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Handbook of Economic Forecasting part 55

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Handbook of Economic Forecasting part 55. 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 | This page intentionally left blank Chapter 10 FORECASTING WITH MANY PREDICTORS JAMES H. STOCK Department of Economics Harvard University and the National Bureau ofEconomic Research MARK W. WATSON Woodrow Wilson School and Department of Economics Princeton University and the National Bureau of Economic Research Contents Abstract 516 Keywords 516 1. Introduction 517 1.1. Many predictors Opportunities and challenges 517 1.2. Coverage of this chapter 518 2. The forecasting environment and pitfalls of standard forecasting methods 518 2.1. Notation and assumptions 518 2.2. Pitfalls of using standard forecasting methods when n is large 519 3. Forecast combination 520 3.1. Forecast combining setup and notation 521 3.2. Large-n forecast combining methods 522 3.3. Survey of the empirical literature 523 4. Dynamic factor models and principal components analysis 524 4.1. The dynamic factor model 525 4.2. DFM estimation by maximum likelihood 527 4.3. DFM estimation by principal components analysis 528 4.4. DFM estimation by dynamic principal components analysis 532 4.5. DFM estimation by Bayes methods 533 4.6. Survey of the empirical literature 533 5. Bayesian model averaging 535 5.1. Fundamentals of Bayesian model averaging 536 5.2. Survey of the empirical literature 541 6. Empirical Bayes methods 542 We thank Jean Boivin Serena Ng Lucrezia Reichlin Charles Whiteman and Jonathan Wright for helpful comments. This research was funded in part by NSF grant SBR-0214131. Handbook of Economic Forecasting Volume 1 Edited by Graham Elliott Clive WJ. Granger and Allan Timmermann 2006 Elsevier B.V. All rights reserved DOI 10.1016 81574-0706 05 01010-4 516 J.H. Stock and M.W. Watson 6.1. Empirical Bayes methods for large- linear forecasting 543 7. Empirical illustration 545 7.1. Forecasting methods 545 7.2. Data and comparison methodology 547 7.3. Empirical results 547 8. Discussion 549 References 550 Abstract Historically time series forecasts of economic variables have used only a .