Sequential bargaining with pure common values and incomplete information on both sides

We study the alternating-offer bargaining problem of sharing a common value pie under incomplete information on both sides and no depreciation between two identical players. We characterise the essentially unique perfect Bayesian equilibrium of this game which turns out to be in gradually increasing offers.Gradual bargaining; Common values; Incomplete information; Repeated games

Effect of depreciation of the public goods in spatial public goods games

In this work, depreciated effect of the public goods is considered in the public goods games, which is realized by rescaling the multiplication factor r of each group as r' = r(nc/G)^beta (beat>= 0). It is assumed that each individual enjoys the full profit of the public goods if all the players of this group are cooperators, otherwise, the value of the public goods is reduced to r'. It is found that compared with the original version (beta = 0), emergence of cooperation is remarkably promoted for beta > 0, and there exit optimal values of beta inducing the best cooperation. Moreover, the optimal plat of beta broadens as r increases. Furthermore, effect of noise on the evolution of cooperation is studied, it is presented that variation of cooperator density with the noise is dependent of the value of beta and r, and cooperation dominates over most of the range of noise at an intermediate value of beta = 1.0. We study the initial distribution of the multiplication factor at beta = 1.0, and find that all the distributions can be described as Gauss distribution

Sequential bargaining with pure common values

We study the alternating-offers bargaining problem of assigning an indivisible and commonly valued object to one of two players in return for some payment among players. The players are asymmetrically informed about the object’s value and have veto power over any settlement. There is no depreciation during the bargaining process which involves signalling of private information. We characterise the perfect Bayesian equilibrium of this game which is essentially unique if offers are required to be strictly increasing. Equilibrium agreement is reached gradually and nondeterministically. The better informed player obtains a rent.Sequential bargaining; Common values; Incomplete information; Repeated games

Quasigeometric Distributions and Extra Inning Baseball Games

Each July, the eyes of baseball fans across the country turn to Major League Baseball’s All-Star Game, gathering the best and most popular players from baseball’s two leagues to play against each other in a single game. In most sports, the All-Star Game is an exhibition played purely for entertainment. Since 2003, the baseball All-Star Game has actually ‘counted’, because the winning league gets home field advantage in the World Series. Just one year before this rule went into effect, there was no winner in the All-Star Game, as both teams ran out of pitchers in the 11th inning and the game had to be stopped at that point. Under the new rules, the All-Star Game must be played until there is a winner, no matter how long it takes, so the managers need to consider the possibility of a long extra inning game. This should lead the managers to ask themselves what the probability is that the game will last 12 innings. What about 20 innings? Longer? In this paper, we address these questions and several other questions related to the game of baseball. Our methods use a variation on the well-studied geometric distribution called the quasigeometric distribution. We begin by reviewing some of the literature on applications of mathematics to baseball. In the second section we will define the quasigeometric distribution and examine several of its properties. The final two sections examine the applications of this distribution to models of scoring patterns in baseball games and, more specifically, the length of extra inning games

A mean-field game economic growth model

Here, we examine a mean-field game (MFG) that models the economic growth of a population of non-cooperative rational agents. In this MFG, agents are described by two state variables - the capital and consumer goods they own. Each agent seeks to maximize their utility by taking into account statistical data of the total population. The individual actions drive the evolution of the players, and a market-clearing condition determines the relative price of capital and consumer goods. We study the existence and uniqueness of optimal strategies of the agents and develop numerical methods to compute these strategies and the equilibrium price

Imperfect credibility of the band and risk premia in the European Monetary System

Estimation;Depreciation;Franc;EMS;Deutschmark;Lira

Avoiding the Curse of Dimensionality in Dynamic Stochastic Games

Continuous-time stochastic games with a finite number of states have substantial computational and conceptual advantages over the more common discrete-time model. In particular, continuous time avoids a curse of dimensionality and speeds up computations by orders of magnitude in games with more than a few state variables. The continuous-time approach opens the way to analyze more complex and realistic stochastic games than is feasible in discrete-time models.

Avoiding the Curse of Dimensionality in Dynamic Stochastic Games

Discrete-time stochastic games with a finite number of states have been widely ap- plied to study the strategic interactions among forward-looking players in dynamic en- vironments. However, these games suffer from a "curse of dimensionality" since the cost of computing players' expectations over all possible future states increases exponentially in the number of state variables. We explore the alternative of continuous-time stochas- tic games with a finite number of states, and show that continuous time has substantial computational and conceptual advantages. Most important, continuous time avoids the curse of dimensionality, thereby speeding up the computations by orders of magnitude in games with more than a few state variables. Overall, the continuous-time approach opens the way to analyze more complex and realistic stochastic games than currently feasible.