323 research outputs found

    Twilight of the American State

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    The sudden emergence of the Trump nation surprised nearly everyone, including journalists, pundits, political consultants, and academics. When Trump won in 2016, his ascendancy was widely viewed as a fluke. Yet time showed it was instead the rise of a movement—angry, militant, revanchist, and unabashedly authoritarian. How did this happen? Twilight of the American State offers a sweeping exploration of how law and legal institutions helped prepare the grounds for this rebellious movement. The controversial argument is that, viewed as a legal matter, the American state is not just a liberal democracy, as most Americans believe. Rather, the American state is composed of an uneasy and unstable combination of different versions of the state—liberal democratic, administered, neoliberal, and dissociative. Each of these versions arose through its own law and legal institutions. Each emerged at different times historically. Each was prompted by deficits in the prior versions. Each has survived displacement by succeeding versions. All remain active in the contemporary moment—creating the political-legal dysfunction America confronts today. Pierre Schlag maps out a big picture view of the tribulations of the American state. The book abjures conventional academic frameworks, sets aside prescriptions for quick fixes, dispenses with lamentations about polarization, and bypasses historical celebrations of the American Spirit

    An examination of leading through change using Snyder’s hope theory and Lewin’s 3-step model

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    Never has the world experienced such rapid change, and the environment in which organizations operate necessitates increased change capability and organizational agility (Argyris, 1991). Strebel (1996) found success rates for change initiatives in Fortune 1000 companies ranged from a low of 20% to a high of 50%. Later studies would substantiate Strebel’s (1996) findings, claiming that, on average, failure rates of transformational change initiatives approach 70% (Beer & Nohria, 2000; Sirkin et al., 2005). Suppose this is so, and companies wish to thrive in such a dynamic environment. A fundamental understanding of why change efforts fail and how to drive more positive outcomes across organizations must be examined. With transformational leadership best practices well documented and time-tested change management models available to all, what then is missing? Applying Snyder’s (2002) hope theory, this study explores how the narratives of hopeful leaders advance organizational change faster and with greater reliability than their lower-hope counterparts. Through narrative inquiry, stories of hopeful change leaders offered ways and means for developing hopeful thinking in themselves, other organizational change leaders, and followers participating in organizational change. The narratives also addressed dynamics inhibiting hopeful thinking, complementing and enhancing Lewin’s (1947a) three-step change management model. Fifteen narrative approaches aligned with unfreezing, changing, and refreezing an organization are surfaced. Most importantly, suggestions are made for how change leaders can operationalize the building blocks of hope throughout their organizations

    Robust Stackelberg Equilibria

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    This paper provides a systematic study of the robust Stackelberg equilibrium (RSE), which naturally generalizes the widely adopted solution concept of the strong Stackelberg equilibrium (SSE). The RSE accounts for any possible up-to-δ\delta suboptimal follower responses in Stackelberg games and is adopted to improve the robustness of the leader's strategy. While a few variants of robust Stackelberg equilibrium have been considered in previous literature, the RSE solution concept we consider is importantly different -- in some sense, it relaxes previously studied robust Stackelberg strategies and is applicable to much broader sources of uncertainties. We provide a thorough investigation of several fundamental properties of RSE, including its utility guarantees, algorithmics, and learnability. We first show that the RSE we defined always exists and thus is well-defined. Then we characterize how the leader's utility in RSE changes with the robustness level considered. On the algorithmic side, we show that, in sharp contrast to the tractability of computing an SSE, it is NP-hard to obtain a fully polynomial approximation scheme (FPTAS) for any constant robustness level. Nevertheless, we develop a quasi-polynomial approximation scheme (QPTAS) for RSE. Finally, we examine the learnability of the RSE in a natural learning scenario, where both players' utilities are not known in advance, and provide almost tight sample complexity results on learning the RSE. As a corollary of this result, we also obtain an algorithm for learning SSE, which strictly improves a key result of Bai et al. in terms of both utility guarantee and computational efficiency

    Composing Efficient, Robust Tests for Policy Selection

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    Modern reinforcement learning systems produce many high-quality policies throughout the learning process. However, to choose which policy to actually deploy in the real world, they must be tested under an intractable number of environmental conditions. We introduce RPOSST, an algorithm to select a small set of test cases from a larger pool based on a relatively small number of sample evaluations. RPOSST treats the test case selection problem as a two-player game and optimizes a solution with provable kk-of-NN robustness, bounding the error relative to a test that used all the test cases in the pool. Empirical results demonstrate that RPOSST finds a small set of test cases that identify high quality policies in a toy one-shot game, poker datasets, and a high-fidelity racing simulator.Comment: 26 pages, 13 figures. To appear in Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023

    A Game-Theoretic Framework for AI Governance

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    As a transformative general-purpose technology, AI has empowered various industries and will continue to shape our lives through ubiquitous applications. Despite the enormous benefits from wide-spread AI deployment, it is crucial to address associated downside risks and therefore ensure AI advances are safe, fair, responsible, and aligned with human values. To do so, we need to establish effective AI governance. In this work, we show that the strategic interaction between the regulatory agencies and AI firms has an intrinsic structure reminiscent of a Stackelberg game, which motivates us to propose a game-theoretic modeling framework for AI governance. In particular, we formulate such interaction as a Stackelberg game composed of a leader and a follower, which captures the underlying game structure compared to its simultaneous play counterparts. Furthermore, the choice of the leader naturally gives rise to two settings. And we demonstrate that our proposed model can serves as a unified AI governance framework from two aspects: firstly we can map one setting to the AI governance of civil domains and the other to the safety-critical and military domains, secondly, the two settings of governance could be chosen contingent on the capability of the intelligent systems. To the best of our knowledge, this work is the first to use game theory for analyzing and structuring AI governance. We also discuss promising directions and hope this can help stimulate research interest in this interdisciplinary area. On a high, we hope this work would contribute to develop a new paradigm for technology policy: the quantitative and AI-driven methods for the technology policy field, which holds significant promise for overcoming many shortcomings of existing qualitative approaches

    Game theoretic optimisation in process and energy systems engineering: A review

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    Game theory is a framework that has been used by various research fields in order to represent dynamic correlation among stakeholders. Traditionally, research within the process and energy systems engineering community has focused on the development of centralised decision making schemes. In the recent years, decentralised decision-making schemes have attracted increasing attention due to their ability to capture multi-stakeholder dynamics in a more accurate manner. In this article, we survey how centralised and decentralised decision making has been facilitated by game theoretic approaches. We focus on the deployment of such methods in process systems engineering problems and review applications related to supply chain optimisation problems, design and operations, and energy systems optimisation. Finally, we analyse different game structures based on the degree of cooperation and how fairness criteria can be employed to find fair payoff allocations

    Operational Research: methods and applications

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    This is the final version. Available on open access from Taylor & Francis via the DOI in this recordThroughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

    Operational research:methods and applications

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    Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

    MONETARY POLICY AND BANKING: NON-LINEAR DYNAMIC MODELS EVOLVING AS ADAPTIVE SYSTEMS

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    Questa tesi presenta cinque capitoli su diversi aspetti della teoria della politica monetaria con un’analisi approfondita degli strumenti a disposizione delle banche centrali (BC) per stabilizzare e correggere gli squilibri nei mercati economici e finanziari globalizzati. I recenti shock provocati dalla recessione del Covid-19 e dalla crisi energetica hanno modificato le interdipendenze tra i principali attori economici, influenzando pesantemente il meccanismo di trasmissione della politica monetaria. L’obiettivo della tesi è indagare l’impatto di tali strumenti monetari in un costrutto teorico che include relazioni non-lineari tra variabili, eterogeneità degli agenti e razionalità limitata, frizioni di mercato e asimmetrie informative. In particolare, le aspettative degli agenti giocano un ruolo cruciale nelle decisioni di politica monetaria e, in questo lavoro, sono ben rappresentate da schemi adattivi che consentono l’apprendimento, l’interazione sociale, l’imitazione e il cambiamento di opinioni. Gli schemi adattivi sono modellati nella forma di sistemi dinamici a tempo discreto e continuo e la loro analisi fornisce nuove intuizioni economiche sul processo evolutivo che porta a situazioni di equilibrio o disequilibrio. Ciò si rivela prezioso in una prospettiva di policy-maker poiché aiuta a comprendere le fragilità intrinseche dei sistemi economici/finanziari, fornendo appropriate misure di policy per mitigarle. Dopo una breve rassegna della letteratura, il capitolo due si concentra sull’identificazione di una regola di Taylor endogena e dinamica per il tasso di interesse a breve termine al fine di ridurre l'inflazione e l'output gap. Lo scopo è quello di mitigare squilibri e shock economici temporanei. I risultati evidenziano il dilemma che le BC si trovano ad affrontare in scenari di trade-off in cui non è possibile raggiungere pienamente entrambi gli obiettivi con un unico strumento a disposizione. Il terzo capitolo fornisce un’analisi approfondita sulla relazione dinamica tra rapporto debito pubblico PIL e tasso di inflazione. Si esamina come diverse politiche monetarie (tasso di interesse, quantitative easing, monetizzazione) e regole fiscali attive possano evitare percorsi insostenibili del debito pubblico e fluttuazioni eccessive dell'inflazione. In scenari di bassa inflazione, il quantitative easing e una modesta monetizzazione finanziaria possono essere utili a stabilizzare l’evoluzione del debito grazie al loro ruolo di contenimento degli spread e di stimolo alla crescita, mentre l’effetto di incremento dell’inflazione è generalmente limitato. Inoltre, la politica basata sui tassi d'interesse da sola non è sufficiente a controllare l'inflazione: la credibilità della BC nel guidare le aspettative di inflazione risulta essere cruciale per controllare l'andamento dei prezzi e raggiungere la stabilità macroeconomica. Una delle novità di questa analisi è la presenza di un livello soglia sia per il rapporto debito/PIL che per l'inflazione, oltre il quale il rapporto debito/PIL diventa insostenibile seguendo un percorso esplosivo. Il quarto capitolo fa luce sui meccanismi attraverso i quali una BC può implementare i rischi legati al cambiamento climatico nelle sue operazioni monetarie non convenzionali (ad esempio, un programma di acquisto di obbligazioni societarie). La cosiddetta politica monetaria verde mira a orientare o a far convergere l'allocazione di attività e garanzie verso i settori industriali a basse emissioni di carbonio. Nel modello sviluppato, questa strategia della BC riduce effettivamente il costo del capitale per le obbligazioni verdi rispetto a quelle convenzionali, favorendo così gli investimenti/tecnologie sostenibili sul mercato...This thesis presents five chapters on different aspects of monetary policy theory with a thorough analysis of the instruments at disposal of central banks (CBs) to stabilize and correct imbalances in globalized economic and financial markets. The recent shocks posed by the Covid-19 recession and energy crisis have changed the interdependencies between key economic actors, heavily affecting the mechanism of transmission of monetary policy. The aim of the thesis is to investigate the impact of such monetary instruments in a theoretical construct that includes non-linear relationships among variables, agents’ heterogeneity and limited rationality, market frictions, and asymmetric information. In particular, the agents’ expectations play a crucial role in monetary policy decisions and, in this work, are well represented by adaptive schemes that allow for learning, social interaction, imitation, and changing beliefs. Adaptive schemes are modeled in the form of discrete or continuous dynamical systems and their analysis provides new economic insights into the evolution process that leads to equilibrium or disequilibrium situations. This turns out to be precious from a policy-maker perspective because it helps to understand the intrinsic fragilities of the economic/financial systems, providing appropriate policy measures to mitigate them. After a brief literature review, chapter two focuses on the identification of an endogenous and dynamic Taylor rule for the short-term interest rate to target inflation and output gaps. The aim is to mitigate temporary economic unbalances and shocks. The results highlight the dilemma faced by the CBs in trade-off scenarios where it is not possible to fully achieve both goals with a unique instrument at their disposal. The third chapter provides an in-depth analysis of the dynamic relationship between the public debt ratio and the inflation rate. It is explored how different monetary policies (interest rate, quantitative easing, monetization) and active fiscal rules can avoid unstainable government debt paths and excessive inflation fluctuations. In low inflation scenarios, quantitative easing and moderate money finance can be helpful in stabilizing debt evolution thanks to their role in containing spreads and stimulating growth, while the effect on inflation rise is generally limited. Furthermore, interest-rate-based policy alone is not sufficient to control inflation: the CB’s credibility in driving inflation expectations results to be crucial to control price developments and achieving macroeconomic stability. One of the novelties of this analysis is the presence of a threshold level for both debt ratio and inflation, beyond which the debt ratio becomes unsustainable following an explosive path. Chapter four sheds light on the mechanisms through which a CB can implement the risks related to climate change in its unconventional monetary operations (e.g. a corporate bonds purchase program). The so-called green monetary policy aims to steer or tilt the allocation of assets and collateral toward low-carbon industries. In the model developed, this CB strategy effectively reduces the cost of capital for green bonds as opposed to conventional bonds, and thus favors sustainable investment/technology in the market. However, there still could be technology trap equilibria in which no investment in green technology occurs in the long-run, even if the non-green investment equilibrium is inefficient. The green monetary policy can help firms to leave these technology traps and the degree of market competition and of market imperfections can contribute to amplifying the effects of this instrument by the transmission channel..

    Austerity from the left explaining the fiscal policies of social democratic parties in response to the Great Recession

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    Defence date: 15 March 2019Examining Board: Professor Hanspeter Kriesi, European University Institute (Supervisor); Professor Dorothee Bohle, European University Institute; Professor Herbert Kitschelt, Duke University; Professor Jonas Pontusson, University of GenevaAusterity has come to define the post-crisis European political economy as the predominant policy response to the Great Recession since 2010. After a brief period of “emergency Keynesianism” from 2008 to 2010, even social democratic parties abandoned plans for deficit-spending and accepted austerity as the dogma of the day. Most of the existing literature attempts to explain this outcome either by pressures from financial markets or by the influence of external institutions, for example the European Union or the International Monetary Fund. However, social democratic parties also accepted fiscal orthodoxy in countries where the pressures from financial markets and external institutions were weak or absent, and thus they are not a sufficient explanation to explain austerity from the left. This thesis instead shifts the focus towards the popular coalitions that underlie macroeconomic policy by examining the elite and the popular politics of austerity. It argues that social democratic parties had both electoral and ideational reasons to support orthodox fiscal policies during the crisis, as they were trapped by the legacy of the Third Way that they had embarked upon prior to the crisis. On the one hand, social democratic parties believed that there was a high public support for fiscal consolidation. Influenced by the differentiation of interests among their traditional constituencies, they attempted to increase their economic credibility in order appeal to centre-left voters from the expanded middle class. On the other hand, social democratic parties were influenced by mainstream economic ideas. They drew on New Keynesianism, endogenous growth theory, and the social investment paradigm, which had become popular among social democrats at the end of the 20th century, to legitimize their support for the “austerity settlement” during the Great Recession. This combination of electoral and ideational forces created powerful pressures for social democrats to support orthodox economic policies over Keynesian deficit-spending which many failed to resist. To make this argument, this thesis combines qualitative and quantitative methods and draws on a wide range of empirical evidence. Among others, it uses evidence from quantitative content analysis, survey experiments as well as insights from over 40 elite interviews with leading social democratic politicians and policy-makers in Germany and the UK. In this way, the thesis studies both the popular and the elite politics of austerity in Western Europe and provides a new account of social democratic austerity.Chapter 2 'Theoretical Framework' and parts of chapter 6 'The Fiscal Policies of the British Labour Party in Times of Crisis' and 7 'The Fiscal Policies of the German SPD in Times of Crisis' draw upon an earlier version published as an article published jointly with Sean McDaniel 'The ideational foundations of social democratic austerity in the context of the Great Recession' (2019) in the journal 'Socio-economic reviewChapter 3 'The Programmatic Response' of the PhD thesis draws upon an earlier version published as an article 'The missing left? : economic crisis and the programmatic response of social democratic parties in Europe' (2018) in the journal 'Party politics
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