Time Series And Dynamic Models (themes In Modern Econometrics)

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Concisely written and up-to-date, this book provides a unified and comprehensive analysis of the full range of topics that comprise modern time series econometrics. While it does demand a good quantitative grounding, it does not require a high mathematical rigor or a deep knowledge of economics. One of the book's most attractive features is the close attention it pays throughout to economic models and phenomena. The authors provide a sound analysis of the statistical origins of topics such as seasonal adjustment, causality, exogeneity, cointegration, prediction, and forecasting. Their treatment of Box-Jenkins models and the Kalman filter represents a synthesis of the most recent theoretical and applied work in these areas.

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In this book Christian Gourieroux and Alain Monfort provide an up-to-date and comprehensive analysis of modern time series econometrics. They have succeeded in synthesising in an organised and integrated way a broad and diverse literature. While the book does not assume a deep knowledge of economics, one of its most attractive features is the close attention it pays to economic models and phenomena throughout. The coverage represents a major reference tool for graduate students, researchers and applied economists. Section one, Traditional methods, provides a detailed treatment of classical seasonal adjustment or smoothing methods, giving a central role to empirical analysis, a subject which is often ignored in textbooks. Section two, Probabilistic and statistical properties of stationary processes, gives a thorough coverage of various mathematical tools (in particular Box-Jenkins methodology). Section three, Times series econometrics: stationary and nonstationary models, is the heart of the book. It is devoted to a range of important topics including causality, exogeneity shocks, multipliers, lag structure, structural forms, error correction models, cointegration, and fractionally integrated models. The final section, State space models, describes the main contribution of filtering and smoothing theory to time series econometric problems. Time Series and Dynamic Models Themes in Modern Econometrics PETER Managing editors C.B. PHILLIPS, Yale University and ADRIAN PAGAN, Australian National University Advisory editors GOURIEROUX, CREST and CEPREMAP, MICHAEL WICKENS, University of York CHRISTIAN Paris Themes in Modern Econometrics is designed to service the large and growing need for explicit teaching tools in econometrics. It will provide an organised sequence of textbooks in econometrics aimed squarely at the student population, and will be the first series in the discipline to have this as its express aim. Written at a level accessible to students with an introductory course in econometrics behind them, each book will address topics or themes that students and researchers encounter daily. While each book will be designed to stand alone as an authoritative survey in its own right, the distinct emphasis throughout will be on pedagogic excellence. Titles in the series Statistics and Econometric Models: Volume One CHRISTIAN GOURIEROUX a n d ALAIN MONFORT Translated by QUANG VUONG Statistics and Econometric Models: Volume Two CHRISTIAN GOURIEROUX a n d ALAIN MONFORT Translated by QUANG VUONG Time Series and Dynamic Models CHRISTIAN GOURIEROUX a n d ALAIN MONFORT Translated and edited by GIAMPIERO M. GALLO Time Series and Dynamic Models Christian Gourieroux CREST and CEPREMAP, Paris Alain Monfort CREST-INSEE, Paris Translated and edited by Giampiero M. Gallo CAMBRIDGE UNIVERSITY PRESS PUBLISHED BY THE PRESS SYNDICATE OF THE UNIVERSITY OF CAMBRIDGE The Pitt Building, Trumpington Street, Cambridge CB2 1RP, United Kingdom CAMBRIDGE UNIVERSITY PRESS The Edi
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