The association between women's economic participation and physical and/or sexual domestic violence against women: A case study for Turkey.

We test in how far women's economic participation can be associated with physical and/or sexual domestic violence against women in Turkey, by mobilizing the Survey "National Research on Domestic Violence against Women in Turkey" (wave 2014). Several studies found that economically active women have a similar, if not a higher risk of experiencing domestic violence than inactive women in Turkey, as well as in other emerging countries. We challenge these findings for Turkey by distinguishing between formal and informal labor market activities as well as between women who do not work because their partner does not allow them to and women who are inactive for other reasons. To increase the control for endogeneity in this cross-sectional setting, we apply an IV-approach based on cluster averages. We find that, while overall employment for women cannot be associated with a lower risk of experiencing domestic violence for women in Turkey, those women who participate in the formal labor market and those women who contribute at least the same as their partner to household income are less exposed to physical and/or sexual domestic violence than their counterparts. Distinguishing between formal and informal employment is thus important when it comes to investigate the association between women's economic activity and domestic violence. This is especially the case in a country like Turkey, which currently undergoes important socio-economic changes and where women in formal and informal employment have therefore very different socioeconomic backgrounds.

Multiple imputation for demographic hazard models with left-censored predictor variables: Application to employment duration and fertility in the EU-SILC.

A common problem when using panel data is that an individual's history is incompletely known at the first wave. We show that multiple imputation, the method commonly used for data that are missing due to non-response, may also be used to impute these data that are "missing by design." Our application is to a woman's duration of fulltime employment as a predictor of her risk of first birth. We multiply-impute employment status two years earlier to "incomplete" cases for which employment status is observed only in the most recent year. We then pool these "completed" cases with the "complete" cases to derive regression estimates for the full sample. Relative to not being fulltime employed, having been fulltime-employed for two or more years is a positive and statistically significant predictor of childbearing whereas having just entered fulltime employment is not. The fulltime-employment duration parameter variances are about one third lower in the multiply-imputed sample than in the complete-data sample, and only in the multiply-imputed sample does the employment-duration coefficient attain statistical significance.