Nonzero-sum Stochastic Games

This paper treats of stochastic games. We focus on nonzero-sum games and provide a detailed survey of selected recent results. In Section 1, we consider stochastic Markov games. A correlation of strategies of the players, involving ``public signals'', is described, and a correlated equilibrium theorem proved recently by Nowak and Raghavan for discounted stochastic games with general state space is presented. We also report an extension of this result to a class of undiscounted stochastic games, satisfying some uniform ergodicity condition. Stopping games are related to stochastic Markov games. In Section 2, we describe a version of Dynkin's game related to observation of a Markov process with random assignment mechanism of states to the players. Some recent contributions of the second author in this area are reported. The paper also contains a brief overview of the theory of nonzero-sum stochastic games and stopping games which is very far from being complete.average payoff stochastic games, correlated stationary equilibria, nonzero-sum games, stopping time, stopping games

Stochastic expansions using continuous dictionaries: L\'{e}vy adaptive regression kernels

This article describes a new class of prior distributions for nonparametric function estimation. The unknown function is modeled as a limit of weighted sums of kernels or generator functions indexed by continuous parameters that control local and global features such as their translation, dilation, modulation and shape. L\'{e}vy random fields and their stochastic integrals are employed to induce prior distributions for the unknown functions or, equivalently, for the number of kernels and for the parameters governing their features. Scaling, shape, and other features of the generating functions are location-specific to allow quite different function properties in different parts of the space, as with wavelet bases and other methods employing overcomplete dictionaries. We provide conditions under which the stochastic expansions converge in specified Besov or Sobolev norms. Under a Gaussian error model, this may be viewed as a sparse regression problem, with regularization induced via the L\'{e}vy random field prior distribution. Posterior inference for the unknown functions is based on a reversible jump Markov chain Monte Carlo algorithm. We compare the L\'{e}vy Adaptive Regression Kernel (LARK) method to wavelet-based methods using some of the standard test functions, and illustrate its flexibility and adaptability in nonstationary applications.Comment: Published in at http://dx.doi.org/10.1214/11-AOS889 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Century of Shocks: The Evolution of the German City Size Distribution 1925 – 1999

The empirical literature on city size distributions has mainly focused on the USA. The first major contribution of this paper is to provide empirical evidence on the evolution and structure of the West-German city size distribution. Using a unique annual data set that covers most of the 20th century for 62 of West-Germany's largest cities, we look at the evolution of both the city size distribution as a whole and each city separately. The West-German case is of particular interest as it has undergone major shocks, most notably WWII. Our data set allows us to identify these shocks and provide evidence on the effects of these `quasi-natural experiments' on the city size distribution. The second major contribution of this paper is that we perform unit-root tests on individual German city sizes using a substantial number of observations to analyze the evolution of the individual cities that make up the German city size distribution. Our main findings are twofold. First, WWII has had a major and lasting impact on the city size distribution. Second, the overall city size distribution does not adhere to Zipf's Law. This second finding is largely based on the results of unit root tests for individual cities to test for Gibrat's Law, the latter being a requirement for Zipf's Law to hold for the overall city-size distribution. Together these two findings are consistent with theories emphasizing increasing returns to scale in city growth.

Reservoir capacity for periodic-stochastic input and periodic output

September 1976.Bibliography: pages 34-35