Table 7: Difference-in-differences estimates of the effect of the Boko Haram insurgency on Intimate partner violence, women’s experience of controlling behavior by husband/partner and women’s decision-making autonomy in Nigeria- Placebo Analysis.

|Variables<br><br>|**(1)**<br>Past year<br>physical or<br>sexual IPV|**(2)**<br>Controlling<br>behavior by<br>husband/partner|**(3)**<br>Women’s household<br>decision- making<br>autonomy|**(4)**<br>Women’s earnings<br>decision-making<br>autonomy|
|---|---|---|---|---|
|PPP<br>y<sup>*****PBBPlBBP</sup>l|-0.008|-0.018|0.236***|0.017|
||(0.021)|(0.043)|(0.049)|(0.016)|
|Covariates|||||
|Individual characteristics|Yes|Yes|Yes|Yes|
|Partner characteristics|Yes|Yes|Yes|Yes|
|Household characteristics|Yes|Yes|Yes|Yes|
|Before BH placebo (Non-BH Area)|5985|5997|5994|4611|
|Before BH placebo (BH Area)|664|664|664|604|
|During BH placebo (Non-BH Area)|3136|3138|3138|2663|
|During BH placebo (BH Area)|460|461|461|433|
|Total|10245|10260|10257|8311|
|R-squared|0.14|0.15|0.31|0.12|

Note: Variables used to estimate the kernel propensity scores are dropped are dropped. Note: The estimations account for state fixed effects to account for the clustering of IPV among women residing in the same state. The kernel density function is epanechnikov with a bandwidth of 0.06. Probit estimation is used for the propensity score in the first stage. Kernel-based DD estimates are on the common support. The results are robust to employing a logit estimation of the propensity scores in the first stage, a gaussian kernel density function as opposed to an epanechnikov kernel density function and varying the bandwidth of the kernel density function.***Significant at the 1% level, **Significant at the 5% level, *Significant at the 10% level. Standard errors in parentheses are robust.

# 5.4 Limitations of the study

It is likely that the study underestimates the effect of the BH insurgency, as areas with the largest number of conflict events are not captured in our analysis. Also, the BH insurgency is a regional crisis and we do not consider BH activities in the neighboring countries of Cameroun, Chad and Niger, which affect Nigerian communities located in areas bordering these countries. Therefore, our estimates represent a lower bound for the effect of the BH insurgency.

Another limitation is caused by the study reliance on GPS coordinates provided in the NDHS as well as the ACLED to identify the BH area. The geo-coordinates of the NDHS clusters are randomly displaced to protect the privacy of the respondents (Elkies et al. 2015). Urban clusters are displaced up to 2km while rural clusters are displaced up to 5km (Perez-Heydrichet al. 2013). The measurement error introduced might lead to attenuation bias in the regressions (Skiles et al. 2013), although robustness analysis does not suggest this is a problem in our estimations.<sup>26</sup> Furthermore, although the NDHS allows us to examine the effect of conflict on some drivers of IPV, it does not provide enough information to examine important pathways through which the BH insurgency may translate to IPV, such as extreme stress and trauma, changing marriage practices and other microsystem and exosystem factors suggested by the ecological framework.

> 26 We check if our results are likely to be affected by this bias by restricting the analysis in tables 4 and 6 to only urban areas where the offset is smaller. We find that our results are robust to this restriction (see appendix table A4a and <u>A4b).</u>

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