Comparing population distributions from bin-aggregated sample data: An application to historical height data from France
AbstractThis 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 is 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.
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Bibliographic InfoPaper provided by Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC) in its series UFAE and IAE Working Papers with number 771.09.
Date of creation: 20 Apr 2009
Date of revision:
Health; health inequality; aggregate data; 19th-century France; welfare;
Other versions of this item:
- Duclos, Jean-Yves & Leblanc, Josée & Sahn, David E., 2011. "Comparing population distributions from bin-aggregated sample data: An application to historical height data from France," Economics & Human Biology, Elsevier, vol. 9(4), pages 419-437.
- 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.
- Jean-Yves Duclos & Josée Leblanc & David Sahn, 2009. "Comparing population distributions from bin-aggregated sample data: An application to historical height data from France," Working Papers 381, Barcelona Graduate School of Economics.
- 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
- I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
- N3 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy
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