distributed, this could become an important tool in agricultural economics research. The theory and
examples above also suggest that the degree of improvement over the normal-error models depends on how
much the true error term distribution deviates from normality and on how well the non-normal error term
distribution on which the partially adaptive estimation procedure is based approximates the true data-
generating distribution. This is why very flexible distributions, such as the expanded form of the Johnson
Su family, should be preferred for partially adaptive estimation. The applications above also illustrate that
proposed technique could be useful if the estimated models will be used to simulate conditional probability
distributions for the dependent variable, which are often used for economic risk analysis.
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