Agriculture Reference
In-Depth Information
Equipment: Ownership versus Contracting
For the data we examine, the choice of equipment control regimes is between ownership and
a simple long-term contract. When farmers rent equipment such as combines and tractors,
they are typically charged by the hour or some other unit of time (for example, day, week,
month).
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Like land, many attributes of leased equipment remain unpriced although the lease
typically assigns responsibility for equipment maintenance. Equipment leases are usually
written and usually last less than a year. Most long-term (greater than one year) equipment
leases have options to buy (Pflueger 1994). As with land, not all of the incentives identified in
table 8.2 are relevant for equipment. Asset moral hazard, capital constraints, and timeliness
costs are the most important incentives. To a lesser degree, asset specialization is a factor.
Again like land, increases in capital constraints are predicted to increase the probability
of leasing. Many pieces of equipment are at least as expensive as a substantial plot of land.
For example, a half section (320 acres) of dry wheat land may be worth $128,000 at $400
per acre. Still, a large modern combine or tractor would easily be worth more than $100,000.
As with land, we measure wealth using WEALTH (the combined value of land, buildings,
and equipment) and NET WEALTH (value of buildings and land).
Timeliness costs are likely to be an important determinant of equipment control in farm-
ing. Equipment is seldom rented for an entire season and is often rented for only a particular
stage of production. For certain kinds of equipment, during crucial stages, timeliness costs
arise because other farmers demand the equipment at the same time. Even in a custom
contract, when the equipment owner is in control, he influences the arrival of the equip-
ment and may arrive too early or too late depending on other commitments. Our model
implies that increases in timeliness costs will decrease the probability of contracting for
assets. In order to test this prediction against our equipment data, we need to distinguish
situations with varying levels of timeliness costs. We use three variables, one that mea-
sures the number of pieces of similar equipment a farmer owns, one that measures the
shared equipment, and one that measures the degree to which a piece of equipment is
specialized.
Farmers often use multiple pieces of the same or similar machines (for example, com-
bines, tractors, trucks). Although these pieces of equipment are used on the farm, in terms
of timing the first piece is the most important. In other words, it is more important to
own one tractor than to own an additional one in order to plant or harvest a crop when
Mother Nature's window of opportunity opens. A dummy variable MULTIPLE EQUIP-
MENT identifies farmers who own additional pieces of the same machine and is predicted
to be positively correlated with the probability of leasing. When a farmer shares equip-
ment with a neighbor, the equipment almost certainly has no timing problems because the
neighbor faces the same seasonal situation as the farmer. A dummy variable SHARED
