Least Square Approach to Non-Normal Disturbances
This paper takes a computationnaly simple LS approach to develop a more efficient estimation procedure, which we call Residual Augmented Least Square (RALS), than OLS when the errors are not normally distributed. The efficiency gain is from manipulating the higher moment conditions implied by the standard i.i.d. assumption. Asymptotic results as well as Monte Carlo Showing small sample performance of RALS comparing with OLS are presented.
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