The issue of stature loss (shrinking)
was a hot topic on a previous incarnation of this blog. For example:
The consequences of non-random
measurement error in height are potentially important, given that stature is often
used in the economics literature to compare the welfare of different cohorts,
and also as a proxy for early environment. Given the frequency of its use,
there is surprisingly little evidence on shrinking.
It proved to be surprisingly
difficult to find the right data to examine this issue properly (ideally longitudinal,
nationally representative, with objectively measured height, and sufficient
observations on the right age group – the over 50s). ELSA is the only survey we
have found so far which meets these criteria. Alan and I discuss our findings
in a recent working paper.
A Tall Story: Characteristics,
Causes, and Consequences of Stature Loss
- Alan Fernihough (Institute for International Integration Studies, Trinity College Dublin)
- Mark E. McGovern (Harvard Center for Population and Development Studies)
Abstract
Height is widely used as an objective measure of health
status. It is commonly used in the large body of research evaluating welfare
trends in historic populations and the long-run impacts of childhood
environment. However, few research papers have examined the extent, causes or
consequences of stature loss in aging populations. This is surprising, as many
studies rely on the assumption that height is fixed in late adolescence. Using
repeated observations on objectively measured data from the English
Longitudinal Study of Ageing (ELSA), we document that stature loss is an
important phenomenon among older individuals, and demonstrate how the use of
unadjusted height will dramatically overstate health improvements for younger
birth cohorts in cross sectional data. We show that there is an absence of
consistent predictors of stature loss at the individual level. However, we
exploit the panel element of the ELSA survey to show how deteriorating health
and stature loss occur in tandem. While our analysis details the inherent bias
of height measurements in older populations, we do not find that significant
differences arise from the use of unadjusted height as an input in typical
empirical health production function models.
JEL Classification: I10, I12, J11
Keywords: Height, Stature Loss, Early Life Conditions,
Health, Ageing
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