One valuable asset of statistical analysis is the ability to hold potentially spurious factors constant. The purpose of including control variables is to rule out competing explanations for the dependent variable. In this case, simply looking at the relationship between the primary independent variables and the child soldier use would leave open the possibility that another factor or factors are driving the relationship between both. That is some uncontrolled Z is causing the observed relationship between X and Y. Thus, it is important to consider additional factors in the proposed models.
Unfortunately, the quantitative literature on child soldiers is limited. However, there are a number of concepts that are thought to influence the use of child soldiers. I primarily use the World Bank's World Development Indicators for these controls (WDI) (World Bank 2010b). There are two distinct ways in which the supply of children able to be pressed into service can be conceptualized. First, Høiskar (2001) suggests that youth unemployment increases the likelihood of child soldier usage because they have few alternatives for livelihood and may volunteer. To proxy for the potential supply of underage volunteers, unemployed youth, is operationalized using the employment to population ratio of youths aged 15-24. The mean is 48.2 with a standard deviation of
15.32. The expected relationship for unemployed youth is positive. The more children are unemployed, the more underage volunteers will be available.
The second form of supply is the number of potential conscripts. Achvarina and Reich (2006) find that large pools of vulnerable recruits contribute to child soldiering in a conflict. I proxy this with two variables: refugees and Internally Displaced Persons (IDPs). Both variables use estimates from the WDI25. Log-refugees is the number of refugees by country of asylum.26 This is averaged over the period 1998-2008. The mean is 9.26 with a standard deviation of 3.5. I also include a measure that records the average highest estimate of IDPs in a country, log-IDPs. Data availability limits the temporal coverage to 2001-2008. The average for log-IDPs is 11.1 with a standard deviation of 4.4. This proxy varies from the Achvarina and Reich's original concept in two ways. First, they do not argue that the number of potential recruits is influential. Rather, it is vulnerability that matters. They use qualitative accounts of 16 civil wars where reports of camp attacks were available. In order to engage in the large-n analysis, I was unable to do the same. Instead, noting that all camps are inherently insecure and very few enjoy
peacekeeper protection (Lischer 2010: 148-149). Therefore, I cautiously accept my chosen measures. Second, and less consequential, their theory predicts that the
vulnerability of refugees IDPs will influence the child to adult soldier ratio, not just the occurrence of child soldiering. However, the same relationship should hold for use/non- use as well. The more refugees and IDPs in a country, the larger the pool of vulnerable
25 Where the data were missing, I linearly interpolated to estimate the values.
youths and the more likely rebels can find potential recruits.27 The expected direction for
log-refugees and log-IDPs is positive. Rebellions in areas with high numbers vulnerable
recruits should be more likely to use child soldiers.
One of the most consistent features within a rebellion that explains when civilians will be abused is the level of internal discipline (Humphreys and Weinstein 2006). Child soldiering is a form of civilian abuse. Therefore, I include a control for the strength of the central command of the rebellion in my models. This is necessary to avoid the possibility that secessionist rebellions are somehow more in control of their forces and would therefore be less able to control for abuses. Strength central is evaluated based on the original EACD coding. I used a dichotomous variable to capture if the group has strong central command, coded as 1; the observation is coded 0 otherwise. There are four categories included in the original data; unclear, low, moderate and strong. To avoid losing 17 “unclear” cases, I opted for a dummy variable.28 Approximately 11.6% of the cases exhibited moderate or strong central control. The expected direction of strength
central is negative. Rebellions with higher levels of central control should be less likely
to use child soldiers. In the original study, Humphreys and Weinstein use individual-level surveys to determine how often punishment would follow transgressions. This process would be very difficult to replicate for my project.
I also control for the level of democracy in the state at the start of the rebellion. Andvig and Gates (2010) point out that government action can lead to grievances, prompting many children to volunteer or parents to send their children to fight with the
27 Ideally, I would have sub-national data for this measure and consider location of refugee-access and rebel use of child soldiers. Unfortunately, I do not. Also, methodological tools to appropriately consider
geographic disaggregation are beyond the scope of this project.
rebel forces. Alternatively, government repression may lead many adults to join the insurgency. This would lead to a glut in the labor market where children would be easier to turn away. One example of this is in the Burmese civil war. There, the government conscripts children because adults are not volunteering (Becker 2010). These arguments justify inclusion of a democracy control variable. I use the average Polity IV value to for the country during the 1998-2008 time period. (Marshall and Jaggers 2000). The mean for democracy is 2.1. The expected direction for democracy is not known because either mechanism could be at work.