Pricing Standing Corn for Silage

by: Dianne E. Shoemaker, Field Specialist Dairy Production Economics

Two perennially challenging questions are how to price a: dairy facilities for rental, and b: crops standing in the field. Since it is September, “b” is the challenging question of the month. If the question is answered correctly, both the buyer and the seller will be satisfied with the transaction. The buyer purchases a good crop at a good price and is able to make good silage. The seller sells a good crop at a good price and doesn’t have to harvest it. Let’s review some information Normand St Pierre, Bill Weiss and I have talked about before.

Base Price
The owner of the crop would like to receive the cost of producing the crop plus a profit. Their base price should be what they would have received if they had harvested the crop as grain less any harvesting/drying/storage/marketing costs.

If corn has been priced, it will obviously need to be harvested to fulfill contract obligations. However for uncommitted corn that would be available for corn silage harvest, how do we set a price? Corn at harvest this month is projected to be worth between $4 and $5 per bushel. If we estimate that on average, a ton of corn silage contains ~7 bushels of corn, then the standing corn for silage would be worth between $28 and $35 per ton before deducting the cost of harvesting for grain (~$40 per acre). Therefore, $26 to $33 per ton after grain harvest costs. This would be a starting point. Additional adjustments must be made.

Optimally, corn silage should be harvested, fermented, stored, and priced at 35% dry matter (DM). If the actual DM is higher or lower, the price should be adjusted. If actual dry matter was 30%, then the value is about $28/t (30/35 = 0.85 x $33/ton) if corn is worth $5/bu. Corn chopped at more than about 38% DM or less than about 30% DM may not ferment properly and can be a problem. The price for this corn silage should be discounted.

Other important considerations when negotiating price for standing crops include:

Feed value – comparing the difference between valuing corn silage using the 7 bushel of corn per ton method plus harvest and storage costs and an adjustment for 10% fermentation loss, vs. pricing based on the prevailing feed nutrient value (Sesame software) pricing method valuing the silage at what it’s nutrients are worth based on a wider selection of feed prices plus the harvest and storage adjustments. St. Pierre found that the ratio of the two methods indicates that the feed value to the cow is usually greater than the market value based on the market price of corn. 27% more between 2005 and 2008.

Risk – When the dairy farmer buys the standing crop from the grower, he plans to get it chopped and ensiled at the correct moisture in a timely manner so that it can ferment properly and he has an excellent feed. However, now all the production risk is the buyer’s. The price for the standing crop should be discounted to reflect this transfer of risk. What is the right amount? That is part of the negotiation process between seller and buyer.

These discussions should take place and an agreement should be reached before the crop is harvested. These agreements are especially important when large amounts of crops (and money!) are involved. Putting them in writing can save disagreements later.

Additional information on pricing forages by Shoemaker, Weiss and St Pierre is available at

Soybean – Corn Price Ratio Since 1975

by: Carl Zulauf, Professor, Ohio State University, September 2013

Economists pay as much attention to price ratios as to the level of prices. Within the U.S. crop sector, the price ratio that arguably receives the most attention is the ratio of soybean to corn prices. The emergence of a late season drought in much of the Midwest has the potential to make this price ratio of more relevance than normal this year because a late season drought normally affects soybean production more than corn production. Characteristics of the soybean – corn price ratio are examined in this post. The focus is on both the ratio’s historical trend and annual variation.

U.S. Soybean – Corn Price Ratio:
The price ratio is examined beginning with the 1975 marketing year. The primary reason for this decision is that, prior to 1973, U.S. farm policy was an on-going, important determinant of prices. The corn and soybean prices used in the analysis are from the U.S. Department of Agriculture (USDA), National Agricultural Statistical Service (NASS) Quick Stats program, available at

Since 1975, the average soybean-corn ratio is 2.52 (see Figure 1). No trend in this ratio is evident. However, variation in the annual ratio is notable. The standard deviation is 0.33, which means there is a 67% probability that the ratio will be between 2.19 (2.52-0.33) and 2.85 (2.52+0.33). The ratio was less than 2.00 in 2 years: 1975 (1.94) and the current year of 2012 (1.99). In these years, the price of soybeans was less than double the price of corn. The ratio was above 3.00 in 4 years: 1986 (3.19), 1996 (3.17), 1987 (3.03), and 2003 (3.03). In these years, the price of soybeans was more than triple the price of corn. If monthly prices are used, the minimum soybean-corn price ratio was 1.72 in July 1996 while the maximum ratio was 4.11 in May 1977. In other words, the maximum monthly soybean-corn price ratio is more than twice the minimum monthly soybean-corn price ratio.

To put the historical variation observed in the soybean-corn price ratio in a more contemporary context, Figure 2 presents the range of soybeans prices for the current 2013 marketing year given the 2013 midpoint price estimate of $4.90 for corn contained in USDA’s August 2013 World Agricultural Supply and Demand Estimates (WASDE). The implied price of soybeans ranges from $9.49 using the lowest observed price ratio of 1.94 to $15.61 using the highest observed price ratio of 3.19. The average price ratio of 2.52 implies a soybean price of $12.34, with a 67% confidence range of $10.73 to $13.95 based on the standard deviation of 0.33 in the price ratio.

The current price ratio based on the average of all 2013 marketing year corn and soybean futures contracts is 2.75. In contrast, the August WASDE ratio was 2.32 using the midpoint price estimate. This change in price ratios is consistent with the emergence of a late season drought expected to have a greater impact on soybean production than on corn production.

Explaining the Soybean – Corn Price Ratio:
The large variation in the annual soybean-corn price ratio prompts an immediate question: what explains the variation? Time constraints did not permit an extensive investigation, but one obvious potential explanatory factor is the ratio of U.S. production of soybeans to corn, measured in bushels. This ratio is presented in Figure 3. Source of the production data is USDA’s Quick Stats program.

As with the price ratio, there is no apparent trend in the ratio of U.S. soybean to corn production since 1975. The average ratio is 0.27, which means that soybean production is on average 27% of the size of corn production in the U.S. The ratio ranges from 0.20 in 1976 to 0.39 in 1983. The latter year was the year of the payment-in-kind (PIK) farm acreage reduction program that coincided with a severe drought. Soybeans never have had an acreage reduction program and thus was largely unaffected by the PIK program. Excluding 1983, the next highest soybean-corn production ratio was 0.31, which occurred in both 1988 and 2002.

Interestingly, the correlation between the annual soybean-corn price ratio and the annual soybean-corn production ratio is -0.20, which is not statistically significant at the commonly-used 95% confidence level. This finding does not rule out U.S. production as a contributing determinant of the soybean-corn price ratio, but it does suggest that other factors have played a more important role historically. Other factors include the relative strength of demand for soybeans and corn and the world-wide supply of soybeans and corn. Additional analysis is needed.

Summary Observations:
A key price ratio for the U.S. crop sector is the ratio of soybean to corn prices. This ratio has importance because soybeans and corn are not only the largest acreage crops in the U.S. but are also crops that often compete for the same acre of land. Understanding this ratio is important to understanding market prices. Despite all the changes in the supply and demand complex since 1975, the ratio of soybean to corn prices exhibits no discernible trend. However, the ratio does exhibit considerable variation from year to year and over longer periods of time.

The soybean-corn price ratio has become a topic of conversation in the markets due to the emergence of the late season 2013 U.S. drought. Current thoughts in the market are that this drought will likely do more damage to the U.S. soybean crop than to the U.S. corn crop since the key production period for U.S. soybeans occurs later in the growing season than for U.S. corn. As a result, the soybean-corn price ratio has trended up since mid-August. Examination of historical data since 1975 suggests that the soybean-corn price ratio is on average more impacted by factors other than the level of U.S. production, with other explanatory factors being the relative demand for soybeans and corn and the world supply of corn and soybeans. Thus, while the current focus is on U.S. production, which is reasonable and understandable; the future direction of the soybean-corn price ratio may rests more upon production outlooks in the rest of the world and the relative demand for soybeans and corn.

This publication is also available at

Click here to read the entire article and to see the Figures.

Sampling Home-Based Food Products: Keeping You Responsible for a Safe Food Product

Catharine Daniels, Attorney, OSUE Agricultural & Resource Law Program So far in a series of posts, we’ve discussed how to sell your baked goods at farmer’s markets (here), what’s required for a home bakery license (here), and how to label … Continue reading

Fertilizer Market Fundamentals Potentially Impacting Prices

by: Barry Ward
Department of Agricultural, Environmental and Development Economics
OSU Extension, Leader, Production Business Management

Fertilizer continues to be the most volatile of the crop input costs and management of this important input may be the difference in being a low cost or high cost producer. Fertilizer prices are currently lower compared to last year at this same time and many producers are asking themselves if this is the right time to buy. While it is hard to know exactly what direction and when prices will move it is wise` to keep up-to-date on important fertilizer products fundamentals.

Healthier farmer balance sheets and continued positive crop profit prospects have signaled the global marketplace to increase planted acreage. These same factors have also caused producers to maintain or increase fertilizer application rates which has led to strong global demand.

On the flipside, potentially large northern hemisphere crops have dampened prices which may lead to tighter profit margins in the short to medium term. These tighter margins may be a precursor to more judicious use of fertilizer as producers look to cut input costs.

Nitrogen (N)
Retail prices have decreased year-over-year for all 3 commonly used nitrogen fertilizers in Ohio. Urea Ammonium Nitrate (UAN) 28% Nitrogen price has decreased approximately 10% while Anhydrous Ammonia (NH3) price has decreased 15% since one year ago. Urea prices have declined approximately 20% at the retail level.

Nitrogen fertilizer price fundamentals are slightly different for the three primary nitrogen fertilizers used in Ohio as their supply and demand differs around the world. For example, urea is used as a nitrogen fertilizer in many parts of the world due to its relative ease of handling and application.

Key issues impacting nitrogen fertilizer prices are crop profit margins (specifically corn profit margins) and nitrogen fertilizer production expansion both domestically and globally. These two primary fundamentals should dictate nitrogen fertilizer prices in the short to medium term as they will be the primary determinants of the supply/demand balance. Potentially lower corn profit margins due to lower global corn prices and somewhat “sticky” crop input costs will possibly restrict N fertilizer demand. This result may lead to supply outpacing demand and may weaken prices. We may already be seeing nitrogen prices react to lower corn prices and lower potential net returns in 2013 and 2014 as suppliers attempt to move product in an ever increasing wait and see marketplace.

The other primary fundamental issue impacting nitrogen fertilizer markets is actual and proposed expansion in nitrogen manufacturing both domestically and globally. A combination of lower domestic natural gas prices (the primary ingredient in manufactured nitrogen fertilizers) due to the expansion of natural gas extraction and the recent period of relatively high net profits in crop production have led to high margins in nitrogen manufacturing. These high margins in nitrogen fertilizer manufacturing have led to a number of brownfield expansion and greenfield (new manufacturing site) development proposals. Although several existing manufacturing sites have been expanded or brought back on line many potential additional expansions and new site development are not certain to be built. One source reports that 30 nitrogen manufacturing expansions or new constructions are being considered in the U.S. alone. The same source reckons that less than half will be finished. With lower potential crop margins affecting demand and more manufacturing capacity globally affecting supply, the short and medium term prospects for nitrogen prices appear to be flat to lower.

Factors that may lead to N price increases include:
+ Large corn acreage prospects for the U.S. again
+ Strong crop farm balance sheet

Factors that may lead to N price decreases include:
– Lower crop prices leading to tighter margins
– Low domestic natural gas price
– More domestic N production coming online Giesmer, La; Donaldsville, La; Augusta, Ga; etc.
– More domestic N production to potentially be built – approximately 9.3m tons (present capacity 13m t)

Potassium (K20)
The retail price of potash has declined approximately 12% since one year ago.

The potash industry essentially operates as a duopoly (two firms, in this case, two consortiums, with dominant control of the market) with Canpotex (Canadian Potash Exporters – Members: Potash Corp., Mosaic, Agrium) and Belarusian Potash Co. (Members: OAO Uralkali and OAO Belaruskali) controlling much of the global potash supply. One estimate is these two entities control 70% of the global potash market. In recent years these two entities have utilized a strategy known as “matching supply with demand”. In other words, they have curtailed supply to keep potash prices at relatively high levels. This strategy has worked well enough that some analysts contend that the potash mining and manufacturing business has had margins of up to 75% in recent years. But all of that may be about to change.

On July 30th, Russia’s OAO Uralkali’s board of directors announced that it would no longer export potash through Belarusian Potash Co. (BPC). This most likely will change the dynamics of the global potash trade and has already impacted global prices. Some analysts have stated there have been disagreements in the past between Uralkali and Belaruskali that have been resolved rather quickly. Vladislav Baumgertner, Uralkali CEO, cited violations of the exclusive exporting arrangement by their partner, Belarusian Potash, as the reason for Uralkali’s decision to leave the consortium. Decree No. 566 by the Belarusian President on December 22, 2012 cancelled the exclusive right of BPC to export Belarusian potash. Following this decree, Belaruskali has made a number of export deals outside of BPC.

Baumgertner, Uralkali CEO, has stated this is not a temporary fall out between Uralkali and Belaruskali and that Uralkali will pursue a volume over price strategy to meet profit goals. He has also been quoted stating the international potash price may decline up to 25% in one interview and $100/MT in another.

Potash Corp. CEO, William Doyle has downplayed the breakup of the other potash consortium stating the break-up would be temporary and that “logic would prevail.” He also stated that no one producer can determine price in response to Baumgertner’s assertion of global price declines.

With the recent arrest of Baumgertner at the hands of Belerusian authorities, the messy affair in eastern Europe is far from over. Analysts speculate that it may come down to a confrontation between Russian President Vladamir Putin and Belerusian President Alexander Lukashenko.

The bottom line is with the break-up of BPC, the global potash market has declined $15- $25/mt. The short term prospects will likely be dictated by the consortium events and potential crop returns (dictated by crop price levels) for 2013 and prospects for 2014. The fundamentals suggest flat to lower (possibly much lower depending on Uralkali’s export activities) potash prices through the end of the year.

An important long term supply and demand issue in the potash industry is BHP Billiton Group’s announcement on August 20th that it will invest an additional $2.6 billion in the Jansen Potash project in Saskatchewan. Jansen may be the world’s best undeveloped potash resource and may be capable of supporting a mine with annual capacity of 10 million metric tons for more than 50 years.

Factors that may lead to K price increases include:
+ Strong crop farm balance sheet
+ Canpotex members may further curtail production?

Factors that may lead to K price decreases include:
– Lower crop prices leading to tighter margins
– Belarusian Potash Co. breakup may increase potash available on the global market?

Outlook information presented here was developed with data from AEDE research, the Energy Information Administration, USDA, other Land Grant research, futures markets and retail sector surveys. While gauged to the best of this author’s capabilities, forward looking statements contained in this document may prove to be incorrect due to changes in supply and demand and other political and economic related events.

Ohio Court Upholds Jury Verdict against Adverse Possession Claim

Peggy Kirk Hall, Asst. Professor, OSUE Agricultural & Resource Law Program     . A recent decision by the Ohio Court of Appeals addressed two important legal standards: the proof necessary to claim title to another’s land by adverse possession and conditions allowing a trial … Continue reading

Comparing Current and 1970 Farm Prosperity: Alcohol for Fuel and the Current Prosperity

by: Carl Zulauf, Professor, and Nick Rettig, Undergraduate Student
Ohio State University, August 2013

Overview: This post is the eighth in a series that compares the current and 1970 periods of farm prosperity. This post examines the role of the alcohol-for-fuel market.

Background: Corn processed into alcohol for fuel was not a factor in the 1970 period of farm prosperity. The U.S. Department of Agriculture’s (USDA) data series on this demand component does not start until 1980 (see Figure 1 presents the share of total corn use in the U.S. that was processed into fuel alcohol for the 1980 through 2012 crops. Corn used for fuel alcohol is net of the feed byproduct that comes from the distillation process. Specifically, 29% of the amount of corn processed into fuel alcohol is assumed to be used as feed for livestock. While estimates of this adjustment factor vary, 29% is reasonable based on current information.

The share of total U.S. corn use processed into fuel alcohol did not reach 5% until the 2001 crop. It passed 10% by 2005 and 20% by 2008. Despite the drought, the share increased from 28% in 2011 to 29% in 2012 as the use of corn for fuel alcohol decreased less than the 54% decline in exports. Current USDA projections for the 2013 crop imply a use ratio of 27% as export and feed use expand more than fuel alcohol use.

Alcohol for Fuel vs. China: Increased demand for food was a key factor in both the 1970 and current period of farm prosperity. In the 1970s, the leading source of this demand was the Soviet Union. During the current period, China is the leading source of this demand. However, as noted above, unlike the 1970s the current period has a second demand driver, the market for fuel alcohol. The existence of two demand drivers prompts the question: which is more important? To provide a simple perspective on this question, the quantity of U.S. corn processed into fuel alcohol, net of the feed byproduct, is expressed as U.S. harvested corn acres. This value is calculated by dividing corn used for fuel alcohol by the average U.S. yield harvested per corn acre during the crop year. Similarly, China’s imports of soybeans from the world (not just the U.S.) are converted into the number of harvested U.S. soybean acres. Included in China’s soybean imports is the soybean equivalent of the amount of soyoil it imported. China’s imports are from while U.S. harvested yields are from The authors would like to thank Matt Roberts for his suggested use of these measures.

Figure 2 presents the calculated acre equivalents. China’s imports of soybeans began to accelerate during the mid-1990s while the processing of corn into fuel alcohol began to accelerate during the early 2000s. By 2005, the year before the current period of farm prosperity began; corn for fuel alcohol was the equivalent of 8 million U.S. acres of corn while China’s import of soybeans was the equivalent of 31 million U.S. acres of soybeans. The magnitude of these acre numbers illustrates the importance of building a demand base before a period of prosperity can begin. By 2012, the acre equivalents were 27 million acres of U.S. corn for fuel alcohol and 62 million acres of U.S. soybeans for China’s imports of soybeans. Thus, between 2005 and 2012, the expanded demand for corn for fuel alcohol claimed the equivalent of an additional 19 million acres of U.S. corn while the expanded demand of China for soybeans claimed the equivalent of an additional 31 million acres of U.S. soybeans. In conclusion, this simple analysis suggests that China’s demand for soybeans has been a notably more important demand driver during the current period of farm prosperity than has been the demand for U.S. corn for fuel alcohol. For a more extensive discussion of China’s demand for food and the current period of farm prosperity, see the post, “Comparing Current and 1970 Farm Prosperity: China and the Current Prosperity,” by Carl Zulauf, Allan Lines, and Xianglin Liu.

Historical Perspective: Government policy has been integral to the development and expansion of the fuel alcohol market for U.S. corn. Tax credits to promote the production and consumption of biofuels date to the 1970s. A tariff on imported ethanol began in the 1980s. Minimum consumption levels, known as Renewable Fuels Standards, were set by the Energy Policy Act of 2005, and then expanded by the Energy Independence and Security Act of 2007. The federal tax credit and import tariff however were allowed to expire on December 31, 2011.

While policy is unquestionably important, focusing on policy misses the bigger picture. Figure 3 presents the ratio of U.S. average corn price to the U.S. average first purchase price of crude oil. To facilitate the presentation, this ratio is benchmarked to the average value of this ratio from 1925 through 1929. This benchmark period is selected because it predates the impact of the Great Depression, which began in late 1929, and the subsequent enactment of farm price support policy beginning in 1933. Corn prices are from the USDA, National Agricultural Statistics Service, available at Crude oil prices are from the U.S. Energy Information Agency, available at

Since 1925-1929, the benchmarked ratio of U.S. corn price to U.S. first purchase price of crude oil has declined from 100% to 12% during the current 2012 crop year. The lowest ratio occurred in 2006 at 6%. The decline was not continuous but largely occurred in 3 steps. The first occurred during 1952-1957 as corn prices declined. This decline in corn price was caused by a transition for U.S. policy for corn from the high fixed price supports of World War II and the Korean War to lower, more market-oriented price supports. The second and third steps occurred during 1975-1979 and 1998-2004, respectively; with the primary reason being increasing oil prices. Even the high corn prices of the last two years have not reversed the third step.

According to Iowa State University’s Ethanol Profitability Model, available at; a net return of 8 cents per bushel of corn above all costs existed for the production of fuel alcohol over the period of January through May 2013. During this period of roughly breakeven production of ethanol, the ratio of U.S. corn price to U.S. first purchase price of oil was 7.4%. Adjusting for the 8 cent profit margin results in an implied corn-to-crude oil breakeven price ratio of 7.3%. The price ratio of corn to crude oil was below this value in 2005 and 2006 (see Figure 3). Moreover, using USDA’s current forecast of the 2013 crop year corn price of $4.90 per bushel and the January through May 2013 average U.S. first purchase crude oil price of $95.10 per barrel results in a ratio of 5.2%.

While many critical assumptions underlie the 7.3% breakeven ratio, including the price of oil, corn, and natural gas as well as the efficiency of the fuel alcohol conversion process; Figure 3 suggests that the long-term decline in the price of U.S. corn relative to U.S. crude oil has reached the point where corn is at the least close to being a competitive source of energy without any government subsidy. By focusing on the role of policy, it is easy to miss the long term change in corn’s competitiveness as a source of fuel energy.

Summary Observations: A major difference between the 1970 and current period of farm prosperity is the existence of two demand drivers during the current period. Increased demand for food was a common demand driver in both periods, but the current period also includes the fuel alcohol market as a demand driver. While this analysis suggests that the fuel alcohol market is the smaller of the two demand drivers, the existence of two demand drivers is probably the reason for the different price paths during the two periods and in particular for the longer uptrend in prices during the current period. For a discussion of the different price trends, see the previous post “Comparing Current and 1970 Farm Prosperity: Crop Prices.” .

While government policy’s role in creating incentives for the fuel alcohol demand driver is important to acknowledge and understand, it also important to note that, given the continuation of current conditions, U.S. corn is now close to a point of non-subsidized competitiveness with crude oil as a source of energy. If this situation has indeed been reached, it represents a fundamental turning point for crop agriculture by opening up a market-sustainable source of non-food demand. It would be a paradigm shift with regard to farming, food, and agriculture. Paradigm shifts invariably set in motion a series of changes that are difficult to foresee but usually result in a major redefinition of the sector as an economic engine and in the way that public policy is conducted toward the sector.

The next post in this series will provide a summary of the various posts, along with implications.

This publication (so readers can view the Figures) is available at

Farm Bill Conference Issues

by: Carl Zulauf, Professor, Ohio State University, and Gary Schnitkey, Professor, University of Illinois at Urbana-Champaign, August 2013

Overview: Both the U.S. Senate and U.S. House of Representatives have passed farm bills. The process now moves to a Conference Committee, which is composed of members of the U.S. Senate and House of Representatives appointed by the leadership of the respective legislative chamber. It is tasked with working out compromises on the differences between the two bills. This post presents a brief listing and discussion of the key differences. It does not attempt to cover all differences or to provide an extensive analysis of the issues. Its purpose is simply to provide a broad-brush outline of key issues. The Senate farm bill is available at while the House farm bill is available at

Potentially Important Differences between the House and Senate Farm Bills:
► Nutrition Programs
► Permanent Law
► Dairy Programs
► Crop Insurance and Conservation Compliance
► Crop Insurance Subsidy Limit
► Payment Limits on Title 1 Crop Safety Net Programs
► Direct Payments and Upland Cotton
► Crop Safety Net:Moving vs. Fixed Targets, Price vs. Revenue Multiple Year Targets, Base vs. Planted Payment Acres

The word, potential, is included to indicate that differences between the House and Senate bills may not turn out to be an issue. One legislative chamber can accept the other legislative chamber’s version or the difference may be easily compromised.

Nutrition Programs: The Senate farm bill contains a nutrition title with spending cuts of $4 billion over 10 years. The House farm bill contains no nutrition title. However, reports indicate the House Republican leadership will seek to pass a nutrition title as a separate bill with spending cuts totaling around $40 billion over 10 years. Thus, two potential issues exist in regard to nutrition programs: will a nutrition title be included in a conference committee farm bill and, if included, what will be the level of funding? The debate over spending on nutrition programs reflects a broader debate over the level of spending for safety net programs, including Social Security, Medicaid, and Medicare.

Permanent Law: The Senate takes the traditional approach of enacting most Title I (Commodities) programs as amendments to so-called permanent law (usually the 1938 and 1949 farm bills). The amendments also have expiration dates. For example, the Senate’s programs for field crops expire after the 2018 crop year. In contrast, the House proposes to replace permanent law with the current farm bill and, more importantly, it has no expiration date. The combination of expiration date and outdated permanent law has provided impetus to reconsider not only the farm safety net but also the entire farm bill. The House proposal reduces and could negate the need to consider farm bills in the future, making it harder to enact changes. Thus, adopting the House approach will likely mean that farm bill actors will want to be more certain than normal that they are getting the programs they want, which in turn could reduce the likelihood of getting a new farm bill.

Dairy Programs: Both the House and Senate farm bills replace the current milk safety net programs with a subsidized insurance program for the margin between milk prices and feed prices. The Senate bill has a provision that seeks to control the supply of milk when the margin declines below a specified value. The House bill does not contain a supply management provision. The bills also differ on the schedule of farm-paid insurance premiums, with the House bill’s schedule being more favorable for smaller milk producers. The latter difference reflects long standing discussions over whether the proposed milk margin program favors large dairy farms.

Crop Insurance and Conservation Compliance:
The Senate bill attaches conservation compliance to Federal crop insurance. To qualify for the federal subsidy on crop insurance, a farm must meet the highly erodible land, sodbuster, and wetland conservation provisions that are currently attached to Title 1 commodity programs. The House bill does not attach conservation compliance to Federal crop insurance. Issues that underpin this difference include consistency between Title 1 and crop insurance programs, whether this provision is needed when most, but not all, buyers of crop insurance are in Title 1 programs, and, more broadly, what should society reasonably expect from farms in return for subsidizing crop insurance premiums.

Crop Insurance Subsidy Limit: The Senate bill contains a 15 percentage point reduction in the crop insurance premium subsidy for entities with an average adjusted gross income exceeding $750,000, but delays implementation for 1 year pending a study to assess the impact this limit will have on the program, including premiums, as well as analysis of attempts to circumvent the limit. The House bill contains no such provision. This difference reflects an intense debate over whether insurance subsidy levels should be the same for small, medium, and large farms. In other words, should the public’s subsidy level take into account the ability to pay for insurance based on the farm’s ability to generate income?

Payment Limits on Title 1 Crop Safety Net Programs: The Senate and House bills limit marketing loan gains and price deficiency payments to $75,000 per payment entity and limit payments by other Title 1 crop programs to $50,000 per payment entity. The Senate bill has a separate payment limit that applies only to peanut program payments; the House bill does not have a separate payment limit for peanuts. Payments are denied to entities with an aggregate gross income (AGI) over 3 years that exceeds $750,000 in the Senate bill and $950,000 in the House bill. Differences exist between the two bills in the programs to which the AGI limit applies, with the House bill applying the limit to a broader range of programs, including conservation programs. Last, the Senate bill, but not the House bill, contains a provision that redefines active involvement in farming. This provision’s objective is to tighten and more consistently enforce who is considered to be actively involved in farming. The existence of these payment limit differences reflect an on-going debate over whether public support to farms should be conditioned on a payment entity’s level of income?

Direct Payments and Upland Cotton: Both the Senate and House farm bills eliminate the direct payment program after the 2013 crop year, except that the House bill retains direct payments for the 2014 and 2015 crops of upland cotton. The payment level is phased down, with the percent of base acres on which payment is made declining from 85% for the 2013 crop to 70% for the 2014 crop and 60% for the 2015 crop. The issue is whether the other crops will also want a phased down extension for direct payments. In addition, if an extension of the 2008 farm bill is the path taken; these lower rates for direct payments could be part of the extension since a number of nonfarm legislators have stated that their support for a farm bill extension will be conditional on reducing or eliminating direct payments.

Multiple Year Crop Safety Net: The House bill provides farms with a choice between a Price Loss Coverage (PLC) and Revenue Loss Coverage (RLC) programs. PLC is a target price program that makes payments when the market price is less than a reference price (i.e., price target). Payment is made on the basis of planted acres subject to a total farm payment limit based on the farm’s historical base acres. The reference target prices are fixed in the House bill. RLC is a revenue target boundary program that covers revenue shortfalls that fall between 75% and 85% of a revenue target. The revenue target moves with the market based on a 5-year Olympic moving average of yield and price. RLC specifies that the crop’s fixed reference price is a lower bound on the price used to calculate the revenue target.

The Senate bill offer farms both an Adverse Market Payment (AMP) program and an Agriculture Risk Coverage (ARC) program. AMP, like PLC, provides price deficiency payments when price is below a reference price. The reference price is set at 55% of a 5-year Olympic moving average (removes low and high value) of prices except that fixed reference prices are specified for rice and peanuts. ARC, like RLC, is a revenue target boundary program. It provides payments when revenue falls within a range between 78% and 88% of a revenue target determined by using a 5-year Olympic moving average of past yields and prices. ARC, like RLC, provide both shallow loss coverage and coverage for multiple year losses since a moving average adjusts more slowly than the market. AMP payments are based on historical base acres. ARC payments are based on planted acres subject to a cap for the farm (not on individual crops) determined by the farm’s planting history for the 2009 through 2012 crops. The Senate bill is able to provide both a price and revenue program to farms because its reference price for most crops is much lower than the reference price fixed by the House bill.

It is easy to focus on the differences between the House and Senate Title 1 farm safety net programs. However, both offer a target price program and both contain a revenue program. They differ on whether the revenue program is an option to the target price program or is available to all farms. They differ on whether reference prices are fixed or variable for most crops. They differ on the use of historical base acres or planted acres. These differences are not trivial but are also surmountable.

Summary Observations: A diverse set of differences exist between the House and Senate farm bills. However, many of the differences concern the farm safety net. These differences can largely be grouped into two categories.

One category contains issues that reflect a broad debate over what society should expect from farms in return for the public subsidies it provides. This set of issues includes payment limits, limits on crop insurance subsidies, and conservation compliance.

The second category contains issues that revolve around the determination of assistance levels for the farm safety net. In this farm bill debate, these issues are largely about multiple-year assistance. Some of the issues arise because the U.S. has decided not to enact annual supply control constraints for most crop safety net programs. The one exception is sugar. The vote by the House to remove the supply control provision in the proposed dairy margin program is consistent with the current situation for crop support programs, excluding sugar.

The lack of an annual supply control program means that any fixed program parameter can end up distorting the market and thus farmers’ production decisions. In contrast, an annual supply control program provides the government with a mechanism for limiting production when policy distortions increase U.S. production. For example, target prices or revenue will distort production when prices or revenues are below the target levels for an extended time. Farms will produce for the target, not the market. Such a situation opens up the U.S. farm safety net to lawsuits at the World Trade Organization (WTO). This situation arose with respect to the U.S. cotton program. Specifically, fixed U.S. cotton price support targets became out of step with the market, leading to the successful Brazilian cotton case at the WTO and by extension to the major redesign of cotton programs contained in both the House and Senate farm bills. In summary, the U.S. has effectively two policy options if it wants to establish target levels: it can have targets that move with the market or it can use fixed targets but include some form of supply control to limit costs and farm production distortions when the market is below the fixed target. U.S. farm policy has struggled with accepting this situation. It will be interesting to see how the farm bill conference committee addresses it.

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Potential Profitability of Strip Intercropping with Corn and Soybeans

Barry Ward, Brian E. Roe and Marvin T. Batte
Department of Agricultural, Environmental and Development Economics

Agronomic trials suggest that planting narrow strips of corn and soybeans side by side in the same field can generate greater total revenue than planting the equivalent number of acres in large, monoculture fields (Lesoing and Francis 1991, West and Griffith 1992). This approach, which is referred to as strip intercropping, may improve the efficiency of light reception for the taller crop (corn), though at the expense of shading the shorter soybean crop. Strip intercropping is viewed as an opportunity to increase total crop production primarily because of greater efficiency of sunlight capture. Recently, trials reporting the effects of strip intercropping on corn yields in industry publications (Winsor 2011) have sparked the imagination of many farmers and affiliated professionals in the North American field crop sector, leading to increased interest in the potential profitability of such a change in cultivation practices. However, these trials have not considered the full cost-side ramifications of altered cropping systems for modern, large-scale corn and soybean production systems nor have these studies explored sensitivity of results to crop prices. Both are crucial for understanding the relative appeal of this cropping system to commercial U.S. farmers.

A group of researchers within the College of Food, Agricultural and Environmental Sciences at The Ohio State University developed a systematic comparison of the relative net revenue differences for a large-scale (5,333 acre) corn-soybean operation under two separate cultivation systems: (1) traditional cultivation practices where each field involves monoculture cultivation of either corn or soybeans and (2) a strip intercropping system featuring narrow strips of corn and soybeans in each field.

Our analyses has shown that because the yield premiums for strip intercropped corn were relatively larger than the yield penalty for soybeans, the intercropping practice generated more gross revenue per unit land than the same crops grown in field-level monoculture. Projecting from yield effects in recent Illinois field trials, we discovered that the gross farm revenue improvements involved in implementing strip intercropping ranged from less than one percent to 12 percent. Narrower strips yielded substantially larger gross revenue relative to monoculture. Expansion to wider strip widths increasingly dilutes the higher-yield edges with wider center row segments, resulting in lower average yields and gross revenues. For example, in a year with normal rainfall and high prices, 4-row corn strips intercropped with a soybean strip of the same width yields an increase in gross revenue per acre of $134 (10%) over monoculture, while a 6-row corn strip intercropped with a soybean strip of the same width yields only a $83/acre improvement. In a dry year, the additional revenue from a 4-row corn strip drops to about $53/ac. Commodity price also is important, both in terms of absolute level and the relative level of prices for the crops in strips. A drop in commodity prices from $7/bu corn, $17.50/bu soybeans to $4/bu corn, $10/bu soybeans results in a decline in the 4-row strip advantage of $57/ac, assuming typical weather. Because corn yields increase while soybean yields decline over the strip cropped area, an increase (decrease) in the soybean/corn price ratio decreases (increases) the revenue advantage of strip intercropping.

Of course, revenue is only one side of the ledger when considering such a substantial change in cultivation practices. We explore differences in labor and machine costs for the 5333 acre corn/soybean operation to implement a 6 row intercropping system. All other costs, including seed, chemical and marketing costs, are assumed to be identical between the systems. More total hours spread across multiple implements are needed to complete field operations for strip intercropping. The total wage bill is nearly double for strip intercropping, as both field hours and hours spent in transition are considerably higher. Machinery ownership costs are 90% higher with strip intercropping as more, smaller implements and tractors are required to accomplish operations in a timely fashion. A key conclusion is that strip intercropping would lead to net revenue improvements over a conventional production system only for high base prices for crops and for normal moisture conditions with the most favorable result occurring when corn has the highest relative price, wages are lowest and fuel is most expensive. In this scenario, strip intercropping would return a modest $30 more per acre than the conventional operation. In other less favorable scenarios, increased costs of strip intercropping typically exceeded improvements in revenues.

These analyses do not consider the one-time costs of altering the machinery complement to allow the strip production system with narrow strips. Such transitional investment requirements might be a significant deterrent to farmer adoption of strip intercropping. On the other hand, our analyses also ignores possible yield boosts from decreased compaction resulting from the smaller equipment used in strip intercropping. Compaction related yield penalties are well documented, but their effect has not be isolated or the accumulated effect traced over time in current agronomic and pilot tests of strip intercropping yield comparisons. Further, additional work is needed to consider the potential profitability for smaller operations that currently possess smaller capacity equipment and may have the capability to expend additional time to plant, spray and harvest smaller strips without risking timeliness of each operational step. Also, we do not consider how row-specific management approaches within a strip intercropped system might affect yields or net revenues, where different planting populations and fertilizer levels for edge rows could spur further yield boosts for corn. Finally, all analyses here assume the prevailing machinery technology is employed for both monoculture and strip intercropping production systems. The advent of radical new technologies might greatly alter the cost calculus for farming small strips, allowing capture of yield advantages of very narrow strips without the much higher machine and labor costs calculated in this study.

Northeast Ohio Dairy Survey– cows coming or going in the future?

by David Marrison, Extension Educator

Milk and cheese production have been major agricultural businesses in northeast Ohio for many years. During the past decade, there has been great contraction in the number of dairy farms in the region. Looking to the future, there are many difficult issues facing continued and expanded milk production. These include generational transition, federal milk pricing, input costs, workforce, waste management, and state regulations.

In effort to understand better how these issues are playing out in northeast Ohio, a group of organizations worked together to develop a survey for dairy farms. These organizations included: OSU Extension, Geauga Growth Partnership, TeamNEO, Growth Partnership for Ashtabula County, Portage Development Board and the Youngstown-Warren Chamber of Commerce. The goal of the survey was to learn more about the concerns and attitudes of dairy farmers in Ashtabula, Geauga, Lake, Portage and Trumbull counties. It is a given that milk and feed prices are a concern of all dairy farms, so this survey attempted to look beyond the scope of these two issues.

Forty-three percent of the 189 dairy farms surveyed replied to questions about their plans, prospects and challenges. Some of the notable survey results included data that showed that over 78% of the local dairy farms plan to continue to operate during the next five years in spite of the many challenges facing dairy operations. Almost 35% percent plan on increasing their herd size during the next five years adding an additional 818 cows in the region.

The survey coalition was interested in learning more about what was limiting local dairy farms from expanding besides milk prices and input costs such as feed and fuel. The top three reasons cited include: land available to grow crops (60.8%), inadequate labor or unavailable labor (31.4%), and access to financing (29.4%).

Participants were asked about the facility improvements they plan on investing in over the next five years with the top three responses being: adding housing for heifers (55.0%), increasing cow comfort (51.7%), and improving their manure handling systems (35.0%). The top three management areas which improvement will be sought by managers over the next five years are: feed management (57.9%), genetic improvement (50.9%), and milking herd health management (45.6%).

Each farm was also asked to respond to general issues affecting their farm. Respondents were asked to rank the importance of related topics to dairy farms and then provide qualitative feedback on their greatest success in dairy farming, their greatest concern for the future of dairy farming in Northeast Ohio, and to provide advice on how to maintain or increase regional milk production. These responses can be found in the survey summary, which can be found at:

The results will be of great help to OSU Extension and our partners as we plan educational programs and implement strategic programs to enhance the northeast Ohio dairy industry in Ashtabula, Geauga, Portage, Lake, and Trumbull Counties.

AEDE Research Update – Recent Papers Presented

One of the most highly anticipated events for AEDE’s faculty and students took place from August 4-6, 2013 in Washington D.C.: the annual meeting of the Agricultural and Applied Economics Association (AAEA). AAEA is the premier professional organization for agricultural and applied economists working in the U.S.

This year’s gathering brought together the country’s top agricultural and resource economists and facilitated networking between AEDE’s faculty and students and their peers working in the academic, public and private sectors. This year’s meeting featured over 150 educational sessions, 200 posters on display, and multiple plenary sessions each day.

As one of the preeminent academic departments working in the field of agricultural and resource economics, AEDE will have a very strong presence at the gathering with more than two dozen faculty and students in attendance. AEDE faculty and graduate students will present their research at a number of the meeting’s events. A list with links to the papers is listed below. All authors are affiliated with OSU’s AEDE unless otherwise noted.

“Cropland Productivity, Carbon Sequestration, and Commodity Prices” by Suk-Won Choi, Sara B. Ohrel from the U.S. Environmental Protection Agency, and Dr. Brent Sohngen.

“Structural Change in US Consumer Response to Food Safety Recalls” by Mykel R. Taylor from Kansas State University, Dr. H. Allen Klaiber, and Fred Kuchler from the USDA-Economic Research Service
“Whither Dairy Policy? Evaluating Expected Government Outlays and Distributional Impacts of Alternative 2013 Farm Bill Dairy Title Proposals” by John C. Newton, Marin Bozic from the University of Minnesota, Dr. Cameron S. Thraen, Brian W. Gould from the University of Wisconsin, and Mark W. Stephenson from Cornell University.

“The Implications of Environmental Policy on Nutrient Outputs in Agricultural Watersheds” by Dr. Brent Sohngen, Kevin King from the USDA-Agricultural Research Service, Sei Jin Kim, and Dr. Abdoul G. Sam.

“From Farmer Management Decisions to Watershed Environmental Quality: A Spatial Economic Model of Land Management Choices.” by Wendong Zhang and Dr. Elena G. Irwin .

“A Latent Class Analysis of Farmer Preferences Regarding Filter Strip Programs” by Gregory E. Howard (East Carolina University) and Dr. Brian E. Roe.

“The Role of Credit and Savings in the Dynamics of Technology Decisions and Poverty Traps” by Isaí Guízar-Mateos, Dr. Mario J. Miranda, and Dr. Claudio Gonzalez-Vega will be presented at a session on issues in development economics.

“A Meta-Analysis and Repeat Sales Approach to Decomposing Local Park Attributes” by Dr. H. Allen Klaiber and Mitchell Livy will be presented at a session on demand for recreation and ecosystem amenities.

“The Role of Calorie Content, Healthiness, Price, and Palatability on School Lunch Purchases” by Matthew V. Pham and Dr. Brian E. Roe will be presented at a session on the role of school lunches in childhood nutrition. Pham will also serve as the moderator for this session.

“Modeling a Dynamic Forest Sector in a General Equilibrium Framework” by Xiaohui Tian, Dr. Brent Sohngen and D. Sands from the USDA-Economic Research Service, will be presented at a session on forest economics. Tian will also serve as the moderator for this session.

“The Wage Premium and Market Structure: The Case of South Korea and Taiwan” by Meng-Fen Yen and Dr. Mario J. Mirandawill be presented at a session on contracting and market structure in developing countries. Also at this session, “The Global Food Price Crisis and China-World Rice Market Integration: A Spatial-Temporal Rational Expectations Equilibrium Model” by Randall Romero-Aguilar, Shu-Ling Chen from National Taipei University, Xianglin Liu, and Dr. Mario J. Miranda will be presented.

“Credit Constraints, Technology Choice and Exports – A Firm Level Study for Latin American Countries” by Syed Hasan will be presented at a session on non-tariff constraints to international trade.

“Premium Benefits? A Heterogeneous Agent Model of Credit-Linked Index Insurance and Farm Technology Adoption” by Katie Farrin and Dr. Mario J. Miranda.

• “Semiparametric Estimation of Binary Response Models With a Parametric Guide: An Application to Agricultural Technology Adoption in Uganda” by Dr. Abdoul G. Sam, Gracious M. Diiro, and Alan P. Ker from the University of Guelph.

“Evading Invasives: How Water-Milfoil Impacts New Lakefront Development” by James Goodenberger and Dr. H. Allen Klaiber.

• “The Role of Tablets in Modernizing the Classroom Experience” by Dr. Steven S. Vickner will be presented at a session on the utility of tablets and technology in teaching agribusiness courses. With Charles Robert Stark, Jr. from the University of Arkansas at Monticello, Dr. Vickner is also serving as an organizer for this session.

• Additionally, several students from the undergraduate chapter of Ohio State’s AAEA student group will attend the gathering. Dr. Steven S. Vickner serves as the supervisor for this team of students. Ohio State will also host a reunion reception at the 2013 meeting.