Get a GRIP: Should Area Revenue Coverage Be Offered through the Farm Bill or as a Crop Insurance Program?

Transcription

1 Ge a GRIP: Should Area Revenue Coverage Be Offered hrough he Farm Bill or as a Crop Insurance Program? Nicholas Paulson and Bruce A. Babcock Working Paper 07-WP 440 January 2007 Cener for Agriculural and Rural Developmen Iowa Sae Universiy Ames, Iowa Nicholas Paulson is a graduae assisan a he Cener for Agriculural and Rural Developmen a Iowa Sae Universiy. Bruce Babcock is a professor of economics and direcor of CARD. This paper is available online on he CARD Web sie: Permission is graned o excerp or quoe his informaion wih appropriae aribuion o he auhors. Quesions or commens abou he conens of his paper should be direced o Bruce Babcock, 578 Heady Hall, Iowa Sae Universiy, Ames, Iowa ; Ph: (515) ; Fax: (515) ; babcock@iasae.edu. Iowa Sae Universiy does no discriminae on he basis of race, color, age, religion, naional origin, sexual orienaion, gender ideniy, sex, marial saus, disabiliy, or saus as a U.S. veeran. Inquiries can be direced o he Direcor of Equal Opporuniy and Diversiy, 3680 Beardshear Hall, (515)

2 Absrac The successful expansion of he U.S. crop insurance program has no eliminaed ad hoc disaser assisance. An alernaive currenly being explored by members of Congress and ohers in preparaion of he 2007 farm bill is o simply remove he ad hoc par of disaser assisance programs by creaing a sanding program ha would auomaically funnel aid o hard-hi regions and crops. One form such a program could ake can be found in he area yield and area revenue insurance programs currenly offered by he U.S. crop insurance program. The Group Risk Plan (GRP) and Group Risk Income Proecion (GRIP) programs auomaically rigger paymens when couny yields or revenues, respecively, fall below a producer-eleced coverage level. The per-acre axpayer coss of offering GRIP in Indiana, Illinois, and Iowa for corn and soybeans hrough he crop insurance program are esimaed. These resuls are used o deermine he amoun of area revenue coverage ha could be offered o farmers as par of a sanding farm bill disaser program. Approximaely 55% of axpayer suppor for GRIP flows o he crop insurance indusry. A significan porion of his suppor comes in he form of ne underwriing gains. The expeced rae of reurn on money pu a risk by privae crop insurance companies under he curren Sandard Reinsurance Agreemen is approximaely 100%. Taking his indusry suppor and adding in he axpayer suppor for GRIP ha flows o producers would fund a couny arge revenue program a he 93% coverage level. Keywords: area revenue insurance, commodiy programs, crop insurance, Group Risk Income Proecion.

3 Inroducion A common jusificaion given for he coninued funding of U.S. crop insurance program subsidies is ha i will eliminae he need for ad hoc disaser programs. For example, par of Presiden Clinon s saemen upon signing he Agriculural Risk Proecion Ac (ARPA) of 2000 was as follows: I have heard many farmers say ha he crop insurance program was simply no a good value for hem, providing oo lile coverage for oo much money. My FY 2001 budge proposal and his bill direcly address ha problem by making higher insurance coverage more affordable, which should also miigae he need for ad hoc crop loss disaser assisance such as we have seen for he las hree years. In 2006 esimony before he House Subcommiee on Agriculure, Rural Developmen, Food and Drug Adminisraion, and Relaed Agencies, former USDA under secreary J.B. Penn said, One of he overarching goals of he crop insurance program has been he reducion or eliminaion of ad hoc disaser assisance. By almos any measure, he drive o induce farmers o increase heir purchase of crop insurance hrough increased premium subsidies and suppor for he crop insurance indusry has been a resounding success. Over 80% of insurable crop acreage was enrolled in he program in 2005, and more han half of hose acres were insured a coverage levels of 70% or higher. Toal liabiliy for he 2006 crop year was approximaely $50 billion. Despie his success, Congress once again seems poised o pass anoher disaser assisance program in Given ha Congress has largely succeeded in is effor o expand he crop insurance program, one can only conclude ha crop insurance canno subsiue for disaser assisance programs. Policymakers are hen lef wih a choice of eiher 1

4 coninuing o live wih he overlapping coverage offered by crop insurance and disaser programs or designing a new approach o he problem of providing farmers wih an efficien financial safey ne. One problem wih coninuing he curren crop insurance program is ha i provides a relaively inefficien way of providing coverage o farmers. Glauber (2007) calculaes ha he marginal cos of inducing farmers o increase heir coverage level is approximaely $26/ac. This high marginal cos is refleced in he average cos of supporing farmers incomes hrough he crop insurance program. Over he firs five crop years under ARPA (2001 o 2005), he ne ransfer o producers (indemniies paid less producer premiums) has oaled $8.8 billion. However, he cos o axpayers of delivering hese funds has oaled $15.5 billion. Anoher way of providing farmers wih financial assisance is hrough group or area crop insurance. I is well recognized ha crop insurance plans based on area yields raher han individual farm yields offer many advanages. Halcrow (1949) firs promoed area yield insurance as a way around he problems inheren in basing guaranees and premium raes on individual farm yields, noing ha yield variabiliy is largely driven by sysemic facors in many areas. Miranda (1991) noes ha area yield insurance offers a soluion o he adverse selecion and moral hazard problems ha plague crop insurance producs ha are based on individual yields. Miranda (1991) models farm yields as a decomposiion of sysemic and poolable componens and demonsraes ha an area yield produc can offer beer proecion agains yield losses han does individual yield insurance. Barne e al. (2005) also show ha he Group Risk Plan (GRP), inroduced in 1993 as he firs area yield plan of insurance in he Unied Saes, ouperforms individual 2

5 yield insurance for some crops and regions. Skees, Black, and Barne (1997) documen he developmen of he GRP program. An ofen over-looked advanage of an area insurance produc is ha i would auomaically provide disaser aid o farmers faced wih unexpecedly low prices or who reside in areas wih low yields. Miranda and Glauber (1991) proposed an area revenue program ha would indemnify producers whenever area revenue fell below a arge revenue program. The program would proec producers agains sysemic price or yield drops. As Congress moves oward a new 2007 farm bill, serious consideraion is being given o a Miranda-Glauber area revenue plan as he basis of a new safey ne ha would also serve as a sanding disaser program. In his paper we examine how provision of an area revenue program could be implemened as he basis for a safey ne for agriculure. We use he Group Risk Income Proecion (GRIP) program as he area revenue insurance ha would be provided o farmers. We compare wo differen delivery mechanisms for GRIP. The firs is delivery as a crop insurance produc in he curren crop insurance program. The second is as a program in he commodiy ile of he farm bill ha would replace markeing loan and counercyclical programs. We compare program coss under he wo approaches and discuss he advanages and disadvanages of each delivery approach. Background Two area crop insurance producs, GRP and GRIP, are currenly eligible for federal reinsurance, premium subsidy, and adminisraive and operaing (A&O) expense reimbursemen as par of he U.S. crop insurance program. GRP is an area plan of insurance ha pays all insured farmers in a couny an indemniy when he couny average 3

6 yield falls below a rigger yield. The rigger yield is chosen by he insured as a percenage (up o 90%) of he expeced (rend) couny yield. GRIP is an area revenue plan ha pays an indemniy when couny average revenue falls below a rigger revenue level. The rigger revenue is chosen by he insured as a percenage of expeced couny revenue, which is he produc of he GRP rend yield and he expeced price as measured by fuures markes. GRIP was developed by IGF Insurance Company and firs sold in In 2004, NAU Companies developed and inroduced an opional endorsemen o GRIP called he Harves Revenue Opion (HRO). 1 The HRO endorsemen urns GRIP ino a GRP policy when he harves price is greaer han he expeced price. Any producion losses under he resuling GRP policy are valued a he harves price. Availabiliy of he HRO endorsemen corresponds o a dramaic increase in acreage insured under GRIP. Insured acreage more han doubled in 2004, doubled again in 2005, and doubled ye again in 2006, when a oal of 11.7 million acres were insured. 2 For he firs ime, an area plan of insurance now ranks among he mos widely used crop insurance producs. 3 In Illinois, 37% of he insured corn acres were insured under GRIP in 2006, compared o 28% insured under Crop Revenue Coverage (CRC) and 22% insured under Revenue Assurance (RA). In 2003, he GRIP marke share was less han 2% for Illinois corn. The incenives o buy and sell GRIP are high. The average 2006 premium of a GRIP-insured corn acre in Illinois was $46.36 compared o approximaely $26 per acre 1 As a noe of disclosure, Bruce Babcock was involved as a consulan wih he developmen and raing of GRIP and GRIP-HRO. 2 Only 18% of he increased GRIP acreage is accouned for by he 2004 expansion in he number of saes able o offer GRIP and he 2005 expansion o coverage of grain sorghum, coon, and whea. Illinois, Indiana, Iowa, Michigan, and Ohio had GRIP in 2003 and accoun for 82% of he acreage increase. 3 Acreage insured under GRP in 2006 oaled 34.1 million, bu only 2.6 million acres of crops were insured. The res of he insured acreage was in forage and rangeland. 4

7 for RA and CRC, he nex wo highes-premium producs. The average premium subsidy rae for GRIP is 55%, which means ha corn farmers paid less han $21 per acre of he $46-per-acre insurance premium. If GRIP is acuarially fair, hen farmers paid $21 for an expeced ne (of premium) gain of $25. This compares o a ne gain of abou $13 under RA and CRC assuming acuarial fairness. The $20-per-acre addiional premium from GRIP (relaive o RA and CRC) means ha agen commissions under GRIP are also higher han under RA and CRC, unless heir commission raes under GRIP are much lower han for oher producs. Prior o 2004, he incenives o buy and sell GRIP wihou he HRO endorsemen were much lower. The average premium in Illinois on corn acreage insured under GRIP in 2003 was $23.37, which was nearly idenical o he premium colleced for RA and CRC in Thus, neiher agens nor farmers had an increased incenive o seek ou an alernaive produc. The dramaic increase in GRIP usage demonsraes ha many farmers recognize ha an area plan of insurance offers sufficien risk managemen benefis. Overall, coninued adopion of GRIP should improve he acuarial performance of he crop insurance program as adverse selecion and moral hazard are reduced. Bu he dramaic growh in acres insured under GRIP raises imporan policy quesions. Because GRIP indemniies can be riggered by low prices, GRIP can duplicae coverage provided by markeing loans and counercyclical paymens available o producers of program crops in U.S. commodiy programs. Producers pay an average of only 45% of he insurance premium for GRIP, and hey are given free farm bill pu opions under he markeing loan and counercyclical programs. This suggess ha 5

8 reconciliaion of he wo programs would increase efficiency as measured by he program cos per dollar of producer risk managemen benefi. This raises he more fundamenal policy quesion of wheher GRIP should be par of he crop insurance program or par of he farm bill. As noed by Miranda and Glauber (1991), an area revenue program provides cos-effecive suppor for farmers faced wih recurring low prices or low yields. Farmers who purchased GRIP before 2004 were purchasing a Miranda-Glauber area revenue program. This suggess ha pre-2004 GRIP could provide an effecive Miranda-Glauber farm bill safey ne program. Farm bill commodiy programs and crop insurance commodiy programs share he objecive of giving financial suppor o farmers. However, Congress has mandaed differen mechanisms for accomplishing his objecive. Farm bill commodiy programs are adminisered hrough he Farm Service Agency, and hey are made available o farmers a minimal adminisraive cos. Crop insurance commodiy programs are adminisered hrough a public-privae parnership beween he Risk Managemen Agency, crop insurance companies, and crop insurance agens. Farmers mus pay a porion of program coss. Ineres is growing in adoping a Miranda-Glauber syle of area revenue plan as he basis for farm bill commodiy programs. For example, Babcock and Har (2005) showed how an area revenue plan can be designed o help he Unied Saes achieve proposed limis on commodiy suppor as par of he Doha Round negoiaions in he World Trade Organizaion. American Farmland Trus (2006) has proposed moving o an area revenue program as par of an overhaul of U.S. farm bill programs. Addiionally, he 6

9 Naional Corn Growers Associaion is working wih an area revenue plan as he basis for heir 2007 farm bill proposal. One consideraion in choosing wheher o run GRIP as a farm bill program or a crop insurance program is he cos and effeciveness of meeing program objecives. Expeced program coss for GRIP in he crop insurance program include easily calculaed A&O reimbursemens and premium subsidies and he more difficul o calculae expeced underwriing gains and expeced indemniies, which require sochasic models for analysis. Expeced program coss of GRIP as a farm bill program equal expeced paymens. In his paper, we esimae hese coss for GRIP for corn and soybeans in he hree saes where GRIP was firs inroduced: Illinois, Indiana, and Iowa. To esimae hese coss, we documen and use he raing procedures ha were used o originally rae GRIP. These procedures are direcly conducive o esimaing expeced underwriing gains under he curren Sandard Reinsurance Agreemen (SRA). We find ha, on average, he per-acre axpayer cos of supporing GRIP in is curren form as a crop insurance produc is equivalen o he expeced paymens ha would be generaed by a Miranda-Glauber area revenue farm bill program ha guaranees couny revenue a a coverage level of a leas 93%. Mehodology The procedures used o rae GRIP and GRIP-HRO are presened below. The resuling premium raes may differ from curren GRIP raes because RMA now uses a smoohing echnique o reduce rae variaions across couny boundaries, and he degree of correlaion beween yields and prices in his sudy are based on a differen ime period han when GRIP raes were calculaed. 7

10 Daa The daa used in he analysis include GRP corn and soybean rend yield daa for Iowa, Illinois, and Indiana counies from 1957 o NASS yield daa for corn and soybeans over he same ime period were also colleced for each couny in hese hree saes, as well as a he naional level. Acual raes used in he hird scenario were he presmoohed 2005 GRIP-HRO premium raes for corn and soybean coverage for each couny in he included saes ha were provided o RMA by NAU Companies. 5 Chicago Board of Trade (CBOT) corn and soybean price daa from 1975 o 2004 were also used in he analysis. Imposing Correlaion Using he yield and price deviaes 6 for U.S. corn and soybean yields and CBOT corn and soybean price daa, he hisorical correlaion srucure of he deviaes was examined over hree differen ime periods. The correlaion srucures calculaed from 1975 o 2005 and 1980 o 2005 showed a lower level of (negaive) own-price correlaion han did he same measure from 1990 o The Pearson correlaion coefficien beween he percen deviaion in U.S. corn yield from rend and he percen change in he December fuures price from spring o fall is for he period 1975 o 2005, for he period 1980 o 2005, and for he period 1990 o The sronger relaionship beween yield and 4 GRP rend yields are calculaed by he Risk Managemen Agency (RMA). The rend yield is he level used for he yield guaranee porion for area yield and revenue coverage policies (i.e., GRP, GRIP, and GRIP-HRO). 5 This paper focuses on GRIP-HRO as a crop insurance program insead of GRIP because he HRO opion is seleced by mos farmers. In addiion, we assume ha farmers choose he maximum liabiliy and coverage level because his reflecs curren program preferences. For example, in McLean Couny, Illinois, 96% of corn farmers who purchased GRIP did so a he 90% coverage level, and of hese, approximaely 90% purchased he HRO opion. The average percenage of maximum liabiliy seleced was 90%. These esimaes were calculaed using RMA s Summary of Business daa. 6 The yield deviaes were calculaed as he percen deviaion from rend. The price deviaes were calculaed as he percen change in price from he spring o he fall for he December fuures conrac. 8

11 price levels can be explained by changes in farm policy saring wih he 1995 farm bill, which increased price responsiveness by reducing he role of governmen in sockholding aciviies (Lence and Hayes, 2002). The more recen correlaion srucure from 1990 o 2005 was chosen for use in he analysis assuming i would more accuraely reflec boh curren and fuure price-yield relaionships. The U.S. corn and soybean yield deviaes from rend from 1957 o 2004 were verically concaenaed 500 imes, yielding 24,000 yield deviae draws from he empirical yield disribuion (Goodwin and Ker, 1998; Ker and Coble, 2003; Vedenov e al., 2004). The empirical disribuion mainains he acual hisorical correlaion srucure beween U.S. corn and soybean yields for a large number of yield realizaions wihou relying on a poenially misspecified parameric form for he marginal yield disribuions (i.e., he bea disribuion). Using a re-soring mehod oulined by Iman and Conover (1982), he empirical yield draws were correlaed wih wo sandard uniform draws o mach he hisorical rank correlaion marix from 1990 o The corn and soybean yield deviae draws were no re-sored in he process o preserve he year-o-year realizaions for he corn and soybean yield deviaes. The sandard uniform draws were hen ransformed o harves price draws assuming lognormaliy, a mean corn price of $3.75, a mean soybean price of $7.00, a corn price volailiy of 27%, and a soybean price volailiy of 20%. 7 Tables 1a and 1b repor he hisorical rank correlaion marix for U.S. corn and soybean yields and prices, and he rank correlaion marix for he corn and soybean yield deviaes and price draws, respecively. The re-soring mehod (Iman and Conover) does an excellen job of 7 The corn and soybean price levels and volailiies were based on he selemen of he December 2007 corn and November 2007 soybean fuures and opions conracs on December 21,

12 replicaing he hisorical correlaion srucure. The correlaion marix of he yield and price draws and he arge hisorical correlaion marix differ by a maximum of Table 1a. Rank correlaions for U.S. corn and soybean yields and prices, Corn Yield Soybean Yield Corn Price Soybean Price Corn yield 1 Soybean yield Corn price Soybean price Table 1b. Rank correlaions for corn and soybean yield and price draws Corn Yield Soybean Yield Corn Price Soybean Price Corn yield 1 Soybean yield Corn price Soybean price Empirical Yield Disribuions Naional Agriculural Saisics Service (NASS) couny-level yield daa for corn and soybeans were derended o 2004 equivalens ( de y ) following Vedenov e al. (2004). This was done by dividing each couny yield observaion ( y ) by he corresponding GRP rend yield ( 2004 rend yield level ( r y ) for he same year and couny. The yield raio was hen muliplied by he r y 2004 ) for ha couny. y de y r = y2004, for = (1) y r The derended couny-level yield daa were hen verically concaenaed 500 imes, providing 24,000 yield realizaions from he 48-year empirical yield disribuion for each couny in Iowa, Illinois, and Indiana. Each row (year) of he derended corn and soybean 8 An excepion is he correlaion beween corn and soybean yields. To ensure ha he yield deviaes were no re-sored (i.e., o preserve he rue empirical disribuion) in he process, he arge correlaion beween corn and soybean yields was se o he acual rank correlaion of he 24,000 yield deviaes (0.50). This differed from he rank correlaion beween corn and soybean yields from 1990 o 2004 (0.65). 10

13 realizaions corresponds o he corresponding row of he empirical disribuion for U.S. corn and soybean yield deviaes. Thus, he rank correlaion beween corn and soybean yield deviaes and prices a he naional level is preserved, while he relaionships beween couny yields and prices are carried hrough by means of he relaionship beween couny and naional yield levels. Reenion of he cross-couny and cross-crop yield correlaions is crucial for conducing valid reinsurance analysis. GRIP-HRO Policy Disribuions Couny-level disribuions of GRIP-HRO indemniies were hen calculaed using he empirical couny yield disribuions and correlaed price draws. GRIP-HRO indemniies in any year are based on a rigger revenue ( TrigRev HRO ) ha is equal o he produc of he coverage level (C), he GRP rend yield for he couny, and he maximum of he expeced harves price level aken from CBOT fuures ( EP [ ]) and he acual price realizaion a harves ( P ). The sandard GRIP policy uses a similar rigger revenue srucure ( TrigRev level. GRIP ), excep he price componen is equal o he expeced harves price HRO r TrigRev = C * y *max[ E[ P ], P ] (2a) GRIP r TrigRev = C * y * E[ P ] (2b) An indemniy ( Indem ) is paid if acual revenue a harves ( AcRev ), defined by he produc of acual yield ( y ) and acual harves price, falls below he rigger revenue. Indemniies ( Indem ) are calculaed based on a percen loss ( % loss ) muliplied by he liabiliy level ( Liab ). The liabiliy level is he produc of he couny rend yield, he expeced harves price, and a liabiliy facor (L), which was se equal o 1.5. The percen 11

14 loss is equal o he maximum of zero and he difference beween he rigger and acual revenue levels divided by he rigger. AcRev = y * P (3) r Liab = L * y * E[ P ] (4) TrigRev AcRev % loss = max,0 TrigRev (5) Indem = % loss * Liab (6) Couny premium levels ( Prem ) were calculaed by muliplying 2005 GRIP-HRO raes ( HROrae 90% ) a a 90% coverage level by he liabiliy levels for he corresponding counies for boh corn and soybean coverage. Disribuions of gross underwriing gains ( GrossGain ) a he couny level were calculaed as he difference beween he indemniy realizaions and premium levels for each couny. Loss raio disribuions ( LR ) were also calculaed as he raio of indemniy realizaions o premium level. Prem = HROrae Liab (7) 90% * GrossGain = Prem Indem (8) LR Indem Prem = (9) The couny-level disribuions for gross underwriing gains, indemniies, and loss raios were hen aggregaed across counies and crops for each sae o define a single disribuion for each variable a he sae level, which is he level used o calculae underwriing gains and losses under he SRA. Corn and soybean premium levels were also aggregaed o define a sae-level premium for each of he hree saes in he analysis. 12

15 The aggregaion was done wih a weighed average using 2005 NASS daa on planed acres for corn and soybeans as he weighs. The sae-level premiums and each realizaion from he indemniy and loss raio disribuions were hen run hrough he SRA o deermine heir effec on he underwriing gains of privae crop insurance providers. The GRIP-HRO policies for each sae were allocaed o he Commercial Fund wihin he SRA. Ne underwriing gains ( NeGain ) and ne loss raios ( NeLR ) are defined as he underwriing gains and loss raios resuling from reinsuring he GRIP-HRO policies under he SRA hrough he Commercial Fund. 9 The ne loss raio is he raio of gross premium less underwriing gains o he gross premium. NeLR Prem NeGain Prem = (10) The expeced ne subsidy ( NeSub ) paid by he Federal Crop Insurance Corporaion (FCIC) (axpayer cos) was hen calculaed as he sum of premium subsidy ( PremSub ), adminisraive and operaing coss (A&O), 10 and he expeced ne underwriing gains for he crop insurance companies. NeSub = ( PremSub + A& O)* Prem + NeGain (11) The yield and price disribuions were hen used wih equaions (2b) and (3)-(6) o calculae he coverage level for a GRIP policy ha, when offered o farmers for free as par of a farm bill program, would resul in axpayer coss equivalen o hose implied by 9 Please refer o he 2005 Sandard Reinsurance Agreemen (FCIC, 2005) for an explanaion of how underwriing gains are calculaed. The quoa share requiremen whereby 5% of oal underwriing gains and losses are ceded back o USDA were no accouned for in his analysis because naional aggregae gains and losses from a company s enire book of business would need o be calculaed. 10 The premium subsidy and A&O coss for 90% GRIP policies are 55% and 19.1% of gross premium, respecively. 13

16 he ne premium subsidy and gross underwriing gains for he curren GRIP-HRO program. This was done by finding he GRIP coverage level a which he average indemniy is equal o he expeced axpayer cos of GRIP-HRO a 90% coverage. The axpayer cos ( TPCos ) was calculaed as he ne premium subsidy less he gross underwriing gains for GRIP-HRO as a resul of FCIC providing reinsurance hrough he SRA. Taxpayer coss are calculaed as a percenage of gross premium for reporing purposes. TPCos NeSub GrossGain Prem = (12) Noe ha he expeced value of gross underwriing gains is equal o zero for an acuarially fair policy. However, we use a larger level of negaive own-price correlaion for corn and soybeans han was used o originally rae GRIP and GRIP-HRO. Thus, he acual GRIP-HRO raes were no acuarially fair in our analysis. 11 We repor resuls for hree differen scenarios in he following secion. The firs scenario uses he acuarially fair raes implied by he simulaion model (premium se equal o he average indemniy paymen for each couny); he second scenario uses he fair raes muliplied by he acual loading facors used by RMA; 12 and he hird scenario uses acual GRIP-HRO raes for he 2005 crop year. 11 Furhermore, if he variabiliy of couny average yields when measured as a percenage of rend yield is now lower han in he pas, hen GRIP is over-raed. Over-raing means ha expeced underwriing gains will be higher han calculaed in his analysis. 12 RMA uses load raes of 15% and 12% for corn and soybean policies, respecively. 14

17 Resuls Scenario 1: Acuarially Fair Raes Table 2 repors he model resuls when premiums are se equal o he average indemniies over he simulaions. The premiums repored in he firs row represen he average premium for corn and soybeans across all counies in he hree saes, weighed by 2005 planed acres (NASS). Noe ha he expeced ne loss raio for he aggregaed book of business is reduced from uniy o 0.90, while he expeced underwriing gains increase from zero o $4.54 per acre, or 9.73% of premium, under he SRA. The expeced cos borne by axpayers, assuming fair premiums, is esimaed o be $39.45 per acre, or 84% of gross premium. Table 2. Loss raios and underwriing gains for 90% GRIP-HRO, fair premiums Iowa Illinois Indiana Aggregae Premium Gross loss raio Ne loss raio Gross gain Ne gain 0 (0%) 4.74 (9.8%) 0 (0%) 4.61 (9.7%) Taxpayer cos (0%) 4.20 (9.4%) Noe: Premiums, underwriing gains, and axpayer coss are repored in $/acre (% of premium). 0 (0%) 4.58 (9.7%) $39.45 (84.0%) Figures 1 and 2 illusrae he disribuion of aggregae gross and ne loss raios, respecively. 13 Gross loss raios are runcaed from below a zero, by definiion, and 13 Figures displaying he disribuions of gross and ne loss raios, underwriing gains, and axpayer coss a he sae level for all hree scenarios are available upon reques from he auhors. 15

18 follow a righ-skewed disribuion wih a maximum of The loss-raio spikes in Figure 1 represen he large losses ha occur in paricular years over he sudy period. For example, he spike of realizaions wih loss raios beween 4.4 and 4.8 corresponds o he 1988 Corn Bel drough. The peaks a loss raios beween 2.5 and 3.2 correspond o he 1974, 1979, 1983, and 1993 crop years. Shown in Figure 2, he Commercial Fund of he SRA has a significan effec on he disribuion of loss raios by capping he maximum ne loss raio a 2 and he minimum ne loss raio a Frequency Gross Loss Raio Figure 1. Disribuion of gross loss raios, fair premiums 16

19 Frequency Ne Loss Raio Figure 2. Disribuion of ne loss raios, fair premiums The disribuions of per-acre gross and ne underwriing gains are repored in Figures 3 and 4, respecively. Gross underwriing gains follow a skewed disribuion, which is runcaed from above a 100% of gross premium. 14 The SRA ighens he disribuion of underwriing gains by capping ne underwriing losses a 100% of he gross premium and ne underwriing gains a 50% of gross premium. Wih fair premiums, gross underwriing losses have an expeced value of $50.33 per acre (107% of premium) and are esimaed o occur one ou of every hree years. Gross underwriing gains are realized roughly wo ou of every hree years, wih an expeced gain equal o $28.32 per acre (60% of premium). A ne underwriing loss occurs wih a 31% probabiliy and an 14 While he heoreical maximum underwriing gain is 100% of he gross premium, here are no realizaions when no indemniies are paid in he aggregaed book of business. The maximum realizaion in our simulaion model was a 99.8% gross underwriing gain. 17

20 Frequency Gross Underwriing Gains (%) Figure 3. Disribuion of gross underwriing gains, fair premiums Frequency Ne Underwriing Gains (%) Figure 4. Disribuion of ne underwriing gains, fair premiums 18

21 expeced value of $21.94 per acre. Ne underwriing gains average $16.40 per acre and are esimaed o occur wih a 69% probabiliy. Figure 5 illusraes he disribuion of he cos o axpayers of a fairly raed GRIP- HRO program. Taxpayer coss range from $10.90 o $ per acre, or 23% o 620% of gross premium. The simulaion resuls imply ha he GRIP-HRO program coss axpayers more han 100% of gross premium ($47.05 per acre) one ou of every four years. Frequency Taxpayer Cos ($/acre) Figure 5. Disribuion of axpayer coss, fair premiums Scenario 2: Loaded Fair Raes In pracice, RMA loads GRIP raes above heir acuarially fair levels. The jusificaion for hese loads is o accoun for unforeseen risks ha have no been accouned for in he 19

22 formal raing model and o help insurance companies build a reserve load o cover large loss years. Table 3 repors he resuls of he model using he fair premiums implied by he simulaion model wih he acual loading facors applied. Under his scenario, privae insurers are esimaed o reduce heir expeced loss raio from 0.87 o 0.86 and o increase heir expeced underwriing gains from $6.73 o $7.76 per acre, or 12.5% o 14.4% of oal premium, by reinsuring under he SRA. Esimaed axpayer coss average $40.88 per acre, or 76% of gross premium. Because of higher premium raes, underwriing gains are larger han in he firs scenario, which, in urn, increases expeced axpayer coss. Table 3. Loss raios, and underwriing gains for 90% GRIP-HRO, loaded premiums Iowa Illinois Indiana Aggregae Premium Gross loss raio Ne loss raio Gross gain Ne gain 6.88 (12.5%) 8.05 (14.6%) 6.81 (12.5%) 7.84 (14.4%) Taxpayer cos (12.4%) 7.00 (13.8%) Noe: Premiums, underwriing gains, and axpayer coss are repored in $/acre (% of premium) (12.5%) 7.76 (14.4%) (76.0%) The shapes of he disribuions (no repored) of underwriing gains, loss raios, and axpayer coss wih loaded fair premiums closely resemble hose given in Scenario 1. Gross underwriing gains and losses wih loaded raes range from a maximum loss of $ per acre (558% of premium) o a maximum gain of $53.70 per acre (99.8% of premium), while he disribuion of ne underwriing gains is runcaed beween a 100% 20

23 loss and a 50% gain under he provisions of he Commercial Fund of he SRA. Gross underwriing losses average $54.44 per acre and occur wih a probabiliy of 29%. Gross underwriing gains occur 71% of he ime wih an expeced gain of $32.18 per acre. Reinsurance reduces he probabiliy and expeced value of underwriing losses o 28% and $22.64 per acre, respecively. Ne underwriing gains are esimaed o occur more han hree ou of four years wih an average value of $19.66 per acre (37% of premium). Esimaed axpayer coss range from 23% o 524% of gross premium ($12.45 o $ per acre) wih coss exceeding 100% of premium in 20% of he simulaions, or once every five years. Scenario 3: Acual 2005 GRIP-HRO Raes Table 4 repors he resuls of he simulaion model when he acual 2005 GRIP-HRO raes were used for premium calculaion. This scenario would be expeced o replicae acual GRIP performance wihin he curren crop insurance program. Using acual raes, he aggregaed per-acre premium for 90% GRIP-HRO coverage was equal o $61.49, while he expeced gross loss raio and underwriing gains equal 0.77% and 23% respecively. Our simulaion model implies ha he acual GRIP-HRO raes may be, on average, 30% higher han acuarially fair raes and 14% higher han loaded fair raes. By reinsuring, privae insurers are esimaed o achieve an expeced ne loss raio and underwriing gain of 0.81% and 19% ($11.55 per acre), respecively, for heir aggregaed book of business. Esimaed axpayer coss average approximaely 69.4% of gross premium, or $42.68 per acre. 21

24 Table 4. Loss raios and underwriing gains for 90% GRIP-HRO, acual premiums Iowa Illinois Indiana Aggregae Premium Gross loss raio Ne loss raio Gross gain Ne gain (22.9%) (18.8%) (24.4%) (19.2%) Taxpayer cos (22.8%) (17.8%) Noe: Premiums, underwriing gains, and axpayer coss are repored in $/acre (% of premium) (23.4%) (18.8%) (69.4%) Insurance companies are esimaed o give up $2.88 per acre (4.7% of premium) in underwriing gains o he FCIC while increasing heir expeced loss raio by This resul differs from hose of Vedenov e al. and he previous scenarios whereby he SRA is esimaed o increase underwriing gains and decrease loss raios. This is aribued o he non-proporional reamen of gains and losses under he SRA and he 2005 GRIP-HRO raes being acuarially unfair wihin our simulaion model. Again, he shapes of he disribuions of underwriing gains, loss raios, and axpayer coss are very similar o hose oulined in he scenario wih fair premiums and are no repored. Gross underwriing gains range from a maximum loss of $ (475%) o a maximum gain of $61.40 (99.8%) per acre. Gross underwriing losses occur wih a probabiliy of 27% wih an expeced loss of $52.19 per acre. Gross gains average $38.48 per acre, or 63% of gross premium. Reinsurance reduces he probabiliy of a loss by 2%, and he expeced size of a loss o $23.02 per acre. Ne underwriing gains average $23.37 per acre (38% of premium) and are esimaed o occur hree ou of every four 22

25 years. Simulaed axpayer coss range from $14.22 o $272 per acre, or 23% o 442% of gross premium. Consisen wih he oher scenarios analyzed, axpayer coss are esimaed o exceed oal premium roughly once every five years. Cos Equivalen GRIP Coverage The cos of adminisering GRIP as a Miranda-Glauber disaser relief program is equal o he GRIP indemniy because here are minimal loss adjusmen coss. Using equaions (2b) and (3)-(6), indemniies for a sandard GRIP policy were calculaed over a range of coverage levels from 70% o 110%. Figure 6 plos he expeced indemniy paymen for each GRIP coverage level. The curren GRIP-HRO program a a 90% coverage level and a 150% liabiliy facor was esimaed o cos axpayers $39.45, $40.88, and $42.68 in scenarios 1, 2, and 3, respecively. Given he expeced indemniies in Figure 6, a GRIP program a a coverage level beween 92% and 94% and a liabiliy facor of 100% would resul in he same expeced per-acre cos o axpayers. This program could be offered o farmers in he form of a Miranda-Glauber disaser relief farm program a an equivalen axpayer cos o insuring he same acreage under GRIP-HRO. However, here would be imporan disribuional impacs of providing GRIP as a farm bill program. Providing GRIP-HRO coverage o farmers as a crop insurance program provides farmers wih a significanly smaller ne benefi han providing GRIP in he farm bill because producers mus pay a porion of he premium in he crop insurance program. As shown in Tables 2 and 4, producers mus pay $27.67 (45% of $61.49) o obain an expeced indemniy of $ Thus, producers ne benefi is $ However, if GRIP were par of he farm bill, producers would obain he full ne benefi of $42.68 per acre, an increase of 120%. The difference beween $42.68 and $19.38 is wha flows 23

26 o he crop insurance indusry in he form of expeced underwriing gains and A&O. Tha is, under he crop insurance program, here is a spli in axpayer suppor, wih 55% going o he crop insurance indusry and 45% going o producers. If GRIP were moved o he farm bill, all he axpayer suppor would flow o producers. $100 $90 $80 $70 Cos ($/acre) $60 $50 $40 $30 $20 $10 $ Coverage Level (%) Figure 6. Expeced cos of GRIP a various coverage levels The second disribuional impac involves axpayers. Alhough axpayer coss would be he same, by definiion, he variabiliy of cos is higher when GRIP is in he farm bill raher han in he crop insurance program. The sandard deviaion (coefficien of variaion) of esimaed axpayer coss in scenarios 1, 2, and 3 were esimaed o be $28.24 (72%), $26.81 (66%), and $25.44 (60%) per acre, respecively. The sandard deviaion (CV) of indemniies for a 93% GRIP farm program was esimaed o be $47.55 (113%). 24

27 Therefore, while a GRIP disaser program providing 93% coverage is esimaed o be cos equivalen o he 90% GRIP-HRO insurance program, coss would also be more volaile. The decrease in he volailiy of axpayer coss from providing GRIP as a crop insurance program raher han as a farm bill program is he crop insurance indusry s primary jusificaion for he subsidies ha hey receive in he crop insurance program. They argue ha i is fair for hem o share in he gains if hey are required o share in he losses. The quesion hen becomes, a wha cos o axpayers? Using he scenario 3 resuls, wih a 25% probabiliy, axpayers gain an average of $23 per acre from he SRA s risk-sharing provisions. However, axpayers pay for his benefi 75% of he ime hrough posiive underwriing gains paid o insurance companies. The average paymen from axpayers o companies in hese years is jus over $23 per acre. Puing hese gains and losses ino insurance erms, axpayers essenially receive an insurance payou from he SRA 25% of he ime. The average payou in hese years is $23 per acre. Muliplying he probabiliy by he average size of he payou in he years in which a payou occurs resuls in he overall expeced indemniy (axpayer benefi) from he SRA. This muliplicaion resuls in an expeced indemniy of $5.75 per acre. The premium ha axpayers pay for his insurance is he overall average underwriing gain paid o crop insurance companies, which is $11.55 per acre in scenario 3. This insurance program has an expeced loss raio of less han 0.5 (5.75/11.55), which means ha he annual expeced rae of reurn ha crop insurance companies obain from puing heir money a risk is more han 100%. Anoher way o look a he SRA s effec on he coss of adminisering GRIP is ha axpayers are effecively acceping a gamble ha pays ou a given amoun wih a 25% probabiliy bu creaes a loss in he 25

28 same amoun 75% of he ime. One would hope ha if axpayers knew ha hey were paying 100% expeced raes of reurn on money being pu a risk by crop insurance companies, hey migh argue ha heir money could be pu o beer use in deb reducion or offseing oher program coss. Of course, he underwriing gains paid o crop insurance companies are par of he financing for a 93% Miranda-Glauber area revenue program in he farm bill. If axpayers kep he underwriing gains and financed he area revenue program wih only producer premium subsidies and A&O expenses, hen he amoun of coverage ha could be offered on a cos-equivalen basis would be approximaely 88%, as shown in Figure 6. Conclusions The expeced cos of running GRIP hrough he crop insurance program in 2007 is approximaely $42.68 per acre for corn and soybeans in Iowa, Illinois, and Indiana. If every acre planed o corn and soybeans in 2006 were insured under GRIP in hese hree saes (55.4 million acres), he expeced cos would be $2.36 billion per year, making i by far he mos expensive farm program of all curren programs. However, farmers would only receive approximaely $1.1 billion of his amoun wih he res going o he crop insurance indusry. If he purpose of he crop insurance program is o provide suppor o producers, i would be difficul o design a more inefficien ransfer sysem. Compare he cos of delivery of his sysem o one in which a pre-2004 GRIP policy ha covered 93% of he produc of expeced price and expeced couny yield was given o farmers. The cos of adminisering his policy would be minimal, so farmers would be receiving one dollar in ne paymen for each dollar of axpayer cos. 26

29 Alhough no explicily examined here, our conclusions abou he division of axpayer suppor for crop insurance beween producers and he insurance indusry are applicable o farm-level insurance programs such as RA and CRC. If a similar analysis were conduced for hese programs, he spli of axpayer suppor would be even more skewed o he indusry and away from farmers because he expeced underwriing gains and A&O would be larger. Much of he increased A&O suppor for farm-level insurance programs would cover loss adjusmen coss raher han agen commissions. As noed by many, a Miranda-Glauber ype of farm program, of which GRIP is simply an example, offers farmers significan risk managemen benefis because i riggers paymens when sysemic risk srikes a crop or a region, and i provides a ransparen and auomaic disaser aid mechanism. Because he program arges revenue raher han price, i would cover risks no currenly covered by curren markeing loan and counercyclical programs, as well as risks currenly covered by crop insurance. Therefore, i could be financed from savings from curren farm programs and he curren crop insurance program. These cos savings perhaps creae a large obsacle o adopion of such an approach. The large and growing ax suppor of he crop insurance indusry has creaed srong vesed ineress of some poliical consiuencies who will ac o proec hese ineress. 27

30 References American Farmland Trus Agenda 2007: A New Framework and Direcion for U.S. Farm Policy. American Farmland Trus, Washingon, DC. Babcock, B.A., and C.E. Har How Much Safey is Available under he U.S. Proposal o he WTO? CARD Briefing Paper 05-BP 48, Cener for Agriculural and Rural Developmen, Iowa Sae Universiy. Barne, B. J., J. R. Black, Y. Hu, and J.R. Skees Is Area Yield Insurance Compeiive wih Farm Yield Insurance? Journal of Agriculural and Resource Economics 30: FCIC (Federal Crop Insurance Corporaion) Sandard Reinsurance Agreemen. U.S. Deparmen of Agriculure. Available online a hp:// Glauber, J Double Indemniy: Crop Insurance and he Failure of US Agriculural Disaser Policy. Working paper, American Enerprise Insiue. Goodwin, B.K., and A.P. Ker Nonparameric Esimaion of Crop-Yield Disribuions: Implicaions for Raing Group-Risk Crop Insurance Conracs. American Journal of Agriculural Economics 80: Halcrow, H.G Acuarial Srucures for Crop Insurance. Journal of Farm Economics 21: Iman, R. and W. Conover A Disribuion-Free Approach o Inducing Rank Correlaion Among Inpu Variables. Communicaions in Saisics B11 3: Ker, A.P., and K. Coble Modeling Condiional Yield Densiies. American Journal of Agriculural Economics 85: Lence, S.H., and D.J. Hayes U.S. Farm Policy and he Volailiy of Commodiy Prices and Farm Revenues. American Journal of Agriculural Economics 84(2): Miranda, M.J Area-Yield Crop Insurance Reconsidered. American Journal of Agriculural Economics 73: Miranda, M. J., and J. W. Glauber Providing Crop Disaser Assisance hrough a Modified Deficiency Paymen Program. American Journal of Agriculural Economics 73:

31 Skees, J.R., J.R. Black, and B.J. Barne Designing and Raing an Area Yield Crop Insurance Conrac. American Journal of Agriculural Economics 79: Vedenov, D.V., M.J. Miranda, R. Dismukes, and J.W. Glauber Economic Analysis of he Sandard Reinsurance Agreemen. Agriculural Finance Review 64(2):