nominal price term as the dependent variable.
Therefore the impact of an increased price level
may well explain the increased standard devia-
tion from before to after order formation in
these three cases. Note, however, that the
standard deviation of the relative price terms
declined in both spring and fall. This result is
expected because the impact of inflation is re-
moved via the relative price terms. Given these
considerations, we can conclude that the use of
a relative variation measure such as the coef-
ficient of variation is appropriate.
SUMMARY AND CONCLUSIONS
We investigate the impact of a market order
established in 1970 on the level and variability
of South Carolina fresh market cucumber
prices. The major provisions of the order that
have an impact on price are price posting by
handlers and uniform USDA inspection. A
time series regression model that covers and
accounts for periods before and after formation
of the order indicates that the order did have a
positive impact on the South Carolina cucum-
ber price level.
Further analysis using the coefficient of
variation as a measure of price variability indi-
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
after regression equations, (3) within-season
price variability, and (4) within-season price
variability in relation to the prices in neighbor-
ing producing regions.
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