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
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 http://www.ers.usda.gov/data-products/feed-grains-database.aspx). 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 http://www.fas.usda.gov/psdonline/psdDownload.aspx while U.S. harvested yields are from http://quickstats.nass.usda.gov/. 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 http://quickstats.nass.usda.gov/. Crude oil prices are from the U.S. Energy Information Agency, available at http://www.eia.gov/petroleum/data.cfm#summary.
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 http://www.extension.iastate.edu/agdm/articles/hof/HofJan08.html; 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 http://aede.osu.edu/publications.
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 http://www.ag.senate.gov/issues/farm-bill while the House farm bill is available at http://docs.house.gov/billsthisweek/20130708/BILLS-113hr-PIH-FAARM-Act.xml.
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.
This publication is also available at http://aede.osu.edu/publications
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.
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: http://go.osu.edu/NEOHdairysurvey
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.
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.
• “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.
by David Marrison, OSU Extension Educator
There is a growing trend in Ohio Agriculture toward the direct marketing of agricultural products featuring locally grown food products. Consumers are becoming more and more aware of the benefits of buying local and buying fresh. As the demand for local food products increases so does the interest in growing and producing a variety of agricultural products for these markets. Perhaps this is something that you have considered for your small acreage but do not know where to begin.
To help land owners decide what to grow or raise on their excess acreage, the Ohio State University Extension offices in Northeast Ohio are pleased to be conducting the Northeast Ohio Small Farmer College for new and aspiring farms. The college will be held on September 12 & 24 and October 3 & 10 from 6:00 to 9:00 p.m. On Saturday, October 12 we will visit two local farms to learn how they have gotten off to a successful start. This college is designed to help landowners increase their profits from their small acreage. This college is open to all new or aspiring farmers, new rural landowners, small farmers, and farm families looking for new ideas.
The small farmer college is split into 5 sessions designed to challenge participants to plan for success. The first session on Thursday, September 12 titled “Getting Started” will help participants build the foundation for their farm business. Some of the session topics will include: developing real-life expectations for your small farm, developing goals and objectives, developing an agricultural business plan, and tax and financial management secrets for small farms. This session will also introduce the local agencies which can help farmers as they start, grow or maintain their business. This class will be held at the Ashtabula County Extension office located at 39 Wall Street in Jefferson, Ohio.
The second session on Tuesday, September 24 titled “Enterprise Selection” will help participants decide what to raise/grow on their farm and how to develop realistic budgets for these enterprises. This session will be tailored-made based on the interests of the group. Learn more about vegetable, greenhouse, fruit, nursery and bio-fuel crops, as well as aquaculture, livestock, hay, traditional and alternative farm enterprises. Let your passions lead you to the right agricultural enterprise to raise or grow. This class will be held at the Ashtabula County Extension office located at 39 Wall Street in Jefferson, Ohio.
The third session on Thursday, October 3 will be a “Work Session” to help the participants get their documents in order. We will work on enterprise budgets, EIN numbers, farm name, mission statements, and farm goals. Each farm will begin building their farm business plan. This class will be held at the Geauga County Extension office located at 14269 Claridon-Troy Road in Burton, Ohio.
The fourth session on Thursday, October 10 titled “Marketing & Resources for Small Farms” will help participants build a marketing direction for their business. Learn how agricultural products are being marketed across northeast Ohio. This class will be held at the Geauga County Extension office located at 14269 Claridon-Troy Road in Burton, Ohio.
The fifth session titled “Learning from the School of Hard Knocks” will be held on Saturday, October 12 from 9:00 a.m. to 12:00 noon at two small farms in Northeast, Ohio. Participants will take tours of each farm to learn about raising, selecting, and marketing agricultural crops. The host farms will be selected based on the interests of the class.
Participants will receive a light meal at sessions 1 through 4; 15 hours of classroom and on-site instruction; resource notebook (1 per family); and connections to resources and people that will help your farm business grow. The registration fee for this college is $99 for the first registrant from each family and $50 for each family registrant thereafter. Call the Ashtabula County OSU Extension office at 440-576-9008 to make your reservations or to receive more information. Reservations are requested by Thursday, September 5, 2013. Space is limited to the first 35 registrants.
Chris Bruynis and Bruce Clevenger, Assistant Professors, OSU Extension
As the profit margins appear to be tightening again for the for grain producers with lower market prices, farmers and lenders are examining balance sheets to determine if there are any strategies that might improve a farm’s financial position. One of the areas that often appear to grow during times of significant cash inflows, similar to what grain farmers have experiences during the past few years, are intermediate assets. Intermediate farm assets have a useful life of more than one but less than 10 years. Examples of assets in this category include tools, vehicles, machinery, equipment and breeding livestock.
A value is placed on assets on the day the balance sheet, also called the net worth statement, is created. Assets can be valued either on a cost basis or market basis on the balance sheet. The market value is the most common approach and the method preferred by most lenders. The cost approach is a more sophisticated method but is useful for farmers and lender to distinguish between changes in net worth due to profits verses external economic forces that either grow or decline the market value of assets. Both methods may be used in the same statement showing two different estimates of net worth. This article will focus only on the market value method.
Some useful guidelines using the market approach to valuing assets include: using well-established markets to determine asset values; be realistic with price expectations (just because you paid $100,000 does not make it worth $100,000 when you want to sell it); don’t forget to subtract selling/marketing costs associated with the assets; and for depreciable assets, such as equipment, review their book value in your farm records to avoid overvaluing their market price.
Once intermediate assets have been accurately valued using the market value approach, farmers and bankers can benchmark these numbers to other farms of similar size. One source of data to use as a benchmark comes from the University of Minnesota FINBIN program. The table below is a comparison of 1,793 grain farms with the data being compiled from the years 2006 through 2008. The data is presented as a group as well as divided by farm size. This data is collected from Extension and farm management professionals working with farmers using the FINPACK software.
For this discussion, focus your attention in the table below to the total amount of intermediate assets in this data set and compare that to your intermediate farm assets. Another item to examine is the amount of intermediate liabilities compared to intermediate assets. This data set indicates that on the average for every $100,000 of intermediate assets, grain farmers have $23,000 dollar of intermediate debt with very little variation across farm size. From the table below; Average of All Farms: $620,461 intermediate assets and $138,491 intermediate liabilities; $138,491/6.20=$22,300 per $100,000 of intermediate assets.
How does your farm compare? Is your intermediate asset market valuation similar to your peers across the Midwest? Do you need to disinvest in intermediate assets, restructure debt, or change your operation in some other way? Contact your local OSU Extension Educator for assistance with these issues or to schedule a FINPACK analysis of your farm business.
Catharine Daniels, Attorney, OSUE Agricultural & Resource Law Program In Ohio, thanks to our cottage food law, there are certain types of low risk food products you may produce and sell right out of your home kitchen with no inspection or … Continue reading
Peggy Hall, Asst. Professor, OSU Extension Agricultural & Resource Law Program . Tree obstructions, unwanted vegetation and noxious weeds are serious matters for Ohio farmers, which is why several Ohio laws provide mechanisms for addressing these problems through the board … Continue reading