Agriculture Reference

In-Depth Information

The Choice of Farm Organization.
Prediction 9.4 says that as the number of cycles

increases, we predict that family farming will be less common. One important element of

seasonality that can be defined empirically is the number of cycles per year for a given

crop in a given location. We classify the crops in our sample into three categories using

the variable CYCLES: crops that potentially have more than one cycle per year; crops that

always have just one cycle per year; and crops that may have fewer than one cycle per

year.
43
In the equations reported in table 9.1, we include the variables CYCLES

>

1 and

1, leaving CYCLES = 1 out of the equations.
44
The distinction between beef

and dairy cattle can also be used to test some predictions of our model. Dairy animals are

kept close to their barns so that they can be milked twice a day, while beef animals usually

range in open pastures. Daily milk production is easier to measure than beef production,

and dairy processors engage in exceptional forms of measurement to ensure that the farmer

does not carelessly handle or tamper with the milk.
45
Finally, there are more routine day-to-

day tasks with dairy production than cow-calf beef operations. None of the beef operations

in our sample are large feedlots with similarly routine daily tasks. All of these factors reduce

monitoring costs on dairy farms. In terms of our model, dairy farms have more cycles and

fewer stages than beef operations. Hence, the use of farm managers and partners is more

viable on dairy farms than beef farms. Since the gains from specialization are greater with

more tasks, our model predicts that the probability of family farm organization will be

higher for beef operations (positive coefficient on BEEF) than for dairy operations (negative

coefficient on DAIRY). The omitted category consists of farms with either no stock or

noncattle stock.

Prediction 9.5 says that as the natural stage uncertainty

CYCLES

<

2

diminishes, the farm is

less likely to be a family farm. Irrigation can control the effect of nature by reducing

variance in output. In terms of the model, irrigation reduces

(σ

)

2
. The coefficient on the

variable IRRIGATION (percent of farmland irrigated) is predicted to have a negative sign.

The estimated equation also included numerous control variables including the percentage

of rented farmland (RENTED LAND), farmer's age (AGE, AGE2), farmer's education

(EDUCATION, EDUCATION
2
), and a dummy for British Columbia (BC).

We use the British Columbia-Louisiana data to estimate the determinants of farm organi-

zation choice and test some specific predictions from our model. The empirical specification,

for the complete model is

σ

F
i
=
X
i
β
i
+
i
i
=

1,

...

,

n

;

and

(9.12)

1,

F
i
>

if

0

F
i
=

(9.13)

F
i
≤

0,

if

0,