Deterministic Calibration and Nash Equilibrium

We provide a natural learning process in which the joint frequency of empirical play converges into the set of convex combinations of Nash equilibria. In this process, all players rationally choose their actions using a public prediction made by a deterministic, weakly calibrated algorithm. Furthermore, the public predictions used in any given round play are frequently close to some Nash equilibrium of the game

Coordination and Stabilization Gains of Fiscal Policy in a Monetary Union

The issue of fiscal coordination in a Monetary Union is recurrent as monetary policy can no longer be used as a national stabilization policy instrument. We measure the increase in welfare due to the coordination of fiscal policies in the typical Neo-Keynesian environment, where monetary policy would have significantive and persistent real effects. We propose a decomposition of coordination gains into a deterministic and a stochastic parcel. We show that the deterministic fiscal coordination gain is high but that the stochastic gain, often called stabilization gain, is very small generating, for our calibration, an increase of 0.0161 percentage points, measured in consumption equivalents.Coordination, Fiscal Policy, Gains, Nash.

Query Complexity of Correlated Equilibrium

We study lower bounds on the query complexity of determining correlated equilibrium. In particular, we consider a query model in which an n-player game is specified via a black box that returns players' utilities at pure action profiles. In this model we establish that in order to compute a correlated equilibrium any deterministic algorithm must query the black box an exponential (in n) number of times.Comment: Added reference

Channel Selection for Network-assisted D2D Communication via No-Regret Bandit Learning with Calibrated Forecasting

We consider the distributed channel selection problem in the context of device-to-device (D2D) communication as an underlay to a cellular network. Underlaid D2D users communicate directly by utilizing the cellular spectrum but their decisions are not governed by any centralized controller. Selfish D2D users that compete for access to the resources construct a distributed system, where the transmission performance depends on channel availability and quality. This information, however, is difficult to acquire. Moreover, the adverse effects of D2D users on cellular transmissions should be minimized. In order to overcome these limitations, we propose a network-assisted distributed channel selection approach in which D2D users are only allowed to use vacant cellular channels. This scenario is modeled as a multi-player multi-armed bandit game with side information, for which a distributed algorithmic solution is proposed. The solution is a combination of no-regret learning and calibrated forecasting, and can be applied to a broad class of multi-player stochastic learning problems, in addition to the formulated channel selection problem. Analytically, it is established that this approach not only yields vanishing regret (in comparison to the global optimal solution), but also guarantees that the empirical joint frequencies of the game converge to the set of correlated equilibria.Comment: 31 pages (one column), 9 figure

Coalition Formation under Uncertainty: The Stability Likelihood of an International Climate Agreement

Results derived from empirical analyses on the stability of climate coalitions are usually very sensitive to the large uncertainties associated with the benefits and costs of climate policies. This paper provides the methodology of Stability Likelihood that links uncertainty about benefits and costs of climate change to the stability analysis of coalitions in a stochastic, empirical setting. We show that the concept of Stability Likelihood improves upon the robustness and interpretation of stability analysis. Our numerical application is based on a modified version of the climate model STACO. It turns out that the only non-trivial coalition structure with a relatively high Stability Likelihood (around 25 percent) is a coalition between the European Union and Japan, though quantitative results depend especially on the variance in regional benefits from abatement.Climate change, Coalition formation, International environmental agreements, Uncertainty