Methods of Nonlinear Analysis

The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. This book clearly distinguishes itself from its competitors by emphasising the techniques

This book presents a theory motivated by the spaces LP, 0 ≤ p

The aim of this book is to demonstrate both the difficulties and the opportunities which the accumulation of statistical information in economically advanced countries offers for studying nineteenth-century society in depth. The chief emphasis is upon quantitative methods of analysis. The main focus of the attention is the census – what information was required on census night; how the information was collected; how accurately and completely population characteristics were recorded, the problems which arise in attempting to use either the published census volumes or the enumerators' books; and the techniques which have proved useful in analysis. Related topics covered include the study of family structure, the use of information about occupation, the measurement of migration, criminal statistics, educational provision and sampling in historical research.

A comprehensive manual on the efficient modeling and analysis of photonic devices through building numerical codes, this book provides graduate students and researchers with the theoretical background and MATLAB programs necessary for them to start their own numerical experiments. Beginning by summarizing topics in optics and electromagnetism, the book discusses optical planar waveguides, linear optical fiber, the propagation of linear pulses, laser diodes, optical amplifiers, optical receivers, finite-difference time-domain method, beam propagation method and some wavelength division devices, solitons, solar cells and metamaterials. Assuming only a basic knowledge of physics and numerical methods, the book is ideal for engineers, physicists and practising scientists. It concentrates on the operating principles of optical devices, as well as the models and numerical methods used to describe them.

Contrasts are statistical procedures for asking focused questions of data. Compared to diffuse or omnibus questions, focused questions are characterized by greater conceptual clarity and greater statistical power when examining those focused questions. If an effect truly exists, we are more likely to discover it and to believe it to be real when asking focused questions rather than omnibus ones. Researchers, teachers of research methods and graduate students will be familiar with the principles and procedures of contrast analysis, but will also be introduced to a series of newly developed concepts, measures, and indices that permit a wider and more useful application of contrast analysis. This volume takes on this new approach by introducing a family of correlational effect size estimates.

Contrasts are statistical procedures for asking focused questions of data. Compared to diffuse or omnibus questions, focused questions are characterized by greater conceptual clarity and greater statistical power when examining those focused questions. If an effect truly exists, we are more likely to discover it and to believe it to be real when asking focused questions rather than omnibus ones. Researchers, teachers of research methods and graduate students will be familiar with the principles and procedures of contrast analysis, but will also be introduced to a series of newly developed concepts, measures, and indices that permit a wider and more useful application of contrast analysis. This volume takes on this new approach by introducing a family of correlational effect size estimates.

This substantial revision of the text Numerical Solution of Partial Differential Equations by the Finite Element Method by C. Johnson is a two volume introduction to the computational solution of differential equations using a unified approach organised around the adaptive finite element method. It presents a synthesis of mathematical modelling, analysis and computation. It provides the student with theoretical and practical tools useful for addressing the basic questions of computational mathematical modelling in science and engineering: How to model physical phenomena using differential equations? What are the properties of solutions of differential equations? How to compute solutions in practice? How to estimate and control the accuracy of computed solutions? The first volume begins by developing the basic issues at an elementary level in the context of a set of model problems in ordinary differential equations. The second volume extends the scope to nonlinear differential equations

This wide-ranging comparative account of the legal regimes for controlling administrative power in England, the USA and Australia argues that differences and similarities between control regimes may be partly explained by the constitutional structures of the systems of government in which they are embedded. It applies social-scientific and historical methods to the comparative study of law and legal systems in a novel and innovative way, and combines accounts of long-term and large-scale patterns of power distribution with detailed analysis of features of administrative law and the administrative justice systems of three jurisdictions. It also proposes a new method of analysing systems of government based on two different models of the distribution of public power (diffusion and concentration), a model which proves more illuminating than traditional separation-of-powers analysis.

This wide-ranging comparative account of the legal regimes for controlling administrative power in England, the USA and Australia argues that differences and similarities between control regimes may be partly explained by the constitutional structures of the systems of government in which they are embedded. It applies social-scientific and historical methods to the comparative study of law and legal systems in a novel and innovative way, and combines accounts of long-term and large-scale patterns of power distribution with detailed analysis of features of administrative law and the administrative justice systems of three jurisdictions. It also proposes a new method of analysing systems of government based on two different models of the distribution of public power (diffusion and concentration), a model which proves more illuminating than traditional separation-of-powers analysis.

Systematically reading Jewish exegesis in light of Homeric scholarship, this book argues that more than 2000 years ago Alexandrian Jews developed critical and literary methods of Bible interpretation which are still extremely relevant today. Maren R. Niehoff provides a detailed analysis of Alexandrian Bible interpretation, from the second century BCE through newly discovered fragments to the exegetical work done by Philo. Niehoff shows that Alexandrian Jews responded in a great variety of ways to the Homeric scholarship developed at the Museum. Some Jewish scholars used the methods of their Greek colleagues to investigate whether their Scripture contained myths shared by other nations, while others insisted that significant differences existed between Judaism and other cultures. This book is vital for any student of ancient Judaism, early Christianity and Hellenistic culture.

Systematically reading Jewish exegesis in light of Homeric scholarship, this book argues that more than 2000 years ago Alexandrian Jews developed critical and literary methods of Bible interpretation which are still extremely relevant today. Maren R. Niehoff provides a detailed analysis of Alexandrian Bible interpretation, from the second century BCE through newly discovered fragments to the exegetical work done by Philo. Niehoff shows that Alexandrian Jews responded in a great variety of ways to the Homeric scholarship developed at the Museum. Some Jewish scholars used the methods of their Greek colleagues to investigate whether their Scripture contained myths shared by other nations, while others insisted that significant differences existed between Judaism and other cultures. This book is vital for any student of ancient Judaism, early Christianity and Hellenistic culture.

Paradoxically, doing corpus linguistics is both easier and harder than it has ever been before. On the one hand, it is easier because we have access to more existing corpora, more corpus analysis software tools, and more statistical methods than ever before. On the other hand, reliance on these existing corpora and corpus linguistic methods can potentially create layers of distance between the researcher and the language in a corpus, making it a challenge to do linguistics with a corpus. The goal of this Element is to explore ways for us to improve how we approach linguistic research questions with quantitative corpus data. We introduce and illustrate the major steps in the research process, including how to: select and evaluate corpora, establish linguistically-motivated research questions, observational units and variables, select linguistically interpretable variables, understand and evaluate existing corpus software tools, adopt minimally sufficient statistical methods, and qualita

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

Social media is an invaluable source of time-critical information during a crisis. However, emergency response and humanitarian relief organizations that would like to use this information struggle with an avalanche of social media messages that exceeds the human capacity to process. Emergency managers, decision makers, and affected communities can make sense of social media through a combination of machine computation and human compassion - expressed by thousands of digital volunteers who publish, process, and summarize potentially life-saving information. This book brings together computational methods from many disciplines: natural language processing, semantic technologies, data mining, machine learning, network analysis, human-computer interaction, and information visualization, focusing on methods that are commonly used for processing social media messages under time-critical constraints, and offering more than 500 references to in-depth information.

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

Aggregation is the process of combining several numerical values into a single representative value, and an aggregation function performs this operation. These functions arise wherever aggregating information is important: applied and pure mathematics (probability, statistics, decision theory, functional equations), operations research, computer science, and many applied fields (economics and finance, pattern recognition and image processing, data fusion, etc.). This is a comprehensive, rigorous and self-contained exposition of aggregation functions. Classes of aggregation functions covered include triangular norms and conorms, copulas, means and averages, and those based on nonadditive integrals. The properties of each method, as well as their interpretation and analysis, are studied in depth, together with construction methods and practical identification methods. Special attention is given to the nature of scales on which values to be aggregated are defined (ordinal, interval, ratio

The theory of Toeplitz matrices and operators is a vital part of modern analysis, with applications to moment problems, orthogonal polynomials, approximation theory, integral equations, bounded- and vanishing-mean oscillations, and asymptotic methods for large structured determinants, among others. This friendly introduction to Toeplitz theory covers the classical spectral theory of Toeplitz forms and Wiener–Hopf integral operators and their manifestations throughout modern functional analysis. Numerous solved exercises illustrate the results of the main text and introduce subsidiary topics, including recent developments. Each chapter ends with a survey of the present state of the theory, making this a valuable work for the beginning graduate student and established researcher alike. With biographies of the principal creators of the theory and historical context also woven into the text, this book is a complete source on Toeplitz theory.

Modeling atmospheric processes in order to forecast the weather or future climate change is an extremely complex and computationally intensive undertaking. One of the main difficulties is that there are a huge number of factors that need to be taken into account, some of which are still poorly understood. The Factor Separation (FS) method is a computational procedure that helps deal with these nonlinear factors. In recent years many scientists have applied FS methodology to a range of modeling problems, including paleoclimatology, limnology, regional climate change, rainfall analysis, cloud modeling, pollution, crop growth, and other forecasting applications. This book is the first to describe the fundamentals of the method, and to bring together its many applications in the atmospheric sciences. The main audience is researchers and graduate students using the FS method, but it is also of interest to advanced students, researchers, and professionals across the atmospheric sciences.

The Lévy Laplacian is an infinite-dimensional generalization of the well-known classical Laplacian. The theory has become well developed in recent years and this book was the first systematic treatment of the Lévy–Laplace operator. The book describes the infinite-dimensional analogues of finite-dimensional results, and more especially those features which appear only in the generalized context. It develops a theory of operators generated by the Lévy Laplacian and the symmetrized Lévy Laplacian, as well as a theory of linear and nonlinear equations involving it. There are many problems leading to equations with Lévy Laplacians and to Lévy–Laplace operators, for example superconductivity theory, the theory of control systems, the Gauss random field theory, and the Yang–Mills equation. The book is complemented by an exhaustive bibliography. The result is a work that will be valued by those working in functional analysis, partial differential equations and probability theory.

The Lévy Laplacian is an infinite-dimensional generalization of the well-known classical Laplacian. The theory has become well developed in recent years and this book was the first systematic treatment of the Lévy–Laplace operator. The book describes the infinite-dimensional analogues of finite-dimensional results, and more especially those features which appear only in the generalized context. It develops a theory of operators generated by the Lévy Laplacian and the symmetrized Lévy Laplacian, as well as a theory of linear and nonlinear equations involving it. There are many problems leading to equations with Lévy Laplacians and to Lévy–Laplace operators, for example superconductivity theory, the theory of control systems, the Gauss random field theory, and the Yang–Mills equation. The book is complemented by an exhaustive bibliography. The result is a work that will be valued by those working in functional analysis, partial differential equations and probability theory.

The previous edition of this text was the first to provide a quantitative introduction to chaos and nonlinear dynamics at undergraduate level. It was widely praised for the clarity of the writing and for the unique and effective way in which the authors presented the basic ideas. These same qualities characterise this revised and expanded second edition. Interest in chaotic dynamics has grown explosively in recent years. Applications to practically every scientific field have had far-reaching impact. As in the first edition, the authors present all the main features of chaotic dynamics using the damped, driven pendulum as the primary model. This second edition includes additional material on the analysis and characterisation of chaotic data, and applications of chaos. This new edition of Chaotic Dynamics can be used as a text for courses on chaos for physics and engineering students at the second and third year level.

Developed fifty years ago by the National Bureau of Economic Research, the analytic methods of business cycles and economic indicators enable economists to forecast economic trends by examining the repetitive sequences that occur in business cycles. The methodology has proven to be an inexpensive and useful tool that is now used extensively throughout the world. In recent years, however, significant new developments have emerged in the field of business cycles and economic indicators. This volume contains twenty-two articles by international experts who are working with new and innovative approaches to indicator research. They cover advances in three broad areas of research: the use of new developments in economic theory and time-series analysis to rationalise existing systems of indicators; more appropriate methods to evaluate the forecasting records of leading indicators, particularly of turning point probability; and the development of new indicators.

Understand the fundamental concepts, theoretical background, major experimental observations, and device applications of graphene photonics with this self-contained text. Systematically and rigorously developing each concept and theoretical model from the ground up, it guides readers through the major topics, from basic properties and band structure to electronic, optical, optoelectronic, and nonlinear optical properties, and plasmonics and photonic devices. The connections between theory, modeling, experiment, and device concepts are demonstrated throughout, and every optical process is analyzed through formal electromagnetic analysis. Suitable for both self-study and a one-semester or one-quarter course, this is the ideal text for graduate students and researchers in photonics, optoelectronics, nanoscience and nanotechnology, and optical and solid-state physics, who are working in this rapidly developing field.

Symplectic geometry originated in physics, but it has flourished as an independent subject in mathematics, together with its offspring, symplectic topology. Symplectic methods have even been applied back to mathematical physics. Noncommutative geometry has developed an alternative mathematical quantization scheme based on a geometric approach to operator algebras. Deformation quantization, a blend of symplectic methods and noncommutative geometry, approaches quantum mechanics from a more algebraic viewpoint, as it addresses quantization as a deformation of Poisson structures. This volume contains seven chapters based on lectures given by invited speakers at two May 2010 workshops held at the Mathematical Sciences Research Institute: Symplectic and Poisson Geometry in Interaction with Analysis, Algebra and Topology (honoring Alan Weinstein, one of the key figures in the field) and Symplectic Geometry, Noncommutative Geometry and Physics. The chapters include presentations of previously

This new edition explains how vibrations can be used in a broad spectrum of applications and how to meet the challenges faced by engineers and system designers. The text integrates linear and nonlinear systems, and covers the time domain and the frequency domain, responses to harmonic and transient excitations, and discrete and continuous system models. It focuses on modeling, analysis, prediction, and measurement to provide a complete understanding of the underlying physical vibratory phenomena and their relevance for engineering design. Knowledge is put into practice through numerous examples with real-world applications in a range of disciplines, detailed design guidelines applicable to various vibratory systems, and over forty online interactive graphics which provide a visual summary of system behaviors and enable students to carry out their own parametric studies. Some thirteen new tables act as a quick reference for self-study, detailing key characteristics of physical systems a

Big Data and methods for analyzing large data sets such as machine learning have in recent times deeply transformed scientific practice in many fields. However, an epistemological study of these novel tools is still largely lacking. After a conceptual analysis of the notion of data and a brief introduction into the methodological dichotomy between inductivism and hypothetico-deductivism, several controversial theses regarding big data approaches are discussed. These include, whether correlation replaces causation, whether the end of theory is in sight and whether big data approaches constitute entirely novel scientific methodology. In this Element, I defend an inductivist view of big data research and argue that the type of induction employed by the most successful big data algorithms is variational induction in the tradition of Mill's methods. Based on this insight, the before-mentioned epistemological issues can be systematically addressed.

Focusing on the period of Milton Friedman's collaboration with Anna J. Schwartz, from 1948 to 1991, this 1996 work examines the history of debates between Friedman and his critics over money's causal role in business cycles. Professor Hammond shows that critics' reactions were grounded in two distinctive features of Friedman and Schwartz's way of doing economic analysis - their National Bureau business cycle methods and Friedman's Marshallian methodology. With the post-war dominance of Cowles Commission methods and Walrasian methodology, Friedman and Schwartz's monetary economics appeared to contemporary critics to be 'measurement without theory'. Drawing extensively upon unpublished materials, Professor Hammond's treatment offers new insights on Milton Friedman's attempts to settle debates with his critics and his eventual recognition of the methodological impediments. The book will interest monetary economists and macroeconomists, as well as historians of economics and methodologists

Focusing on the period of Milton Friedman's collaboration with Anna J. Schwartz, from 1948 to 1991, this 1996 work examines the history of debates between Friedman and his critics over money's causal role in business cycles. Professor Hammond shows that critics' reactions were grounded in two distinctive features of Friedman and Schwartz's way of doing economic analysis - their National Bureau business cycle methods and Friedman's Marshallian methodology. With the post-war dominance of Cowles Commission methods and Walrasian methodology, Friedman and Schwartz's monetary economics appeared to contemporary critics to be 'measurement without theory'. Drawing extensively upon unpublished materials, Professor Hammond's treatment offers new insights on Milton Friedman's attempts to settle debates with his critics and his eventual recognition of the methodological impediments. The book will interest monetary economists and macroeconomists, as well as historians of economics and methodologists

Late Nineteenth-Century American Development is an economist's attempt to interpret a critical period of US history, from Civil War to World War I. The questions raised have always been at the heart of American historiography. What accounts for the retardation up to the turn of the century? How did capital markets operate and what was their influence on the pace and pattern of our growth? What determined farm performance and what impact did that performance have on the economy as a whole? Yet while the questions raised in this book are familiar, the methods are not. This book blends traditional historical analysis with general equilibrium theory, modern macroeconomics and simulation analysis. The result is a provocative book of remarkable scope which offers a fresh interpretation of late nineteenth-century American growth.

When a mechanical system consists of two or more coupled vibrating components, the vibration of one of the component subsystems may destabilize the motion of the other components. This destabilization effect is called autoparametric resonance. It is a concept that has important engineering applications. For example, vibrations in a pipeline induced by high-speed gas flows must be considered in the design and operation of the pipeline. This book is the first completely devoted to the subject of autoparametric resonance in an engineering context. Using the tools of nonlinear analysis, the authors show how to carry out the first crucial step, that is, how to determine the regions of parameter space where the semi-trivial solution is unstable. They describe what happens in these regions and then discuss non-trivial solutions and their stability. The study of autoparametric systems is a lively area of current research in engineering and applied mathematics, and this book will appeal to gra

The world's marine fisheries are in trouble, as a direct result of overfishing and the overcapacity of fishing fleets. Despite intensive management efforts, the problems still persist in many areas, resulting in many fisheries being neither sustainable nor profitable. Using bio-economic models of commercial fisheries, this book demonstrates that new management methods, based on individual or community catch quotas, are required to resolve the overfishing problem. Uncertainty about marine systems may be another factor contributing to overfishing. Methods of decision analysis and Bayesian inference are used to discuss risk management and the precautionary principle, arguing that extensive marine reserves may be the best way to protect fisheries, alongside a controlled catch quota system. This book will be of interest to environmental scientists, economists and fisheries managers, providing novel insights into many well-known but poorly understood aspects of fisheries management.

The world's marine fisheries are in trouble, as a direct result of overfishing and the overcapacity of fishing fleets. Despite intensive management efforts, the problems still persist in many areas, resulting in many fisheries being neither sustainable nor profitable. Using bio-economic models of commercial fisheries, this book demonstrates that new management methods, based on individual or community catch quotas, are required to resolve the overfishing problem. Uncertainty about marine systems may be another factor contributing to overfishing. Methods of decision analysis and Bayesian inference are used to discuss risk management and the precautionary principle, arguing that extensive marine reserves may be the best way to protect fisheries, alongside a controlled catch quota system. This book will be of interest to environmental scientists, economists and fisheries managers, providing novel insights into many well-known but poorly understood aspects of fisheries management.

This graduate-level text gives a self-contained exposition of fundamental topics in equilibrium and nonequilibrium statistical thermodynamics. The text follows a balanced approach between the macroscopic (thermodynamic) and microscopic (statistical) points of view. The first half of the book deals with equilibrium thermodynamics and statistical mechanics. In addition to standard subjects, the reader will find a detailed account of broken symmetries, critical phenomena and the renormalization group, as well as an introduction to numerical methods. The second half of the book is devoted to nonequilibrium phenomena, first following a macroscopic approach, with hydrodynamics as an important example. Kinetic theory receives a thorough treatment through analysis of the Boltzmann-Lorentz model and the Boltzmann equation. The book concludes with general nonequilibrium methods such as linear response, projection method and the Langevin and Fokker-Planck equations, including numerical simulation

As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity.

Analytic combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the analysis of algorithms and for the study of scientific models in many disciplines, including probability theory, statistical physics, computational biology, and information theory. With a careful combination of symbolic enumeration methods and complex analysis, drawing heavily on generating functions, results of sweeping generality emerge that can be applied in particular to fundamental structures such as permutations, sequences, strings, walks, paths, trees, graphs and maps. This account is the definitive treatment of the topic. The authors give full coverage of the underlying mathematics and a thorough treatment of both classical and modern applications of the theory. The text is complemented with exercises, examples, appendices and notes to aid understanding. The book can be used for an advanc

Thoroughly revised for its second edition, this advanced textbook provides an introduction to the basic methods of computational physics, and an overview of progress in several areas of scientific computing by relying on free software available from CERN. The book begins by dealing with basic computational tools and routines, covering approximating functions, differential equations, spectral analysis, and matrix operations. Important concepts are illustrated by relevant examples at each stage. The author also discusses more advanced topics, such as molecular dynamics, modeling continuous systems, Monte Carlo methods, genetic algorithm and programming, and numerical renormalization. It includes many more exercises. This can be used as a textbook for either undergraduate or first-year graduate courses on computational physics or scientific computation. It will also be a useful reference for anyone involved in computational research.

Thoroughly revised for its second edition, this advanced textbook provides an introduction to the basic methods of computational physics, and an overview of progress in several areas of scientific computing by relying on free software available from CERN. The book begins by dealing with basic computational tools and routines, covering approximating functions, differential equations, spectral analysis, and matrix operations. Important concepts are illustrated by relevant examples at each stage. The author also discusses more advanced topics, such as molecular dynamics, modeling continuous systems, Monte Carlo methods, genetic algorithm and programming, and numerical renormalization. It includes many more exercises. This can be used as a textbook for either undergraduate or first-year graduate courses on computational physics or scientific computation. It will also be a useful reference for anyone involved in computational research.

This book is a rigorous introduction to the abstract theory of partial differential equations. The main prerequisite is familiarity with basic functional analysis: more advanced topics such as Fredholm operators, the Schauder fixed point theorem and Bochner integrals are introduced when needed, and the book begins by introducing the necessary material from the theory of distributions and Sobolev spaces. Using such techniques, the author presents different methods available for solving elliptic, parabolic and hyperbolic equations. He also considers the difference process for the practical solution of a partial differential equation, emphasising that it is possible to solve them numerically by simple methods. Many examples and exercises are provided throughout, and care is taken to explain difficult points. Advanced undergraduates and graduate students will appreciate this self-contained and practical introduction.

This book challenges the conventional wisdom that policy performance is the most important determinant of regime support. It does so by focusing on two countries where performance and support do not match. Chile is the economic envy of every country in Latin America, yet support has been surprisingly anemic. By contrast, Venezuela managed to maintain extremely high levels of support during the reign of Hugo Chávez despite severe failures of governance. Resolution of these paradoxes requires turning away from policy decisions and focusing instead on how those decisions are made. Taking inspiration from democratic theory and social psychology, this book argues that extensive opportunities for direct participation in the political process engenders in citizens strong feelings of efficacy - a sense of control over the course of politics. Rhodes-Purdy uses a mixed-methods approach to test this theory, including qualitative case studies, analysis of survey data, and experimental methods.

This book challenges the conventional wisdom that policy performance is the most important determinant of regime support. It does so by focusing on two countries where performance and support do not match. Chile is the economic envy of every country in Latin America, yet support has been surprisingly anemic. By contrast, Venezuela managed to maintain extremely high levels of support during the reign of Hugo Chávez despite severe failures of governance. Resolution of these paradoxes requires turning away from policy decisions and focusing instead on how those decisions are made. Taking inspiration from democratic theory and social psychology, this book argues that extensive opportunities for direct participation in the political process engenders in citizens strong feelings of efficacy - a sense of control over the course of politics. Rhodes-Purdy uses a mixed-methods approach to test this theory, including qualitative case studies, analysis of survey data, and experimental methods.