Handbook of economic forecasting / edited by Graham Elliott, Clive W.J. Granger, Allan Timmermann.

Format:

Book

Contributor:

Elliott, Graham, 1965-

Granger, C. W. J. (Clive William John), 1934-2009.

Timmermann, Allan.

Series:

Handbooks in economics 0169-7218 ; 24.

Handbooks in economics, 0169-7218 ; 24

Language:

English

Subjects (All):

Economic forecasting--Econometric models.

Economic forecasting.

Physical Description:

volumes : illustrations ; 25 cm.

Edition:

First edition.

Place of Publication:

Amsterdam ; Boston : Elsevier North-Holland, 2006-

Summary:

Research on forecasting methods has made important progress over recent years and these developments are brought together in the Handbook of Economic Forecasting. The handbook covers developments in how forecasts are constructed based on multivariate time-series models, dynamic factor models, nonlinear models and combination methods. The handbook also includes chapters on forecast evaluation, including evaluation of point forecasts and probability forecasts and contains chapters on survey forecasts and volatility forecasts. Areas of applications of forecasts covered in the handbook include economics, finance and marketing. *Addresses economic forecasting methodology, forecasting models, forecasting with different data structures, and the applications of forecasting methods *Insights within this volume can be applied to economics, finance and marketing disciplines

Contents:

Part 1 Forecasting Methodology

Chapter 1 Bayesian Forecasting / John Geweke, Charles Whiteman 3

2 Bayesian inference and forecasting: A primer 7

3 Posterior simulation methods 25

4 'Twas not always so easy: A historical perspective 41

5 Some Bayesian forecasting models 53

6 Practical experience with Bayesian forecasts 68

Chapter 2 Forecasting and Decision Theory / Clive W.J. Granger, Mark J. Machina 81

1 History of the field 83

2 Forecasting with decision-based loss functions 87

Chapter 3 Forecast Evaluation / Kenneth D. West 99

2 A brief history 102

3 A small number of nonnested models, Part I 104

4 A small number of nonnested models, Part II 106

5 A small number of nonnested models, Part III 111

6 A small number of models, nested: MPSE 117

7 A small number of models, nested, Part II 122

8 Summary on small number of models 125

9 Large number of models 125

Chapter 4 Forecast Combinations / Allan Timmermann 135

2 The forecast combination problem 140

3 Estimation 156

4 Time-varying and nonlinear combination methods 165

5 Shrinkage methods 170

6 Combination of interval and probability distribution forecasts 176

7 Empirical evidence 181

Chapter 5 Predictive Density Evaluation / Valentina Corradi, Norman R. Swanson 197

1 Estimation, specification testing, and model evaluation 200

Part II Testing for Correct Specification of Conditional Distributions 207

2 Specification testing and model evaluation in-sample 207

3 Specification testing and model selection out-of-sample 220

Part III Evaluation of (Multiple) Misspecified Predictive Models 234

4 Pointwise comparison of (multiple) misspecified predictive models 234

5 Comparison of (multiple) misspecified predictive density models 253

Part IV Appendices and References 271

Appendix B Proofs 275

Part 2 Forecasting Models

Chapter 6 Forecasting with VARMA Models / Helmut Lutkepohl 287

2 VARMA processes 292

3 Specifying and estimating VARMA models 306

4 Forecasting with estimated processes 316

Chapter 7 Forecasting with Unobserved Components Time Series Models / Andrew Harvey 327

2 Structural time series models 335

3 ARIMA and autoregressive models 348

4 Explanatory variables and interventions 352

5 Seasonality 355

6 State space form 361

7 Multivariate models 370

8 Continuous time 383

9 Nonlinear and non-Gaussian models 391

10 Stochastic volatility 403

Chapter 8 Forecasting Economic Variables with Nonlinear Models / Timo Terasvirta 413

2 Nonlinear models 416

3 Building nonlinear models 425

4 Forecasting with nonlinear models 431

5 Forecast accuracy 440

6 Lessons from a simulation study 444

7 Empirical forecast comparisons 445

Chapter 9 Approximate Nonlinear Forecasting Methods / Halbert White 459

2 Linearity and nonlinearity 463

3 Linear, nonlinear, and highly nonlinear approximation 467

4 Artificial neural networks 474

5 QuickNet 476

6 Interpretational issues 484

7 Empirical examples 492

Part 3 Forecasting with Particular Data Structures

Chapter 10 Forecasting with Many Predictors / James H. Stock, Mark W. Watson 515

2 The forecasting environment and pitfalls of standard forecasting methods 518

3 Forecast combination 520

4 Dynamic factor models and principal components analysis 524

5 Bayesian model averaging 535

6 Empirical Bayes methods 542

7 Empirical illustration 545

Chapter 11 Forecasting with Trending Data / Graham Elliott 555

2 Model specification and estimation 559

3 Univariate models 563

4 Cointegration and short run forecasts 581

5 Near cointegrating models 586

6 Predicting noisy variables with trending regressors 591

7 Forecast evaluation with unit or near unit roots 596

Chapter 12 Forecasting with Breaks / Michael P. Clements, David F. Hendry 605

2 Forecast-error taxonomies 609

3 Breaks in variance 614

4 Forecasting when there are breaks 617

5 Detection of breaks 622

6 Model estimation and specification 627

7 Ad hoc forecasting devices 631

8 Non-linear models 635

9 Forecasting UK unemployment after three crises 640

Appendix A Taxonomy derivations for Equation (10) 648

Appendix B Derivations for Section 4.3 650

Chapter 13 Forecasting Seasonal Time Series / Eric Ghysels, Denise R. Osborn, Paulo M.M. Rodrigues 659

2 Linear models 664

3 Periodic models 683

4 Other specifications 691

5 Forecasting, seasonal adjustment and feedback 701

Part 4 Applications of Forecasting Methods

Chapter 14 Survey Expectations / M. Hashem Pesaran, Martin Weale 715

2 Concepts and models of expectations formation 720

3 Measurement of expectations: History and developments 733

4 Uses of survey data in forecasting 748

5 Uses of survey data in testing theories: Evidence on rationality of expectations 754

Appendix A Derivation of optimal forecasts under a 'Lin-Lin' cost function 768

Appendix B References to the main sources of expectational data 769

Chapter 15 Volatility and Correlation Forecasting / Torben G. Andersen, Tim Bollerslev, Peter F. Christoffersen, Francis X. Diebold 777

2 Uses of volatility forecasts 786

3 Garch volatility 798

4 Stochastic volatility 814

5 Realized volatility 830

6 Multivariate volatility and correlation 839

7 Evaluating volatility forecasts 853

Chapter 16 Leading Indicators / Massimiliano Marcellino 879

2 Selection of the target and leading variables 884

3 Filtering and dating procedures 887

4 Construction of nonmodel based composite indexes 892

5 Construction of model based composite coincident indexes 894

6 Construction of model based composite leading indexes 901

7 Examples of composite coincident and leading indexes 915

8 Other approaches for prediction with leading indicators 925

9 Evaluation of leading indicators 934

10 Review of the recent literature on the performance of leading indicators 945

11 What have we learned? 951

Chapter 17 Forecasting with REal-Time Macroeconomic Data / Dean Croushore 961

1 An illustrative example: The index of leading indicators 963

2 The real-time data set for macroeconomists 964

3 Why are forecasts affected by data revisions? 969

4 The literature on how data revisions affect forecasts 974

5 Optimal forecasting when data are subject to revision 978

6 Summary and suggestions for further research 980

Chapter 18 Forecasting in Marketing / Philip Hans Franses 983

2 Performance measures 986

3 Models typical to marketing 992

4 Deriving forecasts 1003.

Notes:

Includes bibliographical references and indexes.

ISBN:

0444513957

OCLC:

70063087

Publisher Number:

9780444513953

Online:

Publisher description