Testing for normality in truncated anthropometric samples

Antonio Fidalgo
Additional contact information
Antonio Fidalgo: HS-Fresenius University of Applied Sciences

No 142, Working Papers from European Historical Economics Society (EHES)

Abstract: Anthropometric historical analysis depends on the assumption that human characteristics—such as height—are normally distributed. I propose and evaluate a metric entropy, based on nonparametrically estimated densities, as a statistic for a consistent test of normality. My first test applies to full distributions for which other tests already exist and performs similarly. A modified version applies to truncated samples for which no test has been previously devised. This second test exhibits correct size and high power against standard alternatives. In contrast to the distributional prior of Floud et al. (1990), the test rejects normality in large parts of their sample; the remaining data reveal a downward trend in height, not upward as they argue.

Keywords: test of normality; truncated samples; anthropometrics (search for similar items in EconPapers)
JEL-codes: C12 C14 J11 N13 N3 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2018-12
New Economics Papers: this item is included in nep-ecm and nep-his
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.ehes.org/wp/EHES_142.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hes:wpaper:0142

Access Statistics for this paper

More papers in Working Papers from European Historical Economics Society (EHES) Contact information at EDIRC.
Bibliographic data for series maintained by Paul Sharp ().