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Comparing Population Distributions from bin-Aggregated Sample Data: an Application to Historical Height Data from France

Author

Listed:
  • Jean-Yves Duclos
  • Josée Leblanc
  • David Sahn

Abstract

This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.

Suggested Citation

  • Jean-Yves Duclos & Josée Leblanc & David Sahn, 2009. "Comparing Population Distributions from bin-Aggregated Sample Data: an Application to Historical Height Data from France," Cahiers de recherche 0910, CIRPEE.
    • Handle: RePEc:lvl:lacicr:0910
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    File URL: http://www.cirpee.org/fileadmin/documents/Cahiers_2009/CIRPEE09-10.pdf
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    Cited by:

    1. David E. Sahn, 2012. "Health Inequality across Populations of Individuals," African Development Review, African Development Bank, vol. 24(4), pages 316-326, December.

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D3 - Microeconomics - - Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I1 - Health, Education, and Welfare - - Health
    • I1 - Health, Education, and Welfare - - Health
    • N3 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy

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