Least Square Approach to Non-Normal Disturbances
AbstractThis 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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Bibliographic InfoPaper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 9603.
Length: 20 pages
Date of creation: 1996
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Web page: http://www.econ.cam.ac.uk/index.htm
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- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
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