In 77
73 7 Bulletin 737 (technical)
May 1970
Demand for Florida Orange Products in
Foodstore, Institutional, and
Export Market Channels
David E. Weisenborn
W. W. McPherson
Leo Polopolus
HUME LIBRARY
JUL 7 1970
I.F.A.S. Univ. of Florida
Agricultural Experiment Stations
Institute of Food and Agricultural Sciences
University of Florida, Gainesville
J. W. Sites, Dean for Research
in cooperation with the
Florida Department of Citrus
LIST OF TABLES ......... .....
INTRODUCTION .. .... .
The Problem and Objectives 
Review of Literature ................
General Methodology .
THE FOODSTORE SECTOR ..
Nature of the Foodstore Sector
The Data ... .. 
List of Symbols 
Demand Estimates at Retail ...
Demand Estimates at FOB .........
THE INSTITUTIONAL SECTOR ..
Nature of the Institutional Sector
The Data ....................... ..............
List of Symbols ....... 
The Analysis and Results 
THE EXPORT MARKET .....
Nature of the Export Sector 
The Data  .. ..
List of Symbols ..........
The Analysis and Results 
SUMMARY ................... .......
ACKNOWLEDGMENTS ... 
LITERATURE CITED .... 
CONTENTS
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LIST OF TABLES
Table Page
1 Foodstore Sector: Retail Regression Coefficients in
Natural Numbers for Florida Orange Products ........ 15
2 Foodstore Sector: Retail Regression Coefficients in
Natural Logarithms for Florida Orange Products 15
3 Foodstore Sector: Retail Flexibility Coefficients
for Florida Orange Products ....... 16
4 Foodstore Sector: Retail Price Elasticity Coefficients
for Florida Orange Products .. ....... 16
5 Foodstore Sector: Wholesale Retail Price Margin
Regression Coefficients for Florida Orange Products 19
6 Foodstore Sector: FOB Regression Coefficients for
Fresh Florida Oranges .... ..... 20
7 Foodstore Sector: FOB Price Flexibility and Price
Elasticity Coefficients for Fresh Florida Oranges ....... 20
8 Institutional Sector: FOB Regression Coefficients
in Natural Numbers for Florida Orange Products ..... 25
9 Institutional Sector: FOB Regression Coefficients
in Natural Logarithms for Florida Orange Products........ .. 26
10 Institutional Sector: FOB Price Flexibility Coefficients
for Florida Orange Products ... .26
11 Export Sector: FOB Regression Coefficients in
Natural Numbers for Florida Orange Products 30
12 Export Sector: FOB Regression Coefficients in
Natural Logarithms for Florida Orange Products .... 30
13 Export Sector: FOB Price Flexibility Coefficients
for Florida Orange Products ........ 31
14 Summary of Price Flexibility Coefficients, Florida
Oranges and Orange Products, FOB in Natural Numbers 34
Demand for Florida Orange Products in
Foodstores, Institutional, and
Export Market Channels
David E. Weisenborn, W. W. McPherson, and Leo Polopolus1
INTRODUCTION
The Problem and Objectives
Recent projections of new citrus acreage in Florida indicate
the possibility that the supply will increase faster than demand,
and consequently, that prices will decline. The production ad
justment problem in citrus is made especially difficult by the
time lag between planting and initial harvest and the subsequent
long bearing period. Thus, there is a strong possibility that the
results will be wide and prolonged deviations from longrun
equilibrium market conditions, with the stronger tendency being
one of supply exceeding demand and prices that would not cover
costs including a normal return on investment.
A more accurate knowledge of demand relationships will
provide the Florida orange industry with the type of informa
tion needed to adjust marketing strategies to available and
prospective quantities produced. This study was specifically
designed to measure price flexibilities and elasticities of demand
(pricequantity relationships) for fresh oranges and major pro
cessed orange juice products in the foodstore, institutional, and
export market channels. While the empirical equations can be
applied in a variety of marketing problem situations, they were
developed primarily for the purpose of determining the optimum
allocation of any given orange supply among alternative product
forms and marketing channels at the FOB level of the processor
or packer in the foodstore and institutional channels and at the
U. S. port in the export sector. The term "FOB" refers to these
points in the marketing channels throughout this report.
This report presents the results of the analysis of demand
for fresh oranges, canned single strength orange juice, chilled
orange juice, and frozen concentrated orange juice in the food
store and institutional market sectors, and for each of these
1Formerly Graduate Research Assistant, Graduate Research Professor,
and Professor, respectively, in the Department of Agricultural Economics,
University of Florida.
four products plus hot pack concentrated orange juice in the
export market. The foodstore sector consists of that part of
the market in which products move through the wholesale mar
ket to retail foodstores where they are purchased and then
consumed within the home. The institutional sector actually
consists of two parts: sales through institutional outlets which
are nontax supported, such as restaurants and drugstore foun
tains; and sales through the tax supported institutions such as
military establishments, hospitals, and schools. The export mar
ket consists of all quantities that are sold for consumption out
side the United States. The primary objective of the part of the
analysis reported here was to estimate the price and quantity
relationships at the FOB point in the marketing system for each
of the product forms in each market sector. The other part of
the overall analysis, which makes use of these results in deter
mining the most profitable allocation of supplies of various
quantities among product forms and market sectors, is included
in a separate report (22).2
Review of Literature
With one exception, all of the previous demand research on
orange products involved the foodstore sector. Of the nine food
store demand reports, five used experimental pricing procedures
in selected markets, while the other four studies relied upon
time series data. All of the experimental pricing studies were
conducted prior to 1965, but none of those in which time series
data were used was completed before 1965. The analysis dealt
mainly with fresh oranges and frozen concentrated orange
juice in those studies.
Experimental pricing techniques as applied to orange demand
analysis were initially developed by Godwin in the early 1950's
(9). The first study, published in 1952, not only investigated
the feasibility of using the experimental approaches, but also
reported estimates of price elasticity of demand for fresh
oranges. In each of the experimental demand studies for orange
products, the analysis related to a particular location or region
of the United States, with little knowledge as to the national
significance of the findings. The 1952 publication was followed
in 1955 by Powell and Godwin's demand estimates for fresh
oranges (15). The other experimental pricing studies include
'Numbers in parentheses refer to references listed in the Literature
Cited.
Godwin and Powell's work in 1957 regarding the demand for
frozen concentrated orange juice (10), Chapman's extended
investigation of price and crossprice elasticities of demand for
California, Florida Interior, and Florida Indian River oranges
in 1963 (1), and Henderson's analysis of demand and substitu
tion relationships between three classes of orange concentrate
brands (11).
Of general significance was the finding of all of the experi
mental pricing studies that the demand both for fresh oranges
and for frozen concentrated orange juice was elastic with respect
to price at the retail level in foodstores. Also, over time the
price elasticity estimates for fresh oranges became relatively
more elastic. Part of this latter result is attributed to the in
creasing substitution of frozen orange concentrate for fresh
oranges.
The four retail demand studies using time series data relied
heavily upon monthly observations. Riggan's work in 1965,
however, provided estimates of the price elasticity of demand
from annual, as well as monthly, data. Riggan analyzed demand
relationships for fresh oranges and frozen orange concentrate
and was the first to provide estimates of price elasticity of
demand for canned single strength orange juice (17). Lang
ham's somewhat unique approach to demand analysis was pub
lished in 1966 (12). The orange demand functions were identi
fied and measured via the large shifts in supply that occurred
following the Florida freezes of the 195758 and 196263 seasons.
Also in 1966, Minden published the first estimates of retail
demand elasticity coefficients for chilled orange juice (14).
Then in 1967, Minden empirically tested the hypothesis of a
kinked demand curve for frozen concentrated orange juice (13).
Mean estimates of demand elasticities were determined to be
different, depending upon the mean retail price level, for three
linear segments of the demand curve.
Only one study of demand for orange products sold in the
institutional market has been completed. Rice, Williams, and
Godwin collaborated in a study conducted in drugstore outlets
of the institutional sector (16). Their work employed experi
mental pricing techniques and was published in 1966. Lack of
data virtually precluded the use of time series data in the esti
mations of demand functions in the institutional sector of the
market.
While some secondary data have been available to study the
export market demand for citrus products, no such work has
been previously attempted in Florida. This may partly reflect
the relatively minor economic importance of Florida orange
exports, except during periods of unusually large Florida pro
duction. The development of relatively large scale processed
orange product markets in Canada and Europe in recent years
and prospectively large domestic supplies, however, have in
creased the need for empirical study of export demand.
General Methodology
Specific matters of methodology are covered later in each of
the respective sections. Only matters of general relevance
throughout the analysis are given here. The basic time period
included in the study is the 196162 through 196667 seasons.
In a few cases slightly different periods were used as a result of
data problems and other matters. The 196667 season was the
latest one for which data were available when this study was
initiated. The selection of the initial year was based on two
factors. The first factor was the freeze in late 1962 which
drastically cut the available quantity of oranges. Beginning
the analysis in 1961 yields data that offer a fairly wide range
of pricequantity fluctuations, since the low quantityhigh price
freeze year is included as well as the large quantitylow price
196667 season. The second factor which influenced selection of
the time period was that increased substitution effects occurred
during this time period, possibly as a result of high prices
following the freeze. The inclusion of many seasons prior to the
freeze could have obscured these relationships.
Observations on a monthly basis were used throughout the
analysis. It was felt that a period as short as a week did not
allow adequate time for pricequantity adjustments to be made
when a change occurred. Annual data appeared to obscure many
important monthly or quarterly changes through the averaging
process. The final selection was between monthly and quarterly
observations. The decision for monthly observations was made
when it was decided that a month represented a sufficient time
period, in most instances, for pricequantity adjustments to
occur.
Monthly retail and wholesale prices used in the analysis were
deflated by the consumer and wholesale price (all items) indices,
respectively, with 195759=100 as reported by the U. S. Depart
ment of Commerce (20). The monthly estimates of personal
income, seasonally adjusted at annual rates, reported by the
U. S. Department of Commerce (20) were adjusted to form
estimates of personal disposable income by substracting the
personal taxes, reported quarterly, from each of the months
in the respective quarters. These monthly estimates of personal
disposable income were then deflated by the wholesale price
index for all items. Hereafter, in this report, these deflated
personal disposable income estimates are referred to as "in
come." Prices and income were deflated because the main use
of the results was aimed at market allocation of products rather
than at prediction of actual prices.
The statistical model selected for use in estimating demand
was the single equation least squares regression, with price of
the product as the dependent variable. The basic condition
generally considered necessary for the use of this method for
estimation of structural coefficients is that the estimating equa
tion for a given product contains only one endogenous variable
and that this variable is used as the dependent variable. The
problem is to designate the variable as either endogenous or
predetermined.
It appeared likely that the monthly prices for the various
products involved could be regarded as endogenous variables.
A period of one month is considered long enough to allow price
adjustments at retail for changes in quantities supplied. The
price variable was, therefore, the choice for the dependent vari
able for each of the products. One of the problems faced in
this particular study was the designation of the quantity vari
ables. If an agricultural product's consumption is equal to pro
duction and the production is regarded as predetermined, then
consumption can also be taken as predetermined. If this is the
case, least squares analysis is acceptable with no reservations.
Given, however, the situation encountered in this study where
orange production is marketed in four principal forms (five in
the export market) to three market sectors for a total of 13
separate equations, a simultaneous equation approach could be
used. In general, each of the four basic product forms differs
between market sectors with respect to quality and type of pack.
The question of whether or not a simultaneous system was
appropriate depended heavily upon the designation of these 13
quantity variables as either endogenous or predetermined and
on the nature of the available data. In view of the conditions
with respect to these two matters, the single equation least
squares model was selected. The production of Florida oranges
in any given season may be regarded as predetermined. Such
production is generally determined by economic decisions made
before the season begins and by subsequent weather conditions.
The only factor which could make this designation partly invalid
would be a price so low that fruit is not harvested. This situa
tion has not been a major factor up to the present time. Thus,
consumption equals production plus net change in storage less
some amount of loss or spoilage within the marketing system.
The storage problem is not of concern since it reacts to changes
in supply in the same direction as consumption.
Although total consumption in any given season appears to
be predetermined, the consumption of each of the 13 product
market forms is not likely to be entirely predetermined. There
is no preset portion of total production which must go to each
of the product forms and market sectors. However, there is
one major factor which makes these quantities sold partly pre
determined, at least in the short run. This factor is the existence
of fixed facilities. A certain amount of fixed investment has
been made to produce each of these products. This is true of
multiproduct as well as singleproduct firms. This implies that
in the short run the firms will produce at least some minimum
quantities of each of the products. Thus, it is likely that in any
given season a substantial portion of each product form is pre
determined. But adjustments can be made in the fixed facilities
in the longer run.
The data available were not suitable for the application of
a simultaneous equation system. Data for the productmarket
equations were not homogeneous with respect to time and stage
within the marketing system. For example, of the four food
store products, demands for three were estimated initially at
the consumer level and one at the FOB level with data for six
and five seasons, respectively. Institutional demands were esti
mated at the FOB level with about three seasons of observations.
Export demands were estimated at the seaport or airport with
data for six seasons. Also, for several substitute product vari
ables, quantities sold were reported but price information was
not available. It is evident that bias exists in the equations
developed in this study because the independent variables are
not entirely predetermined. However, because there is reason to
believe that the quantity variables are partly predetermined, it
is believed that the bias is small (8).
A stepwise multiple regression program was used in esti
mating the coefficients in a linear model. This program enters
each independent variable in a stepwise fashion beginning with
the variable with the highest F level and successively adds vari
ables with progressively lower F values until all independent
variables are entered. The F level is determined for each vari
able after each step is performed. The level of F may be preset
to exclude some variables from entering, but for this study the
level was set low enough to allow all of the independent variables
to enter. All estimates were made with the data in natural
numbers and with the data transformed to natural logarithms.
When price is used as the dependent variable, estimates of
the price and cross elasticities of demand are not obtained
directly. The first results are estimates of price and cross flex
ibilities of demand. The price flexibility of demand is defined as
the percentage change in the price of a given commodity which
results when the quantity of the commodity is changed 1%.
A cross flexibility indicates the effect of a 1% change in the
quantity of the jth commodity on the percentage change in price
of the ith commodity.
When the equation is linear and data are in natural loga
rithms, the price and cross flexibilities are identical with the
coefficient estimates. Flexibilities estimated in this manner are
constant over the whole curve, while those estimated from linear
equations with data in natural numbers are points estimated
at the means of the variables. The flexibility coefficients may
be converted to elasticities by matrix inversion.3
THE FOODSTORE SECTOR
Nature of the Foodstore Sector
The foodstore sector is defined to include all retail food
stores which sell Florida orange products directly to the con
sumer. The Florida orange products considered in this sector
are frozen concentrated orange juice, canned single strength
orange juice, chilled orange juice, and fresh oranges. These
products move generally from packers to distributors or chain
store warehouses to the retail outlets. There is some fresh fruit
sold at auction, but the percentage is small.
The bulk of the processing is carried out by processors
located in Florida. A substantial amount of chilled juice is
packed out of state by reconstituting bulk frozen concentrated
orange juice into chilled juice. This nonFlorida pack is included
in the total of retail sales of chilled juice for the purpose of
demand estimation.
3The methodology is explained further in Weisenborn (21).
The objective was to estimate pricequantity relationships
at the FOB level. However, as the most complete and reliable
data were available at the retail level for frozen concentrated
orange juice, chilled orange juice, and canned single strength
orange juice, demand functions for these items were estimated
initially at the retail level and then converted to the FOB level.
Demand for fresh oranges was estimated directly at the FOB
level.
The Data4
Most of the data used in making retail demand estimates
were taken from published reports of the Florida Citrus Com
mission and the U. S. Department of Agriculture (4, 5, 6, and
19). The data used in the estimates of demand for fresh oranges
were reported by Florida Citrus Mutual. The estimation pro
cedure for the fresh orange equations required FOB prices for
frozen concentrated orange juice, chilled orange juice, and
canned single strength orange juice. These prices were obtained
directly from industry firms. Population, income, and various
price indices were taken from reports of the U. S. Department
of Commerce (20).
The data reported by the Florida Citrus Commission and the
U. S. Department of Agriculture for use in making the retail
demand estimates for frozen orange concentrate, chilled orange
juice, and canned single strength orange juice are based on a
consumer panel report from 7,500 households. The panel figures
were converted to national figures for each of the products.
Serious questions have arisen among industry leaders with re
spect to the reliability of the unadjusted or raw data in recent
years. Many persons felt that the data did not accurately re
flect retail quantities consumed. In an attempt to improve the
accuracy of the quantityconsumed data for frozen orange con
centrate, the Economic Research Department of the Florida
Citrus Commission in collaboration with the Market Research
Corporation of America (MRCA) devised an adjustment for
mula.5 The general purpose of the formula is to adjust down
ward the positive bias apparent in the raw quantity data. This
formula was applied to adjust the frozen concentrated orange
juice quantities included in the demand equations at the retail
level. The quantities consumed of the remaining products under
'A complete set of data is contained in Weisenborn (21).
'This formula is presented in Table 32, Appendix A, Weisenborn (21).
consideration in this section were not adjusted, although it is
suspected that some of these quantity series do not accurately
reflect national quantities consumed.
In spite of the preceding comments, the MRCA quantity
data appear to be reasonably accurate, especially with respect
to trend. They are believed to be far superior to their counter
parts at the FOB level. The price data from the panel are gen
erally considered to be representative of the actual retail prices.
The MRCA data for fresh oranges were not used because they
did not include fresh orange and fresh grapefruit figures for
the 196061 and 196162 seasons, and the prices and quantities
for fresh oranges and fresh grapefruit included substantial
influence from prices and quantities for fresh oranges and fresh
grapefruit produced in other states. The Florida Citrus Mutual
data used in the estimation of demand for fresh oranges at the
FOB level are based on actual reports of handler members of
Florida Citrus Mutual (7). These data are considered to be
accurate estimates of the actual prices and quantities of fresh
oranges and other products.
The FOB prices for frozen concentrated orange juice, canned
single strength orange juice, and chilled orange juice were ob
tained directly from industry firms. The selection of the firms
interviewed was based on judgment rather than on a random
sample. The firms selected were considered by the authors and
by several industry representatives to be the dominant firms
of the industry.
List of Symbols
The following symbols, with their corresponding definitions,
are used in this section:
Prices at retail in the foodstore sector
P FCOJ = deflated average monthly price of frozen concentrated
orange juice, cents per 6ounce can.
F coJ = deflated average monthly price of chilled orange
juice, cents per quart.
P cssoJ = deflated average monthly price of canned single
strength orange juice, cents per 46ounce can.
Prices at FOB in the foodstore sector
P* FCOJ = deflated average monthly price of frozen concentrated
orange juice, cents per 6ounce can.
P* coJ = deflated average monthly price of chilled orange
juice, cents per quart.
P* cssoJ = deflated average monthly price of canned single
strength orange juice, cents per 46ounce can.
P* FFO = deflated average monthly price of fresh Florida
oranges, dollars per 13/5bushel box.
Quantities in the foodstore sector
Q FCOJ = per capital monthly quantity of frozen concentrated
orange juice at retail and FOB, in gallons.
Q cOJ = per capital monthly quantity of chilled orange juice
at retail and FOB, in gallons.
Q cssoJ = per capital monthly quantity of canned single strength
orange juice at retail and FOB, in cases of 24 No.
2 can equivalents, 432 ounces per case.
Q CSSGJ = per capital monthly quantity of canned single strength
grapefruit juice, at retail and FOB, in cases of 24
No. 2 can equivalents, 432 ounces per case.
Q* FFO = per capital monthly quantity of fresh Florida oranges
at FOB, in carlots of 500 boxes.
Q* FFG = per capital monthly quantity of fresh Florida grape
fruit at FOB, in carlots of 500 boxes.
Q* FCO = per capital monthly quantity of fresh California
oranges at FOB, in carlots of 500 boxes.
Other symbols
M = margin between retail and FOB prices.
T = time.
Y = monthly personal disposable income per capital, in
dollars, seasonally adjusted at annual rates.
R3 = coefficient of determination.
Demand Estimates at Retail
After some exploratory analysis, fresh oranges, fresh grape
fruit, prune juice, canned single strength fruit drinks, and time,
which had been included in this exploratory work, were dropped
from the independent variables in the estimating equations for
frozen concentrated orange juice, chilled orange juice, and can
ned single strength orange juice. Synthetic orange products
and other possible substitutes were not included in the model
because data were not available. The final formulations, based
on monthly data from October 1961 to September 1967, for
these three products were as follows:
a. Frozen concentrated orange juice
[1] P FCOJ f[Q FCOJ, Q coJ, Q cssoJ, Q CSSGJ, Y]
b. Chilled orange juice
[2] P coj = f[Q coJ, Q FCOJ, Q cssos, Q CSSGJ, Y]
c. Canned single strength orange juice
[3] P cssoJ = f[Q cssos, Q FCOJ, Q coJ, Q CSSGJ, Y]
The regression coefficients and their standard errors as esti
mated from equations [1] through [3] are presented in Tables
1 and 2.
The flexibility and elasticity coefficients estimated by equa
tions [1] through [3] are given in Tables 3 and 4. The price
Table 1. Foodstore Sector: Retail Regression Coefficients in Natural Numbers
for Florida Orange Products.t
Dependent Variable
Independent P FCOJ P coJ P cssoJ
Variable
Equation [1] Equation [2] Equation [3]
Intercept 59.698 67.218 104.314
Q FCOJ 654.813*** 336.981** 285.045**
(60.553) (70.315) (113.473)
Q coJ 80.283 642.447*** 88.522
(160.251) (186.086) (300.302)
Q cssoJ 466.590 547.805 4651.188***
(543.896) (631.581) (1019.231)
Q CSSGJ 941.296*** 1335.800*** 2674.723**
(309.478) (359.370) (579.944)
Y 0.010*** 0.002 0.015**
(0.003) (0.004) (0.006)
R2 .900 .891 .875
tValues in parentheses are the estimated standard errors of the regression coefficients;
significance at the .10, .05, or .01 levels is denoted by one, two, and three asterisks,
respectively.
Table 2. Foodstore Sector: Retail Regression Coefficients in Natural Logarithms
for Florida Orange Products.t
Dependent Variable
Independent P FCOJ P coJ P cssoJ
Variable
Equation [1] Equation [2] Equation [3]
Intercept 3.293 1.109 2.849
Q FCOJ 0.702*** 0.170"** 0.153**
(0.078) (0.053) (0.060)
Q coJ 0.104 0.271*** 0.061
(0.143) (0.098) (0.111)
Q cssoJ 0.050 0.062 0.333***
(0.087) (0.059) (0.067)
Q CSSGJ 0.222*** 0.123*** 0.206***
(0.063) (0.043) (0.048)
Y 1.138*** 0.230 0.893***
(0.392) (0.267) (0.304)
R2 .899 .855 .899
tValues in parentheses are the estimated standard errors of the regression coefficients;
significance at the .10, .05, or .01 levels is denoted by one, two, and three asterisks,
respectively.
Table 3. Foodstore Sector: Retail Flexibility Coefficients for Florida Orange
Products.
Percentage Change in Price
Associated With 1% Change
in Quantity of:t
Product FCOJ COJ CSSOJ CSSGJ Y
Natural Numbers
FCOJ .827 NS NS .194 1.186
COJ .210 .262 NS .136 NS
CSSOJ .168 NS .333 .257 .820
Natural Logarithms
FCOJ .702 NS NS .222 1.138
COJ .170 .271 NS .122 NS
CSSOJ .153 NS .333 .206 .893
tNegative sign means that changes in price move in the opposite direction from changes
in quantity.
NSNot significant at the .05 level.
Table 4. Foodstore Sector:
Products
Retail Price Elasticity Coefficients for Florida Orange
Percentage Change in Price
Associated With 1% Change in
Price of:t:
Product FCOJ COJ CSSOJ
Natural Numbers
FCOJ 1.236 NS NS
COJ .906 4.140 NS
CSSOJ .531 NS 2.919
Natural Logarithms
FCOJ 1.509 NS NS
COJ .825 4.214 NS
CSSOJ .539 NS 3.008
tBased on matrix inversion of price flexibility estimates in Table 3.
tNegative values mean that price and quantity vary in opposite directions; positive
values mean that price and quantity vary in the same direction.
NSNot significant at the .05 level.
elasticity of demand estimates have negative values of 1.236,
4.140, and 2.919 in natural numbers, and 1.509, 4.214, and 3.008
with the logarithmic data for frozen concentrated, chilled, and
canned single strength orange juice, respectively. The price
elasticity values indicate the percentage change in quantity
associated with a 1% change in the opposite direction in price.
The results between the two sets of data are relatively close
to each other. The negative estimate of 1.236 for frozen con
centrated juice is in line with results found in previous studies
when secondary data were used. Chilled juice is substantially
more elastic here than in any previous estimate. This result is
not entirely unexpected in view of increased substitutes for
orange products, especially for frozen concentrate and chilled
juice. The estimates for canned single strength orange juice
are fairly close to previous estimates for this product.
Canned single strength grapefruit juice was the only product
included in the model that proved to be a strong substitute for
frozen concentrated orange juice. This product was a significant
substitute for chilled orange juice and canned single strength
orange juice. It was found that even though chilled orange
juice did not appear as a substitute for frozen orange concen
trate, frozen orange concentrate appeared as a substitute for
chilled orange juice. This situation also occurred between frozen
and canned orange juice. Thus, considerable doubt is cast on
the a priori assumption that the various citrus products are
close substitutes for each other especially after the products
have been committed to a particular form and market channel.
The income coefficients were negative for frozen orange con
centrate and canned single strength orange juice and not signi
ficant for chilled orange juice. A negative income elasticity
implies that increases in consumer income result in decreases
in quantity of product consumed. It is believed that orange
products are less responsive to income increases at present
than they were in the past. This is partly due to higher per
capital income levels over time which tended to take orange
products out of the luxury class. However, it does not appear
likely that consumption of orange products decreases as income
increases. The negative income coefficients may be a result of
a positive correlation between income and the consumption of
synthetic orange products that have been developed and mar
keted during the period while the net effect is negative due to
expansion of substitutes.
Demand Estimates at FOB
The next step in the analysis of demand in the foodstore sec
tor was to shift the retail demand functions for frozen concen
trated orange juice, canned single strength orange juice, and
chilled orange juice to demand functions at FOB, and to estimate
the demand for fresh oranges at FOB. In the estimates of de
mand for frozen concentrate, chilled, and canned single strength
orange juices at FOB, it was assumed that quantities were the
same at each level and that FOB prices at any quantity would
be equal to the estimated retail price for any given quantity less
an estimated margin. The procedure to develop the margin
estimates involved the following steps:
First, estimate regression coefficients for equation [4].
[4] Pi = a + #'P: + iQi +PTi
i = 1, 2, ..., n
P is the retail price, P* is the FOB price, Q is the quantity
sold and assumed to be equal at retail and FOB, and T is time.
Second, subtract P.* from each side of equation [4] and
1
define P. P* as the wholesaleretail margin, M..
1 1 1
Thus,
[5] Mi = a +(p. 1)Pi* + p2Qi + pITi
i = 1, 2, ..., n
This procedure was carried out for frozen concentrated
orange juice, canned single strength orange juice, and chilled
orange juice with monthly data, October 1961 to September
1967. The coefficients for the margin equations are given in
Table 5. The functions for these three products at the FOB
level were derived by subtracting the appropriate margin from
each of the functions estimated at the retail level, equations [1]
through [3]. This procedure provided the following empirical
FOB equations in natural numbers:
a. Frozen concentrated orange juice
[6] P* FCOJ = 54.161 543.073Q FCOJ 89.894Q CssoJ
+ 522.450Q coJ 1053.989Q cssGJ + .049T .012Y
b. Chilled orange juice
[7] P* coJ = 131.03 3462.74Q coJ 2130.09Q FCOJ
962.32Q cssoJ 8570.16Q CSSGJ + 1.286T .014Y
c. Canned single strength orange juice
[8] P* cssoJ = 116.859 153.615Q cssoJ
494.646Q FcoJ 1275.612Q coJ 4641.521Q cssGJ +
.147T .027Y
The price flexibility estimate for frozen concentrated orange
juice is a negative .883 at the FOB level. This is more flexible
than the price flexibilities estimated at retail by equation [1],
as would be expected from the theory of derived demand,
assuming linear estimation in natural numbers. The price flex
ibility estimate for chilled orange juice is a negative .610, which
is also more flexible than the estimate at retail by equation [2].
On the other hand, the price flexibility for canned single strength
juice is a negative .122, which is less flexible than was estimated
at retail by equation [3]. This result was not anticipated.
Table 5. Foodstore Sector: Wholesale Retail Price Margin
efficient for Florida Orange Products.t
Regression Co
Independent Dependent Variable
Variable P FCOJ P cssoj P coJ
Intercept 11.328 36.972 46.490
P* FCOJ 0.893 b b
(0.069)
P* cssoJ b 0.158 b
(0.069)
P* coj b b 0.576
(0.050)
Q FCOJ 169.806 b b
(52.425)
Q cssoJ b 490.207 b
(123.704)
Q coJ b b 3916.104
(571.083)
T 0.044 0.204 0.805
(0.007) (0.038) (0.015)
R" .964 .958 .928
tValues in parentheses are the estimated standard errors of the regression coefficients;
the P*cssoJ coefficient is significant at the .05 level, all others at the .01 level.
tThese variables were not included in the estimation of the margin function.
The final equation used for fresh Florida oranges at FOB
was as follows:
[9] P* PFO = f[Q* FFO, Q* FFG, Q* FCO, Y]
It was assumed that fresh Florida grapefruit and fresh
California oranges would be substitutes for fresh Florida
oranges. Fresh California oranges make up the bulk of fresh
oranges sold that do not come from Florida. Per capital income
was also included as an explanatory variable. The monthly ob
servations include five 8month seasons, beginning in October
1962 and ending in May 1967.
The estimated regression coefficients and their standard
errors from equation [9] are presented in Table 6. The esti
mates of the flexibility and elasticity coefficients are presented
in Table 7. The price elasticity estimates are the reciprocals of
the price flexibility estimates.
The expected substitution effects of fresh Florida grape
fruit and fresh California oranges did not occur. The grape
fruit coefficients exhibited the expected negative signs, but were
not significant. The coefficient for income was highly signifi
cant, but again the sign was negative.
Table 6. Foodstore Sector: FOB Regression Coefficients for Fresh Florida
Oranges.t
Dependent Variable
Independent
Inde en P* FFO Equation [9]
Variable
Natural Numbers Natural Logarithms
Intercept 22.924 10.854
Q* FFO 265.212*** 0.345***
(73.216) (0.080)
Q* FFG 64.002 0.003
(67.950) (0.082)
Q* FCO 10.624 0.087
(44.792) (0.082)
Y 0.007*** 3.241***
(0.001) (0.486)
R" .748 .779
TValues in parentheses are the estimated standard errors of the regression coefficients;
three asterisks denote significance at the .01 level, and the other coefficients were not
significant at the .10 level.
Table 7. Foodstore Sector: FOB Price Flexibility and Price Elasticity Coeffi
cients for Fresh Florida Oranges.
Percentage Change in Price
Associated With 1% Change
Product in Quantity of:
FFO FFG FCO Y
Natural Numbers
FFO .304 NS NS 3.198
Natural Logarithms
FFO .345 NS NS 3.241
Percentage Change in Quantity
Associated With 1% Change in
Product Price of:t
FFO FFG FCO Y
Natural Numbers
FFO 3.293 NS NS $
Natural Logarithms
FFO 2.900 NS NS $
tReciprocals of price flexibility coefficients.
$Not estimated.
NSNot significant at the .05 level.
THE INSTITUTIONAL SECTOR
Nature of the Institutional Sector
The institutional market should actually be presented as two
separate sectors if there were adequate data to allow such a
breakdown. The first sector would be orange products moving
through private institutions such as restaurants, drugstore
counters, and other similar establishments. The other sector
would consist of tax supported institutions such as hospitals,
military establishments, schools, and other government agencies.
Since adequate data do not exist to allow separation of the two
markets, they were combined in this study.
The four product forms are frozen concentrated orange
juice, canned single strength orange juice, chilled orange juice,
and fresh oranges. No data existed for the estimation of a
demand function for fresh oranges. As in the foodstore channel,
part of the chilled orange juice is reconstituted by outofstate
processors and must be added to the institutional movement of
chilled juice. The remainder of chilled, as well as the other
product forms, is processed in Florida and moves to final institu
tional consumers through a network of distributors.
The Data
FOB prices for frozen orange concentrate, chilled, and
canned single strength orange juice sold in institutional markets
are not reported. The price data used in this study were ob
tained directly from firms which were considered to be the
dominant ones in the industry. Fresh orange FOB prices in
the institutional market were not solicited, since it was already
known that no quantity data for fresh oranges moving to insti
tutional markets were available.
The quantity of frozen concentrated orange juice moving to
institutional markets is reported by Florida Canners Associa
tion (3). The total movement, excluding exports of canned
single strength orange juice, and for recent seasons, chilled
orange juice, is also reported directly by the Florida Canners
Association. However, no foodstore and institutional break
down is reported. Therefore, institutional movement had to be
estimated for both products. The total movement of chilled
juice was not reported in earlier seasons and also had to be
calculated.
Chilled orange juice movement to foodstores and institutional
market sectors was reported by the Florida Canners Association
beginning with the week of February 12, 1966 (3). Estimates of
weekly movement prior to this date were made by calculating a
weekly percentage distribution of chilled juice movement, based
on weekly movement for the 196667 season, and applying this
distribution to the total pack of chilled juice in the 196364,
196465, and 196566 seasons. This procedure gave estimates of
movement from Florida by weeks to foodstore and institutional
markets.
It was known, however, that substantial quantities of chilled
orange juice were made outside Florida by reconstitution of
bulk frozen concentrated juice. Bulk frozen concentrated orange
juice was reported by Florida Canners Association as being
used in three forms (2) : reconstitution for chilled orange
juice, for beverage bases and diluted drinks, and for unidenti
fied purposes. Bulk frozen orange concentrate for chilled
orange juice and bulk concentrate for beverage bases and diluted
drinks were added together. The percentage for chilled use was
obtained on a weekly basis. It was assumed that the unidentified
usage was distributed between chilled orange juice and beverage
bases and diluted drinks. The above percentage was applied to
obtain that portion which went to chilled orange juice on a
weekly basis. The identical procedure was used with concen
trated orange juice which may be reconstituted into chilled
juice.
The above calculations resulted in estimates of the portion of
bulk frozen concentrated orange juice and concentrated orange
juice for manufacturing used for chilled orange juice on a
weekly basis. However, a portion of this total was reconstituted
in Florida and included in the pack and movement figures. This
portion was deducted and the remaining quantity added to the
calculated weekly movement figures. This procedure gave the
total amount of chilled orange juice available for sale to retail
and institutional markets on a weekly basis. Weekly retail sales
figures, obtained from publications of the U. S. Department of
Agriculture and the Florida Citrus Commission, were lagged
two weeks and deducted from the weekly movement estimates.
This provided estimates of weekly movement to institutional
markets. These data were averaged to derive monthly chilled
orange juice movement to institutional markets.
The movement of canned single strength orange juice to
retail and institutional markets was reported by the Florida
Canners Association (3). The retail sales were reported by the
U. S. Department of Agriculture until March 1967 and by the
Florida Citrus Commission from April 1967 through November
1967 (4, 19). These sales data were lagged four weeks and
deducted from the total movement data to provide estimates
of movement to institutional markets.
The FOB price data obtained from the dominant firms are
believed to accurately represent industry prices. The data per
taining to movement of frozen orange concentrate to institu
tional markets should be reliable in that they are collected
directly from processors. However, there are several sources
of possible error in the data calculated to determine institutional
movement of chilled and canned single strength orange juice.
The computation of total chilled movement in the earlier seasons,
by using a percentage distribution of chilled movement in the
seasons in which it was reported, gives rise to possible error.
But it is thought that the trend of chilled movement was fairly
represented even though some errors in the magnitude of the
observations might have been made. The procedure used to
determine institutional movement for chilled and canned single
strength orange juice involved a deduction of quantities sold at
retail from total movement with an appropriate lag time in
cluded. The two sources of error in this case are incorrect lags
and errors in retail sales.
The time period initially chosen was from December 1963
through September 1967. The decision to begin with data for
December of 1963 was based on the availability of the data for
chilled orange juice. No chilled juice prices were available until
December of 1963, as chilled juice was just beginning to be sold
in large quantities. The last figures available at the time of the
analysis were for September 1967. The period from December
1966 through September 1967 was later dropped from the anal
ysis as a result of the unusual effect of large school lunch
purchases by the government during this period. Thus, the
analysis given here is based on monthly data for the period
from December 1963 to November 1966.
Data suitable for institutional orange product demand esti
mates at the consumer level are not available. There are several
reasons which account for this lack of data. First, there has
been little emphasis placed on institutional studies in past
years. The foodstore sector was considered to be the major
market, and the research work has been carried out in that
sector. Also, the consumer level of the institutional sector is
extremely complex with respect to orderly data collection. The
tax supported institutions, in part, do report purchases and pur
chase prices for orange products. For example, military pur
chases are based on contracts and the terms of such contracts
are public information. However, the nontax supported insti
tutions, such as restaurants, present considerable difficulty with
respect to data collection over time. A consumer panel for
reporting retail foodstore purchases of various food items is
reasonably easy to establish. However, obtaining similar data
from a sample of restaurants is less easily accomplished. The
cost of obtaining such data is extremely high and restaurants
are so variable with respect to socioeconomic factors that the
data collected would likely be biased unless the sample could
be quite large. As a result of these conditions, virtually no data
have been collected at the consumer level for orange products
in institutional markets. Thus, in the present analysis, demands
at the FOB level were estimated directly, rather than via adjust
ments of consumer demand.
List of Symbols
The following symbols, with their corresponding definitions,
are used in this section:
Prices at FOB in the institutional sector
P** FCOJ = deflated average monthly price of frozen concentrated
orange juice, dollars per dozen 32ounce cans.
P** coJ = deflated average monthly price of chilled orange
juice, dollars per dozen quarts.
P** cssoJ = deflated average monthly price of canned single
strength orange juice, dollars per dozen 46ounce
cans.
Quantities at FOB in the institutional sector
Q** FCOJ = monthly quantity of frozen concentrated orange
juice, in gallons.
Q** coJ = monthly quantity of chilled orange juice, in gallons.
Q** cssoJ = monthly quantity of canned single strength orange
juice, in cases of 24 No. 2 can equivalents, 432
ounces per case.
Other symbol
R = coefficients of determination.
The Analysis and Results
The functional equations used for the three product forms
were:
a. Frozen concentrated orange juice
[10] P** FCOJ = f[Q** FCOJ, Q** CoJ, Q** CSSOJ]
b. Chilled orange juice
[11] P** COJ = f[Q** coJ, Q** FCOJ, Q** cssoJ]
c. Canned single strength orange juice
[12] P** CssoJ = f[Q** cssoJ, Q** FCOJ, Q** coJ]
The three quantity variables were believed to be substitutes
and were included as independent variables.
The canned juice equation was unacceptable in estimating
the demand for this product in the institutional sector. The basic
causes of such unreasonable estimates are difficult to define.
Probable explanations stem from errors in the observations and
problems of identification. A scatter diagram of pricequantity
observations on canned juice illustrated a fairly wide scatter
of points.
The estimated coefficients and their standard errors from
equations [10] through [12] are presented in Tables 8 and 9.
The flexibility coefficients are presented in Table 10.
The price flexibility estimates for frozen concentrate and
chilled juice have negative values of .272 and .262 with natural
numbers used in the equations and .220 and .224 with logarithms.
The price flexibility for canned juice was not significant. Chilled
Table 8. Institutional Sector: FOB Regression Coefficients in Natural Numbers
for Florida Orange Products.i
Dependent Variable
Independent P** FCOJ P** CoJ P** CssoJ
Variable
Equation [10] Equation [11] Equation [12]
Intercept 13.489 4.627 5.653
Q** FCOJ 865.523*** 191.878* 93.665
(300.383) (104.198) (144.992)
Q** co  131.947*** 51.256*** 82.608**
(25.902) (8.985) (12.503)
Q** CssoJ 52.393 38.890 78.554
(171.974) (59.655) (83.010)
R2 .646 .636 .649
tValues in parentheses are the estimated standard errors of the regression coefficients;
significance at the .10, .05, or .01 levels is denoted by one, two, and three asterisks,
respectively.
Table 9. Institutional Sector: FOB Regression Coefficients in Natural Logarithms
for Florida Orange Products.t
Dependent Variable
Independent P** FCOJ P** coJ P** cssoJ
Variable
Equation [10] Equation [11] Equation [12]
Intercept 0.018 0.261 0.039
Q** FCOJ 0.220** 0.136 0.003
(0.093) (0.102) (0.116)
Q** COJ 0.215*** 0.224*** 0.297***
(0.037) (0.041) (0.047)
Q** cssoJ 0.002 0.005 0.004
(0.015) (0.016) (0.018)
R .702 .664 .641
tValues in parentheses are the estimated standard errors of the regression coefficients;
significance at the .10, .05, or .01 levels is denoted by one, two, and three asterisks,
respectively.
Table 10. Institutional Sector: FOB Price Flexibility Coefficients for Florida
Orange Products.
Percentage Change in Price
Associated With 1% Change
in Quantity of:t
Product FCOJ COJ CSSOJ
Natural Numbers
FCOJ .272 .238 NS
COJ NS .262 NS
CSSOJ NS .344 NS
Natural Logarithms
FCOJ .220 .215 NS
COJ NS .224 NS
CSSOJ NS .297 NS
tNegative values mean that a change in quantity is associated with a change of the
opposite direction in price.
NSNot significant at the .05 level.
orange juice was a substitute for canned single strength orange
juice and for frozen concentrated orange juice, as evidenced
by the negative cross flexibility estimates between these prod
ucts.
The presence of the canned juice flexibility estimate in the
flexibility coefficient matrix does not allow accurate elasticity
estimates to be derived by matrix inversion. The lower limit on
the price elasticity of demand estimates may be found by taking
the reciprocal of the price flexibility estimates. These lower
limit estimates have negative values of 4.541 and 4.456 for
frozen orange concentrate and chilled juice, respectively. While
there are no previous estimates of price elasticity for these two
products with which comparisons may be made, they are logical
in sign and reasonable in absolute magnitude. One would expect
fairly elastic demands in view of the large number of substitute
drinks and juices available in the institutional sector. Also, at
the FOB level where purchases are made in large volumes,
buyers might be expected to be quite responsive to changes in
relative prices.
THE EXPORT MARKET
Nature of the Export Sector
The export sector accounts for a small percentage of the total
sales of orange products, but its importance should not be
minimized, especially with respect to future potential. The
Florida orange products considered in this study which move
into the export market are frozen concentrated orange juice,
chilled orange juice, canned single strength orange juice, hot
pack concentrated orange juice, and fresh oranges. The data for
chilled orange juice are included with canned single strength
orange juice. Hot pack concentrated orange juice is a non
frozen concentrate product which was virtually eliminated from
the domestic sectors when frozen concentrate was introduced.
A small amount of this product is still manufactured, however,
for export markets and domestic food manufacturing markets.
The Canadian market is by far the most important export
market for Florida orange products. The countries of Western
Europe are next in importance. After this, there are numerous
countries which purchase varying amounts of Florida orange
products.
Orange products for use in the export market move directly
from the processor to the port of export. The value of the prod
uct is reported at this point and before tariffs are added.
The Data
All of the data used in estimating demand functions in the
export market were taken from published reports of the U. S.
Bureau of Census (18). Contained within these reports were
quantity and value data for frozen concentrated orange juice,
canned single strength and chilled orange juice, hot pack con
centrated orange juice, and fresh oranges. Also, quantity and
value observations were included for several potential substitute
products, namely, canned single strength grapefruit juice, con
centrated hot pack grapefruit juice, and frozen concentrated
grapefruit juice.
These data are based on a sample of the sales invoices at
the port of export. The value observations are used in place of
actual selling price observations which were not available. Value,
as used in this case, is the selling price at FOB at the processing
or packing plant plus such items as transportation and insurance
for the products from the processor to the port of export. It was
believed that, because of the geographic concentration of the
Florida orange processing facilities near the ports of export,
the addition of the transportation and insurance figures to the
selling price would not have an adverse effect on the analysis.
The transportation and insurance figures should be fairly uni
form for shipments from different processors to different ports
of export. Therefore, while prices may be slightly inflated,
inflation should be uniform and should not affect the relative
magnitudes or the trends of the actual figures. Such a situation
would not hold for processing facilities spread over a wide
geographic area.
Both the quantity and the value figures were believed to be
accurate. The sample used has been tested over many years
and has been improved several times. The situation with fresh
oranges, however, is similar to that encountered at retail in the
foodstore sector. The exports of products from other states are
included in the fresh orange observations. For this reason and
based on the experience with the retail foodstore fresh orange
equation, no attempt was made to estimate export demand for
fresh oranges. The same situation existed with the canned
single strength orange juice exports, but it was assumed that
the bulk of these exports were from Florida. Equations were
estimated for frozen concentrated orange juice, canned single
strength orange juice and chilled orange combined, and hot pack
concentrated orange juice.
Monthly observations from October 1961 through September
1967 were used to estimate the export demand coefficients. The
reason for this starting point was once again influenced heavily
by the late 1962 freeze. This was true in terms of shifts of
export products to domestic uses as well as the adverse effects
of higher prices to the importing countries. By starting the
analysis with October 1961, observations range from relatively
small quantities with high values to large quantities and low
values.
List of Symbols
The following symbols, with their corresponding definitions,
are used in this section:
Prices at FOB in the export sector
P*** FCOJ = deflated average monthly value of frozen concentrated
orange juice, dollars per gallon.
P*** cssoJ = deflated average monthly value of canned single
strength orange juice, dollars per gallon.
P*** HPCOJ = deflated average monthly value of hot pack concen
trated orange juice, dollars per gallon.
Quantities at FOB in the export sector
Q*** FcoJ = monthly quantity of frozen concentrated orange juice,
in thousands of gallons.
Q*** cssoJ = monthly quantity of canned single strength orange
juice, in thousands of gallons.
Q*** HPcoJ = monthly quantity of hot pack concentrated orange
juice, in thousands of gallons.
Q*** cssGJ = monthly quantity of canned single strength grapefruit
juice, in thousands of gallons.
Q***HPCGJ = monthly quantity of hot pack concentrated grapefruit
juice, in thousands of gallons.
Q*** FCGJ = monthly quantity of frozen concentrated grapefruit
juice, in thousands of gallons.
Other symbol
R' = coefficient of determination.
The Analysis and Results
The model equations for analysis of export demand were:
a. Frozen concentrated orange juice
[13] P***FCOJ = f[Q*** FCOJ, Q*** cssoJ, Q*** HPCOJ,
Q*** CSSGJ, Q*** HPCGJ, Q*** FCGJ ]
b. Canned single strength orange juice
[14] P*** cssor = f[Q*** cssoj, Q*** FCOJ,
Q*** HPCOJ, Q*** CSSGJ, Q*** HPCGJ, Q*** FCGJ ]
c. Hot pack concentrated orange juice
[15] P*** HPCOJ = f[Q*** HPCOJ, Q*** FCOJ,
Q*** cssoJ, Q*** CSSGJ, Q*** HPCGJ, Q*** FCGJ ]
Substitute relationships were believed to exist between frozen
concentrated orange juice, canned single strength orange juice,
and hot pack concentrated orange juice in their respective
Table 11. Export Sector: FOB Regression Coefficients in Natural Numbers for
Florida Orange Products.t
Dependent Variable
Independent P*** FCOJ P*** CSSOJ P*** HPCOJ
Variable
Equation [13] Equation [14] Equation [15]
Intercept 4.48769 1.22023 4.01547
Q*** FCOJ 0.00214** 0.00051** 0.00077
(0.00084) (0.00022) (0.00077)
Q*** cssoJ 0.00181*** 0.00050*** 0.00149***
(0.00034) (0.00009) (0.00031)
Q*** HPCOJ 0.00356* 0.00093* 0.00329*
(0.00196) (0.00052) (0.00179)
Q*** CSSGJ 0.00087** 0.00014 0.00022'
(0.00036) (0.00010) (0.00033)
Q*** HPCGJ 0.00613 0.00074 0.00335
(0.00543) (0.00144) (0.00496)
Q*** FCGJ 0.00257 0.00080 0.00583
(0.00572) (0.00152) (0.00523)
R' .5718 .5739 .3159
tValues in parentheses are the estimated standard errors of the regression coefficients;
significance at the .10, .05, or .01 levels for the coefficients is denoted by one, two, and
three asterisks respectively.
Table 12. Export Sector: FOB Regression Coefficients in Natural Logarithms
for Florida Orange Products.t
Dependent Variable
Independent P*** FCOJ P*** cssoJ P*** HPCOJ
Variable
Equation [13] Equation [14] Equation [15]
Intercept 1.494 0.892 0.829
Q*** FCOJ 0.195*** 0.145** 0.086
(0.070) (0.064) (0.075)
Q*** cssoJ 0.368*** 0.376 0.271**
(0.056) (0.050) (0.059)
Q*** HPCOJ 0.100** 0.106*** 0.090**
(0.041) (0.037) (0.044)
Q*** CSSGJ 0.124*** 0.074** 0.031
(0.039) (0.035) (0.042)
Q*** HPCGJ 0.012 0.003 0.011
(0.019) (0.018) (0.021)
Q*** FCGJ 0.000 0.046* 0.029
(0.029) (0.026) (0.031)
Ra .650 .686 .299
tValues in parentheses are the estimated standard errors of the regression coefficients;
significance at the .10, .05, or .01 levels for the coefficients is denoted by one, two, and three
asterisks, respectively.
equations. In addition, canned single strength grapefruit juice,
hot pack concentrated grapefruit juice, and frozen concentrated
grapefruit juice were believed to be substitutes for the above
three products.
The regression coefficients and their standard errors as
estimated from equations [13] through [15] are presented in
Tables 11 and 12. The price flexibility coefficients are given in
Table 13. The frozen concentrated orange juice equations re
sulted in negative price flexibility estimates of .189 and .195 with
natural numbers and natural logarithms, respectively. While
there are no prior estimates of the price flexibility of frozen
concentrate in the export sector, these estimates do not appear
to be unreasonable. Canned single strength orange juice ap
peared as a substitute for frozen concentrate, while canned
single strength grapefruit juice was a complement. The coeffi
cient for hot pack concentrated orange juice was not significant
in the frozen concentrated orange juice equation.
The canned single strength orange juice equation resulted in
negative price flexibility estimates of .304 when natural numbers
were used and .376 when natural logarithms were used. Again,
there are no estimates with which to make comparisons, but it
appears that these estimates are quite reasonable. Frozen
orange concentrate was a substitute in both estimates.
The equation for hot pack concentrated orange juice was not
estimated successfully. The price flexibility coefficient was not
significant when natural numbers were used. It was significant
Table 13. Export Sector: FOB Price Flexibility Coefficients for Florida Orange
Products.
Percentage Change in Price Associated With
1% Change in Quantity of:
Product FCOJ CSSOJ HPCOJ CSSGJ HPCGJ FCGJ
Natezral
Numbers
FCOJ .189 .306 NS t NS NS
CSSOJ .162 .304 NS NS NS NS
HPCOJ NS .220 NS NS NS NS
Natural
Logarithms
FCOJ .195 .386 t t NS NS
CSSOJ .145 .376 t t NS NS
HPCOJ NS .271 t NS NS NS
tSign not acceptable.
NSNot significant at the .05 level.
with logarithmic numbers, but the positive sign was unaccept
able. All of the potential substitutes were either nonsignificant
or had unacceptable signs, except canned single strength orange
juice, which was a substitute. The coefficients of determination
were .316 when natural numbers were used and .299 with
natural logarithms. Both are extremely low and indicate that
the selected set of explanatory variables was rather inadequate.
One observation that might serve to explain part of the problem
with this equation was that the value observations did not
appear to follow a similar pattern to the value observations on
the other products. There was no really noticeable change in the
value figures following the freeze, for example. The quantity
variable, however, did appear to react in a downward direction
following the freeze period. The reason for the unusual behavior
of the value variables was not identified.
SUMMARY
The specific objectives of this study were to make estimates
of pricequantity relationships at the processor or packer FOB
level of the marketing system for Florida oranges and orange
products. The products included fresh oranges, canned single
strength orange juice, chilled orange juice, and frozen concen
trated orange juice in the foodstore and institutional market
sectors, and each of these four products plus hot pack concen
trated orange juice in the export market. Previous work had
been completed for the foodstore sector, particularly for fresh
oranges and frozen concentrated orange juice, but virtually no
previous demand research had been conducted for the institu
tion and export sectors.
A major purpose of this part of the whole study was to
provide the necessary information for estimating marginal
revenues, with respect to quantities of Florida oranges and
orange products, among the major products and marketing
channels. These marginal revenue functions were then used to
determine optimum allocations, of different quantities of supply,
among alternative products and marketing channels. Results
of the allocation analysis are given in a companion report (22).
These two reports jointly provide information that can be used
by planners in the Florida citrus industry to maximize net
returns for given supplies of oranges. While the emphasis in
this study was on the FOB point in the production and mar
keting system, further analysis could reveal any differences in
interests between the grower, FOB, and retail points in the total
system. The increases in vertical integration in recent years,
however, may tend to reduce any difference in interest that
might otherwise exist.
The pricequantity functions were estimated using single
equation least squares regression procedures, and the coefficients
were tested with the F ratio. Product price was used as the
dependent variable. Quantity of the given product, quantity of
each product believed to be a close substitute for which data
were available, and in some cases income and time were used
as independent variables. The equations were estimated with
data in natural numbers and in natural logarithms. The data
were in monthly observations.
In the foodstore sector pricequantity functions were esti
mated for frozen orange concentrate, chilled orange juice, and
canned single strength orange juice at the retail level and ad
justed, by means of estimated margins, to the FOB level. The
function for fresh oranges was estimated directly at the FOB
level. In addition to quantity of the particular orange product,
quantities of other orange products, quantities of grapefruit
and grapefruit products, quantities of other fruit products and
income were used as independent variables in the price equation.
The estimates of retail price elasticity of demand (percent
age change in price associated with a 1% change in quantity)
had negative values of 1.236, 4.140, and 2.919 with data in
natural numbers, and 1.509, 4.214, and 3.008 in natural loga
rithms for frozen concentrated, chilled, and canned single
strength orange juice, respectively. The fact that the coefficients
have negative values means that prices move in the opposite
direction from quantities. Canned single strength grapefruit
juice was a substitute for each of the three products.
In all, pricequantity relationships were estimated for eight
of the 13 product formmarket channel categories considered
initially. Attempts to estimate the pricequantity relationships
were unsuccessful for fresh oranges in the institutional and
export sectors, concentrated hot pack in the export channel, and
single strength canned juice in the institutional sector. Chilled
juice in the export sector was not estimated separately, but in
conjunction with canned single strength orange juice.
The estimated price elasticity of demand for fresh Florida
oranges at the FOB level was a negative 3.293 with data in
natural numbers and 2.900 in natural logarithms. A summary
of the estimates of the price flexibility coefficients is given in
Table 14.
In the institutional sector, functions for frozen concentrated
and chilled orange juice were estimated, but the coefficients in
the equation for canned single strength orange juice were not
significant at the .05 level. Necessary data could not be obtained
for fresh Florida oranges. Price flexibility estimates at the
institutional FOB level for frozen concentrate and chilled juice
had negative values of .272 and .262 with data in natural num
bers. The price elasticity estimates were negative values of
4.541 for frozen concentrate and 4.456 for chilled orange juice
with data in natural numbers.
The price flexibility estimates at FOB for the export sector
for frozen concentrated orange juice had a negative value of
.189 with data in natural numbers. The price flexibility esti
mate for canned single strength orange juice was a negative
.304 in natural numbers. Frozen concentrated orange juice
was a substitute.
In conclusion, the wide range of pricequantity relationships
given in Table 14 indicates that the optimum percentage alloca
tion of Florida oranges, among product forms and market
channels, will depend upon the size of the crop. But to determine
the most profitable allocation, the marginal cost functions in
each product form and market channel, and in turn the net
marginal revenue functions, must be known. The companion
report, cited earlier, carries the analysis into this phase of the
problem (22).
Table 14. Summary of Price Flexibility Coefficients, Florida Oranges and
Orange Products, FOB, in Natural Numbers.
Percentage Change in Price
Product Associated With 1% Change
in Quantity
Foodstore Institutional Export
Sector Sector Sector
Fresh Oranges 0.304 1t
Frozen Concentrate 0.883 0.272 0.189
Chilled Juice 0.610 0.262 tt
Single Strength
Canned Juice 0.122 : 0.304
tNegative vales mean that a change in quantity is associated with a change of the
opposite direction in price.
tNot estimated successfully.
tjData not available; chilled juice data are included in the export data for canned, single
strength.
ACKNOWLEDGMENTS
The materials on which this publication is based were taken
from the Ph.D. dissertation of David Ervin Weisenborn, "Mar
ket Allocation of Florida Orange Production for Maximization
of Net Revenue," Department of Agricultural Economics, Uni
versity of Florida, Gainesville, 1968. Dr. Leo Polopolus, Dr.
D. L. Brooke, Dr. F. W. Williams, and Dr. R. L. Lassiter, Jr.,
served as members of the supervisory committee, and Dr. W. W.
McPherson served as chairman.
In the preparation of the manuscript for publication, we are
very grateful for critical reviews and valuable suggestions re
ceived from our colleagues, Dr. C. D. Covey, Dr. L. H. Myers,
Dr. A. A. Prato, and Dr. J. E. Reynolds, plus several anonymous
reviewers of the Florida Agricultural Experiment Station. We
are grateful, also, to those firms in the industry that supplied
data for use in the study. The support and assistance of the
Florida Citrus Commission is also gratefully acknowledged.
The computer work was done at the University of Florida
Computing Center.
LITERATURE CITED
(1) Chapman, W. F., Jr. Demand and substitution relationships for
Florida and California Valencia oranges produced for fresh market.
Ph.D. dissertation, Univ. of Fla. December 1963.
(2) Florida Canners Association. Frozen concentrated orange juice
Carryover, pack, movement, and goods on hand. Weekly report,
December 7, 1963, through November 25, 1967 issues. Winter Haven,
Florida.
(3) Statistical summary, 196162 through 196667 annual sum
maries. Winter Haven, Florida.
(4) Florida Citrus Commission. Citrus digest, March 1967, through
November 1967 issues. Lakeland, Florida.
(5) . Fresh orange and grapefruit weekly report of national
consumer purchases, weekly reports from October 7, 1961, to October
7, 1967. Lakeland, Florida.
(6) Frozen concentrated, chilled, and canned single strength
orange juice: national consumer purchases, weekly reports from
October 7, 1961, to October 7, 1967. Lakeland, Florida.
(7) Florida Citrus Mutual. Annual statistical report, 196162 through
196667 issues. Lakeland, Florida.
ACKNOWLEDGMENTS
The materials on which this publication is based were taken
from the Ph.D. dissertation of David Ervin Weisenborn, "Mar
ket Allocation of Florida Orange Production for Maximization
of Net Revenue," Department of Agricultural Economics, Uni
versity of Florida, Gainesville, 1968. Dr. Leo Polopolus, Dr.
D. L. Brooke, Dr. F. W. Williams, and Dr. R. L. Lassiter, Jr.,
served as members of the supervisory committee, and Dr. W. W.
McPherson served as chairman.
In the preparation of the manuscript for publication, we are
very grateful for critical reviews and valuable suggestions re
ceived from our colleagues, Dr. C. D. Covey, Dr. L. H. Myers,
Dr. A. A. Prato, and Dr. J. E. Reynolds, plus several anonymous
reviewers of the Florida Agricultural Experiment Station. We
are grateful, also, to those firms in the industry that supplied
data for use in the study. The support and assistance of the
Florida Citrus Commission is also gratefully acknowledged.
The computer work was done at the University of Florida
Computing Center.
LITERATURE CITED
(1) Chapman, W. F., Jr. Demand and substitution relationships for
Florida and California Valencia oranges produced for fresh market.
Ph.D. dissertation, Univ. of Fla. December 1963.
(2) Florida Canners Association. Frozen concentrated orange juice
Carryover, pack, movement, and goods on hand. Weekly report,
December 7, 1963, through November 25, 1967 issues. Winter Haven,
Florida.
(3) Statistical summary, 196162 through 196667 annual sum
maries. Winter Haven, Florida.
(4) Florida Citrus Commission. Citrus digest, March 1967, through
November 1967 issues. Lakeland, Florida.
(5) . Fresh orange and grapefruit weekly report of national
consumer purchases, weekly reports from October 7, 1961, to October
7, 1967. Lakeland, Florida.
(6) Frozen concentrated, chilled, and canned single strength
orange juice: national consumer purchases, weekly reports from
October 7, 1961, to October 7, 1967. Lakeland, Florida.
(7) Florida Citrus Mutual. Annual statistical report, 196162 through
196667 issues. Lakeland, Florida.
(8) Foote, R. H. Analytical tools for studying demand and price
structures. Agricultural Marketing Service, Agricultural Handbook
No. 416, U. S. Dept. of Agriculture, Washington, D. C. August 1958.
(9) Godwin, M. R. Customer response to varying prices for Florida
oranges. Fla. Agr. Exp. Sta. Bull. 508. December 1952.
(10) and L. A. Powell, Sr. Consumer reaction to varying price
for frozen orange concentrate. Fla. Agr. Exp. Sta. Bull. 589.
August 1957.
(11) Henderson, K. R. Demand and substitution relationships for frozen
orange concentrate. Ph.D. dissertation. Univ. of Fla. 1965.
(12) Langham, M. R. Ontree and' instore citrus price relationships.
Proceedings of the Sdcofid Annual Citrus Business Conference, Eco
nomic Research Department, Florida Citrus Commission, FCCERD
661. Lakeland, Florida. January 1966.
(13) Minden, A. J. The demand for frozen concentrated orange juice.
Economic Research Department, Florida Citrus Commission in co
operation with the Department of Agr. Econ., Agr. Exp. Sta., Univ.
of Fla., Agr. Econ. Research Report EC 6613. April 1967.
(14) Economic aspects of Florida chilled orange juice: production,
distribution, and demand. Economic Research Department, Florida
Citrus Commission, Report No. FCCERD6613. Lakeland, Florida.
June 1966.
(15) Powell, L. A., Sr., and M. R. Godwin. Economic relationships in
volved in retailing citrus products. Agr. Exp. Sta., Bull. 567.
August 1955.
(16) Rice, T.G., F. W. Williams, and M. R. Godwin. Demand and substi
tution relationships for Florida orange juice in drugstores. Agr.
Exp. Sta., Univ. of Fla. in cooperation with the Economic Research
Department, Florida Citrus Commission, Agr. Econ. Mimeo Report
EC 6611. May 1966.
(17) Riggan, W. B. Demand for Florida oranges. Ph.D. dissertation.
North Carolina State Univ. Raleigh. 1965.
(18) U. S. Bureau of the Census. U. S. exportsschedule B commodity
by country. Report FT 410, October 1961, through November 1967
issues. Washington, D. C.
(19) U. S. Department of Agriculture, Economic Research Service in
cooperation with the Florida Citrus Commission. Consumer purchases
of citrus: fruit, juices, drinks, and other products. CPFJ168,
October 1961, through March 1967 issues. Washington, D. C.
(20) U. S. Department of Commerce. Survey of current business.
Various issues. Washington, D. C.
(21) Weisenborn, D. E. Market allocation of Florida orange production
for maximization of net revenue. Ph.D. dissertation. Univ. of Fla.
1968.
(22) Weisenborn, D. E., Leo Polopolus, and W. W. McPherson. Market
allocation of Florida orange production for maximum net returns.
Fla. Agr. Exp. Sta. in cooperation with the Florida Department of
Citrus, Bull. 736. 1970.
