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Skewed Sex Ratios and Criminal Victimization in India

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Demography

Abstract

Although substantial research has explored the causes of India’s excessively masculine population sex ratio, few studies have examined the consequences of this surplus of males. We merge individual-level data from the 2004–2005 India Human Development Survey with data from the 2001 India population census to examine the association between the district-level male-to-female sex ratio at ages 15 to 39 and self-reports of victimization by theft, breaking and entering, and assault. Multilevel logistic regression analyses reveal positive and statistically significant albeit substantively modest effects of the district-level sex ratio on all three victimization risks. We also find that higher male-to-female sex ratios are associated with the perception that young unmarried women in the local community are frequently harassed. Household-level indicators of family structure, socioeconomic status, and caste, as well as areal indicators of women’s empowerment and collective efficacy, also emerge as significant predictors of self-reported criminal victimization and the perceived harassment of young women. The implications of these findings for India’s growing sex ratio imbalance are discussed.

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Notes

  1. In Indian demography, the sex ratio is traditionally expressed as the number of females per males. Unless otherwise noted, we adopt the convention for measuring the sex ratio that is used the most elsewhere in the world: the number of males per females.

  2. This question was also asked of the household heads, but the women respondents are likely better positioned to report accurately about the frequency of harassment of young girls.

  3. We also estimated models using the age range 15 to 29, with similar results. However, using the sex ratio for the total population—with no age constraints—generated much weaker and often nonsignificant associations. We tested for nonlinear effects of the sex ratio by including polynomial terms but found no evidence of statistically significant departures from linearity.

  4. Although region could be considered a third level of aggregation, for simplicity, we treat it as a Level 2 variable.

  5. The sample size varies across the dependent variables because of differential (albeit small) amounts of missing data and because the harassment of young girls item was taken from the sample of ever-married women. We present descriptive statistics on the independent variables for the largest sample (N = 41,404), but statistics for the other samples are quite comparable (results not shown).

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Acknowledgments

This research was supported by a grant to the authors from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01 HD067214). The Center for Social and Demographic Analysis of the University at Albany provided technical and administrative support for this research through a grant from NICHD (R24 HD044943). We thank Steven Messner and several anonymous reviewers for helpful comments.

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South, S.J., Trent, K. & Bose, S. Skewed Sex Ratios and Criminal Victimization in India. Demography 51, 1019–1040 (2014). https://doi.org/10.1007/s13524-014-0289-6

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