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Inferring the economic standard of living and health from cohort height: Evidence from modern populations in developing countries
Authors: Yoko Akachi, and David Canning
Source: Economics and Human Biology, 19: 114-128; DOI: 10.1016/j.ehb.2015.08.005
Topic(s): Adult height
Economics
Women's height
Country: More than one region
  Multiple Regions
Published: DEC 2015
Abstract: Average adult height is a physical measure of the biological standard of living of a population. While the biological and economic standards of living of a population are very different concepts, they are linked and may empirically move together. If this is so, then cohort heights can also be used to make inferences about the economic standard of living and health of a population when other data are not available. We investigate how informative this approach is in terms of inferring income, nutrition, and mortality using data on heights from developing countries over the last 50 years for female cohorts born 1951–1992. We find no evidence that the absolute differences in adult height across countries are associated with different economic living standards. Within countries, however, faster increases in adult cohort height over time are associated with more rapid growth of GDP per capita, life expectancy, and nutritional intake. Using our instrumental variable approach, each centimeter gain in height is associated with a 6% increase in income per capita, a reduction in infant mortality of 7 per thousand (or an 1.25 year increase in life expectancy), and an increase in nutrition of 64 calories and 2 grams of protein per person per day relative to the global trend. We find that increases in cohort height can predict increases in income even for countries not used in the estimation of the relationship. This suggests our approach has predictive power out of sample for countries where we lack income and health data.
Web: https://pdf.sciencedirectassets.com/272801/1-s2.0-S1570677X15X00037/1-s2.0-S1570677X15000593/main.pdf?X-Amz-Date=20191107T181800Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Signature=48568865d0b2c28adda40