Methods Of Macroeconomic Dynamics

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 The book includes cutting-edge research and unpublished data, including much of the author's own work.

International Macroeconomic Dynamics provides extensive applications of important macroeconomic dynamic models to the international economy. For a long time, the study of macroeconomics has focused almost exclusively on a closed economy and downplayed the role of international transactions. Today, however, researchers recognize that one cannot fully understand domestic macroeconomic relationships without considering the global economy within which each country operates. Increasingly, economists are treating international transactions as an integral part of the macroeconomic system, and international macroeconomics has become an area of intensive research activity. International Macroeconomic Dynamics provides extensive applications of important macroeconomic dynamic models to the international economy. It adopts the main contemporary macroeconomic framework, the representative agent model, and develops a series of models of increasing complexity. The author considers both small and large economies and analyzes them in both deterministic and stochastic contexts. The emphasis is very much on the development of the analytical models; a novel feature is the extensive use of continuous-time stochastic methods. While the author applies the models to a range of important policy issues, particularly issues of fiscal policy, the reader is invited to view the analyses as blueprints for other applications.

This rigorous but brilliantly lucid book presents a self-contained treatment of modern economic dynamics. Stokey, Lucas, and Prescott develop the basic methods of recursive analysis and illustrate the many areas where they can usefully be applied.

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.

The tasks of macroeconomics are to interpret observations on economic aggregates in terms of the motivations and constraints of economic agents and to predict the consequences of alternative hypothetical ways of administering government economic policy. General equilibrium models form a convenient context for analyzing such alternative government policies. In the past ten years, the strengths of general equilibrium models and the corresponding deficiencies of Keynesian and monetarist models of the 1960s have induced macroeconomists to begin applying general equilibrium models. This book describes some general equilibrium models that are dynamic, that have been built to help interpret time-series of observations of economic aggregates and to predict the consequences of alternative government interventions. The first part of the book describes dynamic programming, search theory, and real dynamic capital pricing models. Among the applications are stochastic optimal growth models, matching models, arbitrage pricing theories, and theories of interest rates, stock prices, and options. The remaining parts of the book are devoted to issues in monetary theory; currency-in-utility-function models, cash-in-advance models, Townsend turnpike models, and overlapping generations models are all used to study a set of common issues. By putting these models to work on concrete problems in exercises offered throughout the text, Sargent provides insights into the strengths and weaknesses of these models of money. An appendix on functional analysis shows the unity that underlies the mathematics used in disparate areas of rational expectations economics. This book on dynamic equilibrium macroeconomics is suitable for graduate-level courses; a companion book, Exercises in Dynamic Macroeconomic Theory, provides answers to the exercises and is also available from Harvard University Press.

This workbook accompanies the second edition of Stephen Turnovsky's Methods of Macroeconomic Dynamics. This workbook accompanies the second edition of Stephen Turnovsky's Methods of Macroeconomic Dynamics. New problems have been added to most of the chapters, particularly those that are new to the second edition of the book. In general, those exercises near the beginning of the book and the first few exercises of each chapter are the easiest to solve.

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.

A significant new edition of a text that offers both tools and sample applications; extensive revisions and seven new chapters improve and expand upon the original treatment.