Macro Econometric Models

This book gives a practical, applications-oriented account of the latest techniques for estimating and analyzing large, nonlinear macroeconomic models. Ray Fair demonstrates the application of these techniques in a detailed presentation of several actual models, including his United States model, his multicountry model, Sargent's classical macroeconomic model, autoregressive and vector autoregressive models, and a small (twelve equation) linear structural model. He devotes a good deal of attention to the difficult and often neglected problem of moving from theoretical to econometric models. In addition, he provides an extensive discussion of optimal control techniques and methods for estimating and analyzing rational expectations models. A computer program that handles all the techniques in the book is available from the author, making it possible to use the techniques with little additional programming. The book presents the logic of this program. A smaller program for personal microcomputers for analysis of Fair's United States model is available from Urban Systems Research & Engineering, Inc. Anyone wanting to learn how to use large macroeconomic models, including researchers, graduate students, economic forecasters, and people in business and government both in the United States and abroad, will find this an essential guidebook.

This is the second edition, essentially a completely newly written state of the art introduction into the field of macro-econometric models. Its first focus is to present the different specifications and strands of ideas of macro-econometric models, its empirical and analytical uses in economic policy, economic theory, economic history and empirical applications. It documents the intellectual achievements and performance of applied macroeconomic models in general, theoretically and by typical and representative illustrations, leading the reader to the frontiers of present research. Secondly, the book is an introductory text into the bibliography of macro models, which is the background of the monograph. Recalling the field of macro-econometric models, there are additional appendices, e.g. explaining the keywords which cover this territory of economic knowledge, and documenting the huge use of such models. A multilingual cross-reference dictionary (German, English, French, Spanish, Italian) concludes the book.

‘Macroeconometric Models for Portfolio Management’ begins by outlining a portfolio management framework into which macroeconometric models and backtesting investment strategies are integrated. It is followed by a discussion on the theoretical backgrounds of both small and global large macroeconometric models, including data selection, estimation, and applications. Other practical concerns essential to managing a portfolio with decisions driven by macro models are also covered: model validation, forecast combination, and evaluation. The author then focuses on applying these models and their results on managing the portfolio, including making trading rules and asset allocation across different assets and risk management. The book finishes by showing portfolio examples where different investment strategies are used and illustrate how the framework can be applied from the beginning of collecting data, model estimation, and generating forecasts to how to manage portfolios accordingly. This book aims to bridge the gap between academia and practising professionals. Readers will attain a rigorous understanding of the theory and how to apply these models to their portfolios. Therefore, ‘Macroeconometric Models for Portfolio Management’ will be of interest to academics and scholars working in macroeconomics and finance; to industry professionals working in financial economics and asset management; to asset managers and investors who prefer systematic investing over discretionary investing; and to investors who have a strong interest in macroeconomic influences on their portfolio.

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.

'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.

Maria-Carmen Guisan, professor of Econometrics, University of Santiago de Compostela, Spain sets out in the footsteps of economists like Nobel Prize Laureate L R Klein, who pioneered macro-econometric modeling. Included are articles of eminent experts wh

This major book presents, for the first time, an authoritative history of developments in macroeconometric modelling since the 1930s. It focuses in particular on the construction of mathematico-statistical models of entire economies, estimated from national accounts and other macroeconomic data. International and comparative in scope, the book contains chapters prepared by specialists from the different countries concerned. This landmark book is indispensable to an understanding of the history and development of large scale econometric models of modern economies.

Observers and Macroeconomic Systems is concerned with the computational aspects of using a control-theoretic approach to the analysis of dynamic macroeconomic systems. The focus is on using a separate model for the development of the control policies. In particular, it uses the observer-based approach whereby the separate model learns to behave in a similar manner to the economic system through output-injections. The book shows how this approach can be used to learn the forward-looking behaviour of economic actors which is a distinguishing feature of dynamic macroeconomic models. It also shows how it can be used in conjunction with low-order models to undertake policy analysis with a large practical econometric model. This overcomes some of the computational problems arising from using just the large econometric models to compute optimal policy trajectories. The work also develops visual simulation software tools that can be used for policy analysis with dynamic macroeconomic systems.