2.1. Land Use, Related Profit Values, and Creation of the Land Decision Grid
Enrollment under CP-42 requires land to meet all CRP requirements, including being historical cropland. To accurately model landowner decisions in CP-42, we created a representative land grid of actual cropping patterns and realistic returns or profits using Goshen County, Wyoming, as a model. Goshen County has the most CRP-eligible land of all counties in Wyoming, and has the highest total value of agricultural products sold, including both crops and livestock [
29]. Located in Southeast Wyoming, bordering Nebraska, Goshen County included the cultivation of a range of crops in 536 farms consisting of 241,491 acres in 2012 [
22].
The model grid was delineated into a ten by ten land grid, where each land parcel in the grid represents an eighth section equivalent to 80 acres of land. The entire land grid represented a total of 8000 acres, and is modeled to represent four landowners each owning 2000 acres. These values are similar to the average farm size in Goshen County of 1735 acres [
29].
To determine the cropping patterns of CRP-eligible land for the model, we obtained data on harvested crops in Goshen County from the agricultural census reports for Wyoming in 2012 [
30]. We also gathered information on typical crop rotations practiced in Goshen County from extension specialists in the County.
Table 1 reports the nature of the crop rotations and the prevalence of their practice. We used this information to calculate the prevalence of individual crops and crop rotations in the land grid model.
Landowner decisions should depend on the relative enrollment incentives under CP-42 compared to the value of crop production. If CP-42 payments exceed the profitability of land, it is expected that a landowner will decide to enroll the land and remove it from agricultural production. In contrast, if the profitability of the land remaining in agricultural production exceeds the value of CP-42 and CRP payments, then the landowner is expected not to enroll the land. Determining the profitability of crop rotations prevalent in Goshen County was necessary to create the proper incentives for experiment participants. The profitability of each cropping rotation was determined using calculated per acre profits per year for single crops with data from the Wyoming Agricultural Statistics 2012, University of Nebraska-Lincoln (UNL) crop budgets 2013 [
30,
31], and from Lee et al.’s [
32] profit estimates. To allow for variations in the profitability of crops, we adopted the method outlined by Lee et al. [
32]. Allowing for variability in crop profitability,
Table 2 shows the average profits generated for individual crops based on the 2012 prices. High and low profit were obtained at the 95th and 5th percentiles of individual crops. Dry beans yield the highest profits at
$883.22 per acre, followed by sugar beets with a profit of
$829.31, and corn with a profit of
$807.21. Marginal lands provide negative profits for certain crops, such as corn, oats, sunflower, and winter wheat.
Since the objective of creating the profitability of cropping land is to model landowner enrollment decisions, profitability measures had to reflect the ten-year enrollment period under CP-42. To compare productive profitability to enrollment payments, we calculated the net present value (NPV) of profits and potential enrollment payments over a ten-year period. A discount rate of five percent was used, as this was representative of a standard operating loan for the case study area in 2012.
Table 3 reports these net present value estimates of crop profits for relevant crop rotations. In addition, we report the net present value for an eighth section, since it provides the profitability of the land patterns used in the created land grid. Although some individual crops may have negative profits, all crop rotations have positive average profits.
Even within the same county, there is strong heterogeneity in profitability of the land. Land that is amenable to a barley, high profit corn, and dry beans rotation generates the highest profit per year at over $570 per acre. In contrast, marginal land that is suitable for only dry wheat production will generate an average of three dollars per acre. Based on the CP-42 payment ($150 per acre) in addition to the $26 per acre average yearly CRP payment in Wyoming, the average payment over the ten-year enrollment period is $410. When properly discounted, the NPV of enrolled land is approximately $400. These values provide the realistic incentives associated with crop production versus program enrollment.
From the profitability of the crop rotations listed in
Table 3 along with the prevalence of each crop in Goshen County, Wyoming, provided in
Table 1, a representative model of crop pattern was developed for the study area (see
Figure 1). This spatial distribution of cropping patterns was developed in consultation with crop extension specialists in Goshen County to best model the County. We assume lower productive land with lower profits is on the border of individually held land. In addition, more productive land is assumed to be grouped together in relatively small patches that are scattered throughout the landscape. Specialty crops, such as oats, sunflowers, alfalfa seed, and sugar beets, are assumed to be grown by only one landowner. Each of these assumptions is based on current cropping patterns in Goshen County.
The values in
Figure 1 were used to assign the various cropping rotations values in the created experimental land grid. This spatially explicit experimental land grid was the basis for participant decisions regarding whether land would be enrolled in CP-42. Note that this approach of making actual land profitability values endogenous in the experimental land grid has not been done previously in these types of reported experiments.
2.2. Experimental Economics Methods
To understand landowner enrollment decisions under CP-42, we use economic experiments designed to elicit conservation behavior from participants. This type of laboratory experiment has been used previously in the literature and shown to work well to test incentive mechanisms for land conservation decisions [
33,
34,
35]. Since CP-42 is a relatively new policy and actual detailed enrollment data are unavailable, we use these economic experiments to predict behavior under the implementation of this policy. Economic experiments reduce the need for expensive policy trial and error, and they have been shown to provide valuable information that can be less expensive than field or pilot data [
36,
37]. Moreover, the use of laboratory experiments eliminates selection bias (as subjects are randomly assigned), allows for better control over variables and influencing factors, and full control over information available to participants [
38].
We conducted the experiments in the fall of 2015 at the University of Wyoming. The experiments received approval by the Institutional Review Board, #20150406CR00732. Eight sessions were conducted with four participants each, generating a sample of 28 participants. We used a software program designed by Dr. Gregory Parkhurst to run the experiments. At the beginning of each session, participants were given an information packet that included a copy of printed instructions and a record sheet to record earnings. Participants were asked to read and sign a human subjects’ consent form that followed standard experiment protocol. Participants were informed that their participation was completely voluntary and they could leave the experiment at any time.
Following standard economic experiment procedure, the instructions were read aloud by the experimenter. The monitor gave the instructions to participants in both printed form and on the computer. Participants were informed they would be presented with a grid of land cells and be making decisions to either cross out (enroll) their land cells (representing a parcel of land in their grid) or not (leave in production). The instructions did not include information on the context of crossing a cell out. Participants were not told the context of their decisions in the experiment (enrolling in CP-42), since this type of parallelism can lead to loss of control over experimental outcomes [
39]. The experiment used the created ten by ten land grid model, consistent with previous studies (e.g., [
33,
40]). Four participants were included in each experimental session representing landowners from Goshen County, Wyoming. Each one of these landowners managed 25 land parcels in a five by five sub-grid and identified as Player-1, Player-2, Player-3, and Player-4 (
Figure 2). The numerical values in each cell were reported in a currency called tokens (100 tokens =
$1.00), and each value represented the profitability of eighth sections of different crop rotations in Goshen County. Profitability in each cell was scaled down by a factor of 100 (rounded) to give values that were easily understandable to participants, but retained their relative values previously described for creating the land grid.
The participants were told that they would be paid at the end of the session based on their decisions in the experiment. They were then told the numerical values listed in each cell were the values (in tokens) that they would earn if they did not cross a cell out. Next, they were instructed that if they decided to cross a cell out, they would not earn the productive value but would earn a set value. The set value for crossed out cells represented the net present value of enrollment under CP-42, which was determined at a value of four in the experiment. Lastly, participants were told that their payment would be based on the sum of the productive value of those cells not crossed out plus the enrollment value for each crossed out cell.
Prior to the actual experiment, the participants participated in three practice rounds. Then, each session consisted of up to ten rounds [
33]. To avoid end-game-effects, the participants were informed that the experiment had a random number of rounds [
41]. As CP-42 requires a minimum of ten years of enrollment, ten rounds equated to 100 years in real time, a reasonable estimate for the length of time of farm ownership in Goshen County.
The computer randomly assigned each participant to one of the four positions (i.e., Player-1 through Player-4). Each participant saw his or her five by five sub-grid in a dark green color on the computer screen, and was able to determine his or her position in relation to the other participants. The grid positions for all participants were constant for all rounds to allow for repeated interactions among the same participants. Repeated interactions more accurately describe reality, as landowners do not typically change locations within such a small geographic area at such small time periods.
The participants had access to an on-screen calculator to determine the estimated payment of their choices before making a decision. The participants could select different configurations of enrolled land parcels and determine the estimated value before the actual choices were submitted. The calculator assured that no participant would make incorrect decisions due to manual computational errors.
A chat window appeared at the bottom of the screen to allow the participants to communicate with one another (we allowed participants to communicate with all other participants, but we limited the number of chats to three per participant per round). This option was designed to recreate real-life situations in which landowners can communicate with each other regarding policy implementation prior to their enrollment deadline. The chat component is important as, outside of the laboratory, decisions to conserve land can impact neighbors. In the real world, neighbors have the ability to discuss their decisions with each other when these decisions may affect one another. In addition, the chat option is also consistent with previous economic experiments modeling land use conservation decisions (e.g., [
40]).
Each participant had three minutes to make a decision and submit his or her choices per round. The time remaining in a round was displayed on the computer screen for the participants to see. If a participant ran out of time, the computer submitted the choice representing the configuration of parcels conserved on the computer at the moment time lapsed. In case a participant had not chosen any parcels to conserve by the end of a round, the computer submitted the choices with no conserved parcels.
At the end of each round, the participants could see their enrollment decisions and the number of tokens earned. In addition, the participants could see the decisions made by the other participants. A history box also appeared on the computer screen that displayed a record of the parcels that each participant in the group conserved in previous rounds. The players could use this information to make decisions in future rounds. The players were also told that the provided record sheets were an optional method to record choices and earnings in each round.
During the experiment, we expect each participant to make decisions that maximize his or her own payoffs. Based on the experimental design, we expect each participant to make enrollment decisions based on the following:
where
i represents one of the 25 parcels each participant has control over in the experiment,
xi is equal to one if parcel
i is not enrolled (left in production) and zero if enrolled, and
Pi is the productive value of parcel
i when left in production. If parcel
i is not conserved, then
xi is equal to one and the payoff from that parcel will be its associated productive value,
Pi. Conversely, if parcel
i is enrolled, then
xi is equal to zero, and the payoff is four tokens (the value of a crossed-out cell) for that particular parcel.
The experiment lasted an average of an hour and a half. Participant earnings accumulated over the rounds and were paid in cash at the end of the experiment. The cash payouts averaged between $22 and $26 per person.