installation time-period attributes (Model 1), and second, as a function of Model 1 variables plus
socio-environmental variables reflecting the potential influence of a variety of field, farm, and
environmental characteristics (Model 2).
GEE equations model the correlation resulting from repeated measures on a given subject,
or dependencies across clusters of observations. The method is also flexible enough to model
correlation within subjects or between groups using a variety of covariance structures. In our case,
we assume that the farmer (the “subject effect”) is faced with a set of land-management practices
[which he may choose to implement, i.e., crop field acres without or with in-field or perimeter-field
conservation structures, or both] (the “within-subject” effects). Because of the trade-offs between
crop production and field acres set aside for conservation structures, the decision to allocate acres to
one production technology or another may be correlated. We specify an unstructured working
correlation matrix to model the potential correlation between these technology choices (i.e. the
correlation matrix structure typically associated with SUR or multivariate probit models).
Corn field acreage-supply equations are estimated for four alternative production technology
decision options: (1) acres of corn production for fields with no conservation structural practices
(i.e., only corn acres); (2) acres of corn production for fields involving only infield structural
practices; (3) acres of corn production for fields involving only perimeter-field structural practices;
and (4) acres of corn production for fields involving both infield and perimeter-field structures.
These acreage supply equations were estimated for both conservation program participants and non-
participants. The acreage supply equations were linearized by taking the natural logarithm of the
acreage function. To account for the problem of zero acres allocated to a particular structure, “one
acre” was added to each crop, in-field, perimeter-field, or (both) technology option, for each
respondent. The GENMOD procedure in SAS version 9 was used to estimate the GEE system.
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