terms of average household assets and years of education for the capital region and the rest of the country in Peru and Zimbabwe, respectively for various survey years. In both countries the level of inequality has remained relatively stable over the entire period.

# **Political Regime Type**

I use data on regime type from the Polity IV data (Marshall & Jaggers, 2003). Like Jaggers & Gurr (1995) I compute one single regime indicator, subtracting the score of autocracy from that of democracy, ranging from –10 (most autocratic) to 10 (most democratic). In order to test the curvilinear relationship between regime type and civil conflict I include a squared term for regime type. Finally, in order to assess whether horizontal inequalities are more dangerous in certain regime types, I split the polity term into three categories: democracies (6 to 10), semi democracies (–5 to 5), and autocracies (–10 to –6), following Ellingsen (2000) and others. I include the dummies for semi democracies and autocracies in the analysis, with democracies as the reference category.

In order to test my hypotheses with an alternative operationalization of regime type, I also include the term SIP (which stands for ‘Scalar Index of Polities’) proposed by Gates et al. (2006).<sup>15</sup> This measure is the average of the scores on the three dimensions: The first dimension is the regulation of Executive Recruitment, based on three indicators from the Polity IV dataset: ‘Regulation of Chief Executive Recruitment’ (XRREG), ‘Competitiveness of Executive Recruitment’ (XRCOMP), and ‘Openness of Executive Recruitment’ (XROPEN). The second dimension characterizes the constraints on the executive and is based on a single indicator ‘Decision Constraints on the Chief Executive’ (XCONST) from Polity IV. The third dimension concerns political participation. Rather than using Gurr’s participation index, Gates et al. (2006) base their measure on a slightly modified version of the Polity Participation index from Vanhanen’s (2000) _Polyarchy_ dataset. The SIP measure ranges from 0 to 1. Finally, in order to test Hypothesis 2, I include interaction terms multiplying regime type and regional HIs.

# **Proximity to Regime Transition**

As stated earlier, semi democracies are found to be the most conflict-prone (Ellingsen 2000; Hegre et al. 2001). This category includes both regimes in transition and institutionally inconsistent regimes. In order to control for whether transitions might make up parts of this relationship as opposed to institutionally inconsistent regimes, as suggested by Hegre et al. (2001), I introduce a variable measuring the time since regime transition when evaluating Hypothesis 2. Polity IV includes a variable ‘DURABLE’ which measures regime durability (i.e. years since regime transition) as a function of the number of years since the most recent regime change (defined by a three-point change in the POLITY score over a period of three years or

> 15 The SIP measures was proposed by Gates et al. (2006) as an alternative to the POLITY IV measure due to various problems with the political participation dimension of the latter noted by the authors. Most notably, Gates et al.  point out that analyses of conflict which use the Polity measure potentially suffer from endogeneity problems because the Polity coding scheme classifies 40% of all the polities as ‘factional’ systems, i.e. systems which are particularly likely to be engaged in civil war. See Gates et al. (2006) for more details.

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