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)
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