This paper is concerned with the large sample efficiency of the asymptotic least-squares (ALS) estimators introduced by Gourieroux, Monfort, and Trognon (1982, 1985) and Chamberlain (1982, 1984). We show how the efficiency of these estimators is affected when additional information is incorporated into the estimation procedure. The relationship between ALS and maximum likelihood is discussed. It is shown that ALS can be used to obtain asymptotically efficient estimates for a large range of econometric models. Many results from the literature on estimation are special cases of the framework adopted in this paper. An application of ALS to a dynamic rational expectation factor demand model in the manufacturing sector in the Netherlands demonstrates the potential of the method in the estimation of the parameters in models which are subject to nonlinear cross-equation restrictions. Copyright 1990 by John Wiley & Sons, Ltd.
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Volume (Year): 5 (1990) Issue (Month): 3 (July-Sept.) Pages: 229-43 Download reference. The following formats are available: HTML
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