PERCENTCHANGE
IN PRICE INDICES
v4{i(ηv,Vas0B⅛βΦO∙*N'∏W,lΛ'Λf4≡O'≡*<Nn∙in'OCκC0OO∙*O3fr>4*in∣0
wMHHHHτ<'HHHHNMtJNNNNMC∙ΠH(*5∕∏nnn<*1
All impulse responses that are statistically MONTHS (STEPS)
non-zero at the one-percent significance level
are denoted with solid characters.
Figure 1. Impulse Response in Egg Prices to a One-Time Increase in Corn Price
impulses are accumulated percent changes in the
indices over the 17-month period when statistically
non-zero change was observed. Each sensitivity
parameter of egg price to com price change repre-
sents a percent change divided by a percent change
and resembles an elasticity defined for the period of
the response variable’s statistically significant
change. For farm egg price, the sensitivity parameter
of 0.40 suggests that each percent of com price
change is associated with slightly more than one-
third of a percent of statistically significant change
in the farm egg price.
For the retail egg price, the parameter value of 0.32
suggests that each percent of com price change is
associated with about one-third of a percent of statis-
tically significant change in the retail egg price. The
less-than-unity nature of these sensitivity
parameters coincides with previous research in in-
dicating that egg price responses are usually less
than the com price change, and that egg price
responses to com price change become weaker for
pricing points located further down the marketing
chain from the farmgate (Babula and Bessler 1989a,
b).
Decompositions of Forecast Error Variance
Analysis of forecast error variance (FEV) is
another t∞l of VAR econometrics for discerning
relationships among the modeled system’s time
series. FEV is, at alternative forecast horizons or
steps, attributed to shocks in each of the dynamic
system’s series, such that a measurement of relative
“strength” of relationships emerges. Error decom-
positions attribute within-sample error variance to
alternative series and thus give measures which are
useful in applied work. Table 1 contains selected
FEV decompositions for the three prices.
A variable’s exogeneity is suggested when its FEV
is largely attributed to its own variation. Likewise, a
variable is highly endogenous to the system when
small proportions of its FEV are attributed to its own
variation, and large FEV proportions are attributed
to the innovations of other variables (Bessler 1984a,
b).
A number of results emerge from Table 1.6 Com
price is largely exogenous with more than 93 percent
of its FEV being self-attributed at all reported
horizons. Farm egg price is exogenous, but to a more
moderate degree than com price. More than 62 per-
cent of PF’s uncertainty is self-attributed. More than
6Table 1 provides further evidence of the VARmodeTs stationarity. Stationarityis SuggestedbecausewhileeachequationlS
standard errors in Table 1 continue to increase at the longer horizons, the standard errors do so by “leveling-off1 toward particular
values at the longer horizons (steps 35-36) (Bessler 1984a).
83