Paolo, Foschi (2005): Estimating regressions and seemingly unrelated regressions with error component disturbances.

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Abstract
The estimation of regressions models with twoway error component disurbances, is considered for the case where both the random effects are nonspherically distributed. The usual approach that first transforms the effects into uncorrelated ones and then applies within and between transformations, cannot be conveniently applied. Here, it is proposed to revert this scheme by firstly applying the within and between transformations. This results in simple General Linear Model which can be partitioned into three smaller GLMs. Then, by exploiting the structure of the models and using the Generalized QR decomposition as a tool, a computationally efficient and numerically reliable method for estimating the regression parameters is derived. This estimation method is generalized to the case of a system of seemingly unrelated regressions.
Item Type:  MPRA Paper 

Institution:  University of Bologna 
Original Title:  Estimating regressions and seemingly unrelated regressions with error component disturbances 
Language:  English 
Keywords:  panel data models; regressions; seemingly unrelated regressions; generalized leastsquares; error components; orthogonal transformation; numerical methods 
Subjects:  C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C32  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C33  Panel Data Models ; Spatiotemporal Models C  Mathematical and Quantitative Methods > C6  Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63  Computational Techniques ; Simulation Modeling 
Item ID:  1424 
Depositing User:  Paolo Foschi 
Date Deposited:  11. Jan 2007 
Last Modified:  24. Mar 2015 23:03 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/1424 