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A Bayesian approach to misclassified binary response: female employment and intimate partner violence in urban India

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  • Yoo-Mi Chin
  • Joon Jin Song
  • James D. Stamey

Abstract

We examine the effect of female employment on the odds of physical spousal violence using a Bayesian misclassification model combined with propensity score regression estimation. While a classical propensity score model finds a significant violence-provoking effect of female employment, our model finds no evidence of a significant effect. This suggests that misleading inferences are caused by falsely small standard errors in a model that does not account for uncertainties around propensity scores. Further, we confirm our misclassification model as a preferred specification using Deviance Information Criterion (DIC).

Suggested Citation

  • Yoo-Mi Chin & Joon Jin Song & James D. Stamey, 2017. "A Bayesian approach to misclassified binary response: female employment and intimate partner violence in urban India," Applied Economics Letters, Taylor & Francis Journals, vol. 24(20), pages 1439-1442, November.
    • Handle: RePEc:taf:apeclt:v:24:y:2017:i:20:p:1439-1442
    DOI: 10.1080/13504851.2017.1282139
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    Cited by:

    1. Maria Kamran, 2022. "A Touch of Violence - Welfare Outcomes under Bride Exchange and Child Brides," IHEID Working Papers 12-2022, Economics Section, The Graduate Institute of International Studies.

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