## _4.3 Control Variables and Statistical Model_

Achen’s (2002) ‘Rule of Three’, states that every analysis with more than three variables on the right-hand side will invariably be invalidated by serious problems of multicollinearity. I do not adhere to this rule, but believe that it is wise to keep the control variables at a minimum, especially given the limited sample size under study.

As noted by Hegre & Sambanis (2005) three core variables are almost always included in models of civil war onset: the natural log of population; the natural log of per capita GDP; and the length of peacetime until the outbreak of a war (i.e. the time since the last conflict). I include these three controls, of which the first is particularly relevant due to potential problems of spuriousness, given that inequality may be related to the actual level of economic development in a society. Data on population size stem from the WDI (World Bank, 2004). The variable is interpolated and log-transformed. To proxy economic development I use log-transformed GDP per Capita measured in constant 1995 US$, also from the WDI (World Bank, 2004). The variable is lagged one year.

As suggested by Beck, Katz & Tucker (1998), I control for temporal dependence through a variable measuring time since the last conflict and three cubic splines that approximate the discrete time hazard rates for conflict. Time since the last conflict counts the number of whole years since the end of the last conflict (peace years). The statistical tests were conducted using STATA, version 8.2 (StataCorp., 2003), and all models were estimated by logit regressions with robust standard errors clustered by countries.

# **5 Results**

The findings from the empirical tests of theoretical propositions are presented in Tables 1–4. All models include the base variables, i.e. the terms for population size, GDP per capita and controls for conflict history (peace years and cubic splines). To these I add my various terms for horizontal inequalities and interactions of these with the terms for political institutions in order to evaluate Hypotheses 1–4.

## _5.1 Do HIs Matter for Conflict across Different Group Identifiers?_

Models 1–6 in Table 1 report the effects of socioeconomic horizontal inequalities (measured in terms of household assets and education years) with regard to conflict onset. I test the impact of HIs between ethnic, religious, and regional groups respectively. As for the control variables the results are inconsistent. I fail to find the positive relationship between population size and conflict reported by most other studies of civil war (see e.g. Collier & Hoeffler, 2004; Fearon & Laitin, 2003). In model 1 the effect is in fact negative at the10% level, but in Model 2 the effect drops below significance. In Models 3–6 the effect is positive but never reaches significance. Similarly, the term for GDP yields inconclusive results, and is only negative and significant in Models 1 and 2, whereas the sign switches in the rest of the models. However, these results are perhaps not so surprising, given that the sample is restricted to low- and medium-income countries. When I run the baseline model (i.e. excluding any term for HIs) on a more inclusive 15