EH.Net Abstracts in Economic History

                ABSTRACTS IN ECONOMIC HISTORY
                     (c) 2003 EH.Net
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Name:  John Komlos
Email:  jk at econhist.de
Institution: Department of Economics, University of Munich,
Germany

Co-author:  Brian A'Hearn
Department of Economics
Franklin and Marshall College
USA

Title: Improvements in Maximum Likelihood Estimators of Truncated 
Normal Samples with Prior Knowledge of the Standard Deviation: A 
Simulation Based Study with Application to Historical Height Samples

Internet Address of abstracted work:
http://www.vwl.uni-muenchen.de/ls_komlos/bias-precision.pdf

By mail:
Ludwigstr. 33/IV  80539 Munich, Germany

Language:  English

Abstract:
Researchers analyzing historical data on human stature have long 
sought an estimator that performs well in truncated-normal samples. 
This paper reviews that search, focusing on two currently widespread 
procedures: truncated least squares (TLS) and truncated maximum 
likelihood (TML). The first suffers from bias. The second suffers in 
practical application from excessive variability. A simple procedure 
is developed to convert TLS truncated means into estimates of the 
underlying population means, assuming the contemporary population 
standard deviation. This procedure is shown to be equivalent to 
restricted TML estimation. Simulation methods are used to establish 
the mean squared error performance characteristics of the restricted 
and unconstrained TML estimators in relation to several population 
and sample parameters. The results provide general insight into the 
bias-precision tradeoff in restricted estimation and a specific 
practical guide to optimal estimator choice for researchers in 
anthropometrics.

Bibliography: Komlos, John and Brian A'Hearn. "Improvements in 
Maximum Likelihood Estimators of Truncated Normal Samples with Prior 
Knowledge of the Standard Deviation: A Simulation Based Study with 
Application to Historical Height Samples." Unpublished manuscript, 
2003.

Subject:  U
Geographical Area:  0
Country/Region:
Time Period:  0

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