The LIML estimator has finite moments!

T.W. Anderson

Journal of Econometrics, 2010, vol. 157, issue 2, 359-361

Abstract: The Limited Information Maximum Likelihood estimator of the vector of coefficients of a structural equation in a simultaneous equation model is the vector that defines the linear combination maximizing the effect variance relative to the error variance. If this "eigenvector" solution is normalized by setting a designated coefficient equal to 1, the second-order moment of the estimator may be unbounded. However, the second-order moment is finite if the normalization sets the sample error variance of the linear combination equal to 1.

Keywords: Limited; Information; Maximum; Likelihood; Bounded; moments; Normalization (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (7)

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