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Interpretation of Graphs that Compare the Distribution Functions of Estimators

Published online by Cambridge University Press:  11 February 2009

Brent R. Moulton
Brent R. Moulton
Affiliation:
U.S. Bureau of Labor Statistics
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Abstract

In this paper I examine graphical comparisons of one-dimensional (or marginal) distribution functions of alternative estimators. It is shown that areas under the c.d.f. (cumulative distribution function) curve can be given a decision-theoretic interpretation as risk under a bounded absolute-error loss function. I also show that by a simple rescaling of the graph's axes, graphical areas are created which can be interpreted as risk under bounded squared-error loss. The bounded loss functions are applied to compare graphically and numerically the risk of exact distributions of the limited-information maximum likelihood and two-stage least-squares estimators in a simultaneous equations model.

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Type
Articles
Information
Econometric Theory , Volume 6 , Issue 1 , March 1990, pp. 97 - 102
Copyright
Copyright © Cambridge University Press 1990

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