The interaction term for political exclusion and regional educational HI (Model 20) is also strongly positive, but not significantly so. In sum, Table 4 provides some empirical support for Hypothesis 4. However, it should be noted that the measure for political exclusion is rather crude. It could be worth retesting the hypothesis with disaggregated data at the sub-national level.

# **6 Concluding Remarks**

This paper represents a first effort at systematically measuring the impact of the political environment on the relationship between socioeconomic horizontal inequalities and civil conflict onset. The main finding is that socioeconomic horizontal inequalities seem to be positively related with conflict for all the three kinds of group identifiers suggested here (ethnic, religious and regional groups). Furthermore the relationship between regional (educational) HIs and conflict seems to be affected by regime type and electoral system, as well as the level of political exclusion in society. In fact horizontal inequalities seem to be particularly conflict provoking in democratic regimes with inclusive electoral systems. This is of course not to say that democracy and/or political inclusiveness as such breed conflict, but that countries with sharp socioeconomic HIs despite democratic rule and a seemingly politically inclusive system may be particularly at risk for conflict. Furthermore, I find a strong interaction effect between regional asset HI and the level of de facto political exclusion of certain minorities. In sum, these results provide some support to all the Hypotheses 1–4, but the estimates are sensitive to what indicator of inequality is used. Sometimes it is the household asset indicator which shows a significant effect, and other times it is the education indicator. These two indicators of social wellbeing are quite interrelated both in theory and statistical correlation, so it would be risky to speculate too much about their potentially different effects.

Despite some interesting findings, several factors call for caution when interpreting the results reported here. First, the sample is limited to developing countries which have hosted DHS-surveys in the period 1986–2003, which calls into question the degree to which the results can be generalized. Also, within this sample the intra- and extrapolations of inequality values could be problematic. However, this should not be too huge a problem, since horizontal inequalities seem to remain quite stable over time, as noted above.<sup>23</sup> Second, there is always a potential problem for producing misleading findings due to poor operationalizations of certain variables. Generating summary measures of horizontal inequalities at the national level is a challenging task. There is a need to define the relevant groups, calculate their respective mean welfare scores, and then measuring inequalities based on these scores. Most empirical work on group differences, including the tests presented here, uses simple measures of differences in performance between the major groups in society, aggregating these for cross–country comparisons. The advantage of such an approach is that the measure is very simple and intuitively makes sense. However, it is potentially problematic since it may ignore certain politically relevant groups in society (see e.g. Stewart, Brown & Mancini, 2005).

> 23 Even so, I reran all the models without allowing for any backward extrapolation of the inequality values. Most of the results remained similar, but some effects dropped below significance (results not reported here). This procedure radically decreases the sample to less than half and the number of conflicts drops to very low figures in many of the models.

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