Height and the Normal Distribution: Evidence from Italian Military Data.
Researchers modeling historical heights have typically relied on the restrictive assumption of a normal distribution, only the mean of which is affected by age, income, nutrition, disease, and similar influences. To avoid these restrictive assumptions, we develop a new semiparametric approach in whi...
| Publicado en: | Demography Vol. 46; no. 1; pp. 1 - 26 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Science & Business Media B.V.
February 2009
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=510761374&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 510761374 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00703370 DEM jtl: Demography issn: 00703370 maglogo: N pubinfo: dt: February 2009 vid: 46 iid: 1 pid: 237 pub: Springer Science & Business Media B.V. artinfo: ui: 510761374 10.1353/dem.0.0049 ppf: 1 ppct: 25 formats: fmt: – @attributes: type: T – @attributes: type: P size: 5.2MB tig: atl: Height and the Normal Distribution: Evidence from Italian Military Data. aug: au: A'Hearn, Brian Peracchi, Franco Vecchi, Giovanni su: Stature Mathematical models Physical anthropology Anthropometry Italy sug: subj: Italy Stature Mathematical models Physical anthropology Anthropometry ab: Researchers modeling historical heights have typically relied on the restrictive assumption of a normal distribution, only the mean of which is affected by age, income, nutrition, disease, and similar influences. To avoid these restrictive assumptions, we develop a new semiparametric approach in which covariates are allowed to affect the entire distribution without imposing any parametric shape. We apply our method to a new database of height distributions for Italian provinces, drawn from conscription records, of unprecedented length and geographical disaggregation. Our method allows us to standardize distributions to a single age and calculate moments of the distribution that are comparable through time. Our method also allows us to generate counterfactual distributions for a range of ages, from which we derive age-height profiles. These profiles reveal how the adolescent growth spurt (AGS) distorts the distribution of stature, and they document the earlier and earlier onset of the AGS as living conditions improved over the second half of the nineteenth century. Our new estimates of provincial mean height also reveal a previously unnoticed “regime switch” from regional convergence to divergence in this period. Reprinted by permission of the publisher. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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