We characterize the unique Markov perfect equilibrium of a tug-of-war without exogenous noise, in which players have the opportunity to engage in a sequence of battles in an attempt to win the war. Each battle is an all-pay auction in which the player expending the greater resources wins. In...

We study an all-pay contest with multiple identical prizes ("lifeboat seats"). Prizes are partitioned into subsets of prizes ("lifeboats"). Players play a two-stage game. First, each player chooses an element of the partition ("a lifeboat"). Then each player competes for a prize in the subset...

We study an all-pay contest with multiple identical prizes ("lifeboat seats"). Prizes are partitioned into subsets of prizes ("lifeboats"). Players play a two-stage game. First, each player chooses an element of the partition ("a lifeboat"). Then each player competes for a prize in the subset...

The formation of an alliance in conflict situations is known to suffer from a collective action problem and from the potential of internal conflict. We show that budget constraints of an intermediate size can overcome this strong disadvantage and explain the formation of alliances.

Countries compete for new FDI investment, whereas stocks of FDI generate agglomeration benefits and are potentially subject to extortionary taxation. We study the interaction between these aspects in a simple vintage capital framework with discrete time and infinite horizon, focussing on Markov...

The formation of an alliance in conflict situations is known to suffer from a collective action problem and from the potential of internal conflict. We show that budget constraints of an intermediate size can overcome this strong disadvantage and explain the formation of alliances.

"We consider the properties of perfectly discriminating contests in which players' abilities are stochastic, but become common knowledge before efforts are expended. Players whose expected ability is lower than that of their rivals may still earn a positive expected payoff from participating in...