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Time Series Models for Business and Economic Forecasting (Themes in Modern Econometrics) [Paperback]

Philip Hans Franses

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Book Description

15 Oct 1998 Themes in Modern Econometrics
The econometric analysis of economic and business time series is a major field of research and application. The last few decades have witnessed an increasing interest in both theoretical and empirical developments in constructing time series models and in their important application in forecasting. In Time Series Models for Business and Economic Forecasting, Philip Franses examines recent developments in time series analysis. The early parts of the book focus on the typical features of time series data in business and economics. Part III is concerned with the discussion of some important concepts in time series analysis, the discussion focuses on the techniques which can be readily applied in practice. Parts IV-VIII suggest different modeling methods and model structures. Part IX extends the concepts in chapter three to multivariate time series. Part X examines common aspects across time series.

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'Franses reviews the more recent developments in modeling time series to focus on generating ex ante forecasts: seasonal unit roots, period models, aberrant observations, and common features. For each method, intuitive motivation and practical considerations are discussed in detail, making the book very readable … should be beneficial for students and instructors of applications-oriented courses as well as for practitioners who wish to obtain a first, but not too technical, impression of time series forecasting using modern , recently developed methods.' Journal of the American Statistical Association

Book Description

This textbook on empirical time series analysis in economics and business synthesizes recent developments, and focuses on the practical implementation in out-of-sample forecasting. Written by one of Europe's leading econometricians, and based around a highly successful lecture programme, it is the most up-to-date book on this subject.

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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Amazon.com: 4.5 out of 5 stars  6 reviews
44 of 44 people found the following review helpful
5.0 out of 5 stars Excellent introductory book on economic time series modeling 10 April 2000
By A Customer - Published on Amazon.com
Format:Paperback
Recently, I reread Franses book and expanded my review, which now includes 10 benefits.
(1) Organization by key features of economic time series (trends, seasonality, outliers, conditional heteroskedasticity, non-linearity), rather than by methods, which provides a practical foundation for the various methodologies. The order in which chapters are presented reflects the order of difficulty in modeling trends, seasonality, etc. Even if there were no other benefits, this organization makes it worthwhile.
(2) Appropriate level for first book on time series models as applied to economic time series, explaining more difficult concepts GARCH and VAR without excess detail. Box and Jenksins book is more a textbook; Brockwell and Davis is also more advanced; Hamilton is comprehensive and technical, but not as friendly. This book is very approachable even if you have had only 1 or 2 statistics courses. In economics, many people are interested in forecasting, and Franeses here is a good start. If you are looking for a more advanced forecasting book, try the recent books by Clements and Hendry from Cambridge U Press.
(3) Clear distinction of the steps of model identification, estimation, diagnostics, and selection; something which other time series analysis books do not seem to do early or easily. (4) Delineates stochastic and deterministic models in the second chapter, providing a framework for when to take differences (eg. ARMA vs ARIMA). His timing is excellent. Many people I have interviewed on time series do not understand why they need to difference (eg use prices instead of returns) or why to transform the series (eg use logs instead of actual values).
(5) Generous use of examples with real not simulated data with a website to download all the data, making it possible to import, graph, and analyze on your own.
(6) A website containing printing corrections. Techincal books are likely to have some errors, but very few keep websites to list what those are.
(7) Revealing graphics, especially for conditional heteroskedasticity, the 'CH' in GARCH. Figures 7.1-7.3 illustrate the concept that large returns tend to follow large returns very cleanly.
(8) His notation is clear and consistent, yet not overwhelming: conventional Greek letters, only 1 level of subscripting, matrix noation where appropriate; even the results are neatly presented, as standard errors appear in () below their point estimates. Finally, Franses uses the same notation from chapter to chapter where the term is the same--not so common when chapters written by different authors.
(9) Great appendices: extensive and updated references, a thorough subject index, and an author index. My only suggestion for improvement is that a second edition or the website should contain some exercises. Highly recommended.
(10) The price! There are books published under Wiley at 3 to 4 times the price! under Springer Verlag for 2 to 3 times the price. Certain books are worth the money, but Cambridge University Press paperback publications, when written well, are exeptional values. I encourage the ambitious time series student to look at other time series books, including one written this year by Franses including Quantitative Models in Market Research.
24 of 25 people found the following review helpful
4.0 out of 5 stars time series for business 9 Feb 2008
By Michael R. Chernick - Published on Amazon.com
Format:Paperback
To make this review short, I will say that I agree with all seven points made by the reviewer from New York, NY, whomever he or she may be. Franses is clear, concise, authoritative and up-to-date on all the advances.
I particularly like the nice coverage of GARCH models that are new to me. It is a great introductory text especially for economics majors. For more advanced books and other treatments of time series consider Kennedy's fourth edition of "A Guide to Econometrics" or the suggestion from reviewer "New York, NY". Also my listmania list on time series will give you several sources to look at.
21 of 22 people found the following review helpful
5.0 out of 5 stars This book is exceptional 21 Nov 1999
By A Customer - Published on Amazon.com
Format:Hardcover
The beauty of this text is it's clarity and the author's choice to stay away from didactic lectures on formal statistical mathematics. I would highly recommend this book for anyone who has an undergraduate background in mathematics, statistics or economics and wants a medium level text to show them how to model time series.
11 of 15 people found the following review helpful
5.0 out of 5 stars Excellent introduction into time series 10 April 2000
By A Customer - Published on Amazon.com
Format:Paperback
This book is a brilliant introduction into time series analysis. I found it a great basis for further analysis, allowing to go into deep with, for example, J.D. Hamilton's classical work. The book has a very well-defined structure, which (in my opinion) serves both auto-didact and (under)graduate teaching. Check out the author's web-page at Erasmus University Rotterdam for a list with corrections of some typos and the data sets used.
4 of 5 people found the following review helpful
5.0 out of 5 stars Good introductory book ! 2 Feb 2003
By A Customer - Published on Amazon.com
Format:Paperback
Full of real-life examples that provide some intuitive insight about the issues that may arise when modelling time series and forecasting. Requires some initial knowledge in statistics and algebra but if you're involved in time series modelling, it should be your first book. All the data thats used is available in the authors webbsite for downloading, very nice.
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