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.
The last twenty years have witnessed tremendous advances in the mathematical, statistical, and computational tools available to applied macroeconomists. This rapidly evolving field has redefined how researchers test models and validate theories. Yet until now there has been no textbook that unites the latest methods and bridges the divide between theoretical and applied work. Fabio Canova brings together dynamic equilibrium theory, data analysis, and advanced econometric and computational methods to provide the first comprehensive set of techniques for use by academic economists as well as professional macroeconomists in banking and finance, industry, and government. This graduate-level textbook is for readers knowledgeable in modern macroeconomic theory, econometrics, and computational programming using RATS, MATLAB, or Gauss. Inevitably a modern treatment of such a complex topic requires a quantitative perspective, a solid dynamic theory background, and the development of empirical and numerical methods--which is where Canova's book differs from typical graduate textbooks in macroeconomics and econometrics. Rather than list a series of estimators and their properties, Canova starts from a class of DSGE models, finds an approximate linear representation for the decision rules, and describes methods needed to estimate their parameters, examining their fit to the data. The book is complete with numerous examples and exercises. Today's economic analysts need a strong foundation in both theory and application. Methods for Applied Macroeconomic Research offers the essential tools for the next generation of macroeconomists.
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 presents an introduction to computational macroeconomics, using a new approach to the study of dynamic macroeconomic models. It solves a variety of models in discrete time numerically, using a Microsoft Excel spreadsheet as a computer tool. The solved models include dynamic macroeconomic models with rational expectations, both non-microfounded and microfounded, constituting a novel approach that facilitates the learning and use of dynamic general equilibrium models, which have now become the principal tool for macroeconomic analysis. Spreadsheets are widely known and relatively easy to use, meaning that the computer skills needed to work with dynamic general equilibrium models are affordable for undergraduate students in Advanced Macroeconomics courses.
This work describes how the discipline has adapted to changing demands by adopting new insights from economic theory and by taking advantage of the methodological and conceptual advances within time series econometrics.
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
The recent financial crisis and the difficulty of using mainstream macroeconomic models to accurately monitor and assess systemic risk have stimulated new analyses of how we measure economic activity and the development of more sophisticated models in which the financial sector plays a greater role. Markus Brunnermeier and Arvind Krishnamurthy have assembled contributions from leading academic researchers, central bankers, and other financial-market experts to explore the possibilities for advancing macroeconomic modeling in order to achieve more accurate economic measurement. Essays in this volume focus on the development of models capable of highlighting the vulnerabilities that leave the economy susceptible to adverse feedback loops and liquidity spirals. While these types of vulnerabilities have often been identified, they have not been consistently measured. In a financial world of increasing complexity and uncertainty, this volume is an invaluable resource for policymakers working to improve current measurement systems and for academics concerned with conceptualizing effective measurement.
Introduction to Agent-Based Economics describes the principal elements of agent-based computational economics (ACE). It illustrates ACE's theoretical foundations, which are rooted in the application of the concept of complexity to the social sciences, and it depicts its growth and development from a non-linear out-of-equilibrium approach to a state-of-the-art agent-based macroeconomics. The book helps readers gain a better understanding of the limits and perspectives of the ACE models and their capacity to reproduce economic phenomena and empirical patterns. - Reviews the literature of agent-based computational economics - Analyzes approaches to agents' expectations - Covers one of the few large macroeconomic agent-based models, the Modellaccio - Illustrates both analytical and computational methodologies for producing tractable solutions of macro ACE models - Describes diffusion and amplification mechanisms - Depicts macroeconomic experiments related to ACE implementations