Agriculture Reference
In-Depth Information
Table 5.10
OLS cropshare regression coefficient estimates
(dependent variable = ln(SHARE/(l
SHARE)))
Independent variables
Full sample
Full sample
Full sample
Predicted sign
CONSTANT
0.1556
0.1102
0.0435
(3.076)
(1.998)
(0.881)
Measurement costs
INPUTS
0.0652
0.0653
0.0581
+
(10.953)
(10.972)
(9.920)
Soil exploitation
ROW CROP
0.12020
0.11691
( 3.471)
( 3.313)
IRRIGATED
0.0985
0.0993
0.1169
+
(4.025)
(4.058)
(4.545)
CORN
0.04282
( 1.364)
OATS
0.1338
+
(4.149)
SOYBEANS
0.0822
( 3.180)
WHEAT
0.1123
+
(4.554)
Controls
YEARS DURATION
0.0031
0.0029
(2.787)
(2.675)
ACRES
1.284 E
05
3.372 E
05
(0.305)
(
0.805)
Observations
1,628
1,628
1,628
F-value
58.84
37.03
31.22
Adjusted R 2
0.096
0.099
0.129
Notes: t-statistics in parentheses.
significant at the 5 percent level (one-tailed test for coefficients with predicted signs).
different crops in different regions, they would have found dominant equilibrium shares
different from 50-50. Indeed, sometimes they can be substantially different. The dominant
share for apples in British Columbia is 85 percent, for sugarcane in Louisiana is 80 percent,
and for wheat in Nebraska is 67 percent.
Focalness often appears when no consideration is given to sharing input costs. Table 5.11
shows frequency distributions for share terms, controlling for crops and for the allocation of
input costs for corn and soybeans from the Nebraska-South Dakota data. When the inputs
are shared, the 50-50 contract dominates in a manner similar to what Young and Burke
 
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