For Masters and PhD students in EconomicsIn this textbook, the duality between the equilibrium concept used in dynamic economic theory and the stationarity of economic variables is explained and used in the presentation of single equations models and system of equations such as VARs, recursive models and simultaneous equations models.The book also contains chapters on: exogeneity, in the context of estimation, policy analysis and forecasting; automatic (computer based) variable selection, and how it can aid in the specification of an empirical macroeconomic model; and finally, on a common framework for model-based economic forecasting.Supplementary materials and notes are available on the publisher's website.
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.
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.
At a level suitable for graduate or advanced undergraduates in economics, explains the principles of constructing dynamic macroeconometric models and their use in economic analyses and forecasting. The econometric methodology described is limited to specific applications of time series analysis. The treatment is updated from the 1983 Lectures in Econometrics to account for the end of the Cold War, which raises questions of economic transition in eastern Europe, and the emergence of information technology that has qualitatively changed the speed and breadth of data flows. Annotation copyrighted by Book News, Inc., Portland, OR
'An excellent reference volume of this author's work, bringing together articles published over a 25 year span on the statistical analysis of economic time series, large scale macroeconomic modelling and the interface between them.' - Aslib Book Guide This major volume of essays by Kenneth F. Wallis features 28 articles published over a quarter of a century on the statistical analysis of economic time series, large-scale macroeconometric modelling, and the interface between them. The first part deals with time-series econometrics and includes significant early contributions to the development of the LSE tradition in time-series econometrics, which is the dominant British tradition and has considerable influence worldwide. Later sections discuss theoretical and practical issues in modelling seasonality and forecasting with applications in both large-scale and small-scale models. The final section summarizes the research programme of the ESRC Macroeconomic Modelling Bureau, a unique comparison project among economy-wide macroeconometric models.
The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series. It examines alternative methodological approaches and concepts, including quantile spectra and co-spectra, and explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore, it demonstrates the application of recent techniques in various fields: in the frequency domain, in the analysis of persistent dynamics, in the estimation of state space models and new classes of volatility models. The book is divided into two parts: The first part applies econometrics to the field of macroeconomics, discussing trend/cycle decomposition, growth analysis, monetary policy and international trade. The second part applies econometrics to a wide range of topics in financial economics, including price dynamics in equity, commodity and foreign exchange markets and portfolio analysis. The book is essential reading for scholars, students, and practitioners in government and financial institutions interested in applying recent econometric time series methods to financial and economic data.
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 main purpose of this monograph is to give a detailed account of a contemporary, state-of-the art, macroeconometric model that is regularly used for policy advising, and for forecasting in commerce and industry.
The revised edition of the essential resource on macroeconometrics Structural Macroeconometrics provides a thorough overview and in-depth exploration of methodologies, models, and techniques used to analyze forces shaping national economies. In this thoroughly revised second edition, David DeJong and Chetan Dave emphasize time series econometrics and unite theoretical and empirical research, while taking into account important new advances in the field. The authors detail strategies for solving dynamic structural models and present the full range of methods for characterizing and evaluating empirical implications, including calibration exercises, method-of-moment procedures, and likelihood-based procedures, both classical and Bayesian. The authors look at recent strides that have been made to enhance numerical efficiency, consider the expanded applicability of dynamic factor models, and examine the use of alternative assumptions involving learning and rational inattention on the part of decision makers. The treatment of methodologies for obtaining nonlinear model representations has been expanded, and linear and nonlinear model representations are integrated throughout the text. The book offers a rich array of implementation algorithms, sample empirical applications, and supporting computer code. Structural Macroeconometrics is the ideal textbook for graduate students seeking an introduction to macroeconomics and econometrics, and for advanced students pursuing applied research in macroeconomics. The book's historical perspective, along with its broad presentation of alternative methodologies, makes it an indispensable resource for academics and professionals.
This volume of Advances in Econometrics contains articles that examine key topics in the modeling and estimation of dynamic stochastic general equilibrium (DSGE) models. Because DSGE models combine micro- and macroeconomic theory with formal econometric modeling and inference, over the past decade they have become an established framework for analy
