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Abstract
Much research work has been conducted in recent
years to evaluate the effects of research
and extension.2/ Some of these efforts were conducted
at the national aggregate level, while
others were conducted at the regional or community
levels. The methodologies used in those
studies varied, but most of the studies were
based on regression analysis of ex post data.
There are several difficulties associated with
the above ex post analyses. First, the time lags
from the time of research resource commitment to
production of extendable technology (invention),
i.e., the leadtime, ranges from a few years to
decades. It is difficult to collect time series
data to accommodate a long leadtime. Besides,
the average lead time is not known unless one
studies specific research projects. Thus, most,
if not all, researchers ignore the leadtime.
They just assume that research output will come
about as soon as the research resources are
committed, even though most researchers recognize
and account for adoption lag.
Secondly, research and extension enter into
the process of technological innovation at
different points in time. Although feedbacks
from extension often result in changes in the
direction or additional research to be conducted,
extension plays little role in the development of
a new technology. When the research is completed
and a new technology is produced, extension comes
into play. Thus, extension follows research in
that process. Many researchers recognize this
lag, but unless dealing with a specific technology,
the lag length is usually unknown. Thirdly, in time series data, research and
extension expenditures are highly collinear.
One reason for the existence of this collinearity
is that the budgets are allocated or authorized
for both functions regarding the same issue at
the same time. Attempts to estimate the separate
effects of research and extension using the regression
analysis often fail.
Fourthly, all ex post analyses were based on
data since World War I when fossil fuel was
cheap and abundant. Since the likelihood of
having cheap and abundant fossil fuel in the
future is very slim, the estimated relationships
may not be relevant in predicting or planning
for the future.
This study proposes an alternative approach
to overcome the above difficulties. The purpose
of this study is to describe proposed methodology
and procedures to estimate the separate rates
of return to research and extension in U.S.
agriculture using an ex ante analysis.