practice, the probability of civil war victory is modelled as depending positively on Q A’s expenditure on war effort and negatively on that of according to the contest success B function (see Tullock, 1980; Hirshleifer, 1989; and Garfinkel and Skaperdas, 2007) . (1) Parameters measure the effectiveness of and respectively in  0 0 A B fighting the civil war. This formulation captures the possibility that the two sides may differ in their fighting ability, with one having access to better hardware, technology and organization (the government), while the other relying on its knowledge of terrain and commitment of its members (the anti-government rebels). In the case where is a more A effective fighter than When the two sides are equally effective fighters, B, ½ if in addition they spend equal sums of resources to fight the civil war, they stand an equal probability of success, Under risk neutrality the ZA=ZB, Q=1–Q=½. expected net payoffs of the two rival factions from fighting civil war are (2.A) UAW = Q(1–)R–ZA . (2.B) UBW = (1–Q)(1–)R–ZB Let and be the election campaign expenditures of the two groups. In common with XA XB the probability that wins the election is modelled as increasing in the resources Q, P A spent by campaigning and decreasing in those of as described by the equation A B, . (3) Parameters measure the effectiveness of and respectively, in their  0 1 A B election campaigns; depend on how good campaigner is in attracting votes, how A well he can translate financial resources to voter support and the like. It bears noting that neither are equal to the number of people who broadly identify with although P A, the latter may affect them. Winning the election depends on the number of those who actually vote for The difference between those who may be counted as members of A. A and those who vote for is explained by franchise restrictions, voter apathy or alienation, A distribution of voters across constituencies, campaign issues and personal appeal of the leader. Similarly, one may presume that positively correlated, if for example they depend on the relative size of group but as explained above it does not have to be A, the case. Unlike the usual assumption of spatial decision models where electoral competition depends on the policy positions of the competing parties, in the present
practice, the probability Q of civil war victory is modelled as depending positively on A’s expenditure on war effort and negatively on that of B according to the contest success function (see Tullock, 1980; Hirshleifer, 1989; and Garfinkel and Skaperdas, 2007) . (1) Parameters 0 0 measure the effectiveness of A and B respectively in fighting the civil war. This formulation captures the possibility that the two sides may differ in their fighting ability, with one having access to better hardware, technology and organization (the government), while the other relying on its knowledge of terrain and commitment of its members (the anti-government rebels). In the case where A is a more effective fighter than B, When the two sides are equally effective fighters, if in addition they spend equal sums of resources to fight the civil war, ZA=ZB, they stand an equal probability of success, Q=1–Q=½. Under risk neutrality the expected net payoffs of the two rival factions from fighting civil war are UAW = Q(1–)R–ZA (2.A) UBW = (1–Q)(1–)R–ZB . (2.B) Let XA and XB be the election campaign expenditures of the two groups. In common with Q, the probability P that A wins the election is modelled as increasing in the resources spent by A campaigning and decreasing in those of B, as described by the equation . (3) Parameters 0 1 measure the effectiveness of A and B respectively, in their election campaigns; depend on how good campaigner A is in attracting votes, how well he can translate financial resources to voter support and the like. It bears noting that neither P are equal to the number of people who broadly identify with A, although the latter may affect them. Winning the election depends on the number of those who actually vote for A. The difference between those who may be counted as members of A and those who vote for A is explained by franchise restrictions, voter apathy or alienation, distribution of voters across constituencies, campaign issues and personal appeal of the leader. Similarly, one may presume that positively correlated, if for example they depend on the relative size of group A, but as explained above it does not have to be the case. Unlike the usual assumption of spatial decision models where electoral competition depends on the policy positions of the competing parties, in the present   ½