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PurposeThis paper quantifies the effects of recent Federal Reserve interest rate changes, specifically recent hikes and cuts in the federal funds rate since 2015, on Midwest farmland values.Design/methodology/approachThe authors apply three autoregressive distributed lag (ARDL) models to a panel data of state-level farmland values from 1963 to 2018 to estimate the dynamic effects of interest rate changes on the US farmland market. We focus on the I-states, Lakes states and Great Plains states. The models in the study capture both short-term and long-term impacts of policy changes on land values.FindingsThe authors find that changes in the federal funds rate have long-lasting impacts on farmland values, as it takes at least a decade for the full effects of an interest rate change to be capitalized in farmland values. The results show that the three recent federal funds rate cuts in 2019 were not sufficient to offset the downward pressures from the 2015–2018 interest rate hikes, but the 2020 cut is. The combined effect of the Federal Reserve's recent interest rate moves on farmland values will be positive for some time starting in 2022.Originality/valueThis paper provides the first empirical quantification of the immediate and long-run impacts of recent Federal Reserve interest rate moves on farmland values. The authors demonstrate the long-lasting repercussions of Federal Reserve's policy choices in the farmland market.

The novel coronavirus SARS‐CoV2 (COVID‐19) severely disrupted the U.S. food supply chain. In its initial aftermath, and as we contemplate a potential reignition, the food supply chain industries, researchers, and policy makers search for evidence, causes, and consequences. This article uses publicly available data on the pork and egg industries and a survey of the turkey industry as a first step to document the impact of COVID‐19. Researchers can learn from the experiences in industries where disruptions evolve differently in the face of simultaneous supply‐ and demand‐side shocks and that stem from differences in structures of the supply chains. This early evidence is used to motivate future research needs and highlight opportunities for industry investments in resiliency strategies.

The pathways between climate information producers and agricultural decision-makers are evolving and becoming more complex, with information increasingly flowing through both public and for-profit intermediaries and organizations. This study characterizes the various channels of climate information flow, as well as the needs and preferences of information intermediaries and end users. We use data from a 2016 survey of farmers and agricultural advisors in 12 U.S. Corn Belt states to evaluate perceptions of climate information and its usability. Our findings reinforce the view that much weather and climate information is not reaching farmers explicitly but also suggest that farmers may not be aware of the extent to which the information is packaged with seed, input, or management recommendations. For farmers who are using weather and climate information, private services such as subscription and free tools and applications (apps) are as influential as publicly provided services. On the other hand, we find that agricultural advisors are engaged users and transformers of both public and private sources of weather/climate information and that they choose sources of information based on qualities of salience and credibility. Our results suggest that climate information providers could improve the use of information in agriculture by engaging advisors and farmers as key stakeholders and by strategically employing multiple delivery pathways through the private and public sectors.

This study analyzes forecasts of U.S. ending stocks for corn, soybeans, and wheat issued by the USDA. The proposed efficiency tests focus on forecast revisions. Forecast errors are decomposed into monthly unforecastable shocks and idiosyncratic residuals. The error covariance matrix allows for heteroscedasticity and auto-correlations. Results suggest that the USDA forecasts are inefficient, providing strong evidence that the USDA is conservative in forecasting the ending stocks. Unforecastable shocks are heteroscedastic, and idiosyncratic residuals are small. Results are consistent across the three decades analyzed, but soybean forecasts are found to be considerably worse from 2005 to 2015.

To test if fungicide applied to hail-injured corn improves yield and reduces disease, we simulated hail at VT and R2 growth stages for three years at three Iowa locations for a total of five site years. Hail damage was simulated using a string trimmer or an ice-propelling machine and non-hail controls were included. Estimated defoliation ranged from 5 to 51%, along with ear and stalk injury. After hail events, Headline AMP fungicide (pyraclostrobin + metconazole) was applied at an “immediate” or “deferred” timing (averaging 3 and 8 days afterwards, respectively). A non-fungicide treated control was included in hailed and non-hail control plots. Hail injury reduced fungal foliar disease compared to plants without hail injury, although overall disease severity was low during this study. Hail events at VT or R2 decreased yield compared to control plots (P = 0.1). Fungicide application did not provide yield-increasing plant health benefits after VT and R2 hail, at either “immediate” or “deferred” timing. While yield differences were not statistically significant, a cost/benefit analysis showed deferred fungicide application after VT hail, and immediate and deferred applications after VT for non-hail plots did provide positive economic returns. Results will help inform decisions about fungicide use in hail-damaged corn when foliar diseases are not present at high levels. Accepted for publication 7 January 2016. Published 13 January 2016.

A fungicide (pyraclostrobin) and an insecticide (alpha-cypermethrin) were applied alone or in combination to hail-injured soybean to determine if yield could be preserved or foliar disease prevented. Pesticides were applied at approximately R3 growth stage and hail injury was simulated with an ice-propelling machine at approximately R1 and R4 growth stages over three years at three Iowa locations. Disease severity was low throughout the study, and included Septoria brown spot, downy mildew, and Cercospora leaf blight. Differences in disease severity among treatments receiving hail and those that did not receive hail were not consistently detected. More importantly, foliar disease severity did not differ among pesticide treatments and untreated controls. Simulated hail caused significant (P = 0.1) yield loss. No difference in yield was observed between untreated and pesticide-treated plots within hail events, except for two site years when hail damage occurred at R1. Seed moisture was generally higher in plots with R1 hail damage. Fungicide and insecticide applied in combination to hail-damaged soybean was more likely to result in a positive economic return than either applied alone. Based on results, R3 fungicide application to soybean injured by hail at R1 or R4 will likely provide little yield-preserving or disease-limiting benefits when foliar disease severity is low. Accepted for publication 21 April 2016. Published 20 June 2016.

Using two different approaches, the relationship between a firm's investment and its financial variables is examined. Imperfections in the credit market such as asymmetric information have led researchers to explore these relationships. This study incorporates the 5 Cs of lending (character, capacity, collateral, credit rating, and capital) into the farmer's investment decision and explores the impacts of these variables on a basic data set. The data set is composed of 590 Iowa farms that are members of the Iowa Farm Business Association and have reported farm level financial and production data from 1991 to 1995;The first approach consists of a composite regression model constructed from various elements of traditional investment models and variables representing the 5 Cs. The second approach derives an investment equation from the firm's optimization problem, an Euler equation approach. The 5 Cs of lending are incorporated into the problem through a borrowing constraint;The composite regression approach is conducted under a Bayesian framework with variable selection and outlier detection components. The results imply strong support for the accelerator model of investment and the inclusion of other relevant variables, among them the value of short-term assets, one of the proxies for the 5 Cs. Another of the proxies, operator age, receives less support. The Bayesian framework with the variable selection and outlier detection components works extremely well;The Euler equation approach is more problematic. Under the original specification looking at net investment, all models are rejected and the most preferred model is also the most restrictive with symmetric adjustment costs and no financial constraint. Within the financial constraint, only the value of short-term assets and net worth are ever found to be statistically significant. Estimated adjustment costs are either negative or positive but extremely small. The shadow value of external finance is estimated to be around 100 percent. Other formulations, extensions, and reduced form models are explored and similar results are found. Given the mostly negative results from the Euler equation framework possible reasons for them are reviewed.

In the Midwestern United States, where a third of the world's maize crop is grown, there are few decision support tools available to help farmers and their advisors plan for an uncertain climatic future. Developing tools that are actually useful and usable to agricultural decision makers necessitates an interdisciplinary team of climate scientists, agronomists, computer scientists, and social scientists. With such diversity come varying levels of engagement (e.g. co-project director, student, technician, etc.) and experience working with farmers and/or serving in an official Extension capacity. Therefore working together to address this challenging issue is not straight-forward. This paper reviews how a survey of a large interdisciplinary team working on developing decision support tools to ensure resilient maize production in this region identified differences between team members and helped improve team functioning and communication. Specifically the team survey revealed some important differences in how team members perceive farmers' use of climate information, the types of decisions that should be addressed with a tool, and how such tools should function. These differences can be primarily explained by disciplinary background and project role and have provided valuable opportunities to learn from each other and build consensus on decision support tools developed. The survey as a feed-back tool complements other team communication approaches and reminds the team of the need for continuous communication and frequent discussion of assumptions.

Options on agricultural commodities with maturities exceeding one year seldom trade. One possible reason to explain this lack of trading is that we do not have an accurate option pricing model for products where mean reversion in spot-price levels can be expected. Standard option pricing models assume proportionality between price variance and time to maturity. This proportionality is not a valid assumption for commodities whose supply response brings prices back to production costs. The model proposed here incorporates mean reversion in spot-price levels and includes a correction for seasonality. Mean reversion and seasonality are both observed in the soybean market. The empirical analysis lends strong support to the model.

The U.S. Cooperative Extension Service was created 100 years ago to serve as a boundary or interface organization between science generated at the nations land grant universities and rural communities. Production agriculture in the US is becoming increasingly complex and challenging in the face of a rapidly changing climate and the need to balance growing crop productivity with environmental protection. Simultaneously, extension budgets are diminishing and extension personnel are stretched thin with numerous, diverse stake- holders and decreasing budgets. Evidence from surveys of farmers suggests that they are more likely to go to private retailers and consultants for information than extension. This paper explores the role that extension can play in facilitating climate change adaptation in agriculture using data from a survey of agricultural advisors in Indiana, Iowa, Michigan and Nebraska and

Since the crop’s humble beginnings in China, the global soybean industry has grown to be a multi-billion dollar enterprise. Since World War II, the USA has been the dominant market for both production and consumption. For the 2015 growing season, US farmers planted over 80 million acres and produced nearly 4 billion bushels of soybeans. With market prices averaging $10 per bushel, that translates to $40 billion in raw production value each harvest. However, the soybean plant was not always one of the dominant crops in the US agricultural landscape. Large-scale soybean production in the USA is a relatively recent phenomenon. Roughly 55% of the world’s soybean crop is directed to feed use currently. Over the course of the past 20 years, another use for soybeans has emerged in the energy sector, biofuel, specifically biodiesel production. Soybean production costs have changed dramatically over the past 20 years. In general, crop production costs can be broken down into four major categories: machinery, land, labor, and crop inputs (seed, chemicals, and fertilizer). Land costs make up nearly half of the total cost of soybean production. Soybean, like many row crops, is a bulk commodity. This means that soybeans produced by one farmer/practice/variety are not differentially marketed or priced from soybeans produced by others (with some rare exceptions for food-grade non-genetically modified varieties or organic practices). Or to put it another way, a soybean is a soybean no matter who produces it or how it is produced. So soybean producers are transacting in a competitive market, where producers can enter and exit the market fairly easily and there is very little room for differentiation. But there is a similar situation for the entities that purchase soybeans as well. So the soybean market is made up of many sellers (producers) and buyers (country elevators, crushing facilities, river terminals, and exporters). In competitive markets like this, prices are generally equal to production costs. If prices exceed costs, the resulting profits will inspire additional production from existing and new producers, leading to larger supplies and lower prices. If costs exceed prices, the resulting losses will drive some producers out of the business, leading to supply reduction and price improvement.

E normous challenges were presented by the 2012 drought. Poor water availability and high temperatures resulted in significant stress during critical phases of corn ( Zea mays L.) and soybean ( Glycine max L.) development. These stress factors lead to management challenges with insects, diseases, and reduced nutrient availability and uptake by plants. The drought triggered soil changes, particularly in conventional tillage systems, such as increased fracturing, crusting, and deterioration of soil structure and aggregation. All this reinforced the need for soil conservation planning, especially its necessary role in buffering against unpredictable conditions and the impacts of dry and wet events on production and soil quality. In 2011, the USDA's National Drought Mitigation Center reported that 43% of Iowa experienced moderate-drought conditions and nearly 10% experienced severe-drought conditions. In 2012, 100% of Iowa experienced severe-drought conditions, while 65% experienced extreme-drought conditions by October. This article addresses several effects of drought on soil and crop production and lessons learned that will help develop appropriate drought mitigation strategies for future soil and crop management practices. The 2012 drought created unfavorable soil conditions for plant development and growth and changes in soil structure in many areas in the Midwest. These changes in soil structure included fracturing…

Futures markets on agricultural commodities typically trade with maximum maturity dates of less than four years. If these markets did trade with maturities eight or ten years distant, futures prices would have value as price forecasts and as a way to structure long-term swaps and insurance contracts. Agricultural commodity markets generally exhibit mean reversion in spot prices and convenience yields. Spot markets also exhibit seasonality. This study develops and implements a procedure to generate long-term futures curves from existing futures prices. Data on lean hogs and soybeans are used to show that the method provides plausible results. Copyright 2012, Oxford University Press.

Emphasis on reducing emissions from the greenhouse gases (GHG), carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) has increased in recent years in the USA, primarily for industry, transportation, energy and agricultural sectors. In this study, we utilized on-farm data collected by the USDA-National Agricultural Statistics Service (NASS) Agricultural Resource Management Survey (ARMS), secured under an agreement with the USDA-Economic Research Service (ERS) to analyze the profitability of organic and conventional soybean production, based on changes that ‘green payments’ in a cap-and-trade system would introduce in agricultural markets in the USA. In particular, the analysis focused on establishing whether organic producers would be better positioned to sequester carbon (C) and reap the benefits of the C-offset scheme compared to conventional producers, given the differences in costs, management practices and environmental benefits between organic and conventional production methods. We estimated several changes in profitability of soybean producers according to management practices, incentives for the generation of offset credits, and increase in energy input prices that a potential cap-and-trade system may introduce in future agricultural markets in the USA. Survey data suggested that even with lower yields, conventional producers could profit from converting to organic agriculture, given organic price premiums. In addition, taking into consideration both direct and indirect costs, average cost for conventional-till (CT) organic soybean production was approximately 9% lower than no-till (NT) conventional production. With a C market and payments for soil C sequestration through potential Clean Energy legislation, additional profit could be accrued by organic producers, because organic production would have 28% greater ton CO2 eq. acre−1 yr−1 sequestration than conventional NT. Thus, the environmental benefits from GHG reduction could incentivize increased conversion from conventional to organic production across the USA.

This study looks at the land use impact of the biofuels expansion on both the intensive and extensive margin, and its environmental consequences. We link economic, geographical and environmental models by using spatially explicit common units of analysis and use remote sensing crop cover maps and digitized soils data as inputs. Land use changes are predicted via economic analysis of crop rotation choice and tillage under alternative crop prices, and the Environmental Policy Integrated Climate (EPIC) model is used to predict corresponding environmental impacts. The study focuses on Iowa, which is the leading biofuels hotspot in the U.S. due to intensive corn production and the high concentration of ethanol plants that comprise 28% of total U.S. production. We consider the impact of the biofuels industry both on current cropland and on land in the Conservation Reserve Program (CRP), a land set-aside program. We find that substantial shifts in rotations favoring continuous corn rotations are likely if high corn prices are sustained. This is consistent with larger scale analyses which show a shift of the current soybean production out of the Corn Belt. We find that sediment losses increase substantially on the intensive margin, while nitrogen losses increase less. Returning CRP land into production has a vastly disproportionate environmental impact, as non-cropped land shows much higher negative marginal environmental effects when brought back to row crop production. This illustrates the importance of differentiating between the intensive and extensive margin when assessing the expansion of biofuel production.

PurposeWhile the demand for weather‐based agricultural insurance in developed regions is limited, there exists significant potential for the use of weather indexes in developing areas. The purpose of this paper is to address the issue of historical data availability in designing actuarially sound weather‐based instruments.Design/methodology/approachA Bayesian rainfall model utilizing spatial kriging and Markov chain Monte Carlo techniques is proposed to estimate rainfall histories from observed historical data. An example drought insurance policy is presented where the fair rates are calculated using Monte Carlo methods and a historical analysis is carried out to assess potential policy performance.FindingsThe applicability of the estimation method is validated using a rich data set from Iowa. Results from the historical analysis indicate that the systemic nature of weather risk can vary greatly over time, even in the relatively homogenous region of Iowa.Originality/valueThe paper shows that while the kriging method may be more complex than competing models, it also provides a richer set of results. Furthermore, while the application is specific to forage production in Iowa, the rainfall model could be generalized to other regions by incorporating additional climatic factors.

I. INTRODUCTION The U.S. sugar program guarantees sugar producers a minimum price for their sugar through a combination of import quotas and restrictions on domestic marketing. The minimum price is called the loan rate because sugar producers can use sugar as collateral for a loan from the Commodity Credit Corporation, a federal corporation in the U.S. Department of Agriculture (USDA). The amount of the loan equals the loan rate multiplied by the quantity of sugar put up as collateral. The loan is a non-recourse loan because the USDA has no recourse to collect payment other than to take ownership of the collateral sugar, which is either refined or raw sugar. If domestic production plus imports exceed domestic consumption at the loan rate, then surplus sugar may be absorbed by the USDA through purchasing at the open market. Otherwise, the sugar price will fall below the loan rate and sugar will flow to the USDA through forfeiture of collateral sugar. Whichever way the USDA accumulates surplus sugar, it will incur program costs to acquire and store surplus sugar. In recent history, the USDA had to acquire and then subsequently dispose of surplus sugar on several occasions. Specifically, in 2000, it entered the sugar market for the first time since 1986 to purchase sugar in an attempt to maintain sugar prices. It also accumulated sugar through loan forfeitures. However, the USDA managed to clear its sugar inventories the following years and succeeded in operating the sugar program at no net cost to taxpayers for the period covered by the last farm bill (2002-2007). Most of the sugar in the USDA inventory was either released through the payment-in-kind (PIK) program or sold to storing warehouse operators. Under the PIK program, sugar producers could reduce their sugar production in return for payment, which was in the form of sugar in government inventory. Because the USDA is required to operate the sugar program at no taxpayer cost, it tries to avoid acquiring sugar. Cuts in future marketing allotments or import quotas have been used to manage domestic sugar supply to support prices at the loan rates. But the ability to restrict imports is becoming more difficult due to trade liberalization agreements that came into effect recently or will become effective in the near future. Notably, beginning in January 2008, Mexico is allowed to export sugar to the United States without restriction. Mexico has the potential to produce exportable sugar, so many feel that the ability to support U.S. sugar prices above world price levels is in jeopardy. (1) In response to these fears Congress created the Feedstock Flexibility Program in the Food, Conservation, and Energy Act (the 2008 farm bill). This program, more commonly known as the sugar-to-ethanol program, is designed to divert surplus sugar from food markets into fuel markets by having the USDA sell its sugar to ethanol producers through competitive procedures. In addition to this program, the farm bill authorizes the USDA to sell surplus sugar to sugar producers who agree to reduce their production by the amount of sale. (2) However, the law does not require the USDA to exercise this authority. The extent to which the domestic sugar industry can be protected from increased import competition depends on the price that the USDA will receive for its surplus sugar and the target of a sugar program operating at no net cost to taxpayers. If the willingness to pay (WTP) for sugar is significantly less than the loan rate, then either taxpayers will have to cover the difference or the U.S. sugar program will have to be modified. The lawmakers who championed the sugar-to-ethanol program insisted that it would reduce the nation's dependence on foreign oil and help protect against imported sugar. The skeptics, including the previous Bush administration, claimed that only at a huge loss could the surplus sugar be sold to ethanol facilities. The objective of this paper is to provide insight into the WTP for surplus sugar by sugar and ethanol producers, that is, the maximum price that these producers are willing to bid for surplus sugar. …

We project U.S. ethanol production and its impact on planted acreage, crop prices, livestock production, trade, and retail food costs. The projections are made using a multicommodity, multicountry, partial equilibrium model. Results indicate that expanded U.S. ethanol production will cause long-run crop prices to increase. In response to higher feed costs, livestock farmgate prices increase enough to cover the feed cost increases. If crude oil prices increase, the U.S. ethanol sector expands. Results of a 1988-type drought scenario combined with a large mandate for ethanol consumption show higher crop prices, a drop in livestock production, and higher food prices. Copyright 2008, Oxford University Press.

The vast majority of crop and revenue insurance policies sold in North America are single-crop policies that insure against low yields or low revenues for each crop grown on a particular farm. This practice of insuring one crop at a time runs counter to the traditional risk management practice of diversifying across several enterprises to avoid putting all of one's eggs in a single basket. This paper examines the construction of a whole-farm crop revenue insurance program to include livestock price risk. The results show that at coverage levels of 95% or lower, the fair insurance premiums for this product on a well-diversified Iowa farm are far lower than the fair premiums for the corn crop alone on the same farm. The calculation of premium rates for the whole-farm insurance product is derived from a method for imposing correlations first proposed by Iman and Conover in 1982. The potential income transfer from crop insurance is also examined. We find that the income transfer due to the subsidization of single-commodity policies is greater than the total premium for whole-farm policies. La grande majorite de polices d'assurances de recolte et de revenu agricole vendues en Amerique du nord sont des polices de recolte individuelle qui assurent contre des rendements faibles ou bas revenu pour chaque recolte cultivee par une ferme particuliere. Cette pratique de n'assurer une recolte a la fois fonctionne a l'oppose de la pratique traditionnelle de gestion des risques par la diversification a travers plusieurs entreprises pour eviter de mettre tous ses oeufs dans un seul panier. Cet article examine la construction d'un programme d'assurance agricole pour l'ensemble des recoltes produites par une ferme y compris le betail evalue le risque. Les resultats montrent qu'aux niveaux d'assurance plus petits ou egaux a 95 pourcents, les primes d'assurance justes pour ce type de police pour une ferme bien diversifiee de l'Iowa sont bien inferieures aux primes justes pour une police de simple couvrant le mais et ce pour la meme ferme. Le calcul des taux de prime pour une police couvrant l'ensemble des recoltes est derive d'une methode pour imposer des correlations originalement proposee par Iman et Conover en 1982. Le transfert potentiel de revenu a partir de l'assurance de recolte agricole est egalement examine. Nous trouvons que le transfert de revenu dua la subvention des polices pour recolte singuliere est plus grand que la prime entiere pour une police couvrant l'ensemble des recoltes.

Increased availability and demand for low-deductible crop insurance policies have increased focus on crop insurance rating methods. Actuarial fairness cannot be achieved if constant multiplicative factors are used to determine how premiums change as coverage levels increase. A comparison of premium rates generated by the factors used by the two most popular crop insurance products with those generated by a standard yield distribution shows that the popular insurance products overcharge for low-deductible policies in most counties. This overpricing may explain why large premium subsidies were required to induce farmers to move from low-deductible to high-deductible policies beginning in 2001. Crop insurance is by far the most popular risk management tool used by the U.S. crop producers. In 2003, the U.S. crop insurance program insured more than 200 million acres, representing more than $37 billion in value, with total premium of over $3.14 billion. The two most popular crop insurance products are Actual Production History (APH), which provides insurance against low yields, and Crop Revenue Coverage (CRC), which is a revenue insurance product. Both of these products offer coverage in 5% increments from 65% to 85% of expected yield or revenue. Beginning with the 2001 crop year, Congress greatly increased subsidy levels to induce producers to purchase more insurance coverage. Producers responded as expected. For example, only 2.3% of Kansas wheat was insured at levels in excess of 65% in 1998. This proportion rose to 71.6% in 2003. This policy change has increased focus on the methods used by the Risk Management Agency (RMA) of USDA to set insurance rates at higher coverage levels. APH premium rates are calculated by multiplying the premium rate at the 75% coverage level by a rate

This study contributes to the q-based empirical investment literature by using a Bayesian approach to analyze the impact of internal financial variables on a q-based investment model, accounting specifically for variable selection and incorporating outliers explicitly within the advocated modeling framework. For the balanced panel analyzed, a farm's liquidity situation is found to affect its investment significantly. Incorporation of an outlier detection component changes the results drastically, in both the variables chosen and the parameter estimates. The results and the nature of most investment data suggest that not accounting for outliers may lead to inaccurate inference.

In contrast with previous index model land applications, this article shows that the land allocation problem is a portfolio model with two constraints, namely, investable funds and land. The two-constraint model implies a drastic reinterpretation of what previous studies have quantified as diversifiable and systematic risks in agricultural production. The article also argues that the constant marginal-rate-of-product-substitution (MRPS) technology implicit in financial portfolio models is unlikely to hold in a production context such as the land allocation problem, and that the index model must be modified accordingly. Farm-level data are used to illustrate and test the hypotheses advanced. Empirical results indicate that most of the risk for corn and soybeans is diversifiable, and that corn and soybeans are characterized by decreasing MRPS. The MRPS effect is found to be large from an economic standpoint and implies that crop diversification may be optimal, even for risk-neutral farmers. Le modele a index est une approximation du modele de choix de portefeuille de type moyenne-variance. Contrairement aux precedentes applications de ce modele, il est demontre que le probleme d‘allocation de la terre est un modele de choix de portefeuille avec deux contraintes, soit la terre et les fonds disponibles a l'investissement. Ce modele a deux contraintes implique une reintepretation radicale des risques systematiques et diversifiables associes a la production agricole et mesures lors d'etudes passees. Il est aussi demontre que l'hypothese d'un taux marginal de substitution entre les produits (MRPS) constant, implicite dans les modeles de choix de portefeuille appliquea la finance, est peu plausible dans un contexte de production tel un probleme d'allocation de la terre. Aussi, le modele a index doit etre modifie. L‘utilisation de donnees du secteur agricole permet de tester les hypotheses avancees. Les resultats empiriques indiquent que la majorite des risques relies a la culture du mais et des grains de soja peuvent etre diversifies et que la culture du mais et des grains de soja est caracterisee par un MRPS decroissant. L'effet du MRPS est notable d'un point de vue economique et implique que la diversification d'une culture peut etre optimale pour des producteurs agricoles meme lorsque ceux-ci sont

A two-factor affine theoretical model is used to estimate the long-term futures curves for wheat in the European Union and the United States, as represented by the Euronext and CME markets, respectively. The CME futures curve exhibits a long-term equilibrium; in contrast, the Euronext futures curve does not show a tendency for futures to revert to a long-term equilibrium value. The estimated seasonality is relatively similar for both markets. However, the seasonal minimum and maximum points in the futures curve occur one to two months later for Euronext compared to the CME. More importantly, the futures curve for Euronext has a much more marked seasonality than the CME futures curve. Credible intervals of the futures curves are also estimated. The width clearly increases for longer maturities, but it does so much faster for Euronext than for the CME. For long-maturity futures, variability in the parameter estimates (as opposed to the residual errors) accounts for most of the width of the credible intervals, especially for Euronext. The proposed model can be used to price long-term futures options, long-term price insurance, and long-term swaps, among other applications. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 33:1118–1142, 2013

This study examines food-fuel trade-offs from the perspective of crop producers and their choices in marketing their grain among food, feed and fuel use. Based on a recent survey of Iowa grain producers, this study finds that price competition from ethanol plants has increased the share of the corn marketed directly to ethanol plants and lowered the market share of corn marketed for domestic and international food/feed purposes. Other factors, such as farm size and market distance, affect the share of corn directed to the fuel, food, and feed markets. The results indicate corn producers are willing to bear higher transportation costs to reach food markets over other market outlets.

Driven by the expanding production of biofuels, the linkage between the agricultural and energy markets is evolving, and that has changed the market for agricultural commodities dramatically. These developments in agricultural markets consequently shifted the distribution of domestic grains and feeds and the utilization of shipping modes for these agricultural products. As the leading producer of corn, soybeans, and biofuels, Iowa is at the forefront of this shift. Because of the importance of maintaining an adequate state transportation system to accommodate the evolving patterns of grain and biofuel flows, it is important to have current information about grain flows from farms and country elevators to destination markets, along with the information about transportation modes utilized for the shipments. Information about biofuel distribution is also crucial for agricultural and transportation policymakers so that they can provide relevant assistance for this growing industry. This study is designed to meet these needs and to provide updated information on grain and biofuel flows in Iowa during the 2006 and 2007 marketing years.

We examined four evolution paths of the biofuel sector using a partial equilibrium world agricultural sector model in CARD that includes the new RFS in the 2007 EISA, a two-way relationship between fossil energy and biofuel markets, and a new trend toward corn oil extraction in ethanol plants. At one extreme, one scenario eliminates all support to the biofuel sector when the energy price is low, while the other extreme assumes no distribution bottleneck in ethanol demand growth when the energy price is high. The third scenario considers a pure market force driving ethanol demand growth because of the high energy price, while the last is a policy-induced shock with removal of the biofuel tax credit when the energy price is high. Standard results hold where the biofuel sector expands with higher energy price, raising the prices of most agricultural commodities through demand side adjustment channels for primary feedstocks and supply side adjustment channels for substitute crops and livestock. On the other hand, the biofuel sector shrinks coupled with opposite impacts on agricultural commodities with the removal of all support including the tax credit. Also, we find that given distribution bottlenecks, cellulosic ethanol crowds marketing channels resulting in a corn-based ethanol price that is discounted. The blenders' credit and consumption mandates provide a price floor for ethanol and for corn. Finally, the tight linkage between the energy and agricultural sectors resulting from the expanding biofuel sector may raise the possibility of spillover effects of OPEC's market power on the agricultural sector.

This report is divided into two sections. The first part reports the statewide results for each of five surveyed groups: Iowa grain marketers, Iowa grain handlers, Iowa corn processors, Iowa soybean processors, and Iowa biodiesel producers. The state-level results provide a general idea of the grain and biofuel flows that occurred and the transportation that was utilized in the biofuel-boom era. In order to gain further insights into the regional level data, we present the survey results of grain marketers and handlers in each crop reporting district (CRD) in the second part of the report.

The vast majority of crop and revenue insurance policies sold in the United States are singlecrop policies that insure against low yields or revenues for each crop grown on the farm. But, increasingly, producer income is based more on the value of crops that have been converted into a value-added product such as ethanol. Moreover, the recent increases in energy and commodity price levels and volatilities emphasize the importance of risk management to ethanol investors. This paper uses an insurance approach to outline a risk management tool which mimics the gross margin level of a typical corn-based ethanol plant. The gross margin, premium, and indemnity levels are calculated on a per bushel basis to enable producers/investors to utilize the product based on their ownership share in the production facility. The fair premium rates are shown to be quite sensitive with respect to corn and energy price levels and volatilities.

Projections of U.S. ethanol production and its impacts on planted acreage, crop prices, livestock production and prices, trade, and retail food costs are presented under the assumption that current tax credits and trade policies are maintained. The projections were made using a multi-product, multi-country deterministic partial equilibrium model. The impacts of higher oil prices, a drought combined with an ethanol mandate, and removal of land from the Conservation Reserve Program (CRP) relative to baseline projections are also presented. The results indicate that expanded U.S. ethanol production will cause long-run crop prices to increase. In response to higher feed costs, livestock farmgate prices will increase enough to cover the feed cost increases. Retail meat, egg, and dairy prices will also increase. If oil prices are permanently $10-per-barrel higher than assumed in the baseline projections, U.S. ethanol will expand significantly. The magnitude of the expansion will depend on the future makeup of the U.S. automobile fleet. If sufficient demand for E-85 from flex-fuel vehicles is available, corn-based ethanol production is projected to increase to over 30 billion gallons per year with the higher oil prices. The direct effect of higher feed costs is that U.S. food prices would increase by a minimum of 1.1% over baseline levels. Results of a model of a 1988-type drought combined with a large mandate for continued ethanol production show sharply higher crop prices, a drop in livestock production, and higher food prices. Corn exports would drop significantly, and feed costs would rise. Wheat feed use would rise sharply. Taking additional land out of the CRP would lower crop prices in the short run. But because long-run corn prices are determined by ethanol prices and not by corn acreage, the long-run impacts on commodity prices and food prices of a smaller CRP are modest. Cellulosic ethanol from switchgrass and biodiesel from soybeans do not become economically viable in the Corn Belt under any of the scenarios. This is so because high energy costs that increase the prices of biodiesel and switchgrass ethanol also increase the price of corn-based ethanol. So long as producers can choose between soybeans for biodiesel, switchgrass for ethanol, and corn for ethanol, they will choose to grow corn. Cellulosic ethanol from corn stover does not enter into any scenario because of the high cost of collecting and transporting corn stover over the large distances required to supply a commercial-sized ethanol facility.

This paper examines the impact of ethanol expansion in the United States, brought about by higher crude oil prices, on agricultural commodity prices. Given the United States's stature as a major producer and exporter of many agricultural commodities, the resulting increase in commodity prices has spillover effects into the global market. Using the price changes estimated within a multi-commodity, multi-country agricultural modeling system, this paper attempts to show how an increase in world commodity prices would affect the costs of food baskets around the world and how higher food costs will impact food security, particularly in developing countries. In general, we find that countries where corn is the major food grain experience larger increases in food basket cost while countries where rice is the major food grain have smaller food basket cost increases. Countries where wheat and/or sorghum are the major food grains fall in between. Consequently, the highest percentage increases are seen in Sub-Saharan Africa and Latin America where food basket costs are estimated to increase by at least 10%. The lowest percentage increases are seen in Southeast Asia, with cost increases of less than 2.5%.