Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/98202
Authors: 
Bodenhorn, Howard
Guinnane, Timothy
Mroz, Thomas
Year of Publication: 
2013
Series/Report no.: 
Center Discussion Paper, Economic Growth Center 1023
Abstract: 
An extensive literature uses anthropometric measures, typically heights, to draw inferences about living standards in the past. This literature's influence reaches beyond economic history; the results of historical heights research appear as crucial components in development economics and related fields. The historical heights literature often relies on micro-samples drawn from sub-populations that are themselves selected: examples include volunteer soldiers, prisoners, and runaway slaves, among others. Contributors to the heights literature sometimes acknowledge that their samples might not be random draws from the population cohorts in question, but rely on normality alone to correct for potential selection into the sample. We use a simple Roy model to show that selection cannot be resolved simply by augmenting truncated samples for left-tail shortfall. Statistical tests for departures from normality cannot detect selection in Monte Carlo exercises for small to moderate levels of self-selection, obviating a standard test for selection in the heights literature. We show strong evidence of selection using micro-data on the heights of British soldiers in the late eighteen and nineteenth centuries. Consequently, widely accepted results in the literature may not reflect variations in living standards during a soldier's formative years; observed heights could be predominantly determined by the process determining selection into the sample. A survey of the current historical heights literature illustrates the problem for the three most common sources: military personnel, slaves, and prisoners.
Subjects: 
self-selection
selection bias
heights
anthropometrics
standards of living
industrialization puzzle
long-run economic growth
JEL: 
I00
N3
O15
O47
C46
C52
C81
Document Type: 
Working Paper

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