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9780324163827

Elements of Forecasting with Economic Applications Card and InfoTrac College Edition

by
  • ISBN13:

    9780324163827

  • ISBN10:

    0324163827

  • Edition: 3rd
  • Format: Paperback
  • Copyright: 2003-09-19
  • Publisher: South-Western College Pub
  • View Upgraded Edition
  • Purchase Benefits
List Price: $196.33

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

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