Pittman, Jerold F.

Wells, Gary J.

English

Research Papers in Economics

SOUTHERN  JOURNAL  OF  AGRICULTURAL  ECONOMICS  DECEMBER,  1980
ASSESSMENT  OF THE  PRICE IMPACT  OF  THE
SOUTH  CAROLINA  CUCUMBER  MARKETING  ORDER
Gary J. Wells and Jerold F. Pittman
In 1970 a marketing order, made possible by  Price  posting  probably  has  enhanced  the
a  1968  state  enabling  act,  was  formed  for  price  discovery  process  for  producers  by
South  Carolina  fresh market cucumbers.  This  reducing  the  number  of  price  changes.  If  we
legislation is similar to current  federal legisla-  assume  that  South  Carolina  cucumber  prices
tion, but South Carolina has no federal market-  are determined as part of a national cucumber
ing order for cucumbers.  Order provisions that  market  which  is  competitive,  price  posting
affect price  formation  are  the  subject  of this  within  South  Carolina  should  reduce  the
article. Price posting and adoption of statewide  frequency  of South Carolina price changes but
USDA inspection  requirements  are  the  order  not substantially alter the price determination
provisions  that  yield  the  largest  and  most  process. Less frequent price changes should re-
direct  price  impact  (S.C.  Cucumber  Board.)'  flect  changed  market  conditions-mainly
The apparent goal of these provisions is higher  shifts in the supply curve-more accurately be-
and more stable prices.  cause market participants have more time and
The objective of our research  is to investigate  more  information  for  making  adjustments.
the  success  of  the South  Carolina  marketing  Therefore,  the dynamic price  adjustment  pro-
order in achieving its goal of higher and more  cess has been altered within South Carolina by
stable fresh market cucumber prices.  the price  posting  provision,  and a  reasonable
A brief description  of the price posting and  hypothesis is that price  variability is reduced
inspection  provisions  is  followed  by informa-  for South Carolina cucumbers.
tion  about  the  order's  mandatory  grower  Another  force  is  present,  however,  which
assessments.  A  model  and  empirical  results  tends to increase price  variability.  For example,
are presented.  if a series of numbers are doubled the variance
is increased  by a  factor  of four.  Therefore  if
price posting increases the price level, the vari-
PRICE  POSTING,  INSPECTION  ance tends  to increase.  It is reasonable  to hy-
PROVISIONS,  AND  GROWER  pothesize  that  within  the  limits  of  national
ASSESSMENTS  price  movements  the average  South Carolina
price level for cucumbers will increase with the
The  price  posting  provision  of  the  South  increased  availability  of price information.  In-
Carolina  Cucumber  Marketing  Order  enables  flation also  increases  the price  variability.  A
the S.C.  Cucumber  Board to require  handlers  relative variability measure is used to compen-
"to  file at the  office  of the Board a  complete  sate for this mechanical aspect of the increased
schedule  of  prices  at which  each  handler  will  variability.  Therefore,  given  more  accurate
quote,  offer for sale,  or sell cucumbers  during  searching  out  of a  new  equilibrium  price,  in-
the regulated  period"  (S.C.  Cucumber  Board,  creased market information, and compensation
p.  4).  The Cucumber Board in return provides  for the mechanical  increase  in variability,  rea-
each  handler  with  a  current  list  of  prices  sonable  hypotheses  seem  to  be  that  the  net
posted by all handlers.  Growers also can obtain  effect of the order's price provision is to reduce
access  to this price  information.  Handlers  are  the  price  variability  in  relation  to  what  it
allowed  to  revise  their  posted  prices  after  would have been otherwise and to increase the
giving at least two hours notice to the Board.  price level for South Carolina cucumbers.
The  regulations  do  not  cover  cucumbers  of-  In  addition to price  posting,  the marketing
fered at auction or shipped on consignment.  order requires uniform USDA inspection of all
Gary J. Wells is Assistant Professor and Jerold F.  Pittman is Professor,  Department of Agricultural Economics,  Clemson University.
Technical Contribution  No. 1852 from the South Carolina Agricultural Experiment Station.
'Other provisions  of the order are (1) packaging, (2)  labeling,  (3)  advertising, (4)  research,  (5) control of unfair competition,  (6)  market development,  (7) educational programs,  and (8)  regulation  of the selling period. Some or all of these provisions could possibly  influence prices, but many  are not functional and others are given only token attention.
15cucumbers sold in South Carolina.  The inspec-  MODEL
tion provision effectively  prevents  the sale  of
culls, and should therefore have a direct impact  A  straightforward  before-and-after  analysis
on  average  prices  if  the  marketing  of  lower  is used to estimate the impact of the marketing
cucumber  grades  is  prevented.  However,  we  order  on  the price  level.  The  prices  of  fresh
believe the direct impact of preventing the sale  market  cucumbers  in  South  Carolina  are
of below-grade  cucumbers  is relatively  minor  hypothesized to depend on production in South
for South  Carolina  producers.  Before uniform  Carolina,  real  income,  prices  of  cucumbers
grading  and inspection  most  cucumbers  that  from adjoining states  sharing market  seasons
would  be  classified  as  culls  are  sorted  and  with South Carolina, the month within the har-
dumped.  Probably  the major  price  impact  of  vest  season,  and  the  implementation  of  the
mandatory inspection is the result of increased  marketing order.2 That is
uniformity  of  pack.  Without  inspection,
growers who do provide a uniform  pack  often  (1)  PSC = f(PROD, GNP, OP, MO, ORDER)
do not receive maximum prices because buyers
lack  cucumber  quality  information.  This  in-  where
direct inspection impact will influence the price
level primarily  by preventing  the sale  of lots  PSC = S.C.  cucumber  price,  by  month,
suspected  to contain  below-grade  cucumbers.  $/cwt
These mixed  lots tend to drive buyers  out  of  PROD = S.C.  production  by season,  1000
the region,  thereby penalizing growers provid-  cwt
ing  uniform  lots.  The  penalty  appears  as  a  GNP = U.S.  real gross national product,
break  in  the  market  price.  Therefore  the  $B
primary impact of uniform USDA inspection is  OP = other  prices,  $/cwt;  during  May-
hypothesized  to  be  a  higher  price  level  for  July  OP  =  North  Carolina's  cu-
South Carolina cucumbers.  Inspection will also  cumber price  and during August-
affect price variability as a result of the change  November OP = Virginia's cucum-
in price level,  but the adjustment to the vari-  ber price
ability mentioned  before will also compensate  MO = 1 if May,  2 if June,  3 if July,  4  if
for this change.  September,  5 if October,  6 if No-
In the following empirical analysis we do not  vember
attempt  to  separate  the  impacts  of  price  ORDER= 1 after  adoption  of  the  pricing
posting  from  those  of implementing  grading  provision of the order, zero other-
standards.  Instead, the net price impact of the  wise.3
formation and operaton of the marketing order
is investigated.  The choice of South  Carolina production  by
Other  aspects  of  the  marketing  order  that  season is expected,  but the other independent
should  be considered  are  grower  assessments  variables  need to be justified.  U.  S.  real gross
and inspection  fees.  Each grower  is charged  a  national  product  is used  because  South  Caro-
per-bushel  fee by  the order.  The  assessments  lina  cucumbers  flow  into the national  market
provide the funds necessary to administer and  chain  and therefore  the demand  is  influenced
staff the  order  and  to carry  out  order  provi-  by consumers  in more than one  region  of the
sions  such  as  advertising.  The  assessments  country. Prices from neighboring producing re-
have  a direct impact on net prices. They  have  gions are used in lieu of national prices because
been levied by the Board since  1970 and have  of the problems of forming an appropriate  na-
ranged  from  zero  to  5 cents  per  bushel,  the  tional  price  measure  and  because  prices  in
maximum  assessment  allowed.  The  assess-  nearby states should better reflect trends that
ment has generally been lower  for the fall har-  would  affect  the  entire  production  region.
vest than for the spring harvest.  In addition to  North Carolina  and Virginia  are among South
paying the grower assessments,  growers must  Carolina's  major  competitors  during  the
pay for the USDA inspection.  As a large pro-  spring  and  fall  harvests,  respectively.  The
portion  of cucumbers  were  inspected  prior to  month  variable  is  included  to  capture  the
order  formation,  this  order  provision  has  an  downward trend in prices observed as the har-
impact only through additional inspection fees.  vest season draws  to a close.  This  type linear
Any success by the marketing order in increas-  time trend is discussed by Draper  and Smith
ing grower  prices  therefore  must be adjusted  (p.  137-8).  The  formulation  of  the  variable
by the amount of the assessment and the addi-  ORDER  is based  on the assumption  that the
tional inspection fees.  impact  of order formation occurs  at one point
'Price flexibility developed by Houck suggests  that other quantities instead of other prices should  be used as an independent  variable.  In our application,  consis-
tent quantity data were not available for many production regions; therefore,  the other price variable is used as a proxy.
'Various interactions and slope shifts were utilized for the season and the ORDER variables, but the formulation in equation 1 was found to reflect best the forma-
tion of the marketing order.
16in time. Given  the nature of the provisions  of  PRICE  VARIABILITY  ANALYSIS
the  South  Carolina  marketing  order,  this
assumption  is  plausible.  Ordinary  least  The hypothesis  of reduced  price  variability
squares  estimation of equation  1 is presented  was investigated by means of two measures of
in the next section.  variability.  The standard  deviation  and  coef-
ficient  of  variation  are  calculated  for  several
variables  for the periods  before  and  after the
EMPIRICAL  RESULTS  formation  of the order. These variables  are (1)
the before  and  after monthly  prices,  (2)  error Equation  1 was  estimated  by  means  of  terms from before and after regression estima-
regression  analysis.  Data  from  1960  to  1978  tions  of equation  1, i.e.,  without the ORDER
were  used  in  the  analysis.  PSC  values  were  term,  (3) average before and after prices for the
taken  from  the  S.C.  Crop  and  Livestock  Re-  spring  and  fall  crops,  i.e.  average  seasonal
porting  Service,  PROD  and  OP  values  from  prices,  and  (4)  before  and after  within-season
various  USDA publications,  and GNP  values  average price  for South Carolina  in relation to
from the Commerce Department.  The primary  the North Carolina  price during spring and in
objective  of the estimation  was to investigate  relation to the Virginia price during fall (Table
the impact of the formation of the South Caro-  1).  Both the standard deviation and coefficient
lina  marketing order  on  the price  level  of cu-  of variation are presented because the hypothe-
cumbers marketed in the state. The estimated  sized price  level increase and inflation tend to
equation is  inflate the standard deviation.  The coefficient
of variation  is the standard  deviation in rela- (2)  PSC = 5.47 -. 0083*PROD + .236*GNP +  tion to the mean, and in essence adjusts for the
(.002)  (.136)  increase  of the  standard  deviation  caused by
higher prices.  Several authors  discuss the use
.471*OP -. 639*MO + 1.07*ORDER  of the coefficient of variation as an appropriate
(.069)  (.138)  (.537)  measure  of  the  relative  variability  in  such
cases  (e.g.,  Snedecor  and  Cochran,  p.  62-5;
R= .73  (standard errors are  in parenthe-  Sanders,  Murph,  and Eng,  p.  84-5).  The  coef-
ses).  ficient of variation declined after order forma-
tion for each  of  the four variables  considered
Each  estimated  coefficient  is  significant  at  (Table 1).  In contrast, three of the six standard
the 10 percent level or better, and each variable  deviations  increased,  indicating  greater
has the expected sign. The results indicate that  absolute variability (Table  1). Two of the three
the marketing order has had an impact of ap-  standard  deviations that increased  applied  to
proximately $1.07 per 100 pounds on the price  nominal  price  measures  whereas  the  third
South Carolina  producers  receive for their cu-  applied to the error term of an equation with a
cumbers.  To obtain this price increase, produc-
ers  pay  assessments  of  up  to  10  cents  per  FOR  A  T
hundred  weight  (5 cents  per bushel).  In addi-  1.  BE  E  ND  ATER  .C.
tion, USDA inspection fees must be paid on all  CUCUMBER MARKET ORDER
cucumbers sold within the state. The addition-  FORMATION  COMPARISONS
al  inspection  charge  is  difficult  to determine  OF  CO  FICIENSTF  VARI
because  some  cucumbers were inspected  priorATION  FOR  FOUR
to  formation  of  the  order,  but  it  would  not  CUCUMBERPRIDEVREIA
negate the estimated  gain. Therefore,  we con-
VARIABLES clude  that  formation  of  the  South  Carolina 
marketing order for cucumbers has had a posi-  AcrossMonths  Ag. win  Sp  n  o  .S.  Fall Std.  Coeff.  Std.  Coeff.  Std.  Coeff.
tive impact on the price level for growers.  Dev.  Variation  Dev.  Variation  Dev.  Variation
As an additional check on the price impact of  I.  Monthly  Price
order formation,  an F-test was conducted.  The  Before  1.59  .27
After  2.40  .24 test compared  an equation  estimated with  ob-
servations  prior  to order  formation with  the  (Before  &  after
same  equation  estimated  with  observations  equations)
covering the period before and after order for-  Befre  1.28  .21
mation. Equation 1 with the ORDER variable  III.  Within  Season
omitted was used in this analysis.  The F-test is  Price
described by Johnston (p.  207). The calculated  efre  1.28  .22  .69  .1208
F-value with 48 and 60  degrees  of freedom is  Within  Season
2.16. This value is  significant at the 1 percent  Relative  Price
level.  The implication  is  that order formation  Before  .39  .29  .18  .16 After  .13  .11  .10  .08 did have a price impact.
17nominal price term as the dependent  variable.  of  South  Carolina  fresh  market  cucumber
Therefore the impact of an increased price level  prices. The major provisions  of the order that
may well explain the increased standard devia-  have  an impact on  price  are price  posting by
tion  from  before  to  after  order  formation  in  handlers  and  uniform  USDA  inspection.  A
these  three  cases.  Note,  however,  that  the  time  series  regression  model  that covers  and
standard  deviation of the relative price terms  accounts for periods before and after formation
declined  in both spring and fall. This result is  of the order indicates that the order did have a
expected  because the impact of inflation is re-  positive impact on the South Carolina  cucum-
moved via the relative price terms. Given these  ber price level.
considerations, we can conclude that the use of  Further  analysis  using  the  coefficient  of
a relative variation  measure  such as the coef-  variation as a measure of price variability indi-
ficient of variation is appropriate.  cates that order formation reduced price varia-
bility.  Four  variables  were  used  to  estimate
before and after price variability:  (1) monthly
price,  (2) the errors of the estimated before and
SUMMARY  AND  CONCLUSIONS  after  regression  equations,  (3) within-season
price  variability,  and  (4)  within-season  price
We investigate the impact of a market order  variability in relation to the prices in neighbor-
established in 1970 on the level and variability  ing producing regions.
REFERENCES
Draper,  N. R. and H. Smith. Applied Regression Analysis. New York:  John Wiley & Sons, Inc., 1966.
Houck, J. P. "A Look at Flexibilities and Elasticities." J. Farm  Econ. 48(1966):225-32.
Johnston, J. Econometric  Methods. New York:  McGraw-Hill Book Company, 1972.
Sanders,  Donald  H.,  A.  F.  Murph,  and  R.  J.  Eng.  Statistics:  A  Fresh Approach. New  York:
McGraw-Hill Book Company, 1980.
South Carolina Crop and Livestock Reporting Service.  "South Carolina Agricultural Prices and Re-
vised Indexes,  1960-1971." AE 357, Department of Agricultural Economics and Rural Soci-
ology, Clemson University, 1972.
" South Carolina Cash Receipts from Farm Marketings."  AE 409, Department of Agricul-
tural Economics and Rural Sociology, Clemson University, 1979.
South Carolina Cucumber Board. "Marketing Order No. 3 for South Carolina Fresh Market Cucum-
bers." Burton, South Carolina, 1975.
Snedecor,  George W. and William G. Cochran. Statistical  Methods. Ames,  Iowa:  The Iowa State
University Press, 1967.
U.S. Department of Agriculture.  "Vegetables:  Fresh Market." Various issues. Washington, D.C.
U.S. Department of Commerce. "Survey of Current Business." Various issues. Washington, D.C.

ASSESSMENT OF THE PRICE IMPACT OF THE SOUTH CAROLINA CUCUMBER MARKETING ORDER

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics