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Problems of Sample-selection Bias in the Historical Heights Literature: A Theoretical and Econometric Analysis

  • Howard Bodenhorn

    ()

    (Department of Economics, Clemson University)

  • Timothy W. Guinnane

    ()

    (Department of Economics, Yale University)

  • Thomas A. Mroz

    ()

    (Department of Economics, Clemson University)

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.

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Paper provided by Economic Growth Center, Yale University in its series Working Papers with number 1023.

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Length: 101 pages
Date of creation: May 2013
Date of revision:
Handle: RePEc:egc:wpaper:1023
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