The name is absent

in time. Given the nature of the provisions of
the South Carolina marketing order, this
assumption is plausible. Ordinary least
squares estimation of equation 1 is presented
in the next section.

EMPIRICAL RESULTS

Equation 1 was estimated by means of
regression analysis. Data from 1960 to 1978
were used in the analysis. PSC values were
taken from the S.C. Crop and Livestock Re-
porting Service, PROD and OP values from
various USDA publications, and GNP values
from the Commerce Department. The primary
objective of the estimation was to investigate
the impact of the formation of the South Caro-
lina marketing order on the price level of cu-
cumbers marketed in the state. The estimated
equation is

(2) PSC = 5.47 - .0083*PROD + .236*GNP +
(.002)           (.136)

.471*OP - .639*MO + 1.07*ORDER
(.069)     (.138)       (.537)

R² = .73 (standard errors are in parenthe-
ses).

Each estimated coefficient is significant at
the 10 percent level or better, and each variable
has the expected sign. The results indicate that
the marketing order has had an impact of ap-
proximately $1.07 per 100 pounds on the price
South Carolina producers receive for their cu-
cumbers. To obtain this price increase, produc-
ers pay assessments of up to 10 cents per
hundred weight (5 cents per bushel). In addi-
tion, USDA inspection fees must be paid on all
cucumbers sold within the state. The addition-
al inspection charge is difficult to determine
because some cucumbers were inspected prior
to formation of the order, but it would not
negate the estimated gain. Therefore, we con-
clude that formation of the South Carolina
marketing order for cucumbers has had a posi-
tive impact on the price level for growers.

As an additional check on the price impact of
order formation, an F-test was conducted. The
test compared an equation estimated with ob-
servations prior to order formation with the
same equation estimated with observations
covering the period before and after order for-
mation. Equation 1 with the ORDER variable
omitted was used in this analysis. The F-test is
described by Johnston (p. 207). The calculated
F-value with 48 and 60 degrees of freedom is
2.16. This value is significant at the 1 percent
level. The implication is that order formation
did have a price impact.

PRICE VARIABILITY ANALYSIS

The hypothesis of reduced price variability
was investigated by means of two measures of
variability. The standard deviation and coef-
ficient of variation are calculated for several
variables for the periods before and after the
formation of the order. These variables are (1)
the before and after monthly prices, (2) error
terms from before and after regression estima-
tions of equation 1, i.e., without the ORDER
term, (3) average before and after prices for the
spring and fall crops, i.e. average seasonal
prices, and (4) before and after within-season
average price for South Carolina in relation to
the North Carolina price during spring and in
relation to the Virginia price during fall (Table
1). Both the standard deviation and coefficient
of variation are presented because the hypothe-
sized price level increase and inflation tend to
inflate the standard deviation. The coefficient
of variation is the standard deviation in rela-
tion to the mean, and in essence adjusts for the
increase of the standard deviation caused by
higher prices. Several authors discuss the use
of the coefficient of variation as an appropriate
measure of the relative variability in such
cases (e.g., Snedecor and Cochran, p. 62-5;
Sanders, Murph, and Eng, p. 84-5). The coef-
ficient of variation declined after order forma-
tion for each of the four variables considered
(Table 1). In contrast, three of the six standard
deviations increased, indicating greater
absolute variability (Table 1). Two of the three
standard deviations that increased applied to
nominal price measures whereas the third
applied to the error term of an equation with a

I. Monthly Price

Before              1.59

After               2.40

11. Error Term

(Before & after
equations)

Before              1.26

After               1.87

III. Within Season

Price

Befo re

After

IV. Within Season
Relative Price

Befo re

After

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