المستخلص: |
The method of least absolute deviation (LAD) provides a robust alternative to least squares, particularly when the disturbances follow distributions that are non-normal and subject to outliers. While inference in least squares estimation is well understood, inferential procedures in the context of least absolute deviation estimation have not been studied as extensively particularly in the presence of auto correlation. In this paper we study two alternative significance test, procedures in least absolute deviation regression, along with two approaches used to correct for serial correlation. The study is based on a Monte Carlo simulation, and comparisons are made based on observed significance levels.
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