SOUTHERN JOURNAL OF AGRICULTURAL ECONOMICS DECEMBER 1990
THE CORN-EGG PRICE TRANSMISSION MECHANISM
Ronald A. Babula and David A. Bessler
Abstract
A vector autoregression (VAR) model of com,
farm egg, and retail egg prices is estimated and
shocked with a com price increase. Impulse respon-
ses in egg prices, t-statistics for the impulse respon-
ses, and decompositions of forecast error variance
are presented. Analyses of results provide insights
on the com∕egg price transmission mechanism and
on how com price shocks pulsate through the egg-
related economy.
Key words: com∕egg price transmissions, vector
autoregression, impulse responses,
Chow test, forecast error variance
decompositions, Kloek-Van Dijk
Monte Carlo procedure
This paper employs vector autoregression (VAR)
econometrics to identify empirical regularities be-
tween com and egg prices and uses the regularities
to demonstrate how these prices have dynamically
interacted since the 1950s. Recent research has used
time series techniques to monitor policy-relevant
dynamics on how farm sector shocks, which work
through crop prices, influence related food prices in
the economy’s noncrop sectors. Babula and Bessler
(1989b) employed vector autoregression methods to
reveal the dynamic characteristics or attributes of
how a farm sector shock, which changes farmgate
wheat price, pulsates through the nonfarm economy
as price changes for wheat-based goods. Babula,
Bessler, and Schluter (1990) used VAR techniques
to examine the dynamic relationships among com
price, farm poultry price, and retail poultry price,
and how these relationships have changed over the
1957-1989 period. This previous research has
focused on the following dynamic attributes con-
cerning how related noncrop prices respond to a
change in farm crop price: (1) reaction times for
responses, (2) directions, patterns, and durations of
responses, (3) how response patterns for related
prices are similar (or dissimilar) across sectors, and
(4) the strengths of the interrelationships among
crop-related prices in different sectors of the
economy.1
In this paper, VAR econometrics is used to identify
empirical regularities from monthly time-ordered
data on how farm com price (PCN), farm-level egg
price (PF), and retail egg price (PR) have dynami-
cally moved together and interacted together
through time. More specifically, this paper uses VAR
econometrics to describe the dynamic attributes
listed above in items (1) through (4) for the PCN-
PF-PR price transmission.
The paper is presented in five additional sections.
First, a digression on VAR modeling is presented.
This section provides a justification for use of VARs
with uncontrolled secondary data. Second, the data
sources are described and a brief summary of the
estimated model is given. At the paper’s focus is the
dynamic relationship among the three series under
investigation, and because these dynamics are best
described in their moving average (impulse response
function) form, rather than in their autoregressive
form (Sims 1980), the estimated autoregressive
model is not presented. The Stationarity of the
residuals from the autoregressive representation and
out-of-sample forecasts from the estimated VAR is
considered as additional evidence on the ap-
propriateness of the estimated VAR. The third sec-
tion of the paper presents the impulse response
functions that are derived from the autoregressive
representation. This section is followed by an
analysis of forecast error variance decompositions,
which measure the strength of dynamic inter-
ɪ Some VAR econometric work on egg prices has appeared: Shrader, Bessler, and Preston (1985); Bessler and Shrader (1980);
and Thurman and Fisher (1988). Thurman and Fisher (1988) examine causality relationships between annual egg and chicken prices.
The other two studies are time series comparisons of competing daily egg quotes at one point in the food chain. The study reported
here is different, in that it uses monthly data to examine egg-related price effects of a faɪm sector shock that influences com price.
Ronald A. Babula is an Agricultural Economist with the National Aggregate Analysis Section, Economic Research Service, U.S.
Department of Agriculture. David A. Bessler is a Professor of Agricultural Economics, Texas A&M. University. The authors wish to thank
Dr. Gerald Schluter, Leader, National Aggregate Analysis Section, Economic Research Service, for input and suggestions in all phases of
this study, and Dr. Dan McLemore and three anonymous reviewers for their helpful comments. The opinions herein are the authors’ and
not necessarily shared by the U.S. Department of Agriculture or Texas A&M.
Not subject to copyright in the United States.
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