On estimators for truncated height samples
Statistical inference from truncated height data is often based on distributional assumptions. In this paper we analyze a data set of over 23,000 conscript height observations, covering nearly all conscripts in Drenthe, a province of the Netherlands, over the period 1826-1860. The data do not satisfy the normality assumption. We demonstrate that the ML estimators of the mean proposed for normally distributed data do not yield satisfactory results. We propose a new estimator that exploits the relationship between the conditional mean of the observations above the minimum height requirement and the conditional mean and proportion of conscripts below the minimum height requirement.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Richard H. Steckel, 1995. "Stature and the Standard of Living," Journal of Economic Literature, American Economic Association, vol. 33(4), pages 1903-1940, December.
- Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
- John Komlos, .
"Shrinking in a Growing Economy? The Mystery of Physical Stature during the Industrial Revolution,"
Articles by John Komlos
7, Department of Economics, University of Munich.
- Komlos, John, 1998. "Shrinking in a Growing Economy? The Mystery of Physical Stature during the Industrial Revolution," The Journal of Economic History, Cambridge University Press, vol. 58(03), pages 779-802, September.
- A'Hearn, Brian & Komlos, John, 2003. "Improvements in Maximum Likelihood Estimators of Truncated Normal Samples with Prior Knowledge of σ," Discussion Papers in Economics 51, University of Munich, Department of Economics.
When requesting a correction, please mention this item's handle: RePEc:eee:ehbiol:v:6:y:2008:i:1:p:43-56. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If references are entirely missing, you can add them using this form.