Research Reports

Report 2006-02: The Pricing Performance of Market Advisory Services in Corn and Soybeans Over 1995-2004

April 2006

Scott H. Irwin, Darrel L. Good, Joao Martines-Filho, and Ryan M. Batts [1]

Copyright 2006 by Scott H. Irwin, Darrel L. Good, Joao Martines-Filho and Ryan M. Batts. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies.

Introduction

Farmers in the U.S. consistently identify price risk as one of the greatest management challenges they face. For example, Smith (1989) conducts a national survey of U.S. agricultural producers and finds that 79% rate marketing as either important or very important to the financial success of their operations. Patrick and Ullerich (1996) survey Midwestern grain producers and report that price variability is the highest rated source of risk by crop producers. Coble et al. (1999) survey producers in Indiana, Mississippi, Nebraska and Texas and find that crop price variability, by a wide margin, is rated as having the most potential to affect farm income. Norvell and Lattz (1999) survey a random sample of Illinois producers and show that price risk management ranks second (following computer education and training) among ten business categories in which producers identify needs for additional consulting services.

In a related vein, a general perception exists among market observers that farmers perform poorly in managing price risk. More specifically, it is a common belief that farmers substantially under-perform the market, which is reflected by the oft-repeated adage that, “Farmers market two-thirds of their crops in the bottom third of the price range.” This belief is apparently widespread even among farmers. Survey results from University of Illinois Extension meetings in December 2000 indicated that 77% of attendees agreed with the statement, “On average, corn and soybean producers market 2/3 of their crop in the bottom 1/3 of the price range.” This perception is also evident in a survey of the membership of the American Agricultural Economics Association by Pope and Hallam (1986). They report that 51% of survey respondents agreed or strongly agreed with the statement, “Marketing, more than production skills, increases net farm income.”

There is considerable evidence that many farmers turn to market advisory services in an effort to improve their performance in managing price risk (e.g., Sogn and Kraner, 1977; Smith, 1989; Patrick and Ullerich, 1996; Patrick, Musser and Eckman; 1998; Schroeder et al., 1998; Norvell and Lattz, 1999; Pennings et al., 2004). For a subscription fee, agricultural market advisory services provide specific pricing advice to farmers, such as when and what amount to hedge in the futures market or sell in the cash market[2]. Available estimates on the use of advisory services, marketing newsletters and marketing consultants range from 21.1% of Illinois farmers (Norvell and Lattz, 1998) to 66% of farmers nationwide (Smith, 1989). There is some evidence that farmers have been increasing their spending on market advisory services. Among Purdue’s Top Farmer Workshop participants, annual expenses on marketing advice moved from the fourth highest expense for consultants to the second highest over 1991 to 2001, growing in absolute terms from $755 to $3,455 per year (Patrick, 2002). Finally, Davis and Patrick (2000), Katchova and Miranda (2004) and Pennings et al. (2004) show that the advisory services have a significant impact on the marketing practices of farmers.

A limited number of academic studies investigate the pricing performance of market advisory services[3]. In the earliest studies, Marquardt and McGann (1975) and Marquardt (1979) evaluate the accuracy of cash price predictions for 10 private and public outlook newsletters in corn, soybeans, wheat, cattle and hogs over 1970-1973. They find that futures prices generally are a more accurate source of forecasts than either the private or public newsletters. Gehrt and Good (1993) analyze the performance of five advisory services for corn and soybeans over the 1985 through 1989 crop years[4]. Assuming a representative farmer follows the hedging and cash market recommendations for each advisory service; a net price received for each year is computed and compared to a benchmark price. They generally find that corn and soybean farmers obtained a higher price by following the marketing recommendations of advisory services. Martines-Filho (1996) examines the pre-harvest corn and soybean marketing recommendations of six market advisory services over 1991 through 1994. He computes the harvest time revenue that results from a representative farmer following the pre-harvest futures and options hedging recommendations and selling 100% of production at harvest. Average advisory service revenue over the four years is larger than benchmark revenue for both corn and soybeans. Kastens and Schroeder (1996) examine the futures trading profits of seven to ten market advisory services for the 1988-1996 crop years. They report negative gross trading profits for wheat and positive gross trading profits for corn and soybeans. The authors indicate that incorporating brokerage commissions and subscription costs would have substantially diminished trading returns. Finally, Kalous, Dhuyvetter and Kastens (2005) investigate the post-harvest marketing recommendations of a single advisory service over 1970-2002 and find that the average net price for a Kansas wheat producer following the service is two cents less than the average harvest price.

While a useful starting point, previous studies have important limitations. First, the cross-section of advisory services tracked for each crop year is quite small, with the largest sample including only ten advisory services. Second, the results may be subject to survivorship bias, a consequence of tracking only advisory services that remain in business at the end of a sample period. The literature on the performance of mutual funds, hedge funds and commodity trading advisors provides ample evidence of the upward bias in performance results that can result from survivorship bias (e.g., Brown et al., 1992; Schneeweis, McCarthy and Spurgin, 1996; Brown, Goetzmann and Ibbotson, 1999). Third, the results may be subject to hindsight bias if advisory service recommendations were not collected on a “real-time” basis (Jaffe and Mahoney, 1999). Hindsight bias is the tendency to collect or record profitable recommendations and ignore or minimize unprofitable recommendations after the fact.

This discussion suggests the academic literature provides farmers with a limited basis for evaluating the performance of market advisory services. The Agricultural Market Advisory Service (AgMAS) Project was initiated in 1994 with the goal of providing unbiased and rigorous evaluation of market advisory services[5][6]. The AgMAS Project has collected marketing recommendations for no fewer than 23 market advisory programs each crop year since the project was initiated. While the sample of advisory services is non-random, it is constructed to be generally representative of the majority of advisory services offered to farmers. Further, the sample of advisory services includes all programs tracked by the AgMAS Project over the study period, so pricing performance results should not be plagued by survivorship bias. Finally, the AgMAS Project subscribes to all of the services that are followed and records recommendations on a real-time basis. This should prevent the pricing performance results from being subject to hindsight bias.

The purpose of this research report is to evaluate the pricing performance of market advisory services for the 1995-2004 corn and soybean crops. Following the literature on mutual fund and investment newsletter performance (e.g., Metrick, 1999; Jaffe and Mahoney, 1999), two basic questions will be addressed in this study: 1) Do market advisory services, on average, outperform appropriate benchmarks? and 2) Do market advisory services exhibit persistence in their performance from year-to-year? Certain explicit marketing assumptions are made to produce a consistent and comparable set of results across the different advisory programs. These assumptions are intended to accurately depict “real-world” marketing conditions facing a representative central Illinois corn and soybean farmer. Several key assumptions are: i) with a few exceptions, the marketing window for a crop year runs from September before harvest through August after harvest, ii) on-farm or commercial physical storage costs, as well as interest opportunity costs, are charged to post-harvest sales, iii) brokerage costs are subtracted for all futures and options transactions and iv) Commodity Credit Corporation (CCC) marketing loan recommendations made by advisory programs are followed wherever feasible. Based on these and other assumptions, the net price received by a subscriber to a market advisory program is calculated for the 1995-2004 corn and soybean crops.

Five quantitative indicators of performance are applied to advisory program prices and revenues over 1995-2004. The first indicator is the proportion of advisory programs in the top-, middle- and bottom third of the price range. The second indicator is the proportion of advisory programs that beat benchmark prices. The third indicator is the average price (or revenue) of advisory programs relative to benchmarks. The fourth indicator is the average price (or revenue) and risk of advisory programs relative to benchmarks. The fifth indicator is the predictability of advisory program performance from year-to-year. Both market and farmer benchmarks are developed for the evaluations. All benchmarks are computed using the same basic assumptions applied to advisory service track records.

The next section of the report describes the procedures used to collect market advisory service recommendations. The second section describes the methods and assumptions used to simulate net advisory prices. The third section presents the methods and assumptions used to compute benchmark prices. The fourth section of the report presents 2004 pricing results for corn and soybeans. The fifth section presents a summary of the combined results for the 1995-2004 crop years. The sixth section discusses performance evaluation results for 1995-2004. The final section presents a summary and conclusions.

Please note that the results for 1995-2003 were released in earlier AgMAS research reports (e.g., Irwin, Good, Martines-Filho, and Hagedorn, 2005), while results for the 2004 crop year are new. In addition, the data collection phase of the AgMAS project is complete with the 2004 crops, and hence, this is the final performance evaluation report for corn and soybeans. Research is ongoing for other commodities tracked over 1995-2004.

Market Advisory Service Recommendations

The market advisory services included in this evaluation do not comprise the population of market advisory services available to farmers. The included services also are not a random sample of the population of market advisory services. Neither approach is feasible because no public agency or trade group assembles a list of advisory services that could be considered the “population.” Furthermore, there is not a generally agreed upon definition of an agricultural market advisory service. To assemble the sample of services for the AgMAS Project, criteria were developed to define an agricultural market advisory service and a list of services was assembled.

Five criteria are used to determine which advisory services are included in the AgMAS study. First, marketing recommendations from an advisory service must be received electronically in real time. The recommendations may come in the form of satellite-delivered pages, Internet web pages or e-mail messages. Services delivered electronically generally ensure that recommendations are made available to the AgMAS Project at the same time as farm subscribers. This form of delivery also ensures that recommendations are received in “real-time.” This avoids the problem of recommendations being delivered after the date of implementation intended by an advisory service. Such a problem could occur frequently with recommendations delivered via the postal service.

The second criterion is that a service has to provide marketing recommendations to farmers rather than (or in addition to) speculators or “traders.” Some of the services tracked by the AgMAS Project do provide speculative trading advice, but that advice must be clearly differentiated from marketing advice to farmers for the service to be included. The terms “speculative” trading of futures and options and “hedging” use of futures and options are only used to identify whether a service is focused on speculators or farmers. Within a clearly defined farm marketing program, a distinction between speculative and hedging use of futures and options is not necessary.

The third criterion is that marketing recommendations from an advisory service must be in a form suitable for application to a representative farmer. That is, the recommendations have to specify the percentage of the crop involved in each transaction --cash, futures or options-- and the price or date at which each transaction is to be implemented. It is also helpful if advisory services make specific recommendations about implementation of the marketing loan program, but that is not required. Note that some advisory services evaluated by the AgMAS Project do not make any futures and options recommendations, so it is not necessary to make such recommendation to be included in the study. Services that make futures and options hedging recommendations, but fail to clearly state when cash sales should be made, or the amount to be sold, are not considered for inclusion.

The fourth criterion is that advisory services must provide “blanket” or “one-size fits all” marketing recommendations so there is no uncertainty about implementation. While different programs may be tracked for an advisory service (e.g., a cash only program versus a futures and options hedging and cash program), it is not feasible to track services that provide “customized” recommendations for individual clients[7].

A fifth criterion addresses the issue of whether a candidate service is a viable, commercial business. This issue has arisen due to the extremely low cost and ease of distributing information over the Internet, either via e-mail or a website. It is possible for an individual with little actual experience and no paying subscribers to start a “market advisory service” by using the Internet. Hence, there is a need to exclude firms that are not viable commercial concerns. At the same time, any filter in this regard should not be so restrictive that newer and smaller advisory services are excluded from the AgMAS study for an unreasonably long period of time. This same issue is prevalent when evaluating the performance of other types of professional investment advisors, such as commodity trading advisors. In these cases, it is not unusual to screen firms by the length of track record and amount of funds under management[8]. An analogous screen for market advisory services can be based on the length of time the service has provided recommendations and the number of paying subscribers. The specific criterion used is that a candidate advisory service must have provided recommendations to paying subscribers for a minimum of two marketing years before the service can be included in the AgMAS study. This criterion should exclude non-viable services, while at the same time providing a relatively low hurdle for new and legitimate market advisory services.

The original sample of market advisory services was drawn from the list of Premium Services available from the two major agricultural satellite networks, Data Transmission Network (DTN) and FarmDayta, in the summer of 1994[9]. While the list of advisory services available from these networks was by no means exhaustive, it did have the considerable merit of meeting a market test. Presumably, the services offered by the networks were those most in demand by farm subscribers to the networks. In addition, the list of available services was cross-checked with other farm publications to confirm that widely followed advisory firms were included in the sample. It seems reasonable to argue that the resulting sample of services was generally representative of the majority of advisory services available to farmers.

Additions and deletions to the sample of advisory services have occurred over time. Additions largely have been due to the increasing availability of market advisory services via alternative means of electronic delivery, in particular, websites and e-mail. Deletions have occurred for a variety of reasons. A total of 41 and 40 advisory service programs for corn and soybeans, respectively, have been included in the sample at some point in time. Table 1 contains the complete list of advisory programs and includes a brief explanation why each program not included for all crop years is added or deleted from the sample. The term “advisory program” is used in the remainder of this report because several advisory services have more than one distinct marketing program. For example, Agri-Edge, AgLine by Doane, Ag Market Pro, Brock, Pro Farmer and Stewart-Peterson Advisory Services each had or have two distinct marketing programs, Risk Management Group had three distinct marketing programs and AgriVisor has four distinct marketing programs. Allendale provides two distinct programs for corn, but only one for soybeans.

The total number of advisory programs evaluated for the 2004 crop year is 27 for corn and 26 for soybeans. Three programs offered by the Risk Management Group were discontinued in March 2005. Since this program issued several recommendations for the 2004 crops by March 2005, it is included for the 2004 crop year. Two programs offered by Ag Market Pro were tracked for the first time for the 2004 corn and soybean crops.

As the above discussion implies, a number of advisory programs are not tracked for all 10 crop years over 1995-2004. Figure 1 shows the distribution of track record lengths for all 41 programs included in the AgMAS study for corn and soybeans. The distribution is quite dispersed, with six programs tracked for only one crop year and fifteen tracked all ten crop years. Track record lengths for the remaining programs are fairly evenly dispersed between two and nine crop years. Overall, the average track record length is 6.3 crop years and the median length is 6 crop years.

Three forms of survivorship bias may be potential problems when assembling an advisory program database. Survival bias significantly biases measures of performance upwards since “survivors” typically have higher performance than “non-survivors” (e.g., Brown et al., 1992; Schneeweis, McCarthy and Spurgin, 1996; Brown, Goetzmann and Ibbotson, 1999). The first and most direct form of survivorship bias occurs if only advisory programs that remain in business at the end of a given sample period are included in the sample. This form of bias should not be present in the AgMAS database of advisory programs because all programs that have been tracked over the entire time period of the study are included in the sample. The second form of survivorship bias occurs if discontinued advisory programs are deleted from the sample for the year when they are discontinued. This is a form of survivorship bias because only survivors for the full crop year are tracked. The AgMAS database of advisory programs should not be subject to this form of bias because programs discontinued during a crop year remain in the sample for that crop year[10]. The third and most subtle form of survivorship bias occurs if data from prior periods are “back-filled” at the point in time when an advisory program is added to the database. This is a form of survivorship bias because data from surviving advisory programs are back-filled. The AgMAS database should not be subject to this form of bias because recommendations are not back-filled when an advisory program is added. Instead, recommendations are collected only for the crop year after a decision has been made to add an advisory program to the database.

Another important consideration when assembling a database on advisory program recommendations is hindsight bias (Jaffe and Mahoney, 1999). This is the tendency to collect or record profitable recommendations and ignore or minimize unprofitable recommendations after the fact. Since the AgMAS Project subscribes to all of the services that are followed and records recommendations on a real-time basis, the database of recommendations should not be subject to hindsight bias. The information is received electronically, via DTN, website or e-mail. For the programs that provide multiple daily updates, information is recorded for all updates. In this way, the actions of a farmer-subscriber are simulated in real-time.

When recording recommendations of each advisory program, specific attention is paid to which year’s crop is being sold (e.g., 2004 crop year), the amount of the commodity to be sold, which futures or options contract is to be used (where applicable) and any price targets that are mentioned (e.g., sell cash corn when March 2005 futures reaches $2.40). If a price target is given and not immediately filled, such as a stop order in the futures market, the recommendation is noted until the order is either filled or canceled. Recommendations for farm marketing programs are not screened for “speculative” versus “hedging” uses of futures and options. Consequently, all futures and options trades presented to farmers as a part of marketing recommendations are included.

As noted above, some advisory services offer two or more distinct marketing programs. This typically takes the form of one set of advice for marketers who are willing to use futures and options (although futures and options are not always used) and a separate set of advice for farmers who only wish to make cash sales[11]. In this situation, both strategies are recorded and treated as distinct strategies to be evaluated. Some programs also differentiate advice based on the availability of on-farm storage. In the past, when a service clearly differentiated strategies based on the availability of on-farm versus off-farm (commercial) storage, only the off-farm storage strategy was tracked. Starting with the 2000 corn and soybean crops, if a service clearly differentiates on-farm and off-farm storage strategies at or before harvest, both strategies are recorded. [12]

Several procedures are used to check the recorded recommendations for accuracy and completeness. Whenever possible, recorded recommendations are crosschecked against later status reports provided by the relevant advisory program. Also, at the completion of the crop year, it is confirmed whether cash sales total exactly 100%, all futures positions are offset and all options positions are offset or expire.

The track records developed by the AgMAS Project provide a wealth of information on the marketing approach, or “style,” of different advisory programs. While a complete analysis of marketing approach is beyond the scope of this report, a brief overview will provide valuable perspective when considering the performance evaluation results presented later in this report. A useful starting point is a simple count of the number of marketing transactions recommended by each program. Tables 2 and 3 present the number of transactions for each program and crop year in corn and soybeans[13]. The count includes all cash, forward, futures, options and marketing loan recommendations. Entry and exit transactions for futures and options positions are counted separately since many positions are entered and exited in an incremental manner. There is a wide variation in the number of recommended transactions within each crop year in both corn and soybeans. For example, the maximum number of transactions in 2004 for corn is 119 and the minimum is 7. The average number of recommended transactions across programs within a given crop year ranges from 17 to 30 in corn and 14 to 27 in soybeans. A total of over 10,000 transactions are recommended in corn and soybeans over 1995-2004.

Table 4 provides descriptive statistics on the number of recommended transactions by individual advisory program. These statistics provide the most direct evidence on the substantial differences in the number of recommended transactions by different advisory programs. In corn, the lowest average for programs active in at least two crop years is 7 transactions per crop year and the highest is 59. In soybeans, the lowest average for programs active in at least two crop years is 5 transactions per crop year and the highest is 49. The average across all programs is 20 transactions per crop year in corn and 19 transactions in soybeans, or a little less than one transaction per month over a two-year window (pre- and post-harvest) for each crop year. It is also interesting to observe the similarity in the average number of transactions across corn and soybeans for the same advisory program.

The transaction counts clearly point towards substantial differences in the marketing approach of different advisory programs. However, counts do not provide any information on the timing or magnitude of the recommended transactions. “Marketing profiles” are a useful device for aggregating the various positions a program recommends at each point in time and showing the time path of the net recommended position. Specifically, a marketing profile shows the net amount priced (sold) by an advisory program, on a cumulative basis, each day over a two-year marketing window beginning approximately one year before harvest and ending one year after harvest[14]. The profiles aggregate the futures, options and cash market positions for a program based on the well-known result that the price exposure of a portfolio of positions is a weighted-average of the price exposures of the individual positions, where the weights are the deltas of the individual positions. As a result, marketing profiles are comparable across programs and crop years[15][16]. Note that all marketing profiles (in concept) start at zero on the first day of the marketing window and end at 100% on the last day of the marketing window.

Two marketing profile examples in corn for the 2000 crop year are presented in Figure 2. These profiles nicely illustrate the large range in marketing approaches found across advisory programs. Panel A shows a conservative program that engages in minimal pre-harvest pricing and makes a small number of pricing transactions post-harvest. Panel B shows an aggressive program, where strategies range from full to no hedging of expected production during the pre-harvest period, some periods where the net position is long during post-harvest (negative net amount priced) and very late sales of much of the cash commodity. This latter example illustrates the large time-series variation in the net amount priced (hedge ratio) often found for advisory programs; a variation much larger than what optimal hedging models typically generate (e.g., Martines-Filho, 1996). This also illustrates the frequency with which advisory programs engage in “selective hedging” strategies (Working, 1962), where hedges are placed and lifted based on price expectations. It is interesting to note that a similar type of behavior has been observed in the risk management programs of financial and non-financial corporations, where it is labeled “hedging with a view” (e.g., Stulz).

While there is a great deal of variability in marketing profiles across programs for a given crop year, there also are definite seasonal tendencies in the average profile for all programs. Figure 3 presents the average marketing profile of all advisory programs tracked in corn and soybeans over the 1995-2004 crop years. On average, the net amount of the corn and soybean crops priced before planting (May 1st) is relatively modest, about 30% in corn and 20% in soybeans. Pricing increases slowly through harvest and then tends to pick up rapidly shortly after harvest. By January 1st after harvest, the average amount priced increases to about 60% in corn and soybeans. Sales rise to an average of about 85% in corn and soybeans by the time the next crop is planted in May following harvest.

Marketing Assumptions

At the end of the marketing period, all of the (filled) recommendations are aligned in chronological order. The advice for a given crop year is considered to be complete for each advisory program when cumulative cash sales of the commodity reach 100%, all futures positions covering the crop are offset, all option positions covering the crop are either offset or expire and the advisory program discontinues giving advice for that crop year. In order to produce a consistent and comparable set of results across the different advisory programs, certain explicit marketing assumptions are made. The assumptions are intended to accurately depict “real-world” marketing conditions facing a representative central Illinois corn and soybean farmer. Based on these assumptions, the returns to each recommendation are then calculated in order to arrive at a weighted average net price that would be received by a farmer who precisely follows the marketing advice (as recorded by the AgMAS Project).

The discussion about marketing assumptions in the following sections centers on the 2004 crop year. It is important to note that some assumptions have changed over time. Specific information on assumptions for the 1995-2003 crop years can be found in earlier AgMAS pricing reports (e.g., Irwin et al., 2005). Assumed values for key variables used in the simulation of advisory service performance over the 1995-2004 crop years can be found in Appendix A.

Geographic Location

The simulation is designed to reflect conditions facing a representative central Illinois corn and soybean farmer. Whenever possible, data are collected for the Central Crop Reporting District in Illinois as defined by the National Agricultural Statistics Service (NASS) of the U.S. Department of Agriculture (USDA). The eleven counties (DeWitt, Logan, McLean, Macon, Marshall, Mason, Menard, Peoria, Stark, Tazewell and Woodford) that make up this District are highlighted in Figure 4.

Caution should be used when applying the results to other areas of the US, because yields and basis patterns may be quite different from those of central Illinois. Differences in yields and basis patterns could have a substantial impact on prices computed for farmers or advisory services in another area. The resulting change could be either up or down relative to AgMAS advisory prices and benchmarks, depending on local conditions. Appendix B to this report, entitled “A Cautionary Note on the Use of AgMAS Net Advisory Prices and Benchmarks,” contains further discussion on this point.

Marketing Window

The time period over which a farmer normally makes pricing decisions for a particular crop is termed the “marketing window.” It also can be referred to as the pricing “decision-horizon” or “timeline” of a farmer. A marketing window does not necessarily equal the time period of observed market activity. The reason is that not taking action (e.g., not hedging pre-harvest) is one type of decision that can be made during a marketing window.

In the present context, the objective is to define the normal marketing window of a representative farmer who subscribes to the advisory programs tracked by the AgMAS Project. Good, Hieronymus and Hinton (1980) provide a useful starting point. They define the marketing window for an Illinois grain farmer as the period extending from the initial production planning time until the end of the storage season. First production decisions in Illinois normally occur in October through November of the year preceding planting (e.g., fall tillage and application of fertilizer), while the storage season typically extends through July or August of the year following harvest. This results in a marketing window between 21 and 23 months in length. Chafin and Hoepner (2002) reach a similar conclusion in their text on commodity marketing:

In building an integrated marketing plan, crop producers must keep in mind the fact that pricing decisions on a single crop span a two-year period: the growing year and the storage year. The first stage of a crop “marketing year” begins in November as production plans are being made for the new crop and continues throughout the growing season until the end of harvest. During the second stage of the “marketing year,” pricing of the harvested (old) crop begins at the end of the 12-month “growing” year and continues for the next 12-month storage year. Thus, the pricing of a single crop spans 730 days-the “growing year” plus the “storage year.” (p. 326)

The actual pricing pattern of advisory programs included in the AgMAS study provides further information for defining the relevant marketing window. As noted above, observed market positions cannot directly reveal the intended pricing window of a representative farmer following advisory program recommendations. However, averages over time and advisors should be suggestive as to the typical starting and ending points used to make recommendations for a crop. The average marketing profiles presented earlier in Figure 3 suggest that a farmer following the recommendations of market advisory programs included in the AgMAS study, on average, will begin making significant marketing decisions (pricing more than one percent) in September of the year before harvest and will not complete marketing until August of the year after harvest[17].

Overall, this discussion indicates it is reasonable to assume a 24-month marketing window for a representative farmer subscribing to advisory programs. In the case of the 2004 crop, the marketing window is defined as the two-year period beginning September 2, 2003 and ending on August 31, 2005. Two further issues need to be discussed with respect to the 2004 market window. The first issue is exceptions to the specific definition. For example, six programs in corn and two programs in soybeans started hedging recommendations before September 2, 2003. The earliest case occurred in corn where the first recommendation was issued on April 2, 2003. In addition, two advisory programs in corn and two in soybeans either had a relatively small amount (10%) of cash bushels unsold as of August 31, 2003 and/or futures or options positions open in the range of 20 to 50% of production. The last of these positions was closed out on December 27, 2005. Because the marketing window is defined as the “normal” window, it is argued that a representative farmer would approach the marketing window with some flexibility, particularly for recommendations that do not extend too far outside the limits of the marketing window. While a few of the 2004 recommendations extend beyond the limits of the marketing window, most do not. All of the transactions in question are nonetheless included in the relevant advisory program’s track record in the interest of completeness and accuracy[18]. The second issue is the definition of business days within the marketing window. This issue arises because different entities in the agricultural sector have different policies with respect to holidays. For the purposes of this study, an “official” business day within the marketing window is defined as a business day where the Chicago Board of Trade is open and cash prices are reported by the Illinois Department of Ag Market News. Finally, note that throughout the remainder of this report the term “crop year” is used to represent the two-year marketing window.

Price

The price assigned to each cash sale recommendation is the central Illinois closing, or overnight, bid. The data are collected and reported by the Illinois Department of Ag Market News[19]. The central Illinois price is the mid-point of the range of bids by elevators in the North Central and South Central Price Reporting Districts, as defined by the Illinois Department of Ag Market News. The North and South Central Illinois Price Reporting Districts are highlighted in Figure 5. Prices in this 35-county area best reflect prices for the assumed geographic location of the representative central Illinois farmer (Central Illinois Crop Reporting District).

Pre-harvest cash forward contract prices for fall delivery are also needed. Pre-harvest bids collected by the Illinois Department of Ag Market News are used when available. The central Illinois pre-harvest price is the mid-point of the daily range of pre-harvest bids by elevators in the North Central and South Central Price Reporting Districts, again, as defined by the Illinois Department of Ag Market News. Pre-harvest forward prices are available from this source for the 2004 corn and soybean crops during the February 9, 2004 through August 31, 2004 period.

The marketing window for the 2004 corn and soybean crops begins in September 2003. Since the Illinois Department of Ag Market News did not begin to report actual cash forward bids until February 9, 2004 for 2004 crops, pre-harvest prices need to be estimated for the first five months of the marketing window. For dates between September 2, 2003 and February 6, 2004, a three-step estimation procedure is adopted. First, the average forward basis for the first five days the Illinois Department of Ag Market News reports actual forward contract bids is computed (February 9-13, 2004 for 2004 crops)[20] . Second, the forward basis is widened in a linear fashion moving back in time from February 2004 to September 2003. This is based on the findings in several studies that the forward basis for corn, soybeans and wheat widens systematically the more distant the time before harvest (Harris and Miller, 1981; Elam and Woodworth, 1989; Brorsen, Coombs and Anderson, 1995; Townsend and Brorsen, 2000; Shi et al., 2004). The widening “factor” for 2004 crops is estimated based on the average change in weekly forward basis bids for central Illinois over the 1973-2004 pre-harvest periods (0.054¢ per bushel per week for corn and 0.094¢ per bushel per week for soybeans)[21]. The weekly change is converted to a daily change by dividing the estimated averages by five (0.011¢ per bushel per day for corn and 0.019¢ per bushel per day for soybeans). The resulting adjustment to the estimated forward basis (and estimated forward contract bids) is rather modest. For example, the widening adjustment on the first day of the marketing window (September 2, 2003 for the 2004 crops) is about one cent per bushel for corn and two cents per bushel for soybeans[22]. Third, the estimated forward basis computed in the previous two steps is added to the settlement price of the Chicago Board of Trade (CBOT) new crop futures prices for the 2004 crop year (2004 December corn futures contract or 2004 November soybean futures contract) between September 2, 2003 and February 6, 2004.

The estimation procedure outlined above is expected to be a reasonably accurate reflection of actual forward prices for the early period of the marketing window, as the actual price of the harvest futures contract is used and only the forward basis is estimated. In addition, the estimation procedure typically is applied to a relatively small number of transactions. For example, the average net amount sold by advisory programs before February 1st over 1995-2004 is only 14% for corn and 8% for soybeans, and many of these transactions are in futures or options contracts rather than forward contracts.

Some market advisory programs recommended the use of post-harvest forward contracts to sell part of the 2004 corn and soybean crops. The Illinois Department of Ag Market News reported post-harvest bids for January and March 2005 deliveries. These central Illinois bids are used wherever applicable. However, 16 positions recommended by advisory programs for the 2004 corn and soybean crops either did not match the January or March delivery period or were made before the Illinois Department of Ag Market News began reporting post-harvest forward contract prices. The following procedure was adopted to estimate the additional post-harvest forward contract prices needed in these cases. First, three elevators in central Illinois who agreed to supply data on spot and forward contract prices on the dates when advisors made such recommendations were contacted. Each of these elevators is in a different county in the Central Illinois Crop Reporting District (Logan, McClean, DeWitt). Second, the spread between each elevator’s forward price and spot price is calculated for the relevant date. Third, the forward spread is averaged across the three elevators for the same date. Fourth, the average forward spread from the three elevators is added to the central Illinois cash price (discussed at the beginning of the section) to arrive at an estimated post-harvest forward contract price for central Illinois. This same procedure was used in a few cases for the 1998, 1999, 2002 and 2003 crop years.

Advisory program recommendations to enter and exit futures and options positions may take a variety of forms, including market orders, limit-price orders, sell-stop orders and buy-stop orders[23]. For example, one program made the following recommendation on April 1, 2004: “Sell November soybean futures at the market to hedge 50% of expected 2004 production.” As another example, a different program made the following recommendation on May 10, 2005: “Repurchase 50% of the 2004 corn crop by buying July corn futures at $2.08.” The first is an example of a market order while the second is an example of a limit-price order. In most cases, advisory programs report “fill” prices for executed transactions. All reported fill prices are cross-checked against the price range of the relevant futures or options contract on the same date. If the fill price for any type of order is within the daily range, it is entered as the executed price for the recommended transaction. If the fill price for a market order is outside the daily range, the settlement price for same day is recorded as the executed price. If the fill price for a limit-price, sell-stop or buy-stop order is outside the daily range, then the recommended transaction is not included in the track record. In addition, price targets for limit-price (as in the second example above), sell-stop and buy-stop orders are cross-checked against the daily price range of the relevant futures or options contract on the reported fill date. If the price target and associated fill price (generally the same) are within the daily price range, then the reported fill price is used. If the price target is not in the daily range, then the recommended transaction is not included in the track record. Finally, in cases where a program does not report a specific fill price, the settlement price for the same day is used.

“Catch-up” transactions may be necessary when a recommended position is not included in an advisory program’s track record due to the cross-check described in the previous paragraph. For limit-price, sell-stop and buy-stop orders, the price target is checked on subsequent days and the position is assumed to be executed at the target if it is hit. If the target is never hit, then the next recommended position is adjusted upwards or downwards to reflect the excluded bushels[24]. If the purpose of an excluded transaction is to close a position and no further related positions are recommended, the settlement price at contract expiration is used to exit the original position.

Quantity Sold

Since most of the advisory program recommendations are given in terms of the proportion of total production (e.g., “sell 5% of 2004 crop today”), some assumption must be made about the amount of production to be marketed. For the purposes of this study, if the per-acre yield is assumed to be 100 bushels, then a recommendation to sell 5% of the corn crop translates into selling 5 bushels. When all of the advice for the marketing period has been carried out, the final per-bushel selling price is the average price for each transaction weighted by the amount marketed in each transaction.

The above procedure implicitly assumes that the “lumpiness” of futures and/or options contracts is not an issue. Lumpiness is caused by the fact that futures contracts are for specific amounts, such as 5,000 bushels per CBOT corn futures contract. For large-scale farmers, it is unlikely that this assumption adversely affects the accuracy of the results. This may not be the case for small- to intermediate-scale farmers who are less able to sell in 5,000-bushel increments[25].

Yields and Harvest Definition

When making hedging or forward contracting decisions prior to harvest, the actual yield is unknown. Hence, an assumption regarding the amount of expected production per acre is necessary to accurately reflect the returns to marketing advice. Prior to harvest, the best estimate of current year expected yield is likely to be a function of yield in previous years. In this study, the assumed yield prior to harvest is the calculated trend yield, while the actual reported yield is used from the harvest period forward. The expected yield for 2004 is based upon a log-linear regression trend model of actual yields from 1972 through 2003 for the Central Illinois Crop Reporting District. Previous research suggests this type of trend model provides a reasonable fit to corn and soybean yield data (Swanson and Nyankori, 1979; Fackler, Young and Carlson, 1993; Sherrick et al., 2004).

In central Illinois, the expected yield for corn is calculated to be 161.3 bushels per acre in 2004. Therefore, recommendations regarding the marketing quantity made prior to harvest for the 2004 crop year are based on yields of 161.3. For example, a recommendation to forward contract 20% of expected 2004 production translates into a recommendation to contract 32.3 bushels per acre (20% of 161.3). The actual reported corn yield in central Illinois is 186 bushels per acre in 2004. The same approach is used for soybean evaluations. The calculated 2004 trend yield for soybeans in central Illinois is 49 bushels per acre and the actual yield is 54 bushels per acre.

It is assumed that after harvest begins, farmers can make reasonably accurate projections of realized yields. Therefore, recommendations made after the start of harvest are assumed to be based on actual yields instead of expected yields. Since harvest does not occur during the same exact period each year, data on harvest progress are needed to establish the relevant harvest window, and in particular, the date that harvest begins. Harvest progress data are reported by NASS for the central Illinois Crop Reporting District; however, the reports typically are not made available soon enough to identify precisely the beginning of harvest. Consequently, the exact “location” of the harvest window cannot be identified based upon available data. The following alternative procedure is used to estimate the harvest window each year. First, the business day nearest to 50% completion of harvest is defined as the mid-point of harvest. Second, the entire harvest period is defined as a five-week window, beginning twelve business days before the mid-point of harvest, and ending twelve business days after the mid-point of harvest (a total of 25 business days, or five weeks). In most years, the five-week window includes at least 80% of the harvest.

Since NASS harvest progress reports are made weekly, the exact date of the harvest mid-point is not known. However, it is possible to estimate the date of the mid-point using the weekly progress numbers of the two reports that encompass 50% harvest progress. As an example, the NASS estimate of corn harvest progress in central Illinois is 38% on September 26, 2004. Harvest progress is estimated to be 62% in the next report on October 3, 2004. A daily progress estimate for this week can be constructed by taking the difference of these estimates and dividing the result by seven; in this example, harvest progressed at rate of approximately 3.43% per day. Counting forward from 38% at a rate of 3.43% per day, the business day closest to 50% progress is September 30, 2001. This mid-point is used to construct the harvest window for corn by counting backwards and forwards twelve business days. The same procedure is used to determine the harvest window for soybeans.

The harvest period for corn in 2004 is defined as September 14, 2004 through October 18, 2004. For soybeans, the harvest period is September 15, 2004 through October 19, 2004. Therefore, recommendations for corn made after September 14, 2004 are applied on the basis of the actual yield of 186 bushels per acre. For soybeans, recommendations made after September 15, 2004 are applied on the basis of the actual yield of 54 bushels per acre.

The issue of changing yield expectations typically is not dealt with in the recommendations of the advisory programs. For the purpose of this study, the actual harvest yield must exactly equal total cash sales of the crop at the end of the marketing time frame. Hence, an adjustment in yield assumptions from expected to actual levels must be applied to cash transactions at some point in time. In this analysis, an adjustment is made in the amount of the first cash sale made after the beginning of the harvest period. For example during the 2004 crop year, if a program advises forward contracting 50% of the corn crop prior to harvest, this translates into sales of 80.65 bushels per acre (50% of 161.3). However, when the actual yield is applied to the analysis, sales-to-date of 80.65 bushels per acre imply that only 43.36% of the actual crop has been contracted (80.65/186*100). In order to compensate, the amount of the next cash sale is adjusted to align the amount sold. In this example, if the next cash sale recommendation is for a 10% increment of the 2004 crop, making the total recommended sales 60% of the crop, the recommendation is adjusted to 16.64% of the actual yield (30.95 bushels), so that the total crop sold to date is 60% of 186 bushels per acre (80.65 + 30.95 = 111.6 = 0.6*186). After this initial adjustment, subsequent recommendations are taken as percentages of the 186 bushels per acre actual yield, so that sales of 100% of the crop equal sales of 186 bushels per acre.

While the amount of cash sales is adjusted to reflect the change in yield information, a similar adjustment is not made for futures or options positions that are already in place. For example, assume that a short futures hedge is placed in the December 2004 corn futures contract for 25% of the 2004 crop prior to harvest. Since the amount hedged is based on the trend yield assumption of 161.3 bushels per acre, the futures position is 40.32 bushels per acre (25% of 161.3). After the yield assumption is changed, this amount represents a short hedge of 21.68% (40.32/186). The amount of the futures position is not adjusted to move the position to 25% of the new yield figure. However, any futures (or options) positions recommended after the beginning of harvest are implemented as a percentage of the actual yield.

If actual yield is substantially below trend, and forward pricing obligations are based on trend yields, a farmer may have difficulty meeting such obligations. This raises the issue of updating yield expectations in “short” crop years to minimize the chance of defaulting on forward pricing obligations. This situation was not encountered in the AgMAS evaluations of corn and soybeans over the 1995-2004 crop years but did arise in earlier evaluations for wheat. Please see the AgMAS research report by Jirik et al. (2000) for a detailed discussion of the issue and associated adjustment procedures.

Hedging Costs

Several costs are associated with hedging positions in futures and options markets. Brokerage commissions are the first type of hedging cost incurred when farmers open or close positions on an exchange. For the purposes of this study, it is assumed that brokerage costs are $50 per contract for round-turn futures transactions and $30 per contract to enter or exit an options position. Further, it is assumed that CBOT corn and soybean futures and options contracts are used, which have a contract size of 5,000 bushels. Therefore, per-bushel brokerage costs are 1.0¢ per bushel for a round-turn futures transaction and 0.6¢ per bushel for each options transaction.

Liquidity costs are the second type of hedging cost incurred when farmers open or close positions on an exchange. These costs reflects the fact that non-floor traders generally must buy at the ask price and sell at the bid price (e.g., Working, 1967; Roll, 1984). The difference between the bid and ask prices, termed the bid-ask spread, is the return earned by floor traders for “making the market.” In other words, the bid-ask spread represents the cost paid to execute a trade quickly at prevailing market prices. Liquidity costs are not explicitly accounted for in this study because fill prices for futures and options transactions are reported by advisory programs for most transactions. Fill prices presumably already reflect liquidity costs. In cases where a program did not report a specific fill price, the settlement price for that day is used. Liquidity costs are not incorporated for settlement transactions, but this should not represent a significant omission since such transactions are a relatively small component of all futures and options transactions. In addition, liquidity costs should be minimized during the settlement period of the daily trading session due to the relatively high trading volume that typically occurs at that time (e.g., Thompson, Eales and Seibold, 1993).

Mark-to-market costs are a third type of hedging cost that may be incurred by farmers in the course of holding futures and options positions on an exchange. These costs can be incurred as a result of the margining system used for futures and some options positions. Specifically, when a farmer opens a futures position a “good faith” margin deposit is required, typically around 5% of contract value. The initial margin can be deposited in the form of available cash, borrowed funds or an interest bearing instrument such as U.S. treasury bills. So, depending on the form of the deposit, the farmer may experience interest opportunity costs, actual interest costs or interest earnings on the initial margin. If the futures position subsequently accrues losses beyond a certain point (e.g., the futures price increases while holding a short position) a further margin deposit is required. In this way, it is possible for interest borrowing costs to accumulate as losses are experienced. If the futures position subsequently accrues gains, no further margin deposit is required but interest may be earned on the accrued profits. The process of marking-to-the market for futures positions occurs daily and is based on settlement futures prices. The question in the present context is the magnitude of mark-to-the market costs for futures positions in agricultural markets. Previous studies suggest that mark-to-market costs are quite small for hedging positions in agricultural futures markets (Nelson, 1985; Alexander, Musser and Mason, 1986; Matthews and Holthausen, 1991). This is a sensible result in reasonably efficient markets, as hedging profits, which generate interest earnings, should over time approximately offset hedging losses, which generate interest charges. Mark-to-market costs are therefore not incorporated in the simulation of advisory program performance for this study.

It is important to emphasize that the above discussion is not meant to imply that cash flow risk is not an important component of the risk of following advisory program recommendations. While interest costs and earnings for a margin account more than likely cancel each other out over time, hedge positions can still generate large negative cash flows during particular time periods. Zulauf et al. (2001) examine routine pre-harvest marketing strategies for representative Ohio corn and soybean producers over 1986-1999 and find that cash outflow during short crop years can be substantial. For example, cash outflow for a standard short hedging strategy (50% of expected production at planting) during the drought of 1988 exceeds $100 per acre. This highlights the potential for large cash outflows that may result from following advisory program recommendations.

LDP and Marketing Assistance Loan Payments

While the 1996 “Freedom-to-Farm” Act did away with government set-aside and target price programs, price protection for farmers in program crops such as corn and soybeans was not eliminated entirely. Minimum prices are established through a “loan” program. Specifically, if market prices are below the Commodity Credit Corporation (CCC) loan rate for corn or soybeans, farmers can receive payments from the U.S. government that make up the difference between the loan rate and the lower market price[26]. There is considerable flexibility in the way the loan program can be implemented by farmers. This flexibility presents the opportunity for advisory programs to make specific recommendations for the implementation of the loan program. Additionally, the price of both corn and soybeans was below the loan rate during significant periods of time in the 1998/99-2001/02 and 2004/05 marketing years, so that use of the loan program was an important part of marketing strategies. As a result, net advisory program prices may be substantially impacted by the way the provisions of the loan program are implemented. Finally, all of the advisory programs tracked by the AgMAS project for the 2004 crop year make specific recommendations regarding the timing and method of implementing the loan program for the entire corn and soybean crops.

Before describing the decision rules, it is useful to provide a brief overview of the loan program mechanics. Then, the rules developed to implement the loan program in the absence of specific recommendations can be described more effectively.

Program Mechanics

There are two mechanisms for implementing the price protection benefits of the loan program. The first mechanism is the loan deficiency payment (LDP) program. LDPs are computed as the difference between the loan rate for a given county and the posted county price (PCP) for a particular day. PCPs are computed by the USDA and change each day in order to reflect the average market price that exists in the county. For example, if the county loan rate for corn is $2.00 per bushel and the PCP for a given day is $1.50 per bushel, then the LDP is $0.50 per bushel. If the PCP increases to $1.60 per bushel, the LDP will decrease to $0.40 per bushel. Conversely, if the PCP decreases to $1.40 per bushel, the LDP will increase to $0.60 per bushel[27].

LDPs are made available to farmers over the period beginning with corn or soybean harvest and ending May 31st of the calendar year following harvest. Farmers have flexibility with regard to taking the LDP, because they may simply elect to take the payment when the crop is sold in a spot market transaction (before the end of May in the particular marketing year), or choose to take the LDP before the crop is delivered and sold. Note that LDPs cannot be taken after a crop has been delivered and title has changed hands.

The second mechanism is the non-recourse marketing assistance loan program. A loan cannot be taken on any portion of the crop for which an LDP has been received. Under this program, farmers may store the crop (on the farm or commercially), maintain beneficial interest, and receive a loan from the CCC using the stored crop as collateral. The loan rate is the established rate in the county where the crop is stored and the interest rate is established at the time of loan entry. Corn and soybean crops can be placed under loan anytime after the crop is stored through May 31st of the following calendar year. The loan matures on the last day of the ninth month following the month in which the loan was made.

Farmers may settle outstanding loans in two ways: i) repaying the loan during the 9-month loan period, or ii) forfeiting the crop to the CCC at maturity of the loan. Under the first alternative, the loan repayment rate is the lower of the county loan rate plus accrued interest or the marketing loan repayment rate, which is the PCP. If the PCP is below the county loan rate, the economic incentive is to repay the loan at the posted county price. The difference between the loan rate and the repayment rate is a marketing loan gain (MLG). If the PCP is higher than the loan rate, but lower than the loan rate plus accrued interest, the incentive is also to repay the loan at the PCP. In this case only, interest is charged on the difference between the PCP and the loan rate. If the PCP is higher than the loan rate plus accrued interest, the incentive is to repay the loan at the loan rate plus interest. In this latter case, interest is based on the loan rate. Under the second alternative, the farmer stores the crop to loan maturity and then transfers title to the CCC. The farmer retains the proceeds from the initial loan.

The non-recourse loan program establishes the county loan rate as a minimum price for the farmer, as does the LDP program. For the 2004 crop, the sum of LDPs plus marketing loan gains was subject to a payment limitation of $150,000 per person. Forfeiture on the loans or use of commodity certificates provide a mechanism for receiving a minimum of the loan rate on bushels in excess of the payment limitation.

The average loan rates for the 2004 corn and soybean crops across the 11 counties in the Central Illinois Crop Reporting District are $2.01 and $5.14 per bushel, respectively. Spot cash prices for corn fall below the loan rate during most of the 2004 post-harvest period. Spot cash prices for soybeans fall below the loan rate only during the early post-harvest period. This is reflected in Figure 6, which shows corn and soybean LDP or MLG rates for central Illinois during the 2004 post-harvest period[28][29].

Decision Rules for Programs with a Complete Set of Loan Recommendations

If an advisory program makes a complete set of loan recommendations, the specific advice is implemented wherever feasible. However, specific decision rules are still needed regarding pre-harvest forward contracts because it is possible for an advisory program to recommend taking the LDP on those sales before it is actually harvested and available for delivery in central Illinois. To begin, it is assumed that amounts sold for harvest delivery with pre-harvest forward contracts are delivered first during harvest. Since LDPs must be taken when title to the grain changes hands, LDPs are assigned as these “forward contract” quantities are harvested and delivered. This necessitates assumptions regarding the timing and speed of harvest. Earlier it was noted that a five-week harvest window is used to define harvest. This window is centered on the day nearest to the mid-point of harvest progress as reported by NASS. Various assumptions could be implemented regarding harvest progress during this window. Lacking more precise data, a reasonable assumption is that harvest progress for an individual representative farm is a linear function of time.

Tables 5 and 6 summarize the information used to assign LDPs to pre-harvest forward contracts. The second column shows the amount harvested assuming a linear model. The third column shows the LDP available on each date of the harvest window and the fourth column presents the average LDP through each harvest date. An example will help illustrate use of the tables. Assume that an advisory program recommends, at some point before harvest, that a farmer forward contract 50% of expected corn production. This translates into 80.7 bushels per acre when the percentage is applied to expected production (0.50*161.3 = 80.7). Next, convert the bushels per acre to a percentage of actual production, which is 43.3% (80.7/186 = 0.434). To determine the LDP payment on the 43.3% of actual production forward contracted, simply read down Table 5 to September 28, 2004, which is the date when 43.3% of harvest is assumed to be complete. The average LDP up to that date (September 14, 2004- September 28, 2004) is $0.20 per bushel; the last column of Table 5. This is the LDP amount assigned to the forward contract bushels.

Note that LDPs for any sales (spot, forward contracts, futures or options) recommended during harvest are taken only after all forward contract obligations are fulfilled. Grain industry practices may actually offer more flexibility in establishing LDPs than is assumed here. In addition, so long as prices remain below the loan rate, crops placed under loan by an advisory program do not accumulate interest opportunity costs because proceeds from the loan can be used to offset interest costs that otherwise would accumulate.

Decision Rules for Programs with a Partial Set of Loan Recommendations
Or No Loan Recommendations

If an advisory program makes a partial set of loan recommendations, the available advice is implemented wherever feasible. In the absence of specific recommendations, it is assumed that crops priced before May 31st but after harvest are not placed under loan. Those crops receive program benefits, if any, through LDPs. After May 31st, eligible crops (unpriced crops for which any program benefits have not yet been collected) are assumed to be under loan until priced only if cash prices prevailing on May 31st are near or below the loan rate.

In the absence of specific recommendations, rules for assigning LDPs and MLGs are developed under the assumption that loan benefits are established when the crop is priced or as soon after pricing that is allowed under the rules of the program. This principle is consistent with the intent of the loan program to fix a minimum price when pricing decisions are made. Two rules are most important in the implementation of this principle. First, LDPs on pre-harvest sales (forward contracts, futures or options) are established as the crop is harvested. Second, if the LDP or MLG is zero on the pricing date, or the first date of eligibility to receive a loan benefit, those values are assigned on the first date when a positive value is observed, assuming a beneficial interest in that portion of the crop has been maintained. Specific rules for particular marketing tools and situations follow:

1. Pre-harvest forward contracts. The same decision rules are applied as discussed in the previous section. Specifically, it is assumed that amounts sold for harvest delivery with pre-harvest forward contracts are delivered first during harvest, although not all buyers require that forward contract bushels be delivered first. LDPs, if positive, are assigned as these “forward contract” quantities are harvested and delivered. This necessitates assumptions regarding the timing and speed of harvest. A linear model of harvest progress is assumed in the five-week harvest window. The specific information used to assign LDPs to pre-harvest forward contracts is again found in Tables 5 and 6. As a final point, note that LDPs for any other sales (spot, futures or options) recommended during harvest are taken only after all pre-harvest forward pricing obligations are fulfilled.

2. Pre-harvest short futures. The use of futures contracts to price during the pre-harvest seasons is treated in the same manner as pre-harvest forward contracts. LDPs are assigned on open futures positions as the crop is harvested, or as soon as a positive LDP is available, if the futures position is still in place and cash sales have not yet been made. These are assigned after forward contracts have been satisfied. If the underlying crop is sold before there is a positive LDP, then that portion of the crop receives a zero LDP. During the harvest window, if the futures position is offset before a positive LDP is available and the crop has not yet been sold in the cash market, that portion of the crop is eligible for loan benefits on the next pricing recommendation.

3. Pre-harvest put option purchases. Long put option positions, which establish a minimum futures price, are treated in the same manner as pre-harvest short futures .

4. Post-harvest forward contracts. The main issue with respect to post-harvest forward contracts is when to assign the LDPs or MLGs. Those can be established on the date the contract is initiated, on the delivery date of the contract, or anytime in between. Following the general principle outlined earlier, LDPs and MLGs for post-harvest contracts are assigned on the date the contract is initiated or the first day with positive benefits prior to delivery on the contract.

5. Post-harvest short futures. As with post-harvest forward contracts, the main issue with post-harvest short futures positions is when to assign loan benefits. These are assigned when the short futures position is initiated or as soon as a positive benefit is available if the futures position is still in place and cash sales have not been made. If the underlying crop is sold before a positive LDP is available, that portion of the crop receives a zero LDP. If the short futures position is offset before a positive LDP is available and the cash crop has not yet been sold, that portion of the crop is eligible for loan benefits on the next pricing recommendation.

6. Post-harvest long put positions. Long put option positions established after the crop is harvested are treated in the same manner as post-harvest short futures.

7. Spot sales before May 31^st. If a spot cash sale of corn or soybeans is recommended before May 31^st but after harvest, it is assumed that the LDP, if positive, is established that same day

8. Loan program after May 31^st. Since LDPs are not available after May 31, 2005, it is assumed that any corn in storage and not priced as of this date, for which loan benefits have not been established, are entered in the loan program on that date. This is a reasonable assumption since spot corn prices are near the loan rate in central Illinois on May 31, 2005 and a prudent farmer would take advantage of the price protection offered by the loan program[30]. When the corn bushels are subsequently priced (cash sale, forward contract, short futures, or long put option), the marketing loan gain, if positive, is assigned on that day. Forfeiture is not an issue for these bushels because all cash sales were made before the end of the nine-month loan period. Note also that the $150,000 payment limitation is not considered in the analysis, as production is based on one acre of corn. The same procedures are not used for the 2004 soybean crop since the spot price for soybeans is well above the loan rate in central Illinois on May 31, 2005. A prudent farmer would not necessarily enter the loan program under these circumstances, and hence, when soybeans are subsequently priced (cash sale, forward contract, short futures, or long put option), no marketing loan gain is assigned on that day.

Storage Costs

An important element in assessing returns to an advisory program is the economic cost associated with storing grain instead of selling grain immediately at harvest. The cost of storing grain after harvest consists of two components: physical storage costs and the opportunity cost incurred by foregoing sales when the crop is harvested. Physical storage costs depend on the type of storage available and the horizon used by a farmer to make storage decisions. From a representative farmer’s perspective, there are four relevant physical storage scenarios: i) on-farm storage using a short-run decision-horizon, ii) off-farm (commercial) storage using a short-run decision-horizon, iii) on-farm storage using a long-run decision-horizon and iv) off-farm (commercial) storage using a long-run decision-horizon. Short-run in this context is defined to be one storage season, usually the ten-month period after the harvest of a particular crop. Long-run is defined to be any decision-horizon longer than one storage season. In each of the previous scenarios, the physical storage charge should be the relevant marginal cost of physical storage (Williams and Wright, 1991). In contrast, interest opportunity cost should be the same regardless of the type of physical storage used or whether a short- or long-run decision-horizon is considered.

Early AgMAS pricing reports consider only one scenario: commercial storage using a short-run decision-horizon. Starting with the 2000 crop year, net advisory prices and benchmarks are computed using physical storage costs applicable to each of the four storage scenarios. In all cases for 2004, storage and interest charges are assigned beginning October 19, 2004 for corn and October 20, 2004 for soybeans, the first dates after the end of the respective 2004 harvest windows. It should be noted that the cost of drying corn to 15% moisture and the cost of drying soybeans to storable moisture are not included in the calculations. This cost is incurred whether the grain is stored or sold at harvest, or whether the grain is stored on-farm or off-farm. Therefore, this cost is irrelevant to the analysis and excluded.

The first scenario considered is on-farm storage and a short-run decision-horizon. Because pre-existing storage facilities are assumed to be available on-farm, the marginal cost of physical storage equals the on-farm variable cost of physical storage. Estimates of the on-farm variable cost of physical storage are drawn from a recent study conducted at Kansas State University (Dhuyvetter, Hamman and Harner, 2000). The estimates assume storage occurs in a 25,000 bushel round metal bin, the “medium-sized” storage capacity examined in the Kansas State study. The first component of on-farm physical storage is a flat charge of 6.7¢ per bushel for conveyance, aeration, insecticide and repairs. The flat charge is applied to both corn and soybeans and reflects the fact that most physical costs of on-farm storage are “one-time” in nature. That is, once the decision is made to store, most costs are pre-determined and do not vary with the length of storage.

The second component of on-farm physical storage is shrinkage. Corn shrinkage is assumed in the Kansas State study to start at one-percent per bushel for the first month of storage and increase at a rate of one-tenth of one percent for each month stored thereafter. For example, if corn is stored six months, the total shrinkage is assumed to be 1.5% per bushel. Agricultural engineering specialists at the University of Illinois and Purdue University indicated that the on-farm shrink schedule for corn used in the Kansas State study is reasonable. In addition, the schedule is consistent with published research about shrinkage of corn stored on-farm (Hurburgh et al., 1983). Given that the harvest-time cash price of corn in central Illinois for 2004 is $1.82 per bushel, the shrink charge assigned to corn stored on-farm for one-month in 2004 is 1.82¢ per bushel ($1.82*0.01*100). The shrink charge in 2004 is increased 0.182¢ per bushel ($1.82*0.001*100) for each additional month of storage[31].

Since the Kansas State study did not estimate shrinkage costs for soybeans, the same agricultural engineering specialists noted above were consulted for a reasonable estimate. This turned out to be a constant 0.25% per bushel shrink factor. Given that the harvest-time cash price of soybeans in central Illinois for 2004 is $5.02 per bushel, the flat shrink charge assigned to soybeans in 2004 is 1.26¢ per bushel ($5.02*0.0025*100)[32].

As noted earlier, storage costs include the physical cost of storage and interest opportunity costs. The convention in farm marketing studies is to compute interest costs using a measure of borrowing rates for farm operating loans (e.g., Hieronymus, 1966; Good, Hieronymus and Hinton, 1980; Chafin and Hoepner, 2002). While usually unstated in farm marketing studies, it is implicitly assumed that farmers either forgo the opportunity to pay down existing operating loans or borrow new operating funds if grain is not sold at harvest. Based on this argument, the interest rate for the current study is the typical rate for “New Farm Loans: Other Operating Loans” at Seventh Federal Reserve District (which includes Illinois) agricultural banks in the fourth calendar quarter of each year[33]. Interest rates for the fourth quarter are assumed to most accurately reflect actual opportunity costs on farm operating loans related to storage. The total interest charge for storing grain on-farm is computed as the harvest price times the interest rate compounded daily from the end of harvest to the date of sale. Specifically, interest costs in 2004 are computed using 2004 harvest cash prices for corn and soybeans and an annual interest rate of 6.8%[34].

The second scenario considered is storage off-farm at commercial facilities and a short-run decision-horizon. The marginal cost of physical storage in this case is the sum of commercial storage, drying and shrinkage charges. As in the past, storage costs at commercial elevators in 2004 are drawn from an informal telephone survey of nine central Illinois elevators[35]. Based on this information, physical commercial storage charges are assumed to be a flat 13¢ per bushel from the end of harvest through December 31. After January 1, physical storage charges are assumed to be 2¢ per month (per bushel), with this charge pro-rated to the day when the cash sale is made. The drying charge to reduce corn moisture from 15% to 14% is a flat 2¢ per bushel, while the charge for shrinkage is 1.3% per bushel[36]. The cost of commercial shrinkage is based on the harvest price (no shrinkage is assumed for soybeans in commercial storage). Given that the harvest-time cash price of corn in central Illinois for 2004 is $1.82 per bushel, the charge for volume reduction is 2.37¢ per bushel ($1.82*0.013*100). Therefore, the flat shrink and drying charge assigned to all stored corn in 2002 is 4.37¢ per bushel[37]. Interest opportunity cost is computed using the same procedures and assumptions as outlined above for on-farm storage.

The third and fourth scenarios shift to a long-run decision-horizon, where the on-farm scenario is applicable to a farmer considering the construction of new on-farm storage facilities and the commercial scenario is applicable to a farmer that plans on using commercial storage facilities over the long-run. Since all costs are variable in the long-run, the relevant marginal physical storage cost in both of these scenarios is the total cost. Dhuyvetter, Hamman and Harner (2000) estimate the on-farm fixed cost of physical storage for a 25,000 bushel round, metal bin to be 14.6¢ per year. This fixed cost can be added to the on-farm variable cost estimate discussed earlier to compute the total physical cost of on-farm storage. Presumably, commercial physical storage charges paid by farmers reflect total variable and fixed costs of storage at commercial facilities. Consequently, the commercial storage costs discussed earlier in the context of short-run decisions also represent long-run commercial physical costs.

A comparison of the estimated costs of storage for corn and soybeans in the 2004 crop year is found in Tables 7 and 8, respectively. The first item of note is that the on-farm variable cost of physical storage changes little for corn as the storage length increases and is constant for soybeans as the storage length increases. The reason is the previously mentioned “one-time” nature of most physical costs of on-farm storage. As shown in panels A and B of Figure 7, this results in a “non-linear” relationship between on-farm variable costs of storage per month and the length of storage. For example, the on-farm variable cost for corn stored two months after harvest in 2004 is about 5¢ per month. This can be compared to the on-farm variable cost of corn stored six months after harvest of about 2.5¢ per month. The second item of note is the much lower level of on-farm variable costs versus commercial storage costs. Of course, this is not surprising given that variable on-farm storage costs do not include fixed costs, while commercial storage costs presumably reflect total variable and fixed storage costs at commercial facilities. The third item of note is the similar level of total on-farm costs (variable plus fixed) and total commercial costs for all but the shortest and longest storage lengths. Figure 7 illustrates these findings on a per month basis. This result is not surprising assuming reasonably competitive conditions in the market for storage. If total on-farm storage costs were substantially less than total commercial costs, this would encourage a rapid expansion of on-farm storage and vice versa. In fact, the proportion of on-farm versus off-farm storage capacity in Illinois has been roughly equal for a number of years[38]. This is consistent with a basic equilibrium in the storage market where total on-farm costs and commercial costs are about the same.

Given the information presented in Tables 7 and 8, it is possible to compute net advisory prices and benchmarks under each of the four storage scenarios described at the beginning of this section. It turns out that only two sets of storage costs are necessary to represent all four scenarios. Most obviously, on-farm storage costs in the short-run are estimated by on-farm variable storage costs (fourth column in Tables 7 and 8). Commercial storage costs in the short-run and long-run can be estimated by commercial storage costs (last column in Tables 7 and 8). Based on the equilibrium argument made above, on-farm storage costs in the long-run can also be estimated based on commercial storage costs. Therefore, in the remainder of this report, reference will be made only to on-farm variable storage costs and commercial storage costs.

The calculation of storage charges may be impacted by an advisory program’s loan recommendations and/or the decision rules discussed in the previous section. Specifically, during the period corn or soybeans are placed under loan, interest costs are not accumulated, as the proceeds from the loan can be used to offset interest opportunity costs that otherwise would accumulate. This most commonly occurs after May 31st, 2005 when un-priced grain for which loan benefits have not been collected can be placed under loan until priced[39]. If a crop is priced (forward contracts, futures or options) while under loan but stored beyond the time of pricing, interest opportunity costs are accumulated from the day of pricing until the time storage ceases (since it is assumed the loan is repaid on the date of pricing).

It could be argued that interest opportunity costs should be charged based on the LDP available at harvest but not taken by an advisory program. This adjustment is not made because it would not substantially impact the results due to the small interest opportunity costs involved.

A final issue related to storage costs is the use of different strategies based on the availability of on-farm storage. Specifically, as noted earlier in the “Data Collection” section, advisory programs may issue one set of recommendations assuming on-farm storage is available and another set of recommendations assuming only commercial storage is available. From a practical standpoint, the alternative strategies must be differentiated before grain is placed in on-farm or commercial facilities. After harvest, when grain has already been placed in on-farm or commercial storage facilities, such advice is of little practical value to most farmers. Hence, if a program clearly differentiates on-farm and commercial storage strategies at or before harvest of the 2004 crops, the on-farm recommendations are used in computing the net advisory price under on-farm variable costs and the commercial recommendations are used in computing the net advisory price under commercial costs. In this case, the net advisory price for a program under the two alternative storage cost assumptions will vary due to the difference in costs and underlying strategies. If a service does not clearly differentiate on-farm and commercial storage strategies during harvest of the 2004 crop, the same recommendations are used in computing net advisory prices under on-farm variable and commercial storage costs. In this case, the net advisory price for a program under the two alternative storage cost assumptions will vary only due to the difference in costs, as the underlying strategies are the same[40].

Summary

Based on the marketing assumptions discussed in previous sections, a weighted-average net price for corn and soybeans is computed for each advisory program included in a particular crop year. It should be interpreted as the harvest-equivalent net price received by a farmer who exactly follows the marketing advice for a given program (as recorded by the AgMAS Project). The price is stated on a harvest-equivalent basis because post-harvest sales are adjusted for physical storage and interest opportunity costs. An example will help illustrate the computation of net advisory prices. The highest net advisory price for soybeans in 2004 (assuming commercial storage costs) is $7.45 per bushel. As shown in Figure 8, this price is computed as the unadjusted cash sales price ($5.96) minus commercial storage costs ($0.15) plus futures and options gains ($1.66) minus brokerage costs ($0.09) plus marketing loan benefits ($0.06).

Please note that the marketing recommendations attributed to each advisory program represent the best efforts of the AgMAS Project staff to accurately and fairly interpret the information made available by each program. In cases where a recommendation is vague or unclear, some judgment is exercised as to whether or not to include that particular recommendation or how to implement the recommendation. Given that some recommendations are subject to interpretation, the possibility is acknowledged that the AgMAS track record of recommendations for a given program may differ from that stated by the advisory program, or from that recorded by another subscriber. In addition, the net advisory prices presented in this report may differ substantially from those computed by an advisory program or another subscriber due to differences in marketing assumptions, particularly with respect to the geographic location of production, cash and forward contract prices, fill (execution) prices for futures and options positions, expected and actual yields, storage charges and government programs. [41]

Benchmarks

The essential concept underlying performance evaluation of market advisory programs is fairly simple: the comparison of the net prices generated by advisory programs with prices that could have been obtained by a farmer through one or more appropriate alternative strategies (Sharpe, Alexander and Bailey, 1999, p. 829). The comparison strategies are commonly referred to as benchmarks because they serve as objective standards of performance, much like a yardstick provides an objective measurement of distance. Within this broad framework, two basic types of performance evaluation can be applied to market advisory programs. The first type is based on comparison to “peer-group” benchmarks, whereby net advisory prices are compared to each other or the average price across all advisory programs. The second type is based on comparison to “external” benchmarks, whereby net advisory prices are compared to prices from strategies that do not depend upon market advisory program behavior. In financial markets, it is commonplace to compare investment performance to external benchmarks, such as the Dow-Jones Industrials Index, S&P 500 Index and Wilshire 5000 Index.

The AgMAS study focuses on performance evaluation using external benchmarks. While peer-group evaluation provides useful information about the rank of advisory programs, it cannot answer the question of whether performance of advisory programs as a group or an individual advisory program is “superior” or “inferior” in an absolute economic sense. To answer this question, external benchmarks must be specified based on theories of market pricing.

The first class of external benchmarks is based on the theory of efficient markets. This theory assumes that market participants are rational and that competition instantaneously eliminates all profitable arbitrage opportunities. In its strongest form, efficient market theory predicts that market prices always fully reflect available public and private information (Fama, 1970). The practical implication is that no trading strategy can consistently beat the return offered by the market (e.g., Brorsen and Anderson, 1994; Brorsen and Irwin, 1996; Zulauf and Irwin, 1998; Tomek and Peterson, 2005). Hence, the return offered by the market becomes the relevant benchmark. In the context of the AgMAS study, a market benchmark should measure the average price offered by the market over the marketing window of a representative farmer who follows advisory program recommendations. The average price is computed in order to reflect the returns to a naïve, “no-information” strategy of marketing equal amounts of grain each day during the marketing window. The difference between advisory prices and the market benchmark measures the value of advisory service information. The theory of efficient markets predicts this difference, on average, will equal zero. [42]

If all market participants are rational in the way efficient market theory assumes, then the only interesting external benchmarks are market benchmarks. However, there is growing evidence that many market participants may not be fully rational in the efficient market sense. Hirshleifer (2001) provides a comprehensive review of the judgment and decision biases that appear to affect securities market investors, such as framing effects, mental accounting, anchoring and overconfidence. He also provides an exhaustive review of empirical studies that attempt to measure the potential impact of such biases on securities prices and investment returns. As an example, Barber and Odean (2000) find that individual stock investors under-perform the market by an average of one-and-a-half percentage points per year, an economically significant amount, particularly when viewed over long investment horizons. They argue that a combination of overconfidence and excessive trading explains this finding. Brorsen and Anderson (2001) provide an illuminating discussion of how judgment and decision biases may impact farm marketing. Finally, new “behavioral” theories of market pricing have been developed based on the assumption that market participants are subject to judgment and decision biases (e.g., Daniel, Hirshleifer and Subrahmanyam, 1998).

Behavioral market theory suggests that the average return actually achieved by many market participants may be less than that predicted by efficient market theory, due to the judgment and decision biases that plague most participants. As a result, the average return actually received by market participants becomes an appropriate external benchmark. In the context of the AgMAS study, a behavioral benchmark should measure the average price actually received by farmers for a crop. The difference between net advisory prices and a farmer benchmark should then measure the value of market advisory service information relative to the information used by farmers. Behavioral market theory does not predict a specific value for this difference. It may be positive, negative or zero, depending on the impact of judgment and decision biases on advisory programs versus farmers. Finally, it is important to emphasize that the farmer benchmark should be based on the pricing performance of farmers who do not follow the advisory programs tracked by the AgMAS Project, otherwise, the value of market advisory service information relative to the information used by farmers cannot be “cleanly” disentangled.

It is important to re-iterate that market and farmer benchmarks convey quite different information about the performance of market advisory programs, even though both are forms of an external benchmark. This should be carefully considered when making performance comparisons based on the two types of benchmarks. In addition, there are some desirable properties from a practical perspective that both types of benchmarks should possess: i) they should be relatively simple to understand and to calculate; ii) they should represent the returns to a marketing strategy that can be implemented by farmers; and iii) they should be directly comparable to net advisory prices (Good, Irwin and Jackson, 1998).

Weaker versions of the theory of efficient markets predicts advisory services may profit to the degree they have superior access to information and/or superior analytical ability (e.g., Zulauf and Irwin, 1998). While logically appealing, it is quite difficult, if not impossible, to specify market benchmarks based on weaker versions of the theory because it requires knowledge of the average access to information and analytical ability of market participants.

Market Benchmarks

As pointed out in the previous section, a market benchmark is designed to measure the average price offered by the market to farmers. The appropriate time period for computing the average price is the marketing window of a farmer who follows the recommendations of the advisory programs included in the AgMAS study. This window was defined earlier (see the “Marketing Window” section) as the 24-month period that begins on September 1 st of the year before harvest and ends on August 31 st of the year after harvest. A 24-month market benchmark is simply computed as the average price over the two-year marketing window. It should be noted that this specification of a market benchmark is substantially different than common practice of using the average harvest price as a market benchmark. The analysis found later in this section implies that using the average price during a relatively short time period, such as harvest, may introduce excessive year-to-year variation in the benchmark.

Figure 9 presents average marketing profiles for market benchmarks and advisory programs in corn and soybeans over the 1995-2004 crop years. For comparison purposes, average marketing profiles for 24- and 20-month market benchmarks are included. The 20-month benchmark simply deletes the first four months of the 24-month marketing window from the computations of the average market price. As a result, this benchmark is based on the average price over the period that begins on January 1 of the year of harvest and ends on August 31 of the year after harvest. For both corn and soybeans, the market benchmarks appear to provide a surprisingly good “fit” to the average profile of the advisory programs. More specifically, if a simple linear trend regression is fit to the average profile of the advisory programs (not shown), the estimated trend line is remarkably close to the 24-month benchmark for corn and the 20-month benchmark for soybeans.

The results discussed in the previous paragraph suggest there is some uncertainty about specification of the most appropriate market benchmark for corn and soybean performance evaluations. Leamer (1983) argues persuasively (and famously) that in this type of situation it is crucial to understand the “fragility” of results when key assumptions are changed. Consequently, both a 24-month and a 20-month market benchmark will be used in comparisons to net advisory prices. Cash forward prices for central Illinois are used during the pre-harvest period, while daily spot prices for central Illinois are used for the post-harvest period. The same forward and spot price series applied to advisory program recommendations are used to construct both market benchmarks. Details on the forward and cash price series can be found in the earlier “Prices” section of this report.

Three adjustments are made to the daily cash prices to make the 24-month and 20-month average cash price benchmarks consistent with the calculated net advisory prices for each marketing program. The first is to take a weighted-average price, to account for changing yield expectations, instead of taking the simple average of daily prices. This adjustment is consistent with the procedure described previously in the “Yields and Harvest Definition” section. The daily weighting factors for pre-harvest prices are based on the calculated trend yield, while the weighting of the post-harvest prices is based on the actual reported yield for central Illinois . The second adjustment is to compute post-harvest cash prices on a harvest equivalent basis, which is done by subtracting on-farm variable or commercial storage costs (physical storage, shrinkage and interest) from post-harvest spot cash prices. The daily storage charges are calculated in the same manner as those for net advisory prices. The third adjustment is made with respect to the loan program. In the context of evaluating advisory program recommendations, it was argued earlier that a “prudent” or “rational” farmer would take advantage of the price protection offered by the loan program, even in the absence of specific advice from an advisory program. This same logic suggests that a “prudent” or “rational” farmer will take advantage of the price protection offered by the loan program when following the benchmark average price strategy. Based on this argument, the 24-month and 20-month average cash price benchmarks are adjusted by the addition of LDPs and MLGs. Bushels marketed in the pre-harvest period according to the benchmark strategy are treated as forward contracts, with the LDPs assigned at harvest. Bushels marketed each day in the post-harvest period are awarded the LDP or MLG in existence for that particular day. Finally, just as in the case with comparable advisory program recommendations, it is assumed that all un-priced corn (but not soybeans) on May 31, 2005 is placed under loan. Interest opportunity costs are not charged to the benchmark after this date if the cash price for corn on the date of loan redemption is below the CCC loan rate. [43]Since market prices are substantially above the loan rate on May 31, 2005 for soybeans, it is assumed that un-priced soybean bushels are not placed under loan on this date for the 2004 crop.

While the 24- and 20-month market benchmark prices can obviously differ for a given crop year, averages of the two benchmark prices across crop years are not expected to differ substantially. First, the difference in the marketing windows for the two benchmarks is relatively small, as the 20-month benchmark reduces the 24-month marketing window by only about 17%. Second, given a sufficiently large sample of crop years and efficient corn and soybean markets (cash, futures and options), the law of one price implies that annual averages of different average price benchmarks should be equal when stated on a harvest equivalent basis (Brorsen and Anderson, 1994). Of course, if corn and soybean markets are inefficient, the equivalence would not hold. In particular, if pre-harvest prices contain a “drought premium” as some argue (e.g., Wisner, Baldwin and Blue, 1998), then the 24-month benchmark price may be consistently higher or lower than the 20-month benchmark price, depending on the evolution of the drought premium. [44]

In contrast to averages, the variation of 24- and 20-month market benchmark prices across crop years is expected to differ. One reason for the difference is the well-known result in statistics that the sampling variation of the mean (average) is inversely related to the sample size used to compute the average (e.g., Griffiths, Hill and Judge, 1993, p.82). Since the sample of daily prices used in computing the 24-month benchmark is larger than the sample for the 20-month benchmark, the variation of the 24-month benchmark should be smaller than variation of the 20-month benchmark. Another reason is that the volatility of spot prices for storable commodities such as corn and soybeans increases as one moves from early in the 12-month marketing year (e.g., harvest) to later in the marketing year (Williams and Wright, 1991; Peterson and Tomek, 2005). The increase in volatility is driven by the decline in stocks that normally occurs during the marketing year. Specifically, available stocks are largest at harvest and then decline through the remainder of the marketing year, and consequently, a given demand shock will have the largest impact on price later in the marketing year. In terms of market benchmarks, this implies that the 20-month benchmark, which gives more weight to prices later in the marketing year, will be more volatile than the 24-month benchmark. [45]

A practical concern with the market benchmarks is that a farmer may not be able to implement the benchmark strategies since they involve marketing a small portion of the crop every day. There are two reasons to believe this concern is not overly serious. First, a number of companies have developed and offer grain “index” contracts that allow farmers to receive the average market price over a pre-specified time interval. An extensive discussion of these new contracts can be found in the AgMAS research report by Hagedorn et al. (2003). Second, a strategy of routinely selling at less frequent intervals closely approximates the market benchmark prices. For example, a farmer might consider alternative “tracking” strategies of marketing only once a month or once every other month over the 24-month window. [46]Using mid-month prices, a tracking strategy of marketing only once a month (24 times) generates average prices over 1995-2004 that are quite close to 24-month market benchmark prices. The average difference is only two cents per bushel for corn and one cent per bushel soybeans, with a maximum difference for any particular crop year is eight cents per bushel in corn and five cents per bushel in soybeans. A tracking strategy of marketing once every other month (12 times) also generates average prices over 1995-2004 that are close to those of the 24-month market benchmark. The average difference is only two cents per bushel for corn and five cents per bushel for soybeans.

The average difference results for the benchmark tracking strategies should not be a surprise given the previous argument about averages of different benchmark prices in efficient markets. More surprising is the result that the variation of the tracking strategies across crop years for both commodities is only one to three cents per bushel (three to nine percent) more than the 24-month benchmark over 1995-2004. This is surprising because the tracking strategies are based on dramatically smaller samples, 12 or 24 observations compared to about 500 observations for the 24-month benchmark, but have only a marginally higher variation across crop years. The most likely explanation is that observations for the tracking strategies are not selected at random, but are instead equally spaced across the entire marketing window. Further research is needed to fully understand the behavior of tracking strategies in corn and soybean markets.