iowa ag review - center for agricultural and rural development · winter 2004, vol. 10 no. 1...

Iowa Ag ReviewWinter 2004, Vol. 10 No. 1

Risk-Free Farming?Bruce A. [email protected]

Chad [email protected]

The direction of U.S. farmpolicy changed with the pas-sage of the 2002 farm bill and

the 2000 Agricultural Risk ProtectionAct. Previous farm bills, togetherwith the old crop insurance pro-gram, had gradually moved thecrops sector toward greater marketorientation, with farmers taking onmore market risk in exchange forgreater planting flexibility. But thebeginning of this decade broughtwith it increased protection againstboth adverse price movements andcrop losses. These policy changeswere brought about largely at thebehest of farm commodity organiza-tions, who argued that they neededincreased protection against the va-garies of weather and market condi-tions. As we will demonstrate, thereduction in risk that U.S. crop farm-ers obtain from crop insurance andcommodity programs is now so dra-matic that we may have entered anew era of risk-free farming.

The U.S. proposals for farmpolicy reform to the World Trade Or-ganization (WTO) would, if adopted,move U.S. farm policy back toward itsprevious trajectory of greater marketorientation. However, the WTO talkshave stalled, so it is worthwhile totake a step back and assess whereU.S. policy currently stands. We useillustrations of the distribution of re-turns with and without governmentprograms to show the impacts ofthese programs on farm financial riskin a single growing season. The as-

sessment begins with a review of theU.S. farm policy legislation processand whom it most benefits.

WHAT TYPE OF PRODUCER BENEFITSFROM U.S. FARM POLICY?Evidence would suggest that U.S.farm policy is primarily designed tomeet the interests of commodity as-sociations. Early in 2001, LarryCombest, then the chairman of theHouse agriculture committee, askedthe National Corn Growers Associa-tion, the National Cotton Council, theAmerican Soybean Association, theRice Growers Association, the WheatGrowers Association, the NationalBarley Growers Association, andother associations what farm pro-gram provisions they wanted to seein the new farm bill. ChairmanCombest, along with the members ofthe House and Senate agriculturecommittees, then designed a bill tomeet their wishes. The legislationpassed through Congress and wassigned into law by the president inMay 2002.

These commodity associationsare national associations of farmers.It seems self-evident that the associa-tions represent the interests of theirfarmer-members. But typically, theassociation leaders are chosen fromthe most successful farmers, who of-ten have large, well-financed opera-tions with lower-than-average costsand higher-than-average volumes.

Profit incentives in a commoditysystem lead crop producers to focuson low costs and high yields. Thus,commodity organizations, who areled by the most successful commod-ity producers, will tend to supportfarm policies that support the kindsof farm operations that are most suc-cessful in a commodity system.

MECHANISMS OF SUPPORT ANDFINANCIAL IMPACTSHere, we focus on the subsidies thatproducers of corn, wheat, oilseeds,rice, cotton, barley, and grain sor-ghum receive. We examine corn in de-tail to show how farm programs andcrop insurance affect revenue and weinclude wheat and cotton for compari-son. In addition to farm program pay-ments, 75 percent of U.S. corn wasinsured under the U.S. crop insuranceprogram in 2003. The most popularproduct was a form of revenue insur-ance whereby the insurance guaran-tee increases if the harvest price isgreater than the projected harvestprice at planting time. The most popu-lar coverage level is 75 percent cover-age (the farmer takes the first 25percent loss before payments begin).At the 75 percent coverage level, farm-ers pay only 45 percent of the actuari-ally fair premium, which is defined asthe premium that over time wouldgenerate enough total dollars to payall insurance claims. Thus farmers re-ceive a subsidy equal to 55 percent ofthe actuarially fair premium.

2 CENTER FOR AGRICULTURAL AND RURAL DEVELOPMENT WINTER 2004

Iowa Ag Review

ISSN 1080-2193http://www.card.iastate.edu

Iowa Ag Review is a quarterly newsletter pub-lished by the Center for Agricultural and RuralDevelopment (CARD). This publication presentssummarized results that emphasize the implica-tions of ongoing agricultural policy analysis, analy-sis of the near-term agricultural situation, anddiscussion of agricultural policies currently underconsideration.

Editorial StaffSandra Clarke

Managing EditorBetty Hempe

Editorial ConsultantBecky Olson

Publication Design

Editorial CommitteeJohn BeghinTrade and AgriculturalPolicy Division HeadRoxanne ClemensMATRIC Managing Director

Iowa State UniversityIowa State University does not discriminate on thebasis of race, color, age, religion, national origin,sexual orientation, sex, marital status, disability, orstatus as a U.S. Vietnam Era Veteran. Any personshaving inquiries concerning this may contact theDirector of Equal Opportunity and Diversity,1350 Beardshear Hall, 515-294-7612.

IN THIS ISSUERisk-Free Farming? ........................ 1

Targeting Efficiency in theConservation SecurityProgram .......................................... 4

Agricultural SituationSpotlight: Agricultural PriceSwings and Iowa’s Economy......... 6

The Expanding U.S. Marketfor Fresh Produce .......................... 8

Recent CARD Publications ......... 11

Before examining the financialeffects of the various governmentprograms, let’s look at a representa-tive farm’s financial picture withoutfarm programs. At planting time, U.S.farmers do not know either the pricethey will receive for their crops orwhat their harvested yield will be.To capture this uncertainty, we builda representative farm and repeat acrop year 5,000 times and record theoutcome. There are 5,000 differentyield and price outcomes. We chosea representative corn farm in BooneCounty, Iowa, with a local expectedfarm price set at $2.15/bushels (bu)and an expected yield of 150 bu peracre (ac). The standard deviation ofprice is set at $0.45/bu and the stan-dard deviation of yield is 43 bu/ac.

A histogram constructed fromthe 5,000 revenue draws is shown inFigure 1. The histogram shows therange of possible revenue outcomesas well as the probability of out-comes. Variable costs of $150 aresubtracted so that the distributionshows net revenue. One measure ofthe amount of risk that a farmerfaces is the probability that revenuewill not be adequate to cover a cer-tain level of variable productioncosts. A farmer who covers variablecosts has some money left over topay off fixed expenses. Figure 1shows that that average net returnsfor this corn farmer are about $163/ac. There is a very low probability (4percent) that net returns are nega-tive. On average, this farmer will

FIGURE 1. HISTOGRAM OF NET REVENUE FOR A REPRESENTATIVE CORN FARM

FIGURE 2. EFFECT OF GOVERNMENT PROGRAMS AND CROP INSURANCE ON RISK

EditorBruce A. Babcock

CARD Director

Subscription is free and may be obtained for eitherthe electronic or print edition. To sign up for anelectronic alert to the newsletter post, go to www.card.iastate.edu/iowa_ag_review/subscribe.aspxand submit your information. For a print subscrip-tion, send a request to Iowa Ag Review Subscrip-tions, CARD, Iowa State University, 578 Heady Hall,Ames, IA 50011-1070; Ph: 515-294-7519; Fax: 515-294-6336; E-mail: [email protected]; Web site:www.card.iastate.edu.

Articles may be reprinted with permission and withappropriate attribution. Contact the managingeditor at the above e-mail or call 515-294-6257.

WINTER 2004 CENTER FOR AGRICULTURAL AND RURAL DEVELOPMENT 3

Iowa Ag Review

have approximately $163 left over topay all other expenses, includingland, fixed machinery expenses, andmanagement. For a cash renter, landcosts would increase variable costsand the entire histogram would shiftto the left, which demonstrates theincreased risk that cash renters facerelative to owner-operators.

Most other U.S. crop farmersface relatively more risk than thiscorn farmer. Iowa corn farmers havethe advantage of highly productivesoils and a natural hedge betweenprice and yield. When yield is low,the price is likely to be higher thanexpected, thus buffering the nega-tive impacts of low yields. And lowprices are likely caused by a bumpercrop in Iowa, which helps insulate

Iowa corn farmers from financialtrouble.

IMPACT OF GOVERNMENTPROGRAMS AND CROP INSURANCENow let’s look at the effects of gov-ernment programs on the financialrisks of this farm. The effects of allthe programs are revealed by com-paring the distribution of marketplus government receipts to the dis-tribution shown in Figure 1.

Figure 2 shows the aggregate ef-fect of these programs on a farmer’srisk. As can be readily seen, theamount of risk that this farmer facesis now significantly reduced and theexpected returns over variable costsare dramatically increased. Averagenet returns increase 46 percent to

about $239/ac with the programs inplace. Perhaps the best way to char-acterize the effects of the programsis that with the programs in placethere is now less than a one-in-sixchance that total revenue will fallbelow $163/ac, which is the averagerevenue without the programs. Asshown in Figure 2, there is nochance that farmers in BooneCounty will not be able to covertheir non-land variable costs. It is inthis sense that we can speculatethat corn farming in Boone Countyhas become “risk free.”

.THE PICTURE FOR WHEATAND COTTONFigures 3 and 4 depict pictures ofrisk for a wheat farmer in RenoCounty, Kansas, and a cotton farmerin Tallahatchie County, Mississippi.The pictures for wheat and cottonare similar to that of corn but thereare some significant differences.Without government programs,wheat producers in this KansasCounty have a small probability ofnegative returns. Payments and cropinsurance subsidies increase the av-erage return to wheat farming by 72percent. This compares to the 46percent increase for the corn farmer.The probability that returns overvariable costs fall below $60—whichis the average return with no pro-grams—is approximately 7 percent.Thus, if we define risk as the prob-ability that returns over variablecosts are less than expected returnsunder no government programs,then the programs combined withcrop insurance have essentially re-duced the risk for wheat farming tonear zero.

The impact from governmentprograms is even more dramatic forcotton. Based on an expected localprice of $0.52 per pound (lb), an av-erage yield of 700 lb/ac, and variablecosts of $325/ac, the expected mar-ket returns over variable costs forour Mississippi cotton farmer areonly $39/ac. And the probability that

FIGURE 3. RISK REDUCTIONS FROM GOVERNMENT PROGRAMS FOR WHEAT

FIGURE 4. RISK REDUCTIONS FROM GOVERNMENT PROGRAMS FOR COTTON

Continued on page 10


Iowa Ag Review

Resource and EnvironmentalPolicy [email protected]

The much anticipated imple-mentation rules for the Con-servation Security Program

(CSP), authorized in the 2002 FarmSecurity and Rural Investment Act,were unveiled January 2, in the Fed-eral Register. In addition to describ-ing the proposed rules, the NaturalResources Conservation Serviceoutlines the challenge they faced inconstructing a coherent implemen-tation plan for a program that wasinitially developed as an entitlementprogram but later faced fundingcaps. The magnitude of this chal-lenge is aptly summarized by theUSDA’s Economic Research Service,which finds that if all of the 1.8 mil-lion farms and ranches likely to beeligible for the program were to en-roll, the total budgetary cap of $3.77billion would be completely ex-hausted in the first sign up.

One of the approaches pro-posed by USDA to limit the expen-ditures associated with theprogram is to “target” conservationfunds to watersheds identified ashigh priority. This is controversialto some because it means thatsome locations will receive conser-vation dollars to the exclusion ofothers. There are other ways inwhich the proposed rules are tar-geted: payments will differ in differ-ent parts of the country to reflectdifferences in land rental rates, andfarmers with track records in con-servation practices will receivehigher priority.

We briefly describe here thedifferent ways in which conserva-tion funds can potentially be tar-geted, the history of targeting inconservation programs, some evi-dence on the degree to which tar-geting of environmental funds isefficient, and a few insights on the

possible consequences of targetingCSP funds to alternative watershedsin Iowa.

WHAT IS TARGETING?The term “targeting” can apply to avariety of payment practices. Thecommon element among theseschemes is that not all farmers orranchers necessarily receive thesame payment for a given practiceor action. Instead, some criteria areused to differentiate among thesources. Historically, conservation

programs in the United States haveemployed a variety of targeting ap-proaches over the years.

Conservation Reserve Program(CRP) payments initially enrolledland designated as highly erodible.This effectively targets paymentsgeographically based on soil and to-pographical characteristics. A sec-ond way in which CRP has targetedpayments is by using a bidding sys-tem to enroll farmers into the pro-gram who are willing to participateat the lowest cost. This is a form of

Targeting Efficiency in the Conservation Security Program

FIGURE 1. DES MOINES RIVER AND IOWA RIVER WATERSHEDS

Illinois

Missouri

Minnesota

Wisconsin

Iowa

Des Moines RiverWatershed

Iowa RiverWatershed


Iowa Ag Review

cost targeting. The most completeform of targeting used in the CRPhas been the use of the Environ-mental Benefits Index, which con-siders both the environmentalbenefits associated with enrolling aparcel of land in the program (itemssuch as water and air quality, wild-life habitat, and soil quality amongothers) and the costs.

Another significant conservationprogram that has employed varioustargeting tools is the EnvironmentalQuality Incentives Program (EQIP).Notably, EQIP has targeted thosepractices and geographic locationsthat contribute to environmentalbenefits that are specific nationalpriorities, defined by the Natural Re-sources Conservation Service. Inter-estingly, while this program hashistorically targeted both cost andgeographic priority areas, the 2002legislation specifically prohibitssuch targeting.

One relatively new target thatthe CSP program identifies is pro-ducers who have already demon-strated that they are “goodstewards.” In particular, in the pro-posed rules, conservation producerswill be categorized based on theirprevious environmental steward-ship, and those in the highest cat-egories will receive first priority forfunding. This policy has the interest-ing consequence of targeting funds

for environmental improvement tolocations where some improvementshave already occurred.

THE BENEFITS OF TARGETINGWhile the motivation for targeting inthe CSP appears largely to be basedon the high cost of a nontargetedapproach, there is a strong case tobe made for the targeting of conser-vation funds even when conserva-tion budgets are not as strained. Theconservation benefits from enrollinga parcel of land in the CRP, EQIP, orthe new CSP will differ, often sub-stantially, depending upon the soilcharacteristics, slope, previouscropping practices, or location ofthat parcel. For example, creating asmall wetland in an area that drainshighly nutrient-rich farmland willlikely yield substantially greater wa-ter quality benefits than placing thatwetland where nutrient cleaning ben-efits will not occur. Likewise, install-ing a stream buffer on a parcel withhighly erosive soils will yield greatererosion benefits than installing sucha buffer on flat, low-eroding soils.

In fact, the research to date onthe cost effectiveness of targetingconservation funds provides strongsupport for the benefits of such astrategy. In a 1996 study, Babcock etal. demonstrated that 90 percent ofthe water erosion benefits from en-rolling land in CRP could have been

achieved with only half the total CRPbudget if the land chosen for enroll-ment had been targeted specificallyfor water erosion benefits. Similarly,Feng et al. (2003) demonstrated thatat the beginning of CRP, when erosionreduction was a major goal of theprogram, if payments were targetedat land with the highest erodibilityindices, the average erodibility indexof enrolled land in Iowa would bemore than twice as high as that of theactually enrolled land.

It should be noted that not allforms of targeting will necessarilyresult in more cost-effective conser-vation. In fact, as previously noted,the CSP proposal to focus additionalenvironmental improvements onland that is already under some con-servation practices may mean thatland that would most yield environ-mental benefits might be passedover in favor of land that is managedby good stewards.

WATERSHED TARGETING IN THECONSERVATION SECURITY PROGRAMWhile previous research indicatesthat targeting is often very cost ef-fective, generating significantly moreenvironmental benefits with a fixedbudget than would occur if fundswere disbursed indiscriminately, thisdoes not necessarily mean that the

Continued on page 10

TABLE 1. SCENARIO RESULTS FOR THE IOWA AND DES MOINES RIVER WATERSHEDS

(1) (2) (3) (4) (5) (6)Sediment

Annual Reduction per Total Cost AverageAverage Acre Converted of Cost ofBaseline Percentage to Conservation Sediment SedimentSediment Sediment Tillage Reduction Reduction

Scenario (106 mt*) Reduction (mt/acre) (106 dollars) (dollars/mt)

Iowa River inConservationTillage 5.00 5.8 0.108 33.4 115.2

Des Moines Riverin ConservationTillage 2.85 5.7 0.067 26.3 161.9

*mt = metric tons


Iowa Ag Review

Agricultural Price Swings and Iowa’s EconomyChad E. [email protected]

Over the past few months, wehave seen tremendous vari-ability in commodity prices.

Soybean futures prices have in-creased by roughly 50 percent sincemid-July, spurred on by lower-than-expected production and an ever-tightening supply. Cattle futuresprices have fallen by nearly 20 per-cent since the announcement of thebovine spongiform encephalopathy(BSE) case in Washington. But whatdo these price swings mean forIowa’s agricultural and overall stateeconomy?

One way to look at the impactsis through the values of productionfor Iowa’s major agricultural prod-ucts. The big four commodities(corn, soybeans, hogs, and cattle)account for roughly 90 percent of allagricultural cash receipts in Iowa.Table 1 shows the values of produc-tion for these commodities (2003-04figures are projections). On average,the corn crop provides 38 percent oftotal value, followed by hogs at 26percent, soybeans at 24 percent, andcattle at 12 percent.

The projections include theprice increase for soybeans butwere computed before the BSE an-nouncement. But as is evident by acomparison of the 2002 and 2003values, the price increase of 2003was more than offset by the drop insoybean production. However, it isnot always the case that prices andproduction move in opposite direc-tions (at the state level). The in-crease in soybean productionvalues between 2001 and 2002 canbe attributed to increases in bothprices and production. Tables 2 and3 show historical and projectedmarketing year average prices and

production levels for corn, soy-beans, cattle, and hogs.

The projections for 2004 showprices holding steady for corn, alarge drop in the prices of soybeansand cattle, and a slight increase inprices for hogs. Corn production andprices are projected to be near 2003levels. While Iowa soybean produc-tion is expected to rebound in 2004,

Agricultural Situation

Spotlight

soybean prices may fall back to2002 levels. Both hog productionand prices are expected to rise in2004. Before the BSE announcement,cattle production and prices wereexpected to maintain near 2003 lev-els. However, even with a 20 percentreduction in price (following the fu-tures market), Iowa cattle produc-tion values for 2004 would be near

TABLE 2. AGRICULTURAL PRICES FOR IOWA

Year Corn Soybean Cattle Hog

($/bushel) ($/cwt)2000 1.75 4.49 61.63 41.292001 1.90 4.35 70.06 42.902002 2.25 5.40 57.55 30.282003 2.09 6.92 75.10 35.802004 (pre-BSE) 2.11 5.01 74.13 37.312004 (post-BSE) 2.11 5.01 59.30 37.31

TABLE 1. IOWA’S VALUES OF AGRICULTURAL PRODUCTION

Year Corn Soybean Cattle Hog Total(billion $)

2000 3.02 2.09 1.07 2.68 8.852001 3.16 2.09 1.13 2.75 9.132002 4.42 2.67 1.05 2.02 10.162003 3.99 2.48 1.30 2.39 10.172004 (pre-BSE) 3.99 2.39 1.26 2.50 10.132004 (post-BSE) 3.99 2.39 1.01 2.50 9.88

TABLE 3. IOWA’S AGRICULTURAL PRODUCTION LEVELS

Year Corn Soybean Cattle Hog

(million bushels) (million pounds)2000 1,728 465 1,730 6,4792001 1,664 480 1,616 6,4002002 1,964 495 1,818 6,6812003 1,908 359 1,729 6,6812004 (pre-BSE) 1,890 477 1,695 6,7002004 (post-BSE) 1,890 477 1,695 6,700


Iowa Ag Review

. . . in light of the BSEcase, it is important to notethat the large price swingswe see in agriculture havesmaller effects on Iowa’s

overall economy than mightbe anticipated by the

general public, especiallywhen the price swings are

viewed as temporarymovements in the market.

2002 levels and the total value ofproduction for the four commodi-ties would approach $9.9 billion, farexceeding the production values for2000 and 2001.

But looking at production val-ues does not tell the whole storyas far as agriculture’s impact onIowa’s economy. Oftentimes, whenyou hear news reports on the sizeof Iowa’s economy, it is stated interms of the “gross state product”(GSP). The GSP, much like thegross domestic product (GDP) forthe nation, is a measurement ofthe “values added” in productionby the labor and resources con-tained within the region. Valuesadded is the difference betweenthe value of the output from pro-duction and the value of interme-diate inputs (output from otherproduction sources) used in thecreation of the output. For ex-ample, the values added in live-stock production is the differencebetween the livestock value andthe value of such inputs as feed,machinery, and veterinary ser-vices used to raise the livestock.

The Bureau of Economic Analy-sis, an agency within the U.S. De-partment of Commerce, tracksvalues added, GSP, and GDP. Valuesadded can be obtained for on-farmagricultural production, agriculturalservices, food production (for both

human and animal consumption),manufacturing, other services, andso on. As Figure 1 shows, the GSPdue to on-farm agricultural produc-tion has remained fairly stable since1977. Adding in the values added dueto agricultural services and food pro-duction doubles the impact of agri-culture on Iowa’s economy. However,these direct impacts are somewhatsmall in comparison to Iowa’s totaleconomy. Since the late 1970s, Iowaeconomy has tripled in size, fromjust over $25 billion in 1977 to $90billion in 2001. Production

FIGURE 1. IOWA’S TOTAL GROSS STATE PRODUCT AND AGRICULTURE’SDIRECT SHARE

agriculture’s share of the gross stateproduct has fallen from 14 percent in1978 to under 3.25 percent in the lastfew years. The combination of agri-cultural production, services, andfood production accounts for only 8percent of Iowa’s GSP.

For Iowa, the data for on-farmagricultural production indicatesthat roughly 30 percent of the pro-duction value is considered as val-ues added. Using this as a roughguide to production agriculture’sdirect impact on the State’seconomy, the consequences of theprice downturn in cattle due to BSEare smaller than might be expected.Based on a 20 percent price drop,Iowa cattle production values wouldfall by $250 million. Using the 30percent values-added relationship,this would translate into a $75 mil-lion drop in gross GSP from on-farmproduction. That is less than one-tenth of 1 percent of total GSP.

The point here is not to say thatagriculture is not a major contributorto Iowa’s economy. Estimates ofagriculture’s overall impact (directand indirect through related indus-tries) range from 15 to 25 percent ofthe state’s total GSP. Rather, in lightof the BSE case, it is important tonote that the large price swings wesee in agriculture have smaller ef-fects on Iowa’s overall economy thanmight be anticipated by the generalpublic, especially when the priceswings are viewed as temporarymovements in the market. ◆


Iowa Ag Review

Roxanne [email protected]

The U.S. Center for NutritionPolicy and Promotion urgesconsumers to eat between five

and nine servings of fresh fruits andvegetables per day. Not all consum-ers are reaching that goal, but percapita consumption of fresh produceis steadily increasing (see Figure 1).Between 1980 and 2001, per capitaconsumption of fresh fruits in-creased by 19 percent and consump-tion of vegetables (includingpotatoes) increased by 29 percent.At the same time, new technologiesto extend shelf life and new tradeagreements have increasingly al-lowed imports of fresh produce tofill gaps where domestic supplies aretoo small and domestic products areout of season.

As a result, between 1980 and2001, fresh fruit imports increasedby 155 percent and fresh vegetableimports increased by 265 percent(see Figure 2). In 2001, imports ac-counted for 38.9 percent of U.S. freshfruit consumption, up from 24.2 per-cent in 1980. Fresh vegetable im-ports accounted for 11.6 percent ofU.S. consumption in 2001, up from5.5 percent in 1980.

IMPORTS FROM NORTH ANDSOUTH OF THE BORDERAs shown in Table 1, the majority ofimported produce is comprised of afew products originating from a fewcountries within the Americas (seeTable 1). Costa Rica’s tropical climatemakes it the largest supplier of freshfruits. Mexico is the largest supplierof fresh vegetables (including pota-toes), in part because of relativelylow transportation costs. And al-though import volumes from Canadaare lower than are those from othertop suppliers, Canada supplies a sur-prisingly large volume of vegetablesto the U.S. market, in part because ofincreased greenhouse production.

The Expanding U.S. Market for Fresh Produce

As expected, produce importsare highly dependent on U.S. produc-tion and seasonal fluctuations. Forexample, bananas account for morethan 22 percent of total fresh fruitconsumption and for 60 percent oftotal fresh fruit imports. Because ba-nana production is virtually nonex-istent in the United States, importsare not strongly affected by seasonalchanges. This contrasts with melonimports, which are the second larg-est fresh fruit import by volume buthighly seasonal. Imports are large in

March and April and negligible forJuly through September.

The USDA forecasts that thetrend toward increased consumptionof fresh fruits and vegetables willcontinue. Per capita expenditures onfruits and vegetables are expected tohave the highest increases among alltypes of foods through 2020. Theseincreases will be driven by higherincomes, the large number of agingbaby boomers, a gradually increas-ing population, increasing consump-tion of ethnic foods, and higher

FIGURE 1. PER CAPITA U.S. FRESH FRUIT AND VEGETABLE CONSUMPTION

FIGURE 2. U.S FRESH FRUIT AND VEGETABLE IMPORTS


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TABLE 1. U.S. FRESH PRODUCE IMPORTS BY LARGEST SUPPLIERS, 2002

levels of education among consum-ers. Of these factors, higher real in-come is the most important becauseconsumers can purchase more ex-pensive food products and can paypremiums for desired attributes.

ADDITIONAL SPENDING FORQUALITY, VARIETYFood choices are moving towardsafe, nutritious products, a greatervariety of foods, and convenience.

Consumer willingness to pay morefor safe, high-quality, value-addedproducts will create niche marketsthat commodity-style imports can-not supply. For vegetables (exclud-ing potatoes), away-from-homeconsumption is expected to growmore quickly than is at-home con-sumption, but the proportion ofeach market held by commoditysuppliers is expected to remain al-most unchanged. For fruits, con-

sumption at home will increase morethan will that away from home. Inboth cases, a segment of U.S. con-sumers will pay more for additionalvariety and quality that commodityproduction cannot provide.

In determining where to spendtheir food dollars, consumers aredemanding more natural foods. Or-ganic production is growing, and theUSDA reports that fresh produce isthe top-selling organic category.Also, a desire to “buy local” and apreference for foods produced in anenvironmentally sound manner areimportant considerations for someconsumers.

GREATER SELECTION FILLSTHE SHELF SPACEConsumers are also demandinggreater variety. In 1994, small andlarge supermarkets stocked lessthan 350 produce items. This year,large supermarkets are expected tostock 558 items, and small supermar-kets are expected to stock about 540items. These data include floral andother nonfresh items, but the major-ity of the increase is attributable tofresh produce. Supermarkets are de-livering greater variety by offeringmore items, more kinds of a singleitem, and more further-processeditems (for example, pre-cut fruitsand vegetables). Packaging can in-crease the desirability and value ofproduce by adding convenience (forexample, resealable bags), more de-sirable packaging materials, or abroader selection of sizes.

The sheer size of the U.S. marketfor fresh fruits and vegetables dic-tates that commodity-type productswill continue to dominate the marketand that the percentage of the mar-ket supplied by imports will con-tinue to increase. In a growingportion of the market, however, con-sumers will be willing to spend moremoney on higher-quality produce. Asa result, growing niche markets fornoncommodity products are ex-pected to provide greater opportuni-ties for both foreign and domesticproducers to increase the farm valueof fresh produce. ◆

Percentage PercentageMetric of Total of Product

Product Tons Imports by Country

Total Fruit 7,417,776Bananas 4,144,627 55.9

Ecuador 1,094,600 26.4Guatemala 968,941 23.4Costa Rica 914,235 22.1

Melonsa 680,275 9.2Guatemala 213,393 31.4Costa Rica 174,159 25.6Mexico 128,106 18.8

Grapes 518,267 7.0Chile 399,015 77.0Mexico 103,175 19.9

Pineapples 405,714 5.5Costa Rica 344,731 85.0

Total Vegetablesb 3,178,567

Tomatoes 859,502 27.0Mexico 723,425 84.2Canada 100,499 11.7

Peppers 401,159 12.6Mexico 322,627 80.4Canada 41,545 10.4

Cucumbers/Gherkins 394,040 12.4Mexico 334,681 84.9

Vegetables, Fresh 351,239 11.1Mexico 293,685 83.6

Potatoes 281,890 8.9Canada 281,785 99.9

Onions and Shallots 270,243 8.5Mexico 157,468 58.3Canada 55,133 20.4

Source: USDA data.aExcludes watermelons.bIncludes potatoes.


Iowa Ag Review

market returns will be greater thanvariable costs is only 54 percent.Government programs increase ex-pected returns by 516 percent to$200/ac. And the probability thatreturns over variable costs fall be-low expected revenue with no gov-ernment programs is zero. Thus,

government has taken the risk outof cotton farming.

U.S. crop producers largely haveobtained what they sought: risk-freefarming courtesy of governmentprograms. This conclusion impliesnothing about the relative merits ofthe various programs or whetherthe programs should be modified.But the programs do create the in-centive for farmers and landlords tofocus on growing the commodities

Risk Free Farming?Continued from page 3

targeting of watersheds will beequally beneficial.

In an attempt to provide someinsight into the potential importanceof targeting funds to various water-sheds, we employed a water qualitymodel, the Soil and Water Assess-ment Tool, to simulate adoption ofconservation tillage (one of the prac-tices included in the CSP) in the DesMoines River Watershed and theIowa River Watershed. We combinedthis model with an economic modelpredicting the costs of obtainingadoption of conservation tillage inthese watersheds based on a pay-ment program like the CSP. To high-light the potential consequences oftargeting, we consider two sce-narios: full adoption of conservationtillage in the Des Moines River Wa-tershed with no additional adoptionin the Iowa River Watershed and theopposite adoption pattern (no newadoption in the Des Moines Riverand full adoption in the Iowa RiverWatershed).

Table 1 shows the levels of sedi-ment (based on a 20-year projectedaverage) and the estimated costs atthe watershed outlets. As columns 1-3 indicate, the estimated percentagereduction in sediment erosion be-tween the two scenarios is about thesame (about 6 percent), but theoriginal level of sediment load ismuch higher in the Iowa River Wa-tershed than in the Des Moines RiverWatershed. Thus, the total sedimentload reduction is about twice as highby targeting the Iowa River Water-shed. This is consistent with column4, which reports the average sedi-ment load reduction per acre of landconverted to conservation tillage.

However, the costs of adoptioncan vary significantly with targetingand need to be considered in assess-ing the consequences of targeting.The median cost of adopting conser-vation tillage in the two watershedsis about 20 percent higher in theIowa River Watershed (we estimatethe median costs of adoption to be$11/acre in the Des Moines River Wa-tershed). While the total cost ofsediment reduction is higher in theIowa River Watershed, the per ton

cost of sediment reduction is signifi-cantly lower (see columns 5 and 6).Targeting the Iowa River Watershedresults in a higher overall reductionin sediment at a lower average costper ton than does targeting the DesMoines River Watershed.

This particular example is onlyindicative of the different outcomesthat could occur under various tar-geting mechanisms. However, the re-sults of this simple simulationsuggest that by targeting different wa-tersheds, as proposed in the CSP, theNatural Resources Conservation Ser-vice will significantly affect the loca-tion, degree, and cost effectiveness ofwater quality improvements. Detailsof this research and other studies fo-cusing on the consequences of target-ing and conservation programs canbe found at www.card.iastate.edu/environment/.◆

Resource and Environmental Policystaff who contributed to this article areHongli Feng, Philip Gassman, LubaKurkalova, Silvia Secchi, andCatherine Kling.

“Targeting” Efficiency in theConservation Security ProgramContinued from page 5

that are supported by farm pro-grams. Furthermore, an increasedincentive to plant those hybrids andvarieties that have the highest yieldsand lowest costs is what we wouldexpect from a program designed tomeet the interests of the most effi-cient producers of commodities. Theprograms would look quite differenthad the durum wheat and whitecorn producers been instrumental intheir design. ◆

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iowa ag review - center for agricultural and rural development · winter 2004, vol. 10 no. 1...

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