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Example
21
Bootstrapping to Compare
Estimation Methods
Introduction
This example demonstrates how bootstrapping can be used to choose among
competing estimation criteria.
Estimation Methods
The discrepancy between the population moments and the moments implied by a
model depends not only on the model but also on the estimation method. The
technique used in Example 20 to compare models can be adapted to the comparison
of estimation methods. This capability is particularly needed when choosing among
estimation methods that are known to be optimal only asymptotically, and whose
relative merits in finite samples would be expected to depend on the model, the sample
size, and the population distribution. The principal obstacle to carrying out this
program for comparing estimation methods is that it requires a prior decision about
how to measure the discrepancy between the population moments and the moments
implied by the model. There appears to be no way to make this decision without
favoring some estimation criteria over others. Of course, if every choice of population
discrepancy leads to the same conclusion, questions about which is the appropriate
population discrepancy can be considered academic. The present example presents
such a clear-cut case.