Table Of ContentFrancis X. Diebald
University of Pennsylvania
THOM* SON
SOUTH-WESTERN
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THOM* SON
SOUTH-WESTERN
Elements of Forecasting, Fourth Edition
Francis X. Diebold
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THE LIBRARY
UNIVERSITY OF GUELPrf
To Lawrence Klein, Marc Nerlove, and Peter Pauly,
who taught me forecasting.
Most good texts arise from the desire to leave one's stamp on a discipline by
training future generations of students, coupled with the recognition that ex
isting texts are inadequate in various respects. My motivation is no different.
There is a real need for a concise and modern introductory forecasting text.
A number of features distinguish this book. First, although it uses only ele
mentary mathematics, it conveys a strong feel for the important advances
made since the work of Box and Jenkins more than 30 years ago. In addition
to standard models of trend, seasonality, and cycles, it touches—sometimes
extensively—upon topics such as
• data mining and in-sample overfitting
• statistical graphics and exploratory data analysis
• model selection criteria
• recursive techniques for diagnosing structural change
• nonlinear models, including neural networks
• regime-switching models
• unit roots and stochastic trends
• smoothing techniques in their relation to stochastic-trend unobserved-
components models
• vector autoregressions
• cointegration and error correction
• predictive causality
• forecast evaluation and combination
• simulation and simulation-based methods
• volatility measurement, modeling, and forecasting
Preface v
Much of that material appears in the "Exercises, Problems, and Comple
ments" following each chapter, which form an integral part of the book.
The Exercises, Problems, and Complements are organized so that instruc
tors and students can pick and choose according to their backgrounds and
interests.
Second, the book does not attempt to be exhaustive in coverage. In fact,
the coverage is intentionally selective, focusing on the core techniques
with the widest applicability'. The book is designed so that it can be covered re
alistically in a one-semester course. Core material appears in the main text,
and additional material that expands on the depth and breadth of coverage is
provided in the Exercises, Problems, and Complements, as well as the Biblio
graphical and Computational Notes, at the end of each chapter.
Third, the book is applications-oriented. It illustrates all methods with de
tailed real-world applications designed to mimic typical forecasting situations.
In many chapters, the application is the centerpiece of the presentation. In
various places, the book uses applications not simply to illustrate the methods
but also to drive home an important lesson, the limitations of forecasting, by
presenting truly realistic examples in which not everything works perfectly!
Fourth, the book is in touch with modern modeling and forecasting
software. It uses Eviews, which is a good modern computing environment for
forecasting, throughout. At the same time, I am not a software salesman, so
the discussion is not wed to any particular software. Students and instructors
can use whatever computing environment they like best.
The book has found wide use among students in a variety of fields, includ
ing business, finance, economics, public policy, statistics, and even engineer
ing. The book is directly accessible at the undergraduate and master's levels;
the only prerequisite is an introductory statistics course that includes linear re
gression. To help refresh smdents' memories, Chapter 2 reviews linear regres
sion from a forecasting perspective. The book is also of interest to those with
more advanced preparation, because of the hard-to-find direct focus on fore
casting (as opposed, for example, to general statistics, econometrics, or time
series analysis). I have used it successfully for many years as the primary text in
my undergraduate forecasting course, as a background text for various other
undergraduate and graduate courses, and as the primary text for master V
level Executive Education courses given to professionals in business, finance,
economics, and government.
SUPPLEMENTS
Data Sets and Eviews Programs
Selected data and Eviews programs, as used both in the text chapters and in
the Exercises, Problems, and Complements at the end of each chapter, are
available on the text Web site at www.thomsonedu.com/economics/diebold.
Preface
Text Web Site
The text Web site at www.thomsonedu.com/economics diebold provides
teaching resources, including the solutions manual for instructors; learning
resources, including data sets and Eviews programs; and many more features.
Solutions Manual
Prepared by Francis Diebold, University of Pennsylvania, the solutions manual
contains remarks, suggestions, hints, and solutions for many of the end-of-
chapter exercises, problems, and complements. It is available on the text
Web site and may be downloaded for use by adopting instructors.
Eviews Software
Upon the instructor's request, Eviews Student Version can be bundled with
the text. With Eviews, students can do homework anywhere they have access
to a PC. For more information on this special Eviews offer, contact your
Thomson South-Western representative or call the Academic Resource Center
at 1-800-423-0563.
Economic Applications
Economic Applications includes South-Western's dynamic Web features:
EronNews, EconDebate, and EconData Online. Organized by pertinent eco
nomic topics and searchable by topic or feature, these features are easy to
integrate into the classroom. EconNews, EconDebate, and EconData all
deepen students' understanding of theoretical concepts through hands-on ex
ploration and analvsis for the latest economic news stories, policy debates, and
data. These features are updated on a regular basis. For more information,
visit wwwthomsonedu.com.
InfoTrac
With InfoTrac College Edition, students can receive anytime, anywhere online
access to a database of full-text articles from thousands of popular and schol
arly periodicals, such as Xeivsnwk, Fortune, and Nation's Business, among others.
InfoTrac is a great wax to expose students to online research techniques, with
the securitv that the content is academically based and reliable. For more in
formation, xisit www.ihomsonedu.com.
You can start using manv of these resources right away by following the di
rections on the access card that came with the purchase of a new book. Get
started today at www.thomsonedu.com!
Preface vii
ACKNOWLEDGEMENTS
Many people have contributed to the development of this book—some
explicitly, some without knowing it. One way or another, all of the following
deserve thanks:
Joan B. Anderon Robert F. Engle
University of Sun Diego University of California, San Diego
Scott Armstrong Farzad Farsio
I!n wersity of Pen nsytvan in Montana State University, Billings
Alan Auerbach Robert Fildes
University of California. Berkeley University of Lancaster
David Bivin Jessica Gamburg
Indiana University-Purdue University at Heitman
Indianapolis
Antonio Garcia-Ferrer
Gregory A. Charles Universidad Autonoma de Madrid
Oregon Health Csf Science University Patrick A. Gaughan
Chris Chatfield Farleigh-Dickenson University
University of Bath Give Granger
Jen-Chi Cheng University of California, San Diego
Wichita State University Craig Hakkio
Sidhartha Chib Federal Reserve Bank of Kansas City
Washington University in St. Louis Eric Hillebrand
Peter Christoffersen Louisiana State University
McGilf Lhi wersity Eric C. Howe
Jorg Clostei mann Un iversity of Saskatcheiua n
Unix>ersity of Applied Sciences, Der An Hsu
Fachhochsch it le Ingolsladt University of Wisconsin, Milwaukee
Dean Croushore Lawrence R. Klein
Federal Reserve Bank of Philadelphia University of Pen nsylvania
Robert A. Dickler James Kozik
IMADKC University SPSS, Inc.
Tom Doan Junsoo Lee
Estima University of Alabama
Michael Donihue Tae-Hwy Lee
Colby College University of California, Riverside
Jean-Marie DuFour David Lilien
University of Montreal Unwersity of California, Irvine
Jeffrey Edwards Jose Lopez
Texas Tech University Federal Reserve Bank of New York
Preface
Ron Michener James H. Stork
University of Virginia Harvard University
Ray Nelson Mark Strazicich
Brigham Young University University of Central Florida
Caitlin O'Neil Norman Swan son
Goldman, Saclis & Co. Texas AcrM i Diversity
Llad Phillips Hirokuni Tamura
University of California, Santa Barbara University of Washington
W. Robert Reed George Tavlas
University of Oklahoma Bank of Greece
Russell Robins Hiroki Tsurumi
Tulane University Rutgers University
Philip Rothman William Veloce
East Carolina University Brock University
Glenn D. Rudebusch
Mark W. Watson
Federal Reserve Bank of San Francisco Pn n ceton 17n n >eisity
Robert Rycroft
Barry Wreller
Mary Washington College
Penn State University, Erie
Richard Saba
Kennedi D. West
Auburn University
University of Wisconsin
John H. Shannon
Koichi Yoshimine
Royal Melbourne Institute of Technology University of British Columbia
Steven Shwiff Toshiyuki Yuasa
Texas A&M University-Commerce University of Houston
Gokce Soydemir
Tao Zha
University of Texas, PanAmerican
Federal Reserve Bank of Atlanta
Robert Stine
University of Pennsylvania
I am especially grateful to all members of the Thomson South-Western team,
past and present, including Elycia Arendt, Jennifer Baker, Jack Calhoun,
Jennifer Garamv, Dennis Hanseman, Leslie Kauffman, and Michael Worls,
without whose encouragement and guidance this book would not have been
written. I am similarly grateful to the many energetic undergraduate and grad
uate student assistants that I have had over the vears, who read and improved
much of the manuscript, including Boragan Aruoba, Adam Buresh, Morris
Davis, Atsushi Inoue, John Schindler, Eric Schwartz, Chiara Scotti, Georg
Strasser, Anthony Tay, Karen Toll, and Ginger Wu.
Finally. I apologize and accept full responsibility for the many errors and
shortcomings that undoubtedly remain—minor and major—despite ongoing
efforts to eliminate them.
The fourth edition maintains the emphasis of earlier editions on providing an
intuitive building-block approach to the development of modern and practi
cal methods for producing, evaluating, and combining forecasts. Within that
framework, several improvements have been implemented, including
1. Enhanced and extended discussion of the elements of probability and sta
tistics of maximal relevance to forecasting, now included as a separate
Chapter 2,
2. Many new exercises, problems, and complements, which emphasize practi
cal implementation of the methods developed in the text, including sim
ple drills to check understanding,
3. Selectively reworked and/or rearranged material, to maximize clarity and
pedagogical effectiveness.
Throughout, my intent has been to insert and delete where needed, sparingly,
avoiding the temptation to fix parts "that ain't broke." Hopefully I have moved
forward.
F.X.D
August 2006
ix
