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Haskell A: Graphic Charts in Business:
How to Make and Use Them

Graphic Charts in Business: How to Make and Use Them

In striking black-and-white portraits, dozens of survivors of Michigan's cruel sentencing of children to life without parole-now free adults-are portrayed with irrepressible dignity&nbsp; 
 
The United States is the only country in the world that sentences children to serve time in adult prisons without the possibility of parole. The portrayal of children in conflict with the law, particularly children of color, as inherently threatening, dangerous, and adult-like has been key to denying these youth a second chance and foundational in justifying their cruel and excessive punishment in the criminal legal system.. 
 
In&nbsp;Morning from Now On, LaBelle, himself a survivor of childhood incarceration, cocreates astute and nuanced portraits with more than fifty of the hundreds of people in Michigan incarcerated as children. Accompanying essays provide critical context on the history of and impact on a society that locks away our children. 
 
In witnessing these survivors' yearning for freedom, the obstacles they face upon reentry, as well as the wonder and joy of being reunited with their families and communities, this collection reminds us of their unfathomable losses and calls on us to cherish&nbsp;all&nbsp;our children. 
 
With contributions by Jose Burgos, Bernardine Dohrn, Xavier McElrath-Bey, Timothy Connors, and Alison Leal Parker

Portraits of Life after Juvenile Incarceration

Morning from Now On

Decisions are everywhere--from a group's choice of pizza to a decision on a family vacation to the elections of political leaders. Central to the functioning of our organizations is the belief that these decisions reflect the wishes of voters. Yet most voting rules are unreliable and can lead to unfair outcomes. And, while a large body of academic literature describes the flaws and limitations of standard voting methods, little is known about why they occur.

In Fair Voting Methods, Donald G. Saari explores the difficulties that have plagued social choice theory for over seventy-five years. Focusing on ranked choice voting and group decision-making, Saari expands on Arrow's impossibility theorem and presents a more precise statement: all standard voting rules either fail to always rank the candidates to determine who is preferred to whom, or the voting outcomes can result in inferior choices that are not what the voters wanted. Saari then identifies and resolves the structures that negatively impact voting systems. While Arrow's seminal result asserted that the problems of standard voting systems are unavoidable, Saari makes a bold and compelling case that there are indeed usable fair voting methods. He introduces one such method that achieves Arrow's objectives of always ranking candidates with outcomes that reflect voters' intent. The book concludes by applying insights from voting theory into other topics where parts are also assembled into wholes, including judgement aggregation, corporate structures, crime prevention, the US Electoral College, and standard scientific procedures.

Resolving Arrow's Theorem and Other Paradoxes

Fair Voting Methods

The First Principle in Empirical Research

Significance by Sight

21st Century Progressivism and the Original Schools of Pragmatism and Institutional Economics

Self, Society and Economy

Critical and Post-Keynesian Perspectives

A History of Modern Macroeconomics

Routledge Frontiers of Political Economy

The Political Economy of Financial Capitalism

Marx and Financialisation

Routledge Critical Studies in Finance and Stability

Power, Interdependence and Diversity in Finance-led Capitalism

Global Regimes of Financialization

A groundbreaking new framework for business leaders and policymakers In Passionomics, Raja Rajamannar introduces an original intellectual framework that equips CEOs, CMOs, strategists, boards, and policymakers with a new lens for driving growth, innovation, and enduring customer loyalty. Where behavioral economics examines how individuals make decisions, Passionomics reveals how collective passion - the synchronized intensity of millions of people acting in concert - moves markets, reshapes industries, and creates extraordinary value for the organizations and institutions that learn to harness it. Rajamannar makes the case through vivid, real-world phenomena every leader recognizes but few have truly decoded: the economic waves generated by a Taylor Swift tour, the industry-wide momentum of Formula 1, the societal mobilization of the FIFA World Cup and the Olympic Games. These are not anecdotes. They are windows into a dynamic that, once understood, becomes a deliberate strategic advantage - one that transforms how companies build brands, design products, earn loyalty, and compete, and how policymakers shape economies, cities, and public life. Business leaders and policymakers will discover: <ul> <li>A new strategic framework - Passionomics - that explains how collective intensity operates as a distinct and powerful dynamic separate from individual behavior</li> <li>Why passion is a renewable source of innovation, loyalty, and growth - and why the organizations and institutions that ignore it are leaving extraordinary value on the table</li> <li>How to recognize, cultivate, and harness collective passion inside organizations, brands, entire categories, and public institutions</li> <li>Case studies from sports, entertainment, culture, and commerce that reveal the architecture of passion-driven growth</li> <li>A practical lens for boards, CEOs, CMOs, senior leaders, and policymakers who want to move beyond conventional playbooks and unlock step-change performance</li> </ul> Passionomics is essential reading for business leaders and policymakers who sense that something critical is missing from the standard strategic toolkit - and who want a rigorous, original framework for building companies, brands, institutions, and economies that win in ways others cannot replicate.

Why Passion Is the Most Overlooked Advantage in Business

Passionomics

A New Compass

The Common Good Economy

Chapman and Hall/CRC Series on Statistics in Business and Economics

Bayesian methods are now central to empirical macroeconomics, with routine use in academic research and at central banks for forecasting and policy analysis. As the models applied in practice have become increasingly high-dimensional and computationally intensive, a working understanding of the estimation algorithms-not only the models themselves-has become essential. While many existing texts treat Bayesian econometrics broadly, Bayesian Macroeconometrics focuses specifically on the models and methods used in modern Bayesian macroeconomic analysis, for readers who want both to understand these methods and to implement them.Bringing together modeling, posterior derivations, algorithmic design, and computation, the book derives each method step by step and integrates MATLAB code directly into the text. It pays particular attention to how posterior samplers are constructed in high-dimensional settings, where implementation choices can determine whether a method is practical for empirical work.A single idea ties the material together: linear regression as a recurring building block, with state space models and vector autoregressions treated as collections of linear regressions linked by latent states or dynamic dependence. From this foundation, the book moves to the models at the center of modern practice, including stochastic volatility, dynamic factor models, vector autoregressions, time-varying parameter VARs, and large VARs, alongside global-local shrinkage priors and Bayesian nonparametrics.Each chapter is anchored by worked examples using real macroeconomic data, closes with exercises, and is supported by a companion website providing datasets and code in MATLAB, Python, and R. The book is suitable as a primary text for graduate courses in Bayesian macroeconometrics and Bayesian time-series analysis, and as a reference for researchers and central-bank practitioners.Key Features:<ul> <li>Comprehensive coverage of Bayesian macroeconometric models - from basic Bayesian regressions and mixture models to linear Gaussian state space models, stochastic volatility models, and vector autoregressions.</li> <li>Emphasis on practical implementation - each model is illustrated with empirical applications using macroeconomic data and supported by reproducible code in MATLAB, Python, and R.</li> <li>Discussion of modern computation techniques - covering a range of advanced Markov chain Monte Carlo methods, including Hamiltonian Monte Carlo.</li> <li>Accessible style - technical results are derived in a step-by-step manner and are complemented by intuitive explanations and worked examples.</li> <li>Coverage of cutting-edge models and methods - including Dirichlet process mixtures, Gaussian process regressions, large VARs, and global-local priors.</li> </ul>

Methods and Applications

Bayesian Macroeconometrics

Studies in National Governance and Emerging Technologies

This book examines how artificial intelligence systems and their applications in security and defence are entangled with governance and policy processes in the EU. Combining concepts and insights from (critical) security studies and science and technology studies, it argues that behind the various AI-related policy initiatives in the EU are particular narratives on security and defence based on European fears of technological innovation and strategic gaps. In this respect, the book casts light on how such beliefs have become increasingly instrumentalized in the European governance dynamics, and subsequently embedded in successive policy initiatives and security and defence research programmes. It challenges conventional understandings of AI technologies as mere security and defence-enabling instruments, by providing a conceptually driven analysis of how certain visions of AI help govern and control one of the most dynamic emergent socio-technical fields. The book will appeal to all those interested in artificial intelligence, security studies, technology and European governance.&nbsp;
 
 Raluca Csernatoni is a Research Fellow at Carnegie Europe, where she works on the nexus between European defence and emerging technologies. She is also Guest Professor at the Centre for Security, Diplomacy and Strategy (CSDS), Vrije Universiteit Brussel, Belgium, and Visiting Faculty in the Department of International Relations, Central European University, Austria.

This book examines how artificial intelligence systems and their applications in security and defence are entangled with governance and policy processes in the EU. Combining concepts and insights from (critical) security studies and science and technology studies, it argues that behind the various AI-related policy initiatives in the EU are particular narratives on security and defence based on European fears of technological innovation and strategic gaps. In this respect, the book casts light on how such beliefs have become increasingly instrumentalized in the European governance dynamics, and subsequently embedded in successive policy initiatives and security and defence research programmes. It challenges conventional understandings of AI technologies as mere security and defence-enabling instruments, by providing a conceptually driven analysis of how certain visions of AI help govern and control one of the most dynamic emergent socio-technical fields. The book will appeal to all those interested in artificial intelligence, security studies, technology and European governance.&nbsp;

Artificial Security and the Politics of Hype in the EU

Chapman and Hall/CRC Financial Mathematics Series

Introduction to Financial Derivatives with Python, Second Editon continues to provide an accessible introduction to derivatives and quantitative finance. Starting from first principles, the book develops the foundations of derivative pricing before progressing to numerical methods and advanced volatility models. Mathematical concepts are introduced progressively, allowing the reader to develop the necessary tools alongside their financial applications. Financial intuition, mathematical foundations, and Python implementation are integrated throughout the book.The book covers the essential topics in derivative pricing and introduces numerical methods widely used in quantitative finance. It also develops advanced volatility models, including CEV, local volatility, Heston, and SABR.Features<ul> <li>Suitable for undergraduate and graduate students, as well as practitioners and anyone seeking an accessible introduction to quantitative finance</li> <li>Covers derivative pricing from fundamental principles to advanced volatility models</li> <li>Introduces numerical pricing techniques, including binomial trees and Monte Carlo simulation</li> <li>Provides chapter summaries, exercises, and examination material</li> <li>Accompanied by a GitHub repository containing the Python code used throughout the book</li> <li>No prior programming experience is required; introductions to Python and coding are provided.</li> </ul>New to the Second Edition<ul> <li>Fresh material on the Bachelier model and normal implied volatility</li> <li>A new chapter on local volatility covers the motivation for local volatility modelling, the CEV model, and Dupire's formula</li> <li>A new chapter on stochastic volatility develops the Heston and SABR models</li> <li>Python implementations to help the reader understand the concepts presented</li> <li>A new appendix including sample exams. This allows readers to practice the concepts learned throughout the book.</li> </ul>

Introduction to Financial Derivatives with Python

Graphic Charts in Business: How to Make and Use Them

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