Elements of Forecasting with Economic Applications Card and InfoTrac College Edition

by DIEBOLD

• ISBN13: 9780324163827
• ISBN10: 0324163827
• Additional ISBN(s): 9780324359046
• Edition: 3rd
• Format: Paperback
• Copyright: 2003-09-19
• Publisher: South-Western College Pub
• More Book Details
• Purchase Benefits

Summary

Written by a leading expert on forecasting, this concise, modern survey of business and economic forecasting methods is intentionally selective and focuses only on the core techniques with the widest applicability. Assuming readers have a limited background in statistics, the book is extremely applications oriented and illustrates all methods with detailed real-world applications - many of them international in flavor - that reflect typical forecasting situations in todayà ;'s global marketplace. Offering a practical blend of traditional and contemporary topics, Elements of Forecasting, 3e covers trend, seasonality and cycles, as well as more modern topics such as model selection, volatility models, unit roots and stochastic trends, vector autoregressions and cointegration. It devotes full chapters to volatility, statistical graphics, and evaluating and combining forecasts.

Author Biography

Francis X. Diebold is William Polk Carey Professor of Economics and Professor of Finance and Statistics at the University of Pennsylvania and its Wharton School, and Faculty Research Associate at the National Bureau of Economic Research in Cambridge, Massachusetts

Table of Contents

1 Introduction to Forecasting: Applications, Methods, Books, Journals, and Software	1	(30)
1. Forecasting in Action	1	(3)
2. Forecasting Methods: An Overview of the Book	4	(2)
3. Useful Books, Journals, Software, and Online Information	6	(3)
4. Looking Ahead	9	(1)
Problems and Complements	10	(2)
Concepts for Review	12	(1)
References and Additional Readings	12	(1)
Appendix: The Linear Regression Model	13	(14)
Additional Problems and Complements	27	(3)
Additional Bibliographical and
Computational Notes	30	(1)
Additional Concepts for Review	30	(1)
2 Six Considerations Basic to Successful Forecasting	31	(18)
1. The Decision Environment and Loss Function	32	(5)
2. The Forecast Object	37	(1)
3. The Forecast Statement	38	(4)
4. The Forecast Horizon	42	(2)
5. The Information Set	44	(1)
6. Methods and Complexity, the Parsimony Principle, and the Shrinkage Principle	44	(1)
7. Concluding Remarks	45	(1)
Problems and Complements	46	(1)
Bibliographical and Computational Notes	47	(1)
Concepts for Review	48	(1)
References and Additional Readings	48	(1)
3 Statistical Graphics for Forecasting	49	(24)
1. Why Graphical Analysis Is Important	49	(4)
2. Simple Graphical Techniques	53	(5)
3. Elements of Graphical Style	58	(4)
4. Application: Graphing Four Components of Real GNP	62	(3)
5. Concluding Remarks	65	(1)
Problems and Complements	66	(4)
Bibliographical and Computational Notes	70	(1)
Concepts for Review	70	(1)
References and Additional Readings	71	(2)
4 Modeling and Forecasting Trend	73	(32)
1. Modeling Trend	73	(9)
2. Estimating Trend Models	82	(1)
3. Forecasting Trend	83	(1)
4. Selecting Forecasting Models Using the Akaike and Schwarz Criteria	84	(6)
5. Application: Forecasting Retail Sales	90	(8)
Problems and Complements	98	(4)
Bibliographical and Computational Notes	102	(1)
Concepts for Review	102	(1)
References and Additional Readings	103	(2)
5 Modeling and Forecasting Seasonality	105	(14)
1. The Nature and Sources Of Seasonality	105	(3)
2. Modeling Seasonality	108	(2)
3. Forecasting Seasonal Series	110	(1)
4. Application: Forecasting Housing Starts	111	(4)
Problems and Complements	115	(2)
Bibliographical and Computational Notes	117	(1)
Concepts for Review	117	(1)
References and Additional Readings	117	(2)
6 Characterizing Cycles	119	(28)
1. Covariance Stationary Time Series	120	(6)
2. White Noise	126	(5)
3. The Lag Operator	131	(2)
4. Wold's Theorem, the General Linear Process, and Rational Distributed Lags	133	(4)
5. Estimation and Inference for the Mean, Autocorrelation, and Partial Autocorrelation Functions	137	(3)
6. Application: Characterizing Canadian Employment Dynamics	140	(2)
Problems and Complements	142	(3)
Bibliographical and Computational Notes	145	(1)
Concepts for Review	145	(1)
References and Additional Readings	146	(1)
7 Modeling Cycles: MA, AR, and ARMA Models	147	(42)
1. Moving-Average (MA) Models	148	(8)
2. Autoregressive (AR) Models	156	(9)
3. Autoregressive Moving-Average (ARMA) Models	165	(2)
4. Application: Specifying and Estimating Models for Employment Forecasting	167	(11)
Problems and Complements	178	(5)
Bibliographical and Computational Notes	183	(2)
Concepts for Review	185	(1)
References and Additional Readings	186	(3)
8 Forecasting Cycles	189	(24)
1. Optimal Forecasts	189	(1)
2. Forecasting Moving-Average Processes	190	(5)
3. Making The Forecasts Operational	195	(1)
4. The Chain Rule of Forecasting	196	(4)
5. Application: Forecasting Employment	200	(5)
Problems and Complements	205	(6)
Bibliographical and Computational Notes	211	(1)
Concepts for Review	211	(1)
References and Additional Readings	212	(1)
9 Putting It All Together:A Forecasting Model with Trend Seasonal and Cyclical Components	213	(34)
1. Assembling What We Have Learned	213	(3)
2. Application: Forecasting Liquor Sales	216	(16)
3. Recursive Estimation Procedures For Diagnosing and Selecting Forecasting Models	232	(6)
4. Liquor Sales, Continued	238	(2)
Problems and Complements	240	(4)
Bibliographical and Computational Notes	244	(1)
Concepts for Review	245	(1)
References and Additional Readings	245	(2)
10 Forecasting with Regression Models	247	(46)
1. Conditional Forecasting Models and Scenario Analysis	248	(1)
2. Accounting for Parameter Uncertainty In Confidence Intervals for Conditional Forecasts	248	(3)
3. Unconditional Forecasting Models	251	(1)
4. Distributed Lags, Polynomial Distributed Lags, and Rational Distributed Lags	252	(2)
5. Regressions with Lagged Dependent Variables, Regressions with ARMA Disturbances, and Transfer Function Models	254	(3)
6. Vector Autoregressions	257	(2)
7. Predictive Causality	259	(2)
8. Impulse-Response Functions and Variance Decompositions	261	(4)
9. Application: Housing Starts and Completions	265	(17)
Problems and Complements	282	(6)
Bibliographical and Computational Notes	288	(1)
Concepts for Review	289	(1)
References and Additional Readings	290	(3)
11 Evaluating and Combining Forecasts	293	(38)
1. Evaluating a Single Forecast	293	(4)
2. Evaluating Two or More Forecasts: Comparing Forecast Accuracy	297	(3)
3. Forecast Encompassing and Forecast Combination	300	(5)
4. Application: Oversea Shipping Volume on the Atlantic East Trade Lane	305	(15)
Problems and Complements	320	(6)
Bibliographical and Computational Notes	326	(1)
Concepts for Review	326	(1)
References and Additional Readings	327	(4)
12 Unit Roots, Stochastic Trends ARMA Forecasting Models and Smoothing	331	(50)
1. Stochastic Trends and Forecasting	331	(8)
2. Unit Roots: Estimation and Testing	339	(9)
3. Application: Modeling and Forecasting the Yen/Dollar Exchange Rate	348	(12)
4. Smoothing	360	(6)
5. Exchange Rates, Continued	366	(1)
Problems and Complements	367	(9)
Bibliographical and Computational Notes	376	(2)
Concepts for Review	378	(1)
References and Additional Readings	378	(3)
13 Volatility Measurement, Modeling, and Forecasting	381	(30)
1. The Basic ARCH Process	383	(4)
2. The GARCH Process	387	(4)
3. Extensions of ARCH and GARCH Models	391	(4)
4. Estimating, Forecasting, and Diagnosing GARCH Models	395	(2)
5. Application: Stock Market Volatility	397	(8)
Problems and Complements	405	(3)
Bibliographical and Computational Notes	408	(1)
Concepts for Review	409	(1)
References and Additional Readings	409	(2)
Bibliography	411	(12)
Name Index	423	(4)
Subject Index	427