Using mixture models to detect sex bias in health outcomes in Bangladesh

Jonathan J. Morduch, Hal S. Stern

Research output: Contribution to journalArticlepeer-review


Many interesting economic hypotheses entail differences in behaviors of groups within a population, but analyses of pooled samples shed only partial light on underlying segmentations. Finite mixture models are considered as an alternative to methods based on pooling. Robustness checks using t-regressions and a Bayesian analogue to the likelihood ratio test for model evaluation are developed. The methodology is used to investigate pro-son bias in child health outcomes in Bangladesh. While regression analysis on the entire sample appears to wash out evidence of bias, the mixture models reveal systematic girl-boy differences in health outcomes.

Original languageEnglish (US)
Pages (from-to)259-276
Number of pages18
JournalJournal of Econometrics
Issue number1
StatePublished - Mar 1997


  • Bangladesh
  • Gender bias
  • Health production
  • Mixture model
  • Switching regression

ASJC Scopus subject areas

  • Applied Mathematics
  • Economics and Econometrics


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