Assessing the Magnitude of the Concentration Parameter in a Simultaneous Equations Model

Donald Poskitt and Christopher Skeels

No 29/04, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: Poskitt and Skeels (2003) provide a new approximation to the sampling distribution of the IV estimator in a simultaneous equations model. This approximation is appropriate when the concentration parameter associated with the reduced form model is small and a basic purpose of this paper is to provide the practitioner with a method of ascertaining when the concentration parameter is small, and hence when the use of the Poskitt and Skeels (2003) approximation is appropriate. Existing procedures tend to focus on the notion of correlation and hypothesis testing. Approaching the problem from a different perspective leads us to advocate a different statistic for use in this problem. We provide exact and approximate distribution theory for the proposed statistic and show that it satisfies various optimality criteria not satisfied by some of its competitors. Rather than adopting a testing approach we suggest the use of p-values as a calibration device.

Keywords: Concentration parameter; simultaneous equations model; alienation coefficient; Wilks-lambda distribution; admissible invariant test. (search for similar items in EconPapers)
JEL-codes: C12 C39 C52 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2004-12
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Assessing the magnitude of the concentration parameter in a simultaneous equations model (2009)
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