An Alternative Approach to Obtaining Nagar-Type Moment Approximations in Sumultaneous Equation Models
The paper examines asymptotic expansions for estimation errors expressed explicitly as functions of unferlying random variables. Taylor series expansions are obtained from which first and secomd moment approximationc are derived. While the expansions are essentially equivalent to the traditional Nagar-tupe, the terms are expressed in a form which enables moment approximations to be obtained in a particular straightforward way, once the partial derivatives have been found. The approach is illustrated by considering the k-class estimators in a static simultaneous equation model where the distrubances are non-spherical.
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