Abstract
Adaptive estimation is frequently used when the error distribution is non-normal. We propose a partially adaptive estimator based on the maximum entropy estimate of the error distribution. Under the conditions specified in McDonald and Newey (1988), the proposed estimator is asymptotically normal and efficient for the slope parameters. We investigate the finite sample performance of the proposed method and compare it with existing methods. We also apply the estimator to real world data.
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