incompatible with the soybean price data. The confidence bands for the soybean price occurrences under the
non-normal model (Figure 2) are markedly non-symmetric about the predictions, reflecting the kurtosis and
right-skewness of the estimated error term distribution. The 95% band leaves one observation above and one
below its boundaries (1.25 required). The, 90, 85 and 80% bands leave three and two, five and three, and six
and four observations below and above their boundaries, respectively, vs. the theoretically required numbers of
2.5, 3.75 and five, respectively. When all of the 16 confidence bands are considered, 59 and 42 observations
are found below and above their lower bounds, respectively, versus the theoretically required number of 50
(Table 4). Compatibility with the data is improved by lower bounds that are consistently higher than their
normal counterparts, and thus closer to the low price occurrences, combined with upper bounds that become
relatively higher than the normal bounds at reduced α levels (Table 2 and Figures 1 vs. 2). The non-normal
confidence bands are also narrower than the normal bands, on average and up to the 93% confidence interval.
On average, the 16 non-normal confidence bands for the corn price occurrences also appear more
compatible with the observed data than the bands under the normal-error model, leaving 52 and 46
observations below and above their lower bounds, respectively, vs. 28 and 45, respectively. They are also
narrower than the normal bands on average and up to the 93% confidence interval (Table 4).
The fact that the non-normal models result in confidence bands that are more consistent with the
observed data is important given the many empirical applications of confidence intervals. It also provides for
an intuitive explanation of the more precise slope parameter and dependent variable predictions afforded by the
non-normal models. That is, the degree of uncertainty about the location of the true regression line (or hyper
plane in the multiple regression case) is reduced by an improved accounting of the phenomena causing the data
deviations form the line (or hyper plane), i.e. by the improved modeling of the error term distribution.
An Empirical Model of the West Texas Cotton Basis
Another issue of importance to agricultural economists is the behavior of the basis in a futures
market, and measuring the impact of market and policy factors on the level and variability of the basis
(Seamon and Kahl). For the purposes of this study, the monthly (January 1980 to December 2000) West
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