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Adjustment of age-related height decline for Chinese: a ‘natural experiment’ longitudinal survey using archival data

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  • Stephen Morgan

    (University of Nottingham)

Abstract

"Height data are a useful and concise summary measure of human welfare for historical populations in absence of conventional economical data. Most historical studies use the final attained height of adults aged between about 20-23 and 49 years on the premise that younger subjects were still growing and older subjects had begun to shrink. Data outside this range are discarded. For many studies the data lost is small and of little consequence for the study. However, where the sample includes many people older than 50 years the exclusion of these may make analysis impractical because of the resulting small sample size. Several studies have used a variety of approaches adjust height-for-age of older subjects to estimate the original attained height before next estimating the secular trend in heights. These adjustments are based on studies of the aging of European-origin populations, which may not fit the pattern observed in other human populations, such as the Chinese. In this paper I use data for nineteenth-century born Chinese immigrants to Australia whose heights were recorded repeatedly to simulate a longitudinal age-related height shrinkage study. The estimates of shrinkage are compared with estimates from other studies and applied to other archive-derived height data for Chinese to examine the reliability of adjusted height estimates in calculating secular trends in height, and in turn making inferences about their welfare."

Suggested Citation

  • Stephen Morgan, 2010. "Adjustment of age-related height decline for Chinese: a ‘natural experiment’ longitudinal survey using archival data," Working Papers 10022, Economic History Society.
  • Handle: RePEc:ehs:wpaper:10022
    as

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    References listed on IDEAS

    as
    1. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521828284.
    2. John Komlos, 1994. "Stature, Living Standards, and Economic Development: Essays in Anthropometric History," Books by John Komlos, Department of Economics, University of Munich, number 11, June.
    3. Costa, Dora L., 2004. "The Measure of Man and Older Age Mortality: Evidence from the Gould Sample," The Journal of Economic History, Cambridge University Press, vol. 64(1), pages 1-23, March.
    4. Baten, Joerg & Ma, Debin & Morgan, Stephen & Wang, Qing, 2010. "Evolution of living standards and human capital in China in the 18-20th centuries: Evidences from real wages, age-heaping, and anthropometrics," Explorations in Economic History, Elsevier, vol. 47(3), pages 347-359, July.
    5. Baten, Joerg & Ma, Debin & Morgan, Stephen & Wang, Qing, 2009. "Evolution of living standards and human capital in China in 18-20th century: evidences from real wage and anthropometrics," Economic History Working Papers 27870, London School of Economics and Political Science, Department of Economic History.
    6. Morgan, Stephen L., 2009. "Stature and economic development in South China, 1810-1880," Explorations in Economic History, Elsevier, vol. 46(1), pages 53-69, January.
    7. Stephen L. Morgan, 2006. "Australian Immigration Archives As Sources For Business And Economic History," Australian Economic History Review, Economic History Society of Australia and New Zealand, vol. 46(3), pages 268-282, November.
    8. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521535380.
    9. Steckel, Richard H., 2009. "Heights and human welfare: Recent developments and new directions," Explorations in Economic History, Elsevier, vol. 46(1), pages 1-23, January.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    China; human welfare; height; age-related shrinkage; measurement;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • N30 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - General, International, or Comparative
    • N35 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Asia including Middle East

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