John Rawls, 1921-2002: A chastened but not trivial liberalism

No description supplie

Fiscal costs of climate mitigation programmes in the UK: A challenge for social policy?

This paper asks whether the policies and programmes enacted to reduce greenhouse gas emissions in the UK will compete with other goals of public policy, in particular social policy goals. The Climate Change Act 2008 has set the UK some of the most demanding targets in the world: to reduce GHG emissions (compared with 1990) by at least 80% by 2050 and by at least 34% by 2020 - just nine years away. A wide array of climate change mitigation policies (CCMPs) have been put in place to bring this about. Will these compete fiscally with the large public expenditures on the welfare state? We address this question by surveying and costing all UK government policies that have a climate change mitigation objective and which are expressed through taxation, government expenditures and government-mandated expenditures by energy suppliers and other businesses and which are directed toward the household sector. Our conclusion is that expenditures on CCMPs are tiny - around one quarter of one per cent of GDP - and will not rise significantly. Within this the share of direct spending by government will fall and that obligated on utility companies will rise. Green taxes are also planned to fall as a share of GDP. There is no evidence here of fiscal competition between the welfare state and the environmental state. However, the use of mandated electricity and gas markets will impose rising costs on the household sector, which will bear more heavily on lower income households and will increase 'fuel poverty'. Thus demands on traditional social policies are likely to rise. More radical policy reforms will be needed to integrate climate change and social policy goals.carbon mitigation policy, social policy, fiscal competition

The monodromy groups of Schwarzian equations on closed Riemann surfaces

Let \theta:\pi_1(R) \to \PSL(2,\C) be a homomorphism of the fundamental group of an oriented, closed surface R of genus exceeding one. We will establish the following theorem. Theorem. Necessary and sufficient for \theta to be the monodromy representation associated with a complex projective stucture on R, either unbranched or with a single branch point of order 2, is that \theta(\pi_1(R)) be nonelementary. A branch point is required if and only if the representation \theta does not lift to \SL(2,\C).Comment: 80 pages, published versio

Utility Design for Distributed Resource Allocation -- Part I: Characterizing and Optimizing the Exact Price of Anarchy

Game theory has emerged as a fruitful paradigm for the design of networked multiagent systems. A fundamental component of this approach is the design of agents' utility functions so that their self-interested maximization results in a desirable collective behavior. In this work we focus on a well-studied class of distributed resource allocation problems where each agent is requested to select a subset of resources with the goal of optimizing a given system-level objective. Our core contribution is the development of a novel framework to tightly characterize the worst case performance of any resulting Nash equilibrium (price of anarchy) as a function of the chosen agents' utility functions. Leveraging this result, we identify how to design such utilities so as to optimize the price of anarchy through a tractable linear program. This provides us with a priori performance certificates applicable to any existing learning algorithm capable of driving the system to an equilibrium. Part II of this work specializes these results to submodular and supermodular objectives, discusses the complexity of computing Nash equilibria, and provides multiple illustrations of the theoretical findings.Comment: 15 pages, 5 figure

A risk-security tradeoff in graphical coordination games

A system relying on the collective behavior of decision-makers can be vulnerable to a variety of adversarial attacks. How well can a system operator protect performance in the face of these risks? We frame this question in the context of graphical coordination games, where the agents in a network choose among two conventions and derive benefits from coordinating neighbors, and system performance is measured in terms of the agents' welfare. In this paper, we assess an operator's ability to mitigate two types of adversarial attacks - 1) broad attacks, where the adversary incentivizes all agents in the network and 2) focused attacks, where the adversary can force a selected subset of the agents to commit to a prescribed convention. As a mitigation strategy, the system operator can implement a class of distributed algorithms that govern the agents' decision-making process. Our main contribution characterizes the operator's fundamental trade-off between security against worst-case broad attacks and vulnerability from focused attacks. We show that this tradeoff significantly improves when the operator selects a decision-making process at random. Our work highlights the design challenges a system operator faces in maintaining resilience of networked distributed systems.Comment: 13 pages, double column, 4 figures. Submitted for journal publicatio

Some Reverses of the Generalised Triangle Inequality in Complex Inner Product Spaces

Some reverses for the generalised triangle inequality in complex inner product spaces that improve the classical Diaz-Metcalf results and applications are given

Joint strategy fictitious play with inertia for potential games

We consider multi-player repeated games involving a large number of players with large strategy spaces and enmeshed utility structures. In these ldquolarge-scalerdquo games, players are inherently faced with limitations in both their observational and computational capabilities. Accordingly, players in large-scale games need to make their decisions using algorithms that accommodate limitations in information gathering and processing. This disqualifies some of the well known decision making models such as ldquoFictitious Playrdquo (FP), in which each player must monitor the individual actions of every other player and must optimize over a high dimensional probability space. We will show that Joint Strategy Fictitious Play (JSFP), a close variant of FP, alleviates both the informational and computational burden of FP. Furthermore, we introduce JSFP with inertia, i.e., a probabilistic reluctance to change strategies, and establish the convergence to a pure Nash equilibrium in all generalized ordinal potential games in both cases of averaged or exponentially discounted historical data. We illustrate JSFP with inertia on the specific class of congestion games, a subset of generalized ordinal potential games. In particular, we illustrate the main results on a distributed traffic routing problem and derive tolling procedures that can lead to optimized total traffic congestion