Diersen, Matthew

Dodson, Tia

English

Research Papers in Economics

            E C O N O M I C S 
   C O M M E N T A T O R 
South Dakota State University      No. 506                              February 27, 2009
 
INSURING CORN, 
SOYBEANS, AND WHEAT 
_____________ 
Contact the authors at matthew.diersen@sdstate.edu or tia.dodson@sdstate.edu or either at 605-688-4141. 
 
 
by 
 
Matthew Diersen 
Associate Professor 
 
Every year brings another round of crop insurance 
choices.  For the 2009 crop year the change in price 
limits on revenue products makes a revisit of the 
product type choice vital to making sound risk 
management decisions.  Market conditions also affect 
what products may look attractive and what coverage 
level would best fit the needs of individual farms.   
 
Crop insurance is widely used on the major crops in 
South Dakota.  In 2008 producers purchased $3.8 
billion of coverage on corn, soybeans, and wheat.  
Insurance is a major input cost as producers paid $264 
million in premiums (after subsidies of 58%) for 
coverage, which is over $22 per acre on major crops.  
Revenue coverage has dominated the product choice 
in recent years.  Production problems that would have 
caused insured losses were limited last year, but price 
declines resulted in indemnity payments of $334 
million. 
 
What follows are analyses of recent insurance trends 
for corn, soybeans, and wheat and of aspects to 
consider when choosing coverage now and when 
marketing crops later in the year. 
 
Corn Choices 
Producers have overwhelmingly insured corn using 
Revenue Assurance (RA) over the past decade (figure 
1).  Typically they include the Harvest Price Option,  
labeled RA-HPO, meaning the maximum indemnity 
(Continued on page 2) 
  
YIELD RATIOS 
AND INCOME 
 
                by 
 
Tia Dodson 
Research Associate 
 
As the time to purchase crop insurance approaches, I 
thought I would take this opportunity to introduce 
myself and share some results of my graduate 
research.  I am a new research associate in the 
Economics department having recently moved to 
Brookings from California where I worked as a policy 
analyst for UC Berkeley’s Institute for Transportation 
Studies.  Prior to living in Berkeley, I was studying 
agricultural economics and political science at 
Colorado State University. 
 
This research is timely because it involves making 
strategic insurance decisions.  It was conducted in 
Colorado in response to some discontent among 
wheat growers who were experiencing increasing 
premiums.  The study closely examined the premium 
calculation to uncover important characteristics that 
affect the cost of insurance.  The results of the 
research demonstrate the premium calculation’s affect 
on different groups of producers and suggests ways to 
optimize insurance choices. 
 
Insurance is meant to be reflective of risk, meaning 
the riskier the operation the higher the premium.  
From the insurers’ standpoint, predicting and 
estimating risk can be difficult. To assess the 
accuracy of insurance, a common measurement is 
employed by which the total collected premium is 
divided by total indemnities paid.  In the short run, 
this ratio may be larger or smaller than one, but  
(Continued on page 3)    
 
(Insuring Corn …  continued from page 1)  
can increase with harvest price increases.  RA was 
first offered in 1999 and quickly replaced Crop 
Revenue Coverage (CRC), a competing revenue 
insurance product.  Use of yield only products, based 
on Actual Production History (APH) has also steadily 
given way to use of RA.  Typically producers have 
found RA-HPO to cost less per acre at desired 
coverage levels compared to buying CRC.  In 
addition, subsidized premiums help make revenue 
insurance less expensive than obtaining similar 
protection by combining APH products with put 
options. 
0.0
1.0
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08 07 06 05 04 03 02 01 00 99
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Source: USDA-RMA
Figure 1. Corn by Coverage  Type
CRC RA APH
 
Beginning with the 2009 crop year the price limits for 
RA-HPO and CRC are now the same at 200% of the 
projected harvest or base price.  The features of the 
two products on corn are more similar than they were 
in the past.  Having a price limit reduces the 
maximum level of coverage of RA-HPO and should 
lower the premiums.  The price limit is changed from 
a fixed dollar amount for CRC with an ambiguous 
change to the premiums.  The result is the relative 
cost of the two product types could change and 
disrupt the historic heavy use of RA for corn.  The 
two types now provide the same coverage except for 
using a different month to compute the harvest price. 
 
CRC will continue to settle to the October average of 
the December futures price.  RA-HPO will continue 
to settle to the November average of the December 
futures price.  Prior to 2006, this difference mattered 
very little (table 2).  Small price changes between 
October and November tended to average out quickly.  
However, harvest prices have been relatively high and 
more volatile in recent years.  In 2006 the corn 
revenue insurance products had a beginning price 
election level of $2.59 per bushel.  CRC coverage 
finished with a price election of $3.03 per bushel and 
RA-HPO finished at $3.56 per bushel.  Similar 
changes were observed in 2007 and 2008. Thus, 
producers with contracts or hedges to be lifted earlier 
(later) in the harvest period may favor CRC (RA-
HPO).  However, the cost difference should also be 
considered. 
 
Table 1. Price Election Levels on Corn 
 
 
Year 
Base or 
Projected 
Price 
CRC 
Harvest 
Price 
RA-HPO 
Harvest 
Price 
2004 2.83  2.05  1.99 
2005 2.32  2.02  1.93 
2006 2.59  3.03  3.56 
2007 4.06  3.58  3.80 
2008 5.40  4.13  3.74 
Source: USDA-RMA 
 
Volatility has not been confined to harvest time.  The 
spring volatility level (used to set the premiums for 
revenue insurance) has increased in recent years.  
Corn price volatility historically fluctuated around 
20%, but rose steadily since 2006 to 30% in 2008.  
Thus, more futures price movements were expected 
between the time insurance was established and 
finally settled at harvest.  For 2009 the early volatility 
estimate is 37%.  So even though the base or 
projected price election is similar to 2007, at $4.04 
per bushel, the higher volatility means higher 
premiums.  For perspective, the increase in volatility 
would more than double the cost of an at-the-money 
option on corn futures compared to when volatility 
was lower. 
 
Soybean and Wheat Choices 
Producers may recall some substantial shifts across 
product types for soybeans (figure 2).  In 2002 the 
price election level on yield insurance products was 
higher than for revenue insurance products, leading to 
a pronounced spike in APH coverage.  In 2009 the 
price election levels are similar across product types.  
The revenue price election is $8.80 per bushel for 
2009.  RA has dominated the type choice the past few 
years.  Producers that used CRC on soybeans in 2008 
saw coverage limited by the fixed limit move.  
Because RA-HPO and CRC have the same harvest 
period calculation dates and now the same price  
 
limits, producers can readily select the coverage type 
with the lowest cost. 
0.0
1.0
2.0
3.0
4.0
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08 07 06 05 04 03 02 01 00 99
A
c
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Source: USDA-RMA
Figure. 2. Soybean by Coverage  Type
CRC RA APH
 
Insuring wheat is a little more complex when looking 
at aggregated activity in South Dakota.  Both winter 
and spring wheat are covered with various ending 
dates, different price election levels and insurance 
periods.  CRC is more commonly used further west.  
RA is more commonly used on spring wheat.  
Producers have also continued to use APH coverage 
because the cost of revenue coverage is relatively 
high as a percent of all wheat production costs.  
Producers of spring wheat that used CRC in 2008 had 
indemnity payments limited by the old price limit on 
that coverage.  The price election level on 2009 
spring with for APH at $8.77 per bushel is much 
higher than the level for revenue products at $6.20 per 
bushel.  Thus, a shift to APH would be likely for 
some spring wheat producers, especially for those that 
do little pre-harvest marketing. 
 
Summary 
The major price changes in 2009 will likely cause 
producers to again consider their optional insurance 
coverage.  The change in the limits on revenue 
products is an added incentive to actively study which 
product will be the most cost effective.  The desired 
coverage level and type of unit structure will also be 
important considerations.  After insurance is 
purchased, concentrating on marketing can resume.  
Without the unlimited protection that RA-HPO used 
to provide, prudent producers will be looking at 
making covered sales in 2009.  That implies that any 
forward sales or hedges be covered by the purchase of 
inexpensive call options. 
***************************************** 
Yield Ratios … (continued from page 1) 
averaged over several years the loss ratio should be 
close to one.  For years this indicator showed that 
insurance was paying out more than it was collecting 
(Goodwin, 1994).   To provide premium estimations 
that are more accurate, RMA established a class 
rating system and then instituted a continuous base 
rating system in 2001 (Schnapp, 2006). 
 
The cost structure was changed from a discrete model 
to a continuous rating system, whereby a producers’ 
individual risk is estimated.  The discrete, or class 
rating system grouped producers into set categories 
based on their actual production history (APH) and 
assigned a premium based on these groups.  The 
continuous base rating system uses an individual 
producers’ yield ratio to determine relative risk. The 
yield ratio is a producers’ APH divided by the current 
year’s county average.  In general, if a producer’s 
APH is above the county average that producer is 
viewed as less risky.  The opposite is true for 
producers with an APH below the county average.  
Because this risk estimation directly affects the cost 
of the insurance, producers above the county average 
are paying less for insurance than producers that are 
below the county average.  The magnitude of the 
difference in premium depends on the insurance. 
Three different types of insurance products were 
included in the study, Actual Production History 
(APH) insurance, Revenue Assurance (RA), and Crop 
Revenue Coverage (CRC). 
 
The effects of crop insurance were demonstrated by 
using a simulation that calculated net revenue for a 
model farm in Eastern Colorado.  The main variables 
in the revenue model were premium and indemnity 
levels, thereby examining cost and payoffs from 
insurance.  Yields and prices were stochastic to 
capture appropriate levels of variability. Two 
scenarios demonstrated the difference in yield ratios.  
Scenario I was a farm with yields consistently above 
the county average and scenario II was a farm below 
the county average. 
 
By only adjusting the county average the simulation 
was akin to taking a producer and putting him/her in 
two different counties, one where the producer has 
yields lower than the county average and one where 
the producer has yields higher than the county 
average. This approach ensures that the two scenarios  
 
can be compared because the insured amount and 
yield variability are the same across scenarios. 
 
The resulting calculation of net revenue took into 
account the costs and benefits of each insurance 
option.  The insurance options were ranked using a 
stochastic dominance test, which is used to rank risky 
alternatives (Richardson 2006). Stochastic 
dominance, with respect to a function, assumes a risk 
averse personality so if a producer takes on additional 
risk they must be compensated more.  The rankings of 
product types and yield election levels are presented 
in the following table.  Note that for scenario I RA at 
the 65% level is the dominant insurance choice.  For 
Scenario II CRC at the 65% level is preferred, while 
APH and the benchmark of no insurance are also 
highly ranked choices.  These rankings are not 
prescriptive but are meant to illustrate the effect a 
producer’s relative risk position can have on the cost 
and therefore the effectiveness of insurance. 
 
Stochastic dominance rankings 
Level of Preference 
Scenario I 
(high) 
Scenario II 
(low) 
Most preferred  RA 65  CRC 65 
2nd most preferred  CRC 80  APH 65 
3rd most preferred  RA 80  CRC 80 
4th most preferred  CRC 65  Benchmark 
 
For counties like those in Eastern Colorado, there can 
be considerable variation in yields resulting from 
rainfall variability and differences soil type and 
quality.  In general, South Dakota counties are 
smaller and likely less variable than counties in 
Colorado, so the effects of the yield ratio are not 
likely to be as extreme.  This effect, though, is still 
something to be aware of.  A change in relative 
position, dropping below the county average or rising 
above the county average, may signal a need to 
reevaluate insurance decisions by pricing alternatives 
and weighing differences in price against changes in 
coverage. 
 
References 
Goodwin, B. K. “Premium Rate Determination in the 
Federal Crop Insurance Program: What do 
Averages Have to Say About Risk?” Journal of 
Agricultural and Resource Economics 
19(1994):382-395. 
Richardson, J. W., K. D. Schumann, P. A. Feldman. 
“Simulation and Econometrics to Analyze Risk.” 
2006 Simetar Users Manual. 
Schnapp, F. and L. Jansonius. "Continuous Rating". 
National Crop Insurance Services. 2 March 2006 
<www.agrisk.org/NCISPUBS/LAIPPUB/Art1200
.htm>. 
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htm>.

Premium Rate Determination in the Federal Crop Insurance Program: What do Averages Have to Say About Risk?”

Simulation and Econometrics to Analyze Risk.”

Insuring Corn, Soybeans, and Wheat; Yield Ratios and Income

http://repec-sda.sdstate.edu/repec/sda/pdf/Commentator/No506.pdf

Insuring Corn, Soybeans, and Wheat; Yield Ratios and Income

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