Agricultural Policy as a Social Engineering Tool

pursue domestic economic and social policy goals even if the policies affect international
trade.

Descriptive statistics for the independent variables: educational attainment, sales,
age, tenure, and farm income are also presented in Table 2. According to Table 2, 142
farm operators answered the question regarding the last year of school completed by the
principal operator of the farm or ranch. Of that total, 3 (2%) completed grade school, 6
(4%) had some high school education, 32 (23%) had a high school diploma, 32 (23%)
had some college education, 39 (27%) had a bachelor’s degree and 30 (21%) had an
advanced degree. In the sales category, a majority (47%) of farm operators had average
annual sales from their farm operations, including government program benefits, of less
than $10,000. Eighty-five percent of the farm operators were older than 45 years old and
most (74%) own the land that they farm or ranch. A majority of farm operators (45%)
typically earned 1-25% of their family income from farming.

Methodology

The methodology used in this study has been presented elsewhere but is repeated here to
facilitate the discussion (see Tavernier, 2005). The model assumes that farm operators
maximize an intertemporal profit function. Clearly given the current discussions
surrounding the Doha Round trade negotiations, a willingness to restrict trade to pursue
domestic, economic and social policy goals would invite retaliation and may make farm
operators worse off in the long-run as international trade contracts. Following that
rationale, the model assumes that once a farm operator makes the choice to restrict or not
to restrict trade s/he maximizes a profit function subject to uncertainty about that

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