separable are appropriately addressed by incentive contracts, as the “allocation of value and risk will be efficient.” Utilizing incentive contracts for production processes that are not separable creates weak incentives, increases producer risk, and also creates risk of opportunistic behavior by the producer. If production is not separable but highly programmable, contracts can better address moral hazard by controlling the production process, depending on the cost of monitoring. Increasing control through more complete contracting has several drawbacks, however. First, end-users must incur the cost of writing and enforcing additional contract provisions, which may require additional monitoring and enforcement effort. Decreased producer autonomy also requires compensation to overcome participation constraints and disallows potential gains from the producer’s specialized knowledge and skills. Two common examples of this type of control in the agricultural context are production contracts for poultry and hogs—both of which have engendered substantial farmer criticism due to perceptions of feeling trapped or intimidated by the contracts offered by the end-users of their products. An alternative method for the Principal to manage moral hazard is via monitoring. One policing model that end-users could employ is the use of field men, who periodically visit producers. Creating a network of field men yields a number of benefits. First, monitoring in this way increases the number of observable variables, by not only observing directly the production capabilities and practices of individual farmers, but also observing the production environment beyond the producer’s control, such as weather and pest problems. If the field man perceives opportunistic or suboptimal behavior on behalf of the producer, the field man can address the problem before damage occurs to the crop. Although field men may be perceived as “supervisors, spies, or adversaries,” they can provide multiple benefits for producers, and farmers rarely have negative perceptions of these observers.