El efecto de la instrucción sobre los procesos de adquisición

First, I present graphical evidence corresponding to the main difference-in-differences model. By including indicators for up to two years prior to the implementation of LAP and allowing for dynamic treatment effects after in equation 3.1, I estimate the pre- and post- treatment divergence in outcomes between the treated and control agencies. These differences are plotted in Figure C.2. Panel A shows the divergence in the rate of homicides with female victims and male offenders. In panel B I present the divergence in the rate of homicides with female victims aged 18 to 60, male offenders, and the circumstance not identified as a robbery. In both panels the difference between early and late adopting agencies is close to zero prior to treatment (data points to the left of the solid vertical line). The fact that the control and treatment groups are tracking each other prior to treatment corroborates the validity of the identifying assumption. Whereas, in the post treatment period (data points to the right of the solid vertical line), there is a large drop in both outcomes in the agencies that adopted LAP early in comparison to those that didn’t.

This indicates that the introduction of LAP significantly reduced female homicide victimization.

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I formally estimate the effect of LAP on female homicides using equation 3.1 and the results are presented in Table C.4. Panels A and B present results for the effect of LAP on all female homicides and on female homicides with male offenders respectively. Since I expect the effects of LAP to be concentrated on intimate partner homicides, in panel C, I present the effects of LAP on a narrowly defined category of female homicides. This category includes homicides where the victim was between 18 and 60 years of age, the offender was male, and the circumstance of homicide was not a robbery. Column 1 presents the estimates from the negative binomial regression with controls for agency and year fixed effects. I progressively control for time-varying county-level covariates in columns 2 through 5. Columns 6 and 7 present estimates from robustness checks, namely, testing for pre-treatment divergence by including the lead indicator for treatment and allowing for a relaxed identifying assumption by including agency-specific linear time trends.

In all the panels, the estimates change very little when I include controls or allow for agency-specific linear time trends. The coefficients on the lead indicator for treatment (LAP t-1) are small and statistically indistinguishable from zero in all cases. These results are consistent with the assumption that the late-adopting agencies are good counterfactuals for those that adopted LAP early.

Results in panel A suggest that overall female homicide declined between 10 to 20 percent due to the implementation of LAP, but not all estimates are statistically different from zero. Since the intervention is particularly targeted towards homicides that result from domestic violence, this result is understandable. In panel B where the outcome

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variable is the female homicides committed by men, I find a stronger effect. All estimates from the main model (columns 1 through 5) are statistically significant at the 1% level, and they indicate a 35 to 45 percent drop in female homicide victimization by men as a result of LAP. The effects are also pronounced in panel C where I only include homicides of women aged 18 to 60, by men, and under circumstances other than a robbery. All estimates from the main model are statistically significant at least at the 5% level, and indicate that LAP reduced such homicides by around 42 percent.

Research suggests that the rate of domestic violence could be different between married and cohabiting couples (e.g. Stets and Straus, 1989; Yllo and Straus, 1981).

According to a report on intimate partner violence from the Bureau of Justice Statistics (BJS 1998) women in the age group of 16 to 24 experience the highest rate of violence.

To the extent that younger women are less likely to be married this might suggest a higher rate of violence among unmarried couples. The rate of reporting abuse and utilizing domestic violence services could also be different between women that are married to their abusers and those that are not.⁴⁰ Because the effectiveness of LAP depends on both those factors, I test for heterogeneous effects of LAP on intimate partner homicide by the relationship between the victim and the offender. The results are in Table C.5. Panels A and B are restricted to female homicides where the victim was the girlfriend and wife of

40 According to Ms. Kelley Rainey, Director of Domestic Violence Services at the Family and Children’s Services (FMC), Baltimore, MD, married women might have greater difficulty in leaving an abusive relationship because of several reasons (based on my phone communication with her). For instance, the finances may be more interlinked among married couples – the victim may not be able to get a bank account without getting noticed. Married women might also face a greater stigma while making the decision to leave their marriage because of domestic violence.

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the male offender respectively.⁴¹ As shown in panel A of Figure C.1, among the female victims aged 18 to 60 that were killed by men in a situation other than a robbery, nearly 17% were identified as acquaintances of the offender (third highest category after girlfriend and wife).⁴² The nature of the relationship between the victim and offender is not clear in these cases. For instance, a couple that was dating or seeing each other occasionally at the time of the homicide might be classified as acquaintances. So I include this category as the third subgroup in panel C.⁴³ The estimates are large and statistically significant in panels A and C indicating that LAP is effective in saving lives of women who might have otherwise been killed by their boyfriends or male acquaintances. As for the women that are married to their abusers, estimates in panel B are positive and not statistically distinguishable from zero at the 5% level. This may be consistent with the idea that married women could be less willing or able to report domestic abuse or make attempts to escape an abusive relationship.