The Risk-Rating Model is designed to give extension specialists, teachers, and producers a method to analyze production, marketing, and financial risks. These risks may be analyzed either individually or simultaneously. The risk associated with each enterprise, for all combinations of enterprises, and for any combination of marketing strategies is estimated. Optimistic, expected, and pessimistic returns above variable cost and/or total cost are presented in the results. The probability that total return will be equal to or greater than variable cost and/or total cost is also estimated.Farm Management, Risk and Uncertainty,

Anderson, Kim B.

Ikerd, John E.

English

Research Papers in Economics

SOUTHERN JOURNAL  OF AGRICULTURAL  ECONOMICS  JULY,  1985
WHOLE  FARM  RISK-RATING  MICROCOMPUTER  MODEL
Kim  B.  Anderson  and John E.  Ikerd
Abstract  pected  outcomes  are  titled  optimistic.  An
optimistic rating may be  assigned to a favor- The  Risk-Rating  Model  is designed to give able  outcome  at  the  one-sixth  probability extension  specialists,  teachers,  and produc-le  u  e  te  o  o  six  the  actual ^  i  '  '  . ^level.  Thus,  one  time  out  of six the  actual ers  a method to analyze  production,  market-  . . es  a  m  d to  aalye p  tio,  m  t  yield, price, or net return will be higher than ing, and  financial  risks.  These  risks  may  be  iii  i  . i the  optimistic  estimate.  In  a  normal  distri- analyzed  either  individually  or  simultane-
ly  The  ris  a  iated  ith  eac  enter-  bution, the optimistic value  is the mean plus
ously.  The  risk  associated  with  each  enter-  one standard  deviation. one  standard  deviation. prise, for all combinations of enterprises,  and  i  '^~  ~  ~  'i...~  c  i.An  expected rating may be  assigned to the for any  combination  of marketing  strategies  . most  likely outcome.  There  is  a  50  percent is estimated.  Optimistic,  expected,  and pes-  p  t  t  o  '..^  .i  '  ^  probability that the outcome will be less than simistic  returns  above  variable  cost  and/or the expected value, and there is a 50 percent total  cost are  presented  in  the  results.  The  a  i  . '5  probability that the outcome  will be greater probability that total return will be equal  to than the  expected  value. or greater than variable cost and/or total cost  W 
~is aI~so  estimated.  Worse-than-expected  outcomes are labeled
pessimistic.  A pessimistic  rating  may be  as-
Key  words:  risk,  production,  marketing,  fi-  signed to an unfavorable  outcome at the one-
nance,  enterprise,  whole-farm  sixth  probability  level.  Thus,  one  time  out
analysis.  of six the  actual  yield,  price,  or  net return
will  be  less  than  the  pessimistic  estimate.
Risks  associated  withThe  pessimistic value is the mean minus one Risks  associated with  an enterprise,  com-  standard  deviation
binations of enterprises, and combinations of  The  assumption  that  the expected  net re-
marketing  strategies  are  treated  by  a  Risk-  turn is distributed  normally facilitates  com-
Rating Model. Optimistic, expected, and pes-  bining  the  expected  total  returns  for  a
simistic  returns  above  variable  cost  and/or  marketing  strategy  containing  cash  sales
total  cost  are  presented  in the  results.  The  hedging,  forward contracts, and/or basis con-
probability that the total return will be equal  tracts  and  interpreting  the  results  as  opti-
to or greater  than variable  cost and/or total  mistic,  expected,  and pessimistic.  Assuming
cost is  also  estimated.  The  model also  facil-  that yields and net returns  are  normally dis-
itates the  comparison  of the outcomes from  tributed  simplifies  the  calculation  process.
alternate  production,  marketing,  and  finan-  The optimistic, expected and pessimistic val-
cial decisions.  ues are used to calculate the means and stand-
ard  deviations  for the prices  and yields.
THEORETICAL  FOUNDATION  Prices  are  assumed  to  have  a  log  normal
distribution.'  The  mean  return  is calculated
Each situation  is described,  and results are  by  multiplying  expected  price  times  ex-
presented  in  risk  rated  terms.  These  terms  pected yield. The variance of the product of
are  optimistic,  expected,  and  pessimistic  a  log  normal  and  a  normal  distribution  can
(Ikerd and Anderson,  1983).  Better-than-ex-  be  calculated  using the  following  equation
Kim B. Anderson  is an Extension Economist and Assistant  Professor,  Oklahoma State University,  and John E. Ikerd
is  Professor  and Head  of Extension Agricultural  Economics,  University of Georgia.
Microcomputer  software  articles  are  approved  by the  SAEA  microcomputer  software  committee  and the  SJAE
editorial  council,  as per Executive  Committee  action  February  5,  1984.
This model  was  developed  by the  Southern  Extension Joint  Farm  Management  and Marketing  Risk  Task  Force.
Partial  funding was  provided  by the  Farm  Foundation.
'A  review of the  literature indicated  no fundamental justification  for  selecting  a distribution for expected  price.
The  log-normal  distribution  was  recommended  by  Dr.  Richard  Anderson,  statistician  and  author.  The  normal
distribution could  have been  used.
183(Anderson  et al.,  pp.  32-38):2  terprises  are permanently  stored  on disk.  In
(1)  Vpy=  (Up)2  X  ((Vy)  +  (Uy2 X  Vp)  addition,  temporary  data  from  the  last  run
(1)  Vpy  J  are stored. At the beginning  of each analysis,
X  2COVpy),  the user may permanently change the default
where:  values.  During  the  run,  the  user  may  tem-
porarily change  any value.  An  example  data
Vpy  =  variance  of  log  price  times  yield  input  screen  for  a  wheat  enterprise  is  pre-
=  return variance,  sented in Table  1.
Up  =  mean price,  Users  are  required  to estimate  optimistic,
Vp  =  variance  of log price,  expected, and pessimistic prices and yields.3
Vy  =  variance  of yield,  and  Prices must be estimated for cash prices,  and
Uy  =  mean yield.  if alternate selling methods are used, the basis
and  the  forward  contract  price  must be  es- The  mean  and  variance  for  the  sum  of  timated.  The  futures  price  includes  the  fu- normal distributions are calculated  using the  tures contract price; the optimistic  expected
following  equations:  and pessimistic  bases;  and the contract  cost.
(2)  Ur  =  Uri,  If a basis contract is used, the expected basis
is  required  as  well  as  the  optimistic,  ex-
where:  pected,  and  pessimistic  contract  price.  The
Ur  =  expected  return  user  may  specify  one  or  a  combination  in-
Uri  =  return  from  decision  i.  cluding  any  or  all  selling  options  for  each
commodity.
(3)  Vr  =  EVi  +  2(ZECOVij)  i  Z j  Yields  are  estimated  as  optimistic,  ex-
r  V,  pected,  and pessimistic  for crops.  With live-
where:  stock,  the  standard  deviation  of  yield  is
Vr=  variance  of joint returns,  calculated based on optimistic, expected, and
Vi  =  variance from decision i  pessimistic  estimates  of average  daily  gain
=  variance decision  and death  loss.  Variable  cost  is assumed  to COVij  =  covariance  of  decisions  i
CO  i  and i  i  of  dbe  constant for crops but is variable for live- and i,  i  #  j.  stock. stock.
Itemized production  cost per unit must be
DATA  REQUIREMENTS  entered.  The  interest  cost for  an  operating
loan  is  calculated  from  a  specified  percent
Data  for  five  crop  and  one  each  of  cow-  of operating  capital that is borrowed  and an
calf, stocker, feeder, dairy, farrow-feeder hog,  interest rate. Fixed cash costs may be entered.
feeder-finish  hog,  and  farrow-finish  hog  en-  Fixed  costs  are  totaled  and included  in the
TABLE  i.  WHEAT  ENTERPRISE  DATA  FILE  EXAMPLE,  RISK-RATING  MICROCOMPUTER  MODEL
Crop risk section  Date:  April  11,  1983
Number of acres ................................................  80.00  Expected yield/acre ....................................  32.00
Percent crop  hedged  . .......................................  50.00  Optimistic yield  (1  in  6) ................................  40.00
Hedge  price  . . .....................  4.05  Pessimistic  (1  in  6)  ........................................  24.00
Expected  basis..................................................  -0.25  Dollar of nitrogen/acre ......................................  18.00
Pessimistic  (1  in  6)  ......................................  -0.35  Dollar of mixed fertilizer/acre............................  10.00
Optimistic  (1  in 6) .......................................  -0.10  Dollar of lime/acre .................................  .......  0.00
Hedge  cost ..................  ......................  0.04  Dollar of seed or plants/acre ..............................  6.00
Percent  crop sold  by basis contract  ....................  0.00  Dollar of chemical/acre ...................................  5.00
Expected  contract  price  . .....................................  3.60  Dollar of fuel  and oil/acre .................................  15.00
Optimistic  (1  in 6) ........................................  3.90  Dollar repairs/acre..............................................  5.00
Pessimistic  (1  in  6) ........................................  3.30  Dollar  of marketing  and harvesting/acre .............  22.00
Percent crop  forward  contracted  ........................  0.00  Percent  operating capital  borrowed....................  80.00
Contract price ....................................................  3.50  Interest  rate .....................................  15.00
Average  price/unit ..............................................  3.80  Fixed cash  cost.............................................  0.00
Optimistic  (1  in 6) ........................................  4.10  Relationship:  yield-price ...................................  -0.25
Pessim  istic  (1  in  ) ........................................  3.50  : cash price-basis  ........................................  0.00
Enter,  arrows,  tab moves  cursor  (>)  F1  accepts  data  F2  prints screen
2Equation  (1)  is a transformation  of the  equation presented in Anderson  et al. 3Symmetric  estimates  are  not  required.  The  model  determines  and  uses  the  average  difference  between  the
optimistic  and expected  values  and the pessimistic  and expected  values.
184whole  farm  section.  obtaining the specified percent return to  eq-
The  correlation  between  price  and  yield  uity.  Users  must  provide  estimates  of  the
and  the  cash  price  and  the  basis  may  be  correlation  between  enterprises.
accounted  for by entering a number between  The  results  in the Whole  Farm section  in-
-1  and  1. If the  correlation  is  not  known,  elude the expected total return, the expected
a  zero  may be  entered.  total  variable  cost  and  the  expected  fixed
cost. The whole-farm  analysis includes  a sec-
tion to analyze  the risk  impact of additional
nterprise  Results  loans. Whole-farm results include optimistic,
Results  for  an  enterprise  include  the  ex-  expected,  and pessimistic returns above  var-
pected  total  return,  expected variable  cost,  iable  cost  and  also  above  total  cost.  The
fixed  cost,  optimistic,  expected,  and  pessi-  probability that total returns will be  greater
mistic  net  returns  above  variable  cost,  and  than  or  equal  to  variable  and total  costs  is
the  probability  that  total  returns  will  be  also  estimated.
greater  than  or  equal  to  variable  cost.  The
probabilities  are  calculated  by  using  the
properties of the normal distribution. An ex-  IMPLICATIONS  FOR  EXTENSION,
ample of a results screen is presented in Table  TEACHING  AND  PRODUCER  USES
To  analyze  each  type  of risk  individually
TABLE  2.  RESULT  SCREEN  FOR  WHEAT  1,  RISK-RATING  or  all  risks  simultaneously,  producers  need
MICROCOMPUTER  MODEL  to  understand  relatively  complex  relation-
ships.  For example,  they must be capable  of
Crop risk section  Date:  April  11,  1983  estimating yield risk, price risk,  and interest
Results for:  Wheat  1  Total  Per  acre
The  expected  total returns  are  .......  9,344  117  rate  variability.  The  relationships  between
The  expected  variable  costs  are......  7,250  91  price and yield,  and between  enterprises  or
The  expected  fixed  cash  costs are..  80  1  activities  must  also  be  understood  and  esti-
Returns above  variable  cost
Optimistic  =  9344  mated.  This is taught by using the model  to
Expected  =  2,086  concentrate  on production,  marketing,  or fi-
Pessimistic  =  -5,791  nancial  risks.
The probability of total returns  being >=  variable cost  The  model  may be  used  to teach users  to
is 60 percent  identify data requirements  to make risk man-
Press - SPACE  BAR  next activity  F1  to  redo this  one
F2  print screen  ESC to  combine  activities  agement  decisions.  Yield and price  outlook
accuracy  estimates  are  presented  as  guide-
If more  than  one  crop  or  livestock  enter-  lines.  Users  are taught  that data  may be  ob-
prise is included in the analysis,  the user has  tained  from  many  levels  of sophistication.
the  option  to combine  the  net  returns.  The  Producers  may use data from farm records to
correlation between individual enterprise net  make  risk-rated  estimates.  Even  estimates
returns  must  be  entered.  If there  is  no cor-  based on a producer's  memory may be used.
relation  or  if the  correlation  is  not known,  The quality of data is probably less important
a zero  may be entered.  The combined results  than teaching the procedure,  and results us-
are  displayed  in the  same  format as  a single  ing  "best guesses"  are better  than  what has
enterprise.  been  previously  used.
WHOLE  FARM  ANALYSIS  PRODUCTION  RISK
The  user  is  asked  to  enter:  (a)  total  fixed  Production  risk  is  the  probability  of low
cost,  (b)  dollar value of all assets,  (c)  dollar  yields or of high cost per unit of production.
value  of whole  farm  debt,  and  (d)  percent  The risk model has been used to teach farmers
required return to equity. The total fixed cost  or students to predict yields or cost per unit
may be  the annual  fixed  loan payments  or a  of production  as  optimistic,  expected,  and
value  that  includes both cash  and  non-cash  pessimistic rather than predicting just an av-
fixed costs.  erage  yield or  cost per unit of production.
The  dollar value of all assets and of whole-  After  risk  has  been  identified,  approaches
farm  debt  is  used  to  calculate  equity.  This  to reduce  production  risk have been  taught.
value  is used to determine the probability of  Risk-reducing production methods have been
185taught  by  using  traditional  budgeting  cost  seem  more  willing to  accept  the  benefit  of
and return  methods or by increasing  the var-  production,  marketing,  and  financial  strate-
iable  cost in the  risk-rating  model.  Analyses  gies  if the results  are  summarized  by a few
have also been used that show the risk impact  interpretable  numbers.
of  complementary  and  competitive  enter-
prises. prises.*^~~~  ~FIELD  TESTING
MARKET  RISK  The  model  has  been  successfully  used  to
teach  risk  management  and  the  impact  of
Producers  tend to  understand  production  production, marketing,  and finance decisions
risk  and  the  impact  of  low  yields  on  net  on net return. The  situations  included class-
returns.  But,  marketing  risk  appears  to  be  room teaching, producer seminars, and para-
different.  Producers are  shown the results of  professional workshops.  Area  extension  spe-
studies  that  estimate  the  accuracy  of  price  cialists  and  county  extension  agricultural
predictions.  The  risk-rating  model  is  then  agents  in  Connecticut,  Kansas,  Mississippi,
used  to  demonstrate  the  potential  effect  on  Missouri,  Oklahoma,  and  Virginia  are  using
net return of various marketing strategies and  the  Whole  Farm  Risk-Rating  Model  in  edu-
how these  decisions fit into whole-farm  risk  cational  programs.  Professionals  and  para-
situations.  professionals  have  been  taught  to  use  the
The  effect  of  risk-reducing  strategies  is  model  to help  answer  producers'  questions
demonstrated  by  presenting  the  results  as  and solve production,  marketing,  and  finan-
optimistic, expected, and pessimistic returns.  cially  related  problems.  Producers  use  the
For example,  to reduce  risk, the potential for  model  to  assist  them  in  making  decisions
a  large return  is usually sacrificed to reduce  involving risk. Producers and other users have
the  probability  of  a  potentially  large  loss.  not  had  problems  using  the  risk  model  or
However,  if risk  is managed,  it is possible to  the  risk-rated  management  approach.
increase production while reducing risk, thus  Producers  attending  the  risk-rating  work-
increasing expected returns without  increas-  shops were asked to estimate  the probability
ing risk.  that the risk-rated approach would help them
understand  the  nature  of the decisions  they
FINANCIAL  RISK  face  in  agriculture  (Ikerd  and  Anderson,
1984).  Results  indicated  an  average  proba-
Financial  risk  occurs  at  two  levels:  (1)  bility of 77 percent that this approach would
individual enterprise  level in the form of an  help them make  better decisions.  Producers
operating loan, and (2) intermediate  and long-  indicated  an  average  probability  of  80 per-
term  loans.  Operating  loans are  included  in  cent that they would use risk-ratings  in mak-
the  partial  budget  for  each  enterprise.  The  ing  decisions.
user  may  manipulate  both the  interest  rate  The  evaluation  from county agent in-serv-
and the percentage  of operating  capital  bor-  ice training produced  a rating of 80 percent
rowed. Intermediate and long-term debt com-  that  they would  use  the  risk-rated  approach
mitments  may be  included  at the enterprise  to decisionmaking  and the whole farm com-
or whole-farm  levels.  puter program.  County agents and producers
The  risk-rating  model  demonstrates  how  both  responded  that  the  model  helped  to
different  levels  of debt and interest  rates  af-  identify  the  types  of  information  that  are
fect  net return.  Once  producers understand  needed to  make  more  efficient  decisions.
the impact  of debt on  returns,  they may be
taught  the  importance  of reducing  or  man-  HARDWARE  AND  SOFTWARE
aging debt. The value of records  may also be  REQUIREMENTS
taught.
Combining  the  returns  into  a  whole-farm  This  model  is  programmed  and  a  users
net  return  facilitates  teaching  the  relation-  manual  is  available  for  TRS  80 'Model  II,
ships  between  production,  marketing,  and  Model 12, or Model 16 (Anderson and Ikerd).
financial  risks.  Moreover,  the  relationships  The  model is also programmed for the Apple
(competitive  or  complementary)  between  IIe  (configured  with 64K  and Microsoft  CP/
enterprises  are  presented  in  a  manner  that  M)  and computers  using MS/DOS.  The  pro-
producers  can  understand.  Also,  producers  gram  is  free  to  all  land-grant  universities.
186There  is  a  $50  charge  for  producers.  The  (land-grant  universities  must  supply  a  for-
model may be obtained by writing the authors  mated  disk).
REFERENCES
Anderson,  Jock  R.,  John  L. Dillon,  and  Brian  Hardaker.  "Agricultural  Decision  Analyses."
Ames,  Iowa:  The  Iowa  State  University  Press,  1977.
Anderson,  Kim  B.  and John  Ikerd.  "Whole  Farm  Risk-Rating  Model  User's  Manual."  Coop-
erative  Extension  Circular,  E-829,  Oklahoma  State  University,  Stillwater;  September,
1983.
Ikerd, John  E.  and  Kim  B.  Anderson.  "Risk-Rated  Management  Strategies  for  Farmers  and
Ranchers."  OSU  Extension  Facts,  No.  159.  Oklahoma  State  University  Cooperative
Extension  Service,  Stillwater,  1983.
Ikerd, John  E. and Kim  B. Anderson.  "Teaching  Risk-Rated Management  Strategies to Farmers
and Ranchers."  (Unpublished  paper  presented  at: Workshop  for Extension  Specialists
on Marketing,  Risk and Financial Management;  April 4,  1984, Minneapolis,  Minnesota).
A.E.  Paper  8443,  Department  of Agricultural  Economics,  Oklahoma  State  University,
1984.
187188

Agricultural Decision Analyses.&quot;

Risk-Rated Management Strategies for Farmers and Ranchers.&quot;

Teaching Risk-Rated Management Strategies to Farmers and Ranchers.&quot; (Unpublished paper presented at: Workshop for Extension Specialists on Marketing, Risk and Financial Management;

WHOLE FARM RISK-RATING MICROCOMPUTER MODEL

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Research Papers in Economics