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The development of the endogenous growth model rekindled interest in growth theory. In contrast to the neo-classical model, long-run endogenous growth emerged as an equilibrium outcome, reflecting the behaviour of optimizing agents in the economy. This book brings together a number of contributions in growth theory and macroeconomic dynamics, reflecting these developments and the ongoing debate over the relative merits of neo-classical and endogenous growth models. It focuses on the emergence of three important aspects: First, it develops growth models that extend the underlying theory in different directions. Second, it addresses one of the concerns of the literature on growth and dynamics: the statistical properties of underlying data and the effort to ensure that growth models are consistent with empirical evidence. Third, it discusses the increasingly international focus of macrodynamics and growth theory, an inevitable consequence of the integration of the world economy.
V. 1. An introduction to dynamical systems and market mechanisms -- v. 2. An introduction to macroeconomics dynamics.
An attempt to revitalize the traditions of nonmarket clearing approaches to macroeconomics. Using tools from dynamic analysis, the text introduces a consistent, integrated framework for disequilibrium macroeconomic dynamics and explore its relationship to the competing equilibrium dynamics.
An advanced treatment of modern macroeconomics, presented through a sequence of dynamic equilibrium models, with discussion of the implications for monetary and fiscal policy. This textbook offers an advanced treatment of modern macroeconomics, presented through a sequence of dynamic general equilibrium models based on intertemporal optimization on the part of economic agents. The book treats macroeconomics as applied and policy-oriented general equilibrium analysis, examining a number of models, each of which is suitable for investigating specific issues but may be unsuitable for others. After presenting a brief survey of the evolution of macroeconomics and the key facts about long-run economic growth and aggregate fluctuations, the book introduces the main elements of the intertemporal approach through a series of two-period competitive general equilibrium models—the simplest possible intertemporal models. This sets the stage for the remainder of the book, which presents models of economic growth, aggregate fluctuations, and monetary and fiscal policy. The text focuses on a full analysis of a limited number of key intertemporal models, which are stripped down to essentials so that students can focus on the dynamic properties of the models. Exercises encourage students to try their hands at solving versions of the dynamic models that define modern macroeconomics. Appendixes review the main mathematical techniques needed to analyze optimizing dynamic macroeconomic models. The book is suitable for advanced undergraduate and graduate students who have some knowledge of economic theory and mathematics for economists.
Just as macroeconomic models describe the overall economy within a changing, or dynamic, framework, the models themselves change over time. In this text Stephen J. Turnovsky reviews in depth several early models as well as a representation of more recent models. They include traditional (backward-looking) models, linear rational expectations (future-looking) models, intertemporal optimization models, endogenous growth models, and continuous time stochastic models. The author uses examples from both closed and open economies. Whereas others commonly introduce models in a closed context, tacking on a brief discussion of the model in an open economy, Turnovsky integrates the two perspectives throughout to reflect the increasingly international outlook of the field. This new edition has been extensively revised. It contains a new chapter on optimal monetary and fiscal policy, and the coverage of growth theory has been expanded substantially. The range of growth models considered has been extended, with particular attention devoted to transitional dynamics and nonscale growth. The book includes cutting-edge research and unpublished data, including much of the author's own work.
This book provides an in-depth treatment of the overlapping generations model in economics incorporating production.
The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.
Macroeconomic policy is one of the most important policy domains, and the tools of macroeconomics are among the most valuable for policy makers. Yet there has been, up to now, a wide gulf between the level at which macroeconomics is taught at the undergraduate level and the level at which it is practiced. At the same time, doctoral-level textbooks are usually not targeted at a policy audience, making advanced macroeconomics less accessible to current and aspiring practitioners. This book, born out of the Masters course the authors taught for many years at the Harvard Kennedy School, fills this gap. It introduces the tools of dynamic optimization in the context of economic growth, and then applies them to a wide range of policy questions – ranging from pensions, consumption, investment and finance, to the most recent developments in fiscal and monetary policy. It does so with the requisite rigor, but also with a light touch, and an unyielding focus on their application to policy-making, as befits the authors’ own practical experience. Advanced Macroeconomics: An Easy Guide is bound to become a great resource for graduate and advanced undergraduate students, and practitioners alike.
Over the past two decades, the issue of equilibrium indeterminacy has been one of the major research concerns in macroeconomic dynamics. Growth and Business Cycles with Equilibrium Indeterminacy discusses the main topics in this literature. Based on comprehensive surveys and the author’s original research, this book explores sunspot-driven fluctuations in real business cycle models, multiple equilibria in endogenous growth models, and the stabilization effects of fiscal and monetary policy rules. The book also considers equilibrium indeterminacy in open economy models.
The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems. This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field. New for the second edition: “Programming-language agnostic” presentation using pseudocode. New chapter 1 covering conceptual issues concerning Markov chains such as ergodicity and stability. New focus in chapter 2 on algorithms and techniques for program design and high-performance computing. New focus on household problems rather than optimal growth in material on dynamic programming. Solutions to many exercises, code, and other resources available on a supplementary website.