Agricultural Outlook (2000) Managing Farm Risk Issues and Strategies

8/3/2019 Agricultural Outlook (2000) Managing Farm Risk Issues and Strategies

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Risk is an unavoidable element in the businessof agriculture. Production can vary widelyfrom year to year due to unforeseen weather and

market conditions, causing wide swings in com-

modity prices. But risk, while inevitable, is often

manageable.

Risk management involves choosing among alterna-

tives for reducing risks that threaten the economic

success of a farm business. The array of risk manage-

ment strategies available to farm operators includes

crop diversification, controlling cash flow, production

contracting, forward pricing, and acquiring crop and

revenue insurance.

For eligible producers of major field crops, income

support provided in the 1996 Farm Act supplements

the arsenal of risk management strategies, primarily

by providing fixed annual contract payments that

decline over the period 1996-2002, as well as loan

deficiency payments when crop prices drop below

certain levels. Recently, depressed global commodity

prices have pressured farm income as contract pay-

ments declined. In response, Federal emergency

assistance packages were enacted that included

market loss and crop disaster payments, and cropinsurance premium discounts.

In addition, Congress continues to examine legisla-

tive alternatives to address the issues of commodity

yield and price swings and income support for farm

households. Against the backdrop of concern among

policy makers, USDAs Economic Research Service

has examined the nature of farm business risk and

explored the effectiveness of various risk manage-

ment strategies. Throughout 1999,Agricultural

Outlookpublished articles reporting on this work.

Reprinted here, the articles address the following

questions:

Do management/financial strategies used by farm-ers vary by type and size of farm?

How do prices of agricultural commodities vary

seasonally and from year to year?

How effective for risk reduction are combinations

of crop and revenue insurance products and for-

ward pricing strategies?

What recent steps has government taken to broad-

en the array of crop and revenue insurance

options for farmers? What are the costs to the

government?

Reprint/February 2000

Managing Farm Risk: Issues and Strategies

How do factors such as insurance price and farmers risk type affect deci-

sions on purchasing insurance?

Would tax-deferred savings accounts be effective tools in managing risk?

The answers to such questions will likely be useful to policymakers, educa-

tors, producers, and others who monitor risk management developments and

strategies.

Robert Dismukes (202) 694-5294 and Joy Harwood (202) 694-5310

[email protected]

[email protected]

1 Farmers Sharpen Tools to Confront Business Risks

March 1999

6 More Farmers Contracting to Manage Risk

January/February 1999

8 Assessing Agricultural Commodity Price Variability

October 1999

14 Insurance & Hedging: Two Ingredients for a RiskManagement Recipe

April 1999

21 Recent Developments in Crop Yield & Revenue Insurance

May 1999

27 Demand for Yield & Revenue Insurance: Factoring In Risk,Income, & Cost

December 1999

30 Crop & Revenue Insurance: Bargain Rates but Still a Hard Sell

August 1999

34 Tax-Deferred Savings Accounts for Farmers: A PotentialRisk Management Tool

May 1999

Agricultural Outlookis published monthly (except February and July) by the EconomicResearch Service, U.S.Department of Agriculture. Materials may be reprinted without permission. Latest and back issues available at www.econ.ag.gov/epubs/pdf/agout/ao.htm

Editorial staff: Dennis A. Shields, Judith E.Sommer, Mary Reardon,Cynthia Ray

Subscriptions: $65 per year ($130 to foreign addresses, including Canada). Call 1-800-999-6779 or 1-703-605-6220. For free e-mail subscriptions (text only): Go to the ERS website atwww.econ.ag.gov; click on Periodicals, then E-mail subscriptions.


2/37

As in any industry, risk is a part of thebusiness of agriculture. With farm incomecurrently under pressure from declining

farm prices, USDAs Economic ResearchService is exploring the subject of riskmanagement in agriculture. This article,the first in the series, describes a variety

of management techniques farm operatorsuse to survive swings in weather, markets,and the economy. Other topics in the

series include USDAs farm risk initiativesand an analysis of the effectiveness ofdifferent crop and revenue insurance

products.

Farmers face an ever-changing land-scape of weather, prices, yields,government policies, global compe-

tition, and other factors that affect theirfinancial returns and overall welfare. Withthe shift toward less countercyclical gov-

ernment intervention following passage ofthe 1996 Farm Act came recognition ofthe need for a more sophisticated under-standing of farm risk and risk manage-ment. Risk management strategies canhelp mitigate the effects of swings in sup-ply, demand, and prices, so that farmbusiness returns can be closer to expec-tations.

Risk management is, in general, findingthe combination of activities most pre-

ferred by an individual farmer to achievethe desired level of return and an accept-able level of risk. Risk managementstrategies reduce risk within the farmingoperation (e.g., diversification or verticalintegration), transfer a share of risk out-side the farm (e.g., production contracting

or hedging), or build the farms capacityto bear risk (e.g., maintaining cashreserves or evening out cash flow). Usingrisk management does not necessarilyavoid risk altogether, but instead balancesrisk and return consistent with a farmoperators capacity to withstand a widerange of outcomes.

Although farms vary widely with respectto enterprise mix, financial situation, andother business and household characteris-tics, many sources of risk are common toall farmers, ranging from price and yield

risk to personal injury or poor health. Buteven when facing the same risks, farmsvary in their ability to weather shocks.For example, in an area where droughthas lowered yields, falling prices resultingfrom large worldwide production couldhave devastating consequences for localfarm incomes. With such a downturn,some bankruptcies are likely to occur, andproducers who are highly leveraged andhave small financial reserves or lack off-farm income would be most vulnerable.

What do farmers themselves say about therisks they face? USDAs 1996 Agricul-tural Resource Management Study(ARMS), conducted in the spring of 1997(about a year after passage of the 1996Farm Act), asked producers how con-

cerned they were that certain types of riskcould affect the viability of their farms.Three risk factors of greatest concern tofarm operators were uncertainty regardingcommodity prices, declines in crop yieldsor livestock production, and changes ingovernment law and regulation. Issuessuch as price and yield have historicallybeen a focus of government farm pro-grams. But new policy areas, such aswater pollution control and waste man-agement, may well affect future legisla-tion and regulation of agriculture andpose new challenges to operators.

ARMS data show that producers special-izing in wheat, corn, soybeans, tobacco,and cotton were generally more con-cerned about the threat of low yieldand/or low price than any other risk.Reduced government intervention in mar-kets for program crops (wheat, corn, cot-ton, and other selected field crops) underthe 1996 Farm Act may have heightenedproducers uneasiness about price risk.

Producers of other field crops, nursery and

greenhouse crops, and poultry expressedgreater concern about changes in laws andregulations than about other risks. Thisperhaps reflects fears that changes in envi-ronmental and other policies could requirecostly compliance by the agricultural sec-tor. Producers of the other field crops maybe wary of changes in regulations address-ing soil conservation, land use, and tillagepractices, while livestock producers maybe particularly concerned about regula-tions related to waste management and thespread of disease.

Livestock producers also expressed con-cern about their ability to adopt new tech-nology, perhaps because failure to investin new production techniques could putthem at a cost disadvantage to other pro-ducers. For farm operators involved incontracts, expenditures necessary to satis-fy production requirements imposed bycontractors, such as modification of exist-ing livestock buildings, may add to risk.

Risk Management

Agricultural Outlook Reprint/February 2000 Economic Research Service/USDA 1

Farmers Sharpen ToolsTo Confront Business Risks

JackHarrison


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Price & Yield SwingsPose Primary Risk

The possibility of lower-than-expectedyield is one of the risks identified in theARMS as a major concern to farmers,

particularly those planting major fieldcrops. Yield variability for a given cropvaries by geographic area and depends onfactors such as soil type and quality, cli-mate, and use of irrigation. Yield variabil-ity for corn, for example, tends to be low-est in the central Corn Belt, where soilsare deep and rainfall is dependable, aswell as in areas that are irrigated. InNebraska, where much of the corn pro-duction is irrigated, yield variability isquite low. Yield variability is also low inIowa, Illinois, and other Corn Belt states,where climate and soils provide a nearly

ideal growing environment for cornproduction.

In areas less well suited to corn produc-tion, yield variability is generally higher,and producers must deal with the prospectof yields that can deviate significantlyfrom planting-time expectations. Risksassociated with high yield variability andthe resulting income variability can bemitigated by programs such as Federalcrop insurance, as well as by diversifica-tion and other tools to help spread farm-

level risk.

Like yield variability, price variability dif-fers among commodities. In 1987-96,crop prices showed relatively more vari-ability than livestock prices, largelybecause crop supplies are affected byswings in crop yields while livestock sup-plies have been more stablealthoughrecent variability in the hog market illus-trates that some exceptions exist. Cropsthat exhibited the highest price variability(deviations exceeding 20 percent above orbelow the mean) include dry edible beans,

pears, lettuce, apples, rice, grapefruit, andgrain sorghum. The variability of beefcattle, milk, and turkey prices was lessthan 10 percent, perhaps reflecting lowerproduction risk and, in the case of milk,the existence of a Federal dairy program.

Price variability can change across timedepending on year-to-year differences incrop prospects, changes in governmentprogram provisions, and shifts in worldsupply and demand conditions. For exam-

Risk Management

2 Economic Research Service/USDA Agricultural Outlook Reprint/February 2000

Economic Research Service, USDA

Dry edible beansPears for fresh use

LettuceApples for fresh use

RiceGrapefruit, all uses

SorghumOnions

PotatoesAll wheat

CornSoybeans

Oranges, all usesCalves

All hogsUpland cotton

Fresh tomatoesLambsAll hay

All eggsLive broilers

TurkeysAll milk

Cattle, all beef

0 5 10 15 20 25 30

Percent of mean price

Price variability

During 1987-96, Price Variability Was Generally Higher for CropsThan for Livestock

Price variability measures deviation above and below the mean price for the period 1987-96.

1920s 1930s 1940s 1950s 1960s 1970s 1980s 1990-960

20

40

60


Percent of mean price

Price variability

orn Price Variability in the 1990s Is Near the Level of the

Past Two Decades

Price variability measures deviation above and below the mean price for each period.


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ple, corn price variability was quite highduring the 1920s and 1930s, due largelyto the collapse of grain prices after WorldWar I and very low yields in 1934 and1936. Corn prices stabilized during the

1950s and 1960s, a period of high gov-ernment support, stable yields, and con-sistent demand. Sizable purchases of cornby Russia early in the 1970s affectedvariability during that decade, while lowU.S. yields in 1983 and 1988 contributedto increased corn price variability in the1980s. Variability returned to near long-term average levels in 1990-96.

Natural HedgeMay Stabilize Revenues

Price and yield risks faced by a producer

in a given situation, as well as the strengthof the relationship between price andyieldthe price-yield correlationcaninfluence the effectiveness of different riskmanagement strategies. The stronger thenegative correlation (i.e., yield and pricemoving in opposite directions), the betterthe offsetting relationship (or naturalhedge) works to stabilize revenues.

The price-yield correlation for a commod-ity tends to be more strongly negative for

farms in major producing areas, becauseyields there are more positively correlatedwith national yields, and crop yieldsamong farms within a region tend tomove together. For example, in a major

corn-producing area such as the CornBelt, corn yields tend to be more positive-ly correlated with a national corn yield,and therefore more negatively correlatedwith the national corn price. For wheat,where production is more dispersed andU.S. production is a smaller share of theworlds crop, the natural hedge is weaker,making incomes more variable for mostwheat growers.

When other factors are held constant, themagnitude of a producers natural hedgehas important implications for the effec-

tiveness of various risk-reducing tools. Aweaker natural hedge (where low pricesmore often accompany low yields), forexample, implies that forward contractingor hedging in futures is more effective inreducing income risk than when a strongnatural hedge exists. In this situation,locking in a sales price for part of the ex-pected crop works to establish one com-ponent of the farms revenue, reducing thelikelihood of simultaneously low priceand low yield. As a result, hedging can be

an effective risk management strategy forfarms outside major producing regions.

Deciding how much to hedge is morecomplicated than just assessing price-yield correlation. Income risk is also a

function of price variability and yieldvariability. Hedging effectiveness declinesas yield variability increases, and cornyields are typically more variable outsidethe Corn Belt. Since yield variabilitytends to outweigh the impact of price-yield correlation, hedging is generally notas effective in less consistent productionareas as in the Corn Belt.

No Single ApproachSuits All Farms

While factors such as yield variability,price variability, and price-yield correla-tion can be used to gauge the likely effec-tiveness of various risk managementstrategies, producers attitudes toward riskare also determinants in selecting strate-gies. Some farmers are less risk aversethan others, and, for example, might feelmore comfortable in a highly leveragedsituation (e.g., carrying a large mortgage)than would others. Similarly, producersmay differ in their preferences for riskmanagement tools, some perhaps feelingmore at home with forward contracting

with a local elevator while others mayturn to hedging to manage their risks.

Because farmers face different degrees ofvariability and differ in their attitudestoward risk, there can be no singleapproach to suit all farms. Overall, farm-ers appear to be relying increasingly onforward contracting and other risk man-agement tools to reduce their farm-levelrisks, due in part to the recent trendtoward reduced government interventionin farming. Even so, the 1996 ARMSindicates that keeping cash (or liquid

assets) on hand for handling emergenciesand for taking advantage of good businessopportunities was the number-one strategyused by farms of every size, every com-modity speciality, and in every region.

Farm size apparently plays a role inchoice of risk management strategy. TheARMS found that operators with annualgross sales of $250,000 or more weremore likely than smaller operators touse hedging, forward contracting, and

Risk Management


Farm yield variability(percent of mean)

Less than 20

20-24

25-39

40 or more

Corn Yield Variability is Generally Lower for Farms in the Heart

Of the Corn Belt

Based on farm-level data, 1985-94, and long-term county-level yields. Includes counties with at least 500

acres planted to corn.



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Farmers have many options in managing the types of risksthey face. For example, producers may 1) plant short-seasoncrop varieties that mature earlier in the season to beat the

threat of an early frost; 2) install supplemental irrigation inan area where rainfall is inadequate or unreliable; or 3) usecustom machine services or contract/hired labor to plant andharvest quickly during peak periods.

Most producers use a combination of strategies and tools,because they address different elements of risk or the samerisk in a different way. Following are some of the more wide-ly used strategies.

Enterprise diversificationassumes returns from variousenterprises do not move up and down in lockstep, so lowreturns from some activities would as a result likely be off-set by higher returns from other activities. Diversificationcan even out cash flow. According to USDA data, cottonfarmers are among the most diversified in the U.S., whilepoultry farms, with poultry and poultry products account-ing for 96 percent of the value, on average, of their pro-duction, are the least diversified.

Vertical integrationgenerally decreases risk associatedwith the quantity and quality of inputs (or outputs)because the vertically integrated firm retains ownershipcontrol of a commodity across two or more levels ofactivity. Vertical integration also diversifies profit sourcesacross two or more production processes. In farming, ver-tical integration is most common for turkeys, eggs, andcertain specialty crops.

Production contractsguarantee market access, improveefficiency, ensure access to capital, and lower startup costsand income risk. Production contracts usually detail inputsto be supplied by the contractor, the quality and quantity ofthe commodity to be delivered, and compensation to bepaid to the grower. The contractor typically provides andretains ownership of the commodity (usually livestock) andhas considerable control over the production process. Onthe downside, production contracting can limit the entre-preneurial capacity of growers, and contracts can be termi-nated on short notice.

Marketing contractsset a price (or pricing mechanism),quality requirements, and delivery date for a commoditybefore harvest or before the commodity is ready to be mar-keted. The grower generally retains ownership of the com-modity until delivery and makes management decisions.Farmers generally are advised to forward price less than100 percent of their expected crop until yields are wellassured to avoid a shortfall that would have to be made upby purchases in the open market.

Futures contractsshift risk from a party that desires lessrisk (the hedger) to one who is willing to accept risk inexchange for an expected profit (the speculator). Farmers

who hedge must pay commissions and forego interest orhigher earning potential on money placed in margindeposits. Generally, the effectiveness of hedging in reduc-

ing risk diminishes as yield variability increases and therelationship (correlation) between prices and yieldsbecomes more negative. Hedging can reduce, but nevercompletely eliminate, income risk.

Futures options contractsgive the holder the right, butnot the obligation, to take a futures position at a specifiedprice before a specified date. The value of an optionreflects the expected return from exercising this rightbefore it expires and disposing of the futures positionobtained. Options provide protection against adverse pricemovements, while allowing the option holder to gain fromfavorable movements in the cash price. In this sense,options provide protection against unfavorable events simi-lar to that provided by insurance policies. To gain this pro-tection, a hedger in an options contract must pay a premi-um, as one would pay for insurance.

Liquidityinvolves the farmers ability to generate cashquickly and efficiently in order to meet financial obliga-tions. Some of the methods that farmers use to manage li-quidity, and hence financial risk, include: managing thepace of investments (which may involve postponingmachinery purchases), selling assets (particularly in crisissituations), and holding liquid credit reserves (such asaccess to additional capital from lenders through an openline of credit).

Crop yield insuranceprovides payments to crop produc-

ers when realized yield falls below the producers insuredyield level. Coverage may be through private hail insur-ance or federally subsidized multi-peril crop insurance.Risk protection is greatest when crop insurance (yield riskprotection) is combined with forward pricing or hedging(price risk protection).

Crop revenue insurancepays indemnities to farmersbased on revenue shortfalls instead of yield or price short-falls. As of 1999, five revenue insurance programs (CropRevenue Coverage, Income Protection, RevenueAssurance, Group Risk Income Protection, and AdjustedGross Revenue) were offered to producers in selectedlocations. These programs are subsidized and reinsuredby USDAs Risk Management Agency.

Household off-farm employmentmay provide a stream ofincome to the farm operator household that is more reliableand steady than returns from farming. In essence, house-hold members working off the farm is a form of diversifi-cation. In 1996, according to USDAs ARMS data, 82 per-cent of all farm households reported off-farm incomeexceeding farm income. In every sales class (includingvery large farms), at least 28 percent of the associated farmhouseholds had off-farm income greater than farm income.

Risk Management


A Selection of Strategies for Mitigating Risk


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virtually all other types of risk manage-

ment strategies. In contrast, operatorswith sales under $50,000 were less likelyto use forward contracting or hedging,and fewer reported using enterprise diver-sification to reduce risk.

The ARMS data also indicated that pro-ducers in the Corn Belt and NorthernPlains were somewhat more likely to userisk management strategies than those inthe Southern Plains, Northeast, andAppalachia. About 40 percent of produc-ers in the Corn Belt and Northern Plainsregions used forward contracting in 1996and about 25 percent used hedging infutures or options.

Farm legislation also affects adoption ofrisk management strategies. About one-third of producers nationwide reportedreceiving direct government commoditypayments in 1996. Of these, between 5and 8 percent (1-3 percent of all U.S.farmers) indicated they had added orincreased use of at least one risk manage-ment strategy or tool (forward contract-ing, hedging, insurance, or other strategy)

in 1996 in response to provisions of the1996 Farm Act.

A period of financial stress may induce an

operator to shift risk management strate-gies. The 1996 ARMS questioned farmersabout production, marketing, and finan-cial activities they might undertake iffaced with financial difficulty. A largeproportion of producers with sales of$50,000 or more indicated they wouldadjust costs, improve marketing skills,restructure debt, and spend more time onmanagement decisions.

Producers with sales under $50,000 (whogenerally receive a substantial share ofhousehold income from off-farm sources)also responded that they would adjust costswhen faced with financial difficulties. Butsmall-farm operators would be relativelymore likely than larger operators to sellfarm assets or scale back operations. Fur-ther, small-scale producers were much lesslikely to spend more time on managementor on improving their marketing skills.

When individual efforts to deal withfinancial stress fail and large numbers offarms face significant financial loss, theFederal government has often stepped in

with assistance to agriculture in the formof direct payments, loans, and other typesof aid. In 1999, for example, the agricul-

tural appropriations act authorized emer-gency financial assistance to farmers whosuffered losses due to natural disasters.Under this legislation, farmers were eligi-ble for payments either for losses to their1998 crop, or for losses in any 3 or more

crop years between 1994-98. Farmerswith crop insurance received slightlyhigher payments than those without, andthose receiving emergency benefits wererequired to buy crop insurance (if avail-able) in 1999 and 2000. In addition, thelegislation provides an incentive for pur-chasing higher levels of crop insurancecoverage in 1999 by earmarking an esti-mated $400 million to subsidize farmersinsurance premiums. The 2000 agricultur-al appropriations provided crop loss assis-tance and $400 million to continuethrough 2000 the incentives for purchas-

ing high levels of crop insurance.

Such assistance is undoubtedly critical forproducers facing financial difficulty.However, it raises questions as to how thepotential for direct payments in times ofdisaster affects producers decisionmakingwith regard to tools and strategies that canhelp them manage risk and perhaps avoidfinancial stress. Linking receipt of gov-ernment assistance to adoption of a riskmanagement strategy, namely the pur-chase of crop insurance, encourages pro-ducers to gain experience with a programthat can provide protection in crisis yearsin the future. Understanding the risksfaced in farming and the use of differenttools by producers can lead to new strate-gies and educational approaches to cutrisk and can perhaps help reduce the inci-dence of farm financial stress.

Joy Harwood (202) 694-5310, RichardHeifner (202) 694-5297, Janet Perry(202) 694-5152, Agapi Somwaru (202)694-5295, and Keith Coble

[email protected]

[email protected]@econ.ag.gov

AO

Risk Management


What Steps Would Farmers Take to Manage Financial Difficulties?

Small farms* Large farms**

Less than $50,000- $250,000- $500,000 Total$50,000 $249,999 $499,999 or more U.S.

Percent of farms

Management/financial strategy:Restructure debt 24 48 46 49 30Sell assets to reduce debt 31 28 31 29 30Use more custom services 7 18 17 20 10Scale back farm business 26 23 20 24 25Diversify into other farm enterprises 12 23 21 21 15Spend more time on management 19 38 47 45 24Use advisory services 19 22 28 26 20Adjust operating costs 34 54 59 57 40Improve marketing skills 30 47 53 53 35

*Annual gross sales under $250,000. **Annual gross sales $250,000 or more.Source: 1996 Agricultural Resource Management Study, USDA


Managing Risk in Farming: Concepts, Research, and AnalysisA report by USDAs Economic Research Service

* A valuable reference for comparing and assessing risk management strategies* Thorough yet accessible description of risk management concepts

Access it on the ERS website at http://www.econ.ag.gov/epubs/pdf/aer774/index.htmFor printed copies call 1-800-999-6779 (703-605-6220); report #ERS-AER-774


7/37

Almost a third of crops and livestockproduced by American farmers wasgrown or sold under contract in 1997,according to USDAs AgriculturalResource Management Study (ARMS).Departing from a tradition of independentfarm operators who have complete controlover production and marketing decisions,contracting is a growing trend inAmerican agriculture (AO May 1997).Today, more than 1 in 10 farm operatorsreport income from contractual arrange-ments.

Contracting offers farm operators theadvantages of reducing risks of priceswings, sharing production costs, andstabilizing income. For contractors (pri-marily processors and packers), thesearrangements assure a ready supply ofuniform, high-quality farm products andease inventory management problems.

Contractseither written or oral agree-mentswill generally spell out the par-ties understanding of how a commodity

is to be produced and/or marketed, includ-ing specifications for quantity, quality,and price. Marketing contracts are com-monly used for crops, while productioncontracts are more prevalent in the live-stock industry.

Under a marketing contract, a price (orpricing mechanism) is established for acommodity before harvest or before thecommodity is ready for marketing. Mostmanagement decisions remain with thegrower, who retains ownership of bothproduction inputs and output until deliv-

ery. With a marketing contract, the farmerassumes all risks of production but sharesprice risk with the contractor.

Aproduction contractdetails who sup-plies the necessary production inputsthecontractor or the farmer (contractee)aswell as the quality and quantity of a par-ticular commodity and the compensationdue the farmer for services rendered.Under livestock production contracts, thefarmer is paid to provide housing and care

for the animals until they are ready formarket, but the contractor actually ownsthe animals.

Although cash markets still dominate theagricultural sector, nearly $60 billion(31.2 percent) of total production wascovered by contracts. Commoditiesproduced under marketing contractsaccounted for 21.7 percent of the totalU.S. value of production, while thoseunder production contracts accounted for

9.5 percent. In 1997, 9 percent of farmerssold at least part of their output throughmarketing contracts, and 2.2 percent hadsome income from production contracts.

Between 1991 and 1997, the share ofcommodities produced under marketingcontracts increased from 16 percent to 22percent of total U.S. value of production.The production contract share of the totalhas varied between 10 and 15 percent,with no clear trend.

Topping the list of crops produced under

marketing contracts were fruits and veg-etables, with $11 billion sold through

contract, 40 percent of the value of allfruits and vegetables produced. Othercrops with large shares of productionvalue under marketing contracts were cot-ton ($1.9 billion, or 33 percent); corn($1.7 billion, or 8 percent); soybeans

($1.7 billion, or 9.4 percent); and sugarbeets ($973 million, or 82 percent). Justunder 10 percent of the value of cattleproduction was sold under marketing con-tracts, compared with more than 60 per-cent of the value of dairy products.

Production contracts are more likely to beused for livestock. Poultry and poultryproducts accounted for over 50 percent ofthe total value of commodities under pro-duction contracts, and cattle and hogsanother 41 percent. Within the poultrycategory, 70 percent of the commodityvalue of production was produced underproduction contracts. In contrast, 33 per-cent of the value of production of hogsand 14 percent of cattle were covered byproduction contracts.

While farms of all types and sizes engagein contracting, two-thirds of farms withcontracts (marketing and/or production) in1997 were small family farms (salesunder $250,000). However, larger familyfarms (sales $250,000 and over) and non-family farms accounted for more than

three-fourths of the value of productsgrown and sold under contract.

Risk Management


Farm Structure

More Farmers ContractingTo Manage Risk

Typology of U.S. Farms

Small family farms (annual sales under $250,000)

Limited-resource: Operator household income under $20,000, farm assets under$150,000, and gross farm sales under $100,000. Limited-resource farmers may ormay not report farming as their major occupation, or they may be retired.

Retirement: Operators report they are retired (excludes limited-resource farms).

Residential/lifestyle: Operators report primary occupation other than farming(excludes limited-resource farms).

Farming occupation/lower-sales : Operators primary occupation is farming;gross farm sales are under $100,000 (excludes limited-resource farms).

Farming occupation/higher-sales : Operators primary occupation is farming;gross farm sales are $100,000-$249,999.

Larger family farms

Large: Gross farm sales $250,000-$499,999.

Very large: Gross farm sales $500,000 or more.

Nonfamily farms

Nonfamily corporations or cooperatives, as well as farms run by hired managers.


8/37

Larger family farms were more likelyto use contracting than small familyfarms 53 percent compared with 8 per-cent. Larger farms were also more likelythan other farms to use production con-tracts instead of marketing contracts.Larger family farms accounted for 65percent of the total value of commoditiesproduced under production contract,while nonfamily farms accounted for 21percent and small family farms for theremaining 14 percent.

Farms with marketing contracts9 per-cent of all farmsoutnumbered thosewith production contracts by 4 to 1. While

small farms made up almost 70 percent ofthe farms engaged in marketing throughcontracts, they accounted for only 27 per-cent of the total value of production soldunder marketing contracts.

Dairy products marketed by small farmsunder contract were valued at $6.3 billion,or more than half of the marketing con-tract value of production on small farms.Small family farms sold $1.6 billion offruit and vegetables through marketing

contracts20 percent of the value of allfruit contract marketings and 5 percent ofthe value of all vegetable contract market-ings. Other crops raised on small farmsand marketed through contracts includesoybeans, cotton, and corn, but contractedvalue of these commodities totaled just$1.4 billion.

Larger family farms sold 70 percent oftheir total value of dairy products throughmarketing contracts, as well as 66 percentof their fruit and 38 percent of their cot-ton. Other crops grown under marketingcontract on larger family farms includevegetables, corn, and soybeans.

Commodities under marketing contractson nonfamily farms were predominantlyfruits, cattle, and dairy products.

As government programs become moremarket-oriented, all farm operators willneed to continue developing their riskmanagement skills in order to protecttheir operations from high debt levels andunpredictable price swings. Contracting islikely to be a part of farmers efforts toreconcile production preferences withexpected conditions in the marketplace,locking in purchasers for their products,sharing costs with investors, and ensuringcompensation for their labor.

David Banker (202) 694-5559 and JanetPerry (202) [email protected]

[email protected] AO

Risk Management


Two-thirds of Farms with Contracts Are Small...

Larger family farms Nonfamily All

Limited- Retirement Residential/ Farming/ Farming/ Large Very large farms farms

resource lifestyle lower-sales higher-sales

Farms:

All farms (number) 195,572 304,293 811,752 396,698 178,210 79,240 45,804 37,816 2,049,384

All farms (percent) 9.5 14.8 39.6 19.4 8.7 3.9 2.2 1.8 100.0

Farms with contracts (percent) 2.5 9.0 13.9 20.2 21.4 16.5 12.7 3.8 100.0

Value of production:

Total ($ million)1 1,615.5 4,378.2 13,126.7 19,971.5 35,249.7 30,230.7 59,582.5 27,569.3 191,724.0

Contract value($ million) 137.4 542.9 1,758.3 4,678.6 6,834.6 8,421.3 26,409.1 11,043.2 59,825.5

Production contracts ($ million) d 147.2 524.4 943.2 970.7 3,012.6 8,762.3 3,843.8 18,215.7

Marketing contracts ($ million) d 395.6 1,233.9 3,735.4 5,863.9 5,408.7 17,646.9 7,199.4 41,608.8

Share of contract value (percent) 0.2 0.9 2.9 7.8 11.4 14.1 44.1 18.5 100.0

... but Larger Farms Are More Likely to Use Contracting

Percent of farm type with:

Production and/or marketing contracts 2.9 6.7 3.9 11.6 27.2 47.2 62.9 23.1 11.1Production contracts

2d 0.8 0.7 1.9 4.9 13.3 20.0 2.2 2.2

Marketing contracts2 d 5.9 3.3 9.8 23.1 36.2 45.8 21.6 9.2

Percent of value of production 8.5 12.4 13.4 23.4 19.4 27.9 44.3 40.1 31.2

under contract

1. Survey-based estimates exclude Alaska and Hawaii and do not represent official USDA estimates of farm sector activity. 2. Includes some farms that have both

production and marketing contracts.

d - Data insufficient for disclosure.

Source: 1997 Agricultural Resource Management Study, USDA.


Small family farms

For more information on family farms

Structural and Financial Characteristics of U.S. Farms, 1995:20th Annual Family Farm Report to the Congress

To order call 1-800-999-6779. Ask for Stock #AIB-746. $21Also available on the Economic Research Service website:

www.econ.ag.gov/epubs/pdf/aib746/


9/37

Price variability is a component ofmarket risk for both producers andconsumers. Although there is no

consensus as to what constitutes too muchcommodity price variability, it is general-ly agreed that price variability that cannotbe managed with existing risk manage-

ment tools can destabilize farm income,inhibit producers from making invest-ments or using resources optimally, andeventually drive resources away fromagriculture.

Market price volatility that is not offset byapplication of risk management strategiescan lead to sudden and large incometransfers among various market partici-pants. For example, grain producers withhigh variable costs or significant debt mayface increased financial stress because ofunexpected downward swings in prices

and income, and may be unable to repaycreditors. Input suppliers, farm lenders,processors, and producers in both thegrain and livestock sectors may see theirbusiness costs rise and may pass thosehigher costs on to consumers. And insur-ance companies trying to set actuariallysound revenue insurance rates when facedwith increases in price variability mustraise premiums charged to farmers inorder to maintain actuarial soundness(AO August 1999).

Counterbalancing societys interest in thefarm sectors ability to manage price riskis an equally important interest in preserv-ing a natural degree of price variability.Price changes trigger supply and demandadjustments that make markets work moreefficiently. Thus, society has an interest

not only in helping market participantsmanage price risk via appropriate riskmanagement tools, but also in allowingmarkets to function efficiently.

An improved knowledge of the patterns ofcommodity price variability and the forcesbehind it would aid policymakers in pro-viding a policy environment conducive togood risk management practices andwould help farmers to better understandand manage their price risks. USDAsEconomic Research Service (ERS) hasundertaken research designed to identify

trends or patterns in price movements andvariability over timenominal and infla-tion-adjustedand across agriculturalcommodities. The research also exploresfactors influencing price variability, suchas strong seasonal patterns in production,market supply and demand conditions,and government policies.

How Market ConditionsAffect Price Variability

Agricultural commodity prices respondrapidly to actual and anticipated changesin supply and demand conditions.

Because demand and supply of farm prod-ucts, particularly basic grains, are relative-ly price-inelastic (i.e., quantities demand-ed and supplied change proportionallyless than prices) and because weather canproduce large fluctuations in farm produc-tion, potentially large swings in farmprices and incomes have long been char-acteristics of the sector and a farm policyconcern.

The supply elasticity of an agriculturalcommodity reflects the speed with whichnew supplies become available (or supplydeclines) in response to a price rise (fall)in a particular market. Since most grainsare limited to a single annual harvest, newsupply flows to market in response to apostharvest price change must come fromeither domestic stocks or internationalsources. As a result, short-term supplyresponse to a price rise can be very limit-ed during periods of low stock holdings,but in the longer run expanded acreageand more intensive cultivation practicescan work to increase supplies. Whenprices fall, the cost of storage relative to

the price decline helps producers deter-mine if commodities that can be storedshould be withheld from the market.

Similarly, demand elasticity reflects a con-sumers ability and/or willingness to alterconsumption when prices for the desiredcommodity rise or fall. This willingness tosubstitute another commodity when pricesrise depends on several factors, includingnumber and availability of substitutes,importance of the commodity as measuredby its share of consumers budgetaryexpenditures, and strength of consumers

tastes and preferences. Since the farm costof basic grains generally comprises a verysmall share of the retail cost of consumerfood products (e.g., wheat accounts for asmall share of the price of a loaf of breadand corn represents a fraction of the retailcost of meat products), changes in grainprices have little impact on retail foodprices and therefore little impact onconsumer behavior and correspondingfarm-level demand.

Risk Management


Assessing AgriculturalCommodity Price Variability

Chicago

Board

ofTrade


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Increasing demand for grains for industri-al use, whether from processing industriesor from rapidly expanding industrial hogand poultry operations, further reinforcesthe general price inelasticity of demandfor many agricultural commodities.

Industrial use of grains generally is notsensitive to price change, since industrialusers usually try to utilize at least a mini-mal level of operating capacity yearround. Also, in most cases, as with retailfood prices, the price of the agriculturalcommodity represents a small share ofoverall production costs of agriculture-based industrial products.

However, feed demand for grain, particu-larly for cattle feeding in the Southernand Northern Plains states, is far moresensitive to relative feed grain prices,since similar feed energy values may beobtained from a variety of differentgrains. Cattle feeders in these states arequick to vary the shares of different grainsin their feed rations as relative priceschange.

In general, elasticities of demand and sup-ply for agricultural products are both lowbut not uniform or consistent across com-modities. For example, there are severalcharacteristics unique to wheat productionin the U.S. that suggest greater supply and

demand elasticity (and, since supply anddemand respond somewhat faster, lessdramatic price swings) relative to otherfield crops in the face of external supplyand demand shockse.g., crop failure ina competing exporter country or financialcrisis in a major purchasing country.

First, U.S. wheat production is marked bytwo independent seasons, winter andspring, with planting periods nearly 6months apart. If it becomes apparent thatwinter wheat production is substantiallybelow market expectations due to prevent-

ed plantings or weather-related declines inexpected yield, some potential productionlosses can be offset by increased springwheat plantings.

Second, the potential for surplus wheatproduction to enter agricultural marketsfrom a large number of competing wheatexporter nations (principally Canada,Argentina, Australia, the European Union,and occasionally Eastern Europe) increas-es the supply responsiveness of wheat

beyond that of other major grains. Inaddition, since two major U.S. wheatexport competitors are located in theSouthern Hemisphere and their produc-tion cycle runs opposite that of the U.S.,

still greater elasticity of supply in interna-tional markets is possible.

Argentina and Australia have the opportu-nity to expand planted wheat acreage inresponse to supply and demand circum-stances in the U.S. within the same mar-keting year, dampening the potential year-to-year variability of prices in the U.S.market. While this potential additionalsupply limits price rises, it may actuallydeepen price declines because high stor-age costs and limited storage capacity fre-quently push surplus production intointernational markets even when pricesare low.

Third, wheat can serve dual functions aseither food or feed. The feed potential ofwheat can have a dampening effect onprice variability, either by introducing anadditional source of demand that preventsprices from falling too low or by shuttingoff that same demand source when pricesrise too high relative to other feed grains.

Fourth, most government-assisted exportprograms have been directed at wheat andhave had a potential dampening effect onprice variability in much the same manneras feed demandthey introduce an addi-

tional source of demand that moves oppo-site to prices. Because export programsare funded to deliver a fixed value ofcommodities, the volume of U.S. programgrain exports rises during periods ofexcess supply and relatively lower prices,but falls when supplies are tighter andprices higher.

Similarities Common inCommodity Price Movements

In examining long time series of monthlyaverage spot market prices for corn, oats,

soybeans, and several classes of wheatfrom major terminal markets, ERS hasfound strong similarities in nominal andinflation-adjusted price movements andvariability over time and across agricul-tural commodities. Price movementsof corn, oats, and most wheat classesare similar mainly because of theirsubstitutability in livestock feeding,but their market-year price volatilityshows greater differences because the

Risk Management



1913-19 1920-29 1930-39 1940-49 1950-59 1960-69 1970-79 1980-89 1990-970

5

10

15

20

Soft red winter wheat

Hard red winter wheat

Corn

Soybeans

Percent

Coefficientof variation

Cash Price Variability Was Greatest Before World War II and in the 1970s

Based on prices at major terminal markets. Soybean price data for 1913-19 not available. Thecoefficient of variation (CV) is a measure of price variability. CV = (dispersion of monthly inflation-adjusted average cash price over the season divided by mean of monthly average cash price

over the season) multiplied by 100.Source: Constructed by ERS using monthly average cash price data from Bridge News Service andUSDAs Agricultural Marketing Service and the all-urban CPI deflator from the Bureau of LaborStatistics.


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commodities differ in their response tosupply and demand shifts.

Nominal prices for these commodities, asreported by USDAs AgriculturalMarketing Service, have shown a generalupward trend since the early 1930s, inter-rupted by nearly two decades of fairly sta-ble prices in the 1950s and 1960s. Thisperiod of relative stability ended with adramatic price spike in the early 1970s, atumultuous period marked by an unex-pected surge in world grain demand andtrade, coupled with poor harvests and

rapid, dynamic macroeconomic changes(AO September 1996). Since the mid-1970s, nominal prices appear to haveboth a higher mean level and greater vari-ability. The past three seasons (1996-98)have witnessed a precipitous plunge innominal prices from the May 1996 spikewhen corn and two of the high-proteinwheat classeshard red winter and hardred springattained record-high monthlyaverage spot market prices.

When monthly average price data areadjusted for inflation, a different patternemergesdeclining real prices since thelate 1940s, interrupted by the dramaticupward spike in prices of the early1970s. The pattern of inflation-adjustedprice variability is less clear than the pat-tern of nominal price variability, but itsuggests that prices were more variableduring the three pre-World War II decadesthan since.

A common statistic for measuring thevariability of a data series is the coeffi-

cient of variation (CV), which expressesthe dispersion of observed data values asa percent of the mean. Since the CV isunit-free (a percent), it facilitates compar-ison of price changes in different direc-tions, across different periods of time, andfor different commodities. Marketing-yearCVs calculated from each commoditysinflation-adjusted series of averagemonthly spot prices reflect the pricevolatility that occurred within each mar-keting year. The nature and degree of this

within-year price variability affect deci-sions on the mix and level of farm activi-ty, as well as on risk management andmarketing strategies.

On the other hand, comparison of CVs

across market years provides an indica-tion of a commoditys longrun price vari-ability. Such across-year price variabilityinfluences firm expansion and capital-asset acquisition decisions, and has adirect bearing on a firms economic via-bility. In addition, the longrun variabilityof commodity prices across marketingyears reflects the risk environment foragriculture relative to other sectors.

A shortcoming inherent in using historicalaverages as a forecast of price volatility is

that such estimates fail to fully incorporatecurrent market information. For example,prices are likely to be more volatile thanthe historical average during a year thatbegins with very low carryin stocks.

The degree of variability in commodityprices is traditionally believed to dependheavily on stock levels and on the natureand frequency of unexpected shifts indemand and supply. Thus, essentially allmarket forces affecting commodity priceformation could potentially come into playin determining price variability. Such

forces include own supply (carryin stocks,production, and imports), supply of substi-tute crops (depending on end use), andaggregate demand (domestic mill, feed,seed, and industrial use, and exports). Ownsupply and supplies of competitor cropsare directly affected by weather, acreage,government policy, and international tradefactors. Demand is directly affected byprice, income, shifts in tastes and prefer-ences for end uses, and population growth.Grain and seed characteristicsi.e., type,quality, protein content, and colorarealso key factors in price formation.

The possibility of substitution in use iscritical in determining strength of correla-tion between different commodity prices.For example, inflation-adjusted spot mar-ket prices for three winter wheat classessoft red, hard red, and soft white winterand hard red spring wheat are highly cor-related, because they offer some similarcharacteristics to end users. Hard amberdurum, on the other hand, with its highprotein level and specific milling and

Risk Management


Wheat Price Is More Highly Correlated With Corn Price Than With Soybeans. . .

Wheat Corn Soybeans

Soft red Hard red Hard amber

winter winter durum

Correlation coefficient for price

Wheat:Soft red winter 1.00 0.99 0.87 0.90 0.71

Hard red winter 0.99 1.00 0.90 0.90 0.71

Hard amber durum 0.87 0.90 1.00 0.81 0.62Corn 0.90 0.90 0.81 1.00 0.72

Soybeans 0.71 0.71 0.62 0.72 1.00

. . .but Grain Price Variability Is Less Highly Correlated Than Grain Price

Wheat Corn Soybeans

Soft red Hard red Hard amberwinter winter durum

Correlation coefficient for price variabilityWheat:

Soft red winter 1.00 0.94 0.71 0.46 0.39

Hard red winter 0.94 1.00 0.71 0.53 0.35Hard amber durum 0.71 0.71 1.00 0.22 0.30

Corn 0.46 0.53 0.22 1.00 0.39

Soybeans 0.39 0.35 0.30 0.39 1.00

Prices are inflation-adjusted monthly spot market prices during various time periods, 1913-98. The correlationcoefficient indicates similarity between two sets of variables: a coefficient of plus one (+1) indicates a perfectpositive relationship, minus one (-1) a perfect negative relationship, and zero no relationship.Price variability is coefficient of variation (CV) for market-year inflation-adjusted monthly spot market prices.CV = (dispersion of monthly inflation-adjusted average cash price over the season divided by mean inflation-adjusted monthly average cash price over the season) multiplied by 100.Sources: Spot market prices from USDA's Agricultural Marketing Service; daily cash settlement prices fromthe Chicago Board of Trade; and monthly average settlement prices from Bridge News Service.



12/37

end-use qualities, offers the least opportu-nity for substitution with other wheatclasses and, as a result, tends to haveslightly lower price correlations withother wheat classes.

Price correlations among corn, oats, andwheat, although somewhat lower, are stillvery strong and likely reflect their substi-tutability in feed markets. Price correla-tions between these grains and soybeansare lower yet. Soybean prices are princi-pally derived from demand for its jointproductsoil and meal. Soybean meal isgenerally included in feed rations as aprotein source, but may compete directlywith other grains in feed rations as anenergy source, depending on relativeprices. However, soybean oilused prin-cipally as a food with some minor indus-trial useshas limited substitutabilitywith grains (corn oil being the majorexception), thereby weakening the soy-bean-grain price correlation.

Correlations of market-year price CVsfor corn, oats, wheat classes, and soy-beans are sharply lower compared withprice-level correlations. This suggests thatwhile general price levels for most grainsand soybeans may be influenced by ormove in tandem with many of the sameforces, commodity price variabilities are

more distinct and less strongly related toeach other, due likely to disparities intheir respective supply and demandresponsiveness to price changes.

Strong Seasonal Pattern forWithin-Year Price Volatility

The principal difficulty in analyzing with-in-year price variability is that while pricescan be routinely observed for almost anytime period (e.g., year, month, week), theeconomic supply and demand factors thatlikely influence price movements are gen-

erally reported only on a monthly or quar-terly basis. Research conducted jointly byERS and North Carolina State Universityattempted to circumvent this problem bytransforming monthly and quarterly datainto weekly data representations. Thesewere used to assess the importance of rele-vant market information in forecastingwithin-yearprice variability (measured asa rate of change) of settlement prices forthe Minneapolis Grain ExchangesSeptember wheat futures contract and the

Risk Management


Wheat Price Variability Peaks When Uncertainty Is Greatest

Source: USDAs Economic Research Service and North Carolina State University.

-1

0

1

2

Sept. Nov. Jan. Mar. May July Aug.

Uncertainty about condition of winterwheat crop and spring planting intentions

Wheat harvest underway and criticalgrowing period for major feed grains


Price variability factor indicates weekly deviation from expected (or forecast) price variabilitymeasured over the entire time period. Zero indicates price variability during that week is the sameas expected price variability over the entire time period. Seasonal volatility estimated by aneconomic model of volatility using weekly Minneapolis Grain Exchange September wheat futurescontract prices, 1986-97.

Price variability factor

Source: USDAs Economic Research Service and North Carolina State University.

Corn Price Variability Rises During Planting Time and Ebbs During Harvest


-2

-1

0

1

2

3

4

Dec. Feb. Apr. June Aug. Oct. Nov.

Plantingtime

Harvesttime

Price variability factor

Price variability factor indicates weekly deviation from expected (or forecast) price variabilitymeasured over the entire time period. Zero indicates price variability during that week is the sameas expected price variability over the entire time period. Seasonal volatility estimated by an

economic model of volatility using weekly Chicago Board of Trade December corn futurescontract prices, 1986-97.


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Chicago Board of Trades December cornfutures contract during the 1987-96 period.

Futures prices play a critical role in facili-tating seasonal market operations, becausethey provide a forum for forward con-tracting, as well as a central exchange fordomestic and international market supplyand demand information. Regional and

local grain elevators rely on futures com-modity exchanges for hedging grain pur-chases and generally set their grain offerprices at a discount (in areas of surplusproduction, such as the Corn Belt) or at apremium (in deficit production areas, suchas North Carolina) to a nearby futurescontract. As a result, cash prices andfutures contract prices are stronglylinkedi.e., both prices contain much ofthe same information about variability.

Both corn and wheat futures contractprices display distinct patterns of seasonalvariability. For the December corn con-tract, a strong variability peak occurs inJune when there is a great deal of uncer-tainty surrounding the true extent of plant-ings and likely yield outcomes for cornand other spring-planted crops. Much ofthe acreage uncertainty is resolved withrelease of USDAs June 30Acreagereport, while yield uncertainty is resolvedin July after corn pollination has occurred.A second, weaker peak occurs in Octoberand corresponds with the arrival of new

information during the peak corn harvestperiod. The seasonal component of cornprice volatility then declines rapidly priorto contract expiration.

This pattern suggests that the bulk of rele-vant information is synthesized by thecorn market during the critical summergrowing months when estimates of

acreage and yields are largely determined.Supply news then tends to dominate mar-kets into the fall harvest, with little newinformation added during the periodimmediately preceding contract expiration.

The seasonal pattern for September wheatfutures contract price variability alsoshows two peaks, the first a weak early-season peak occurring in January-March,a time of substantial uncertainty about thetrue condition of the winter wheat cropand farmers spring planting intentions.Much of the uncertainty is resolved withUSDAs release of its March 28 PlantingIntentions report.

A second, much stronger peak in variabil-ity occurs in late July and correspondswith the conclusion of winter wheat har-vest and the critical growing period forthe major feed grains and spring wheat.Domestic prices for the U.S. wheat cropalso depend heavily on international sup-ply and demand conditions, and some key

market information governing internation-al developments does not reach the mar-ket until midsummer when USDA beginsforecasting major international crop pro-duction. Following the July harvest-timesurge, the seasonal variability then

declines rapidly prior to contract expira-tion.

The volatility of corn and spring wheatfutures prices also shows a strong negativerelationship with growing conditionsbetter-than-average growing conditions areassociated with lower price variation.However, corn and wheat prices differ inthe association of variability with many ofthe remaining supply and demand factorsstudied. This is likely due to differences intheir respective supply and demandresponsiveness to price changes.

For corn, increases in expected U.S.domestic demandpublished monthly inUSDAs World Agricultural Supply andDemand Estimates (WASDE) reporthada positive influence on price volatility, butchanges in actual levels of corn stocksestimated quarterly by USDAdid notappear important, probably because cornsupply is estimated from a single annualcrop, and because changes in stocks areprimarily a residual of often offsettingchanges in other market forces and

therefore tend to move slowly betweenharvests.

For wheat, changes in expected exportsand domestic demand for all wheatshowed no influence on spring wheatprice volatility, while increases in actualall-wheat private stocks had a dampeningeffect on volatility. Lack of a strong rela-tionship between demand factors andspring wheat price volatility is likelyexplained by winter wheat dominance ofU.S. wheat exports, by the shifting impor-tance of wheat as government food dona-

tions versus commercial export sales, andby the interplay of food-feed markets.

The study found that the level of day trad-ing (day traders enter and exit the marketwith no outstanding balance at the end ofthe trading day) at each commodityexchange correlated positively with bothcorn and spring wheat price variability,likely because day trading allows prices toadjust to information more quickly. Onthe other hand, market concentration

Risk Management


Are Prices More Volatile in Recent Decades Than Earlier?

An examination of the historical record of wheat, corn, oat, and soybean prices dur-ing 1913-97 indicates the following patterns:

Wheat prices tend to be less variable than prices for oats, corn, or soybeans over

the entire period and during most selected subperiods. The most notable exceptionis the 1990-97 period when wheat price variability was above average while soy-bean and oat variability were below the average for the entire period.

All five wheat classes, plus corn and soybeans, exhibited dramatic increases inprice variability during the 1971-75 period.

Price variability for all commodities is noticeably higher in the post-1970s era(1976-97) than during the pre-1970s period (1951-70).

Price variability in the post-1970s period (1976-97) is slightly lower than variabil-ity during the 1913-50 period.

Studying such a long price series gives greater perspective to current levels of pricevariability and suggests that perhaps an anomaly with respect to price variabilityoccurred during the 1950s and 1960s, when heavy government involvement in

agricultural commodity marketsincluding large government stockholdings ofwheat and feed grainscoupled with low absolute levels of world trade (relative tothe post-1971 period) contributed to artificially stable prices.


14/37

measured using Commodity FuturesTrading Commission commitment oftraders data on holdings of the fourlargest tradershad a negative influenceon spring wheat price volatility, suggest-ing that the action of large traders in high-

ly concentrated markets may decrease thevolatility of wheat prices.

Forces Driving Across-YearPrice Variability

In joint research to investigate determi-nants ofacross-yearprice variability, ERSand North Carolina State University con-structed within-year CVs from monthlyaverage cash prices at major terminalmarkets during 1944-97 for Chicago/St.Louis soft red winter wheat, Chicagocorn, and Chicago/Central Illinois soy-

beans. Each CV reflects the price variabil-ity that occurred during a market year.Then these market-year CVs were exam-ined in light of year-to-year changes inmajor supply and demand factors.

As expected, output price variability forall three commodities was found to benegatively correlated with the level ofstocks relative to total disappearance; aready supply available from stocks tendsto make prices less sensitive to new mar-ket information. However, as in the with-

in-year study, corn, soybean, and wheatprice CVs exhibited key differences intheir association with most of the remain-ing supply and demand factors studied,likely because of differences in their sup-ply and demand responsiveness to pricechanges.

Since increases in production tend todampen both prices and price variabilityby contributing to an increase in total sup-ply relative to market demand, any changein acreage and yield (both of which havepositive associations with production) is

expected to have a negative, indirecteffect on price variability through theinfluence on production. Change in yieldshows a strong negative relationship withcorn price variability, but no relationshipwith soybean and wheat CVs. Wheatsdual seasons (winter and spring) within asingle crop year and broad geographicdiversity of production likely diminish theinfluence of a single weather pattern on

the aggregate wheat market. Change inharvested acres is negatively related towheat price variability, but not to corn orsoybean price variability.

Change in demand, on the other hand, is

expected to be positively associated withprice variability since increases in demand,whether domestic or international, drawdown total supplies and stocks, anddecreases in demand have the oppositeeffect. This was confirmed by a positiveassociation between corn price variabilityand both domestic use and exports.

However, wheat price variability showedno relationship to change in domestic useand was negatively related to change inexports. The negative effect of wheat

exports on price variability tends to con-firm the smoothing effect of governmentexport assistance programs, and suggeststhat U.S. wheat exports act as a residualsource of supply to world markets whendomestic prices fall low enough. The off-setting roles of food and feed usage inwheat price volatilitypositive for wide-spread changes in domestic use formilling and other food and industrial uses,but negative (and offsetting) when actingas a residual outlet to feed marketsresult in a net neutral effect.

Similarly, changes in the general level ofinput prices are expected to have positiveassociations with price variability indi-rectly via their negative influences on pro-duction and total supply. For example, ris-ing input prices tend to dampen produc-tion and, in turn, may raise price variabili-ty. However, no relationship was foundwith corn and wheat price CVs. Instead,soybean price variability showed a nega-tive association with changes in inputprices, suggesting that soybean cost sav-ings relative to corn and wheat played arole (AO May 1999). As input prices rise,

producers favor soybeans because soy-bean production costs are relatively lower,resulting in greater acreage, more produc-tion, and lower soybean price variability.

Government policy influences are inher-ent in nearly all related supply anddemand variables. Several governmentprogram initiatives (including some that

preceded the 1996 Farm Act) were studiedto directly measure the influence of loanrates, expected deficiency payments(which were intended to stabilize incomebut often had the unintended consequenceof limiting substitution in production

because of associated acreage restric-tions), and acreage reduction programs(which were designed to reduce supply byremoving acreage from production).Results hint at some effects on commodi-ty price variability for wheat and soy-beans from acreage constraints and pricesupport programs, but no government pol-icy variable was found to influence cornprice variability.

While far from conclusive, these resultssuggest that past government programshad a tendency to produce higher levels ofprice variability, at least for wheat andsoybeans. In every case where a govern-ment policy variable was found to beimportant, it had a positive associationwith price variability. At first glance, thiseffect may seem surprising. However,policies that are intended to stabilizeproducer incomesa central goal of pastpolicyare apparently likely to increasethe volatility of market prices if theydistort production and marketingarrangements.

Since the 1996 Farm Act, governmentpolicy has shifted away from potentiallyprice-destabilizing direct intervention inagricultural production processes andmarkets. Instead, USDAs RiskManagement Agency has been working toprovide the necessary tools and informa-tion for farm operators and other partici-pants in agricultural markets to betterunderstand and manage risks associatedwith producing and selling agriculturalcommodities. Although effective tech-niques for managing inter-year price riskremain elusive, a variety of management

toolse.g., futures and options contracts,and various crop and revenue insuranceproducts (AO April 1999)exist for man-aging within-year price risk.

Randy Schnepf (202) [email protected]

AO

Risk Management



15/37

The past few years have seen a prolif-eration of market-based mechanismsavailable to agricultural producers

for managing yield, price, and revenuerisks. Making the right choices is becom-

ing more complicated. Yet the fundamen-tals for making good risk managementchoices remain the same: 1) understandingthe farms risk environment, 2) knowinghow the available risk management strate-gies work and which risks they address,and 3) selecting the strategy or combina-tion of strategies that will provide the pro-tection that best suits the farms and theoperators individual circumstances.

USDAs Economic Research Service(ERS), using data from the DepartmentsRisk Management Agency (RMA) andNational Agricultural Statistics Service(NASS), has identified general condi-tions underlying farm-level risk manage-ment behavior in the U.S., how condi-tions relate to the performance of differ-ent risk management strategies, and whycertain risk management strategies workbetter than others at reducing farm-spe-cific risk across a range of different riskenvironments. This research has focusedon three field crops with the highestacres plantedcorn, soybeans, and

wheatbut it provides a useful guide forrisk management for other major fieldcrops as well.

Defining a FarmsRisk Environment

Within a single crop year, once cropdecisions have been made and resourceshave been allocated to production agri-culture, the farms principal risk lies inthe uncertainty of the revenue generatedby the production process. Farm revenueuncertainty, particularly the componentrelated to field crop production, is princi-pally a function of yield and price uncer-tainty, as well as the correlation betweenprice and yield.

Weather is the principal cause of yielduncertainty. Within any given agro-climat-ic settingcharacterized by weather pat-tern, soil type and fertility, growing sea-son, day lengthvariability of yield isattributable mainly to factors such as tem-perature, cloud cover, and timeliness andamount of precipitation.

Price uncertainty for farmers combinestwo elements. Price-level uncertainty is

the consequence of imperfect informationabout future domestic and internationalsupply and demand conditions. Basisuncertaintyuncertainty about the differ-ence between a commoditys local cashprice and its nearest futures contract

pricederives from uncertainty aboutfuture commodity movements and haulingcosts. The tendency for price and yield tochange in opposite directions provides anatural hedge which tends to stabilizefarm revenues over time, particularly inmajor producing areas (AO March 1999).

Farmers attitudes towards risk can varygreatly and are a key determinant inselecting risk management strategies. Afarmer with a strong aversion to risk willbe willing to pay more for a given levelof risk reduction than a farmer with aweaker aversion to risk. An operatorsoverall level of wealth can also have astrong bearing on risk decision making. Ingeneral, at higher levels of wealth an indi-vidual is more willing to undertake agiven level of riska phenomenon calleddecreasing absolute risk aversionbutthere are exceptions to this rule. The pre-ferred or optimal risk management strate-gy may also vary because of other man-agement objectives, such as profit maxi-mization or enterprise growth. In addition,lenders may strongly suggest or evenrequire use of risk management tools toprotect their stake in the farms produc-tion outcome.

The Mechanics of Crop& Revenue Insurance

The array of crop and revenue insurancepolicies and coverage levels available toU.S. farmers has been rapidly expandingover the past few years. In spite of thegrowing complexity of agricultural insur-ance programs, the majority of policiesactually sold can still be fairly well repre-

sented by two generic types of agricultur-al insurance: standard yield-based cropinsurance and revenue insurance.

The largest share of farm coverage contin-ues to be traditional yield-based cropinsurance, although revenue insurancecoverage is rapidly gaining. Traditionalyield-based crop insurancereferred to asmultiple peril crop insurance (MPCI)includes both the minimum catastrophiccoverage (CAT) which insures against

Risk Management


Insurance & Hedging:Two Ingredients for aRisk Management Recipe

ChicagoBoardofTrade


16/37

severe losses and whose premiums arefully subsidized by the Federal govern-ment, and higher levels of coveragecalled buy-up coveragewith partiallysubsidized premiums. Revenue insurancepolicies include Income Protection,

Revenue Assurance, and Crop RevenueCoverage. All three of these revenueinsurance programs receive partial subsi-dization of premiums by the Federalgovernment.

Two time periods are relevant in calculat-ing insurance program prices. The first isplanting time, when aProjected Price isused to set insurance premium rates andprice elections, and to value coveragelevels. The second is harvest time, whenthe harvest-time futures price is used tovalue the farms production whether sold

or stored.

For yield-based insurance purposes, RMAestablishes a Projected Price about 3months before the insurance signup peri-od for each commodity. This yield-based-insurance version of the Projected Price isnot derived solely from a futures marketprice average, but is a forecast of the sea-son-average price that incorporates addi-tional market information.

For revenue insurance valuation, the

Projected Price is the average of the dailysettlement prices of the harvest-timefutures contract during the month preced-ing program signup. For the price at har-vest time, the average closing price of theharvest-time futures contract during themonth prior to the contracts expiration isused. For example, the Projected Price fora corn revenue insurance contract is theFebruary average closing price of theChicago Board of Trades (CBOTs)December corn contract. And the harvest-time futures price for the December corncontract would be the average daily settle-

ment price during November.

Yield-based crop insurance (MPCI)paysthe operator an indemnity if the actualyield falls below a yield guarantee, butMPCI does not offer price protection.Under MPCI, the producer pays a pro-cessing fee for minimum CAT coverageand a premium for buy-up coverage toobtain partial protection against yield lossonly. Theyield guarantee is determinedby multiplying the producers average

Risk Management


Offsetting Price-Yield Relationship, a Key Factor in the Farm RiskEnvironment, Varies by Region and Commodity

Corn price-yield correlation

Under -0.40 (strongest)-0.4 to -0.3

-0.29 to -0.15

Above -0.15 (weakest)

Soybean Producers in Western Corn Belt

Corn Producers in Iowa, Illinois, and Indiana

Soybean price-yield correlation

Under -0.25 (strongest)-0.250 to -0.151-0.150 to -0.100

Above -0.10 (weakest)

Wheat price-yield correlation

Under -0.070 (strongest)-0.070 to -0.051-0.050 to -0.020Above -0.020 (weakest)

Winter Wheat Producers in Central Southern Plains


Price-yield correlation indicates strength of offsetting relationship between price andyield movements--the more negative, the better the "natural hedge" works to stabilizerevenue. Based on annual county-level data, 1974-94.


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Risk Management


historical yieldreferred to as the actualproduction history (APH)by the cover-age level. Coverage levels range from 50to 75 percent (expanded to 85 percent insome areas for 1999) of the APH yield,and from 60 to 100 percent of the

Projected Price.

Example of crop insurance:Suppose a corn producer has an APHyield of 150 bushels per acre, theProjected Price is $2.50 per bushel, andthe producer selects 75-percent APH cov-erage with 100-percent price coveragereferred to as the elected price. Theproducers yield guarantee is 112.5bushels per acre (75 percent of 150bushels). An actual yield below 112.5bushels will result in an indemnity pay-ment to the producer equal to the electedprice of $2.50 times the differencebetween the yield guarantee and the actu-al yield, even if the harvest-time pricerises above the Projected Price. However,if the actual yield does not fall below theyield guarantee, even if the harvest-timeprice falls below the Projected Price, theoperator gets no indemnity. Thus MPCIpartially insures against production risk,but does not insure against price risk.

Revenue insurancee.g., IncomeProtection and the standard Revenue

Assurance programsprotects farmersagainst reductions in gross income when acrops prices or yields decline from early-season expectations. The revenue guaran-tee equals the product of the farmersAPH yield, the Projected Price, and thecoverage level selected by the producer. Aproducer receives an indemnity when theactual yield, multiplied by the harvest-time futures price, falls below the revenueguarantee. Since revenue insurance cover-age is generally available at a maximumof 75 percent (85 percent in some desig-nated counties), it provides only partial

protection against both price and yieldrisk, and is less effective at reducing riskwhen the natural hedge is strong.

Revenue insurance with replacementcoverage protection is available to farm-ers via the Crop Revenue Coverage pro-gram or the Revenue Assurance programwhen purchased with an increased priceguarantee option. The added replacementcoverage protection (RCP) feature offers arevenue guarantee that depends on the

higher of the price elected at signup or theharvest-time futures price. Thus, the pro-ducers revenue guarantee may increaseover the season, allowing the producer topurchase replacement bushels if yieldsare low and prices increase during the

season. Replacement coverage comple-ments forward contracting or hedging bypartially ensuring that the farmer can buyback futures contracts or deliver on cashcontracts when yields are low and har-vest-time prices are high. Producers arestill subject to basis risk, and only partialcoverage (up to 85 percent in designatedcounties) can be obtained.

In general, the revenue guarantee of rev-enue insurance with RCP equals the prod-uct of the producers APH yield, the cov-erage level selected, and the higher of theearly-season Projected Price or the har-vest-time futures price. Indemnity pay-ments are triggered when the harvest-timerevenue, based on the harvest-time futuresprice, falls below the revenue guarantee.Thus, revenue insurance with RCP alsoprovides only partial protection againstyield and price risk, and is less effectivewhen the natural hedge is strong, becausehigh prices offset low yields and revenueis more likely to stay at least somewhatabove the guarantee.

The premium for revenue insurance withreplacement coverage is more expensivethan for revenue insurance without RCP,partly because the replacement cost pro-tection provides greater price protection.Also, premium differentials increase whenproducers are permitted to subdivide theiracreage into units, such as by sectionand irrigated/nonirrigated status (as underCRC), rather than basing the premium ona producers total acreage in a county (asunder Income Protection).

Under 75-percent coverage, the standard

revenue insurance guarantee for a cornproducer with an APH yield of 150bushels and a projected harvest-time priceof $2.50 is $281.25 per acre. A revenueinsurance policy with RCP (under 75-per-cent coverage) has $281.25 as an initialminimum revenue guarantee, but thisguarantee may increase if market pricesrise during the growing season. If a lowor normal yield and low harvest-timeprice cause the market value of the cropto fall below the revenue guarantee, rev-

enue insurance policies with or withoutRCP will pay the same indemnity.However, if the low yield is accompaniedby a high harvest-time price, revenueinsurance with RCP will pay an indemni-ty, while policies without RCP will pay a

lower or no indemnity.

What Is Forward Pricing?

Forward pricing involves setting the price,or a limit on price, for a product to bedelivered in the future. Forward pricingstrategies include contracts such as cashforward, futures, options, delayed pricing,basis, minimum price, and maximumprice (for feed purchases). Three generaltypes of forward pricing strategiesacash forward sale, a futures hedge, and aput option hedgeare described here for

comparison with the risk-reducing powerof crop and revenue insurance programs.

A cash forward sale is a contract betweena seller (e.g., a farmer) and a buyer (e.g.,an elevator) requiring the seller to delivera specified quantity of a commodity to thebuyer at some time in the future for aspecified price or in accordance with aspecified pricing formula. Most cropgrowers sell forward at a fixed or flatprice based on an observed futures pricequote. Some farmers use basis contractsthat specify a set price difference rela-tive to the futures price to be applied atdelivery time. Some use hedge-to-arrivecontracts that fix the futures price compo-nent and leave basis to be determined atdelivery time. Cash forward contractseliminate both price-level and basis riskby locking in a local cash market price forthe quantity under contract, but any pro-duction in excess of the hedged amount isstill subject to routine market price risk.

Example of a cash forward sale:Suppose that a corn producer has planted

100 acres of corn with an APH yield of150 bushels per acre. At planting time, theprojected harvest-time price is $2.50 perbushel, the local cash price is $2.38, andthe basis is $0.12. The producer agrees toforward contract the farms entire expect-ed corn production of 15,000 bushels at aprice of $2.38, for an expected revenue of$35,700. If the price at harvest-time is$1.80, the operator still gets $35,700 forthe crop, $8,700 above the cash market.However, if the producer harvests only 85


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Risk Management


bushels per acre, even though the futuresprice rises to $3.50 (local cash price $3.38with constant basis), the net revenueunder this contract will fall to $13,730($35,700 less $21,970) because the opera-tor has to purchase the shortfall (6,500

bushels @$3.38) in the cash market. Thisoutcome illustrates the income risk asso-ciated with yield risk when an operatorforward contracts 100 percent of theexpected production at planting timebased on the projected harvest-time price.

Hedgingis designed to reduce price-levelrisk prior to an anticipated cash sale orpurchase. Afutures hedge involves thesale (short hedge) or purchase (longhedge) offutures contractsstandard-ized contracts traded on a commodityexchangeas a temporary substitute foran intended sale or purchase on the cashmarket. The futures contract is laterbought (sold) to eliminate the futuresposition as the actual commodity is sold(bought). Crop growers are generallyshort hedgers against crops they intend tosell later in the season.

For example, every corn futures contracttraded on the Chicago Board of Trade(CBOT) calls for delivery of 5,000bushels of No. 2 yellow corn during oneof five designated delivery months each

year. Hedging requires relatively littleinvestment, because only a small portionof the futures contracts face value isrequired as a margin good-faith deposit toguarantee performance of the contract.Hedging also provides flexibility, sincethe hedger can eliminate a position in thefutures market by simply contracting foran equal number of offsetting contracts.Still, the primary advantage of a futureshedge is the elimination of the price-levelrisk of an existing cash position by lock-ing in a price.

A producer can hedge by selling futurescontractsshort hedgecovering part orall of anticipated output. For example, acorn grower could sell 10,000 bushels ofDecember corn futures in May to hedgean expected 20,000-bushel corn crop.Such a hedge normally is lifted by buyingan equal number of futures contracts asthe cash commodity is sold. Since near-parallel movements in cash and futuresprices during the period of the hedge tendto offset each other, any losses (gains) in

the cash market are made up by gains(losses) in the futures market.

Any contract, cash or futures, that tendsto fix the price prevents the seller fromgaining from subsequent price increases

as well as losing from subsequent pricedeclines. Moreover, forward pricing con-tracts contain an element of nonperfor-mance or production riskif the quantityactually produced turns out to be less thanthe contracted quantity and the price atdelivery lies above the contracted price,the producer must make up the shortfall ata loss. Thus, risk is minimized by forwardpricing only part of a crop until yield isassured.

Finally, hedging replaces price risk with

basis riskuncertainty about the pricedifference between the futures contractand the cash marketand

Agricultural Outlook (2000) Managing Farm Risk Issues and Strategies

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