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Handbook of Economic Forecasting

Book Description

The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics.  In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects.  Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables.  Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies.  Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals.  The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues.



  • Focuses on innovation in economic forecasting via industry applications
  • Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications
  • Makes details about economic forecasting accessible to scholars in fields outside economics

Table of Contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Dedication
  6. Introduction to the Series
  7. Contributors
  8. Section III: Forecasters’ Objectives
    1. Chapter 12. Forecasters’ Objectives and Strategies
      1. Abstract
      2. 1 Introduction
      3. 2 Model with Mixed Reputational and Contest Payoffs
      4. 3 Development of Reputational and Contest Theories
      5. 4 Equilibrium with Mixed Incentives
      6. 5 Estimation
      7. 6 Robustness and Extensions
      8. 7 Role of Anonymity
      9. 8 Summary and Outlook
      10. Acknowledgments
      11. References
    2. Chapter 13. Forecasting Exchange Rates: an Investor Perspective
      1. Abstract
      2. 1 Introduction
      3. 2 Successful Investing Does Not Require Beating a Random Walk
      4. 3 Constructing a Currency Portfolio
      5. 4 Benchmarks for Currency Investors
      6. 5 Forecast Skill Evaluation: Tilt and Timing
      7. 6 Enhancing Forecasts with Conditioners
      8. 7 Summary
      9. References
  9. Section IV: Methodology
    1. Chapter 14. Variable Selection in Predictive Regressions
      1. Abstract
      2. 1 Introduction
      3. 2 Criterion-Based Methods When N < T
      4. 3 Regularization Methods
      5. 4 Dimension Reduction Methods
      6. 5 Three Practical Problems
      7. 6 Conclusion
      8. Acknowledgments
      9. References
    2. Chapter 15. Forecasting with Bayesian Vector Autoregression
      1. Abstract
      2. 1 Introduction
      3. 2 Bayesian Forecasting and Computation
      4. 3 Reduced Form VARs
      5. 4 Structural VARs
      6. 5 Co-Integration
      7. 6 Conditional Forecasts
      8. 7 Time-Varying Parameters and Stochastic Volatility
      9. 8 Model and Variable Selection
      10. 9 High-Dimensional VARs
      11. Acknowledgements
      12. Appendix A Markov Chain Monte Carlo Methods
      13. Appendix B State-Space Models
      14. Appendix C Distributions
      15. References
    3. Chapter 16. Copula Methods for Forecasting Multivariate Time Series
      1. Abstract
      2. 1 Introduction
      3. 2 Dependence Summary Statistics
      4. 3 Estimation and Inference for Copula Models
      5. 4 Model Selection and Goodness-of-Fit Testing
      6. 5 Other Issues in Applications
      7. 6 Applications of Copulas in Economics and Finance
      8. 7 Conclusions and Directions for Further Research
      9. Acknowledgments
      10. References
    4. Chapter 17. Quantile Prediction
      1. Abstract
      2. 1 Introduction
      3. 2 Prediction
      4. 3 Evaluation
      5. 4 Specific Issues
      6. 5 Conclusion and Directions for Future Research
      7. Acknowledgments
      8. References
    5. Chapter 18. Panel Data Forecasting
      1. Abstract
      2. 1 Introduction
      3. 2 The Best Linear Unbiased Predictor
      4. 3 Homogeneous versus Heterogeneous Panel Forecasts
      5. 4 Caveats, Related Studies, and Future Work
      6. Acknowledgments
      7. References
    6. Chapter 19. Forecasting Binary Outcomes
      1. Abstract
      2. 1 Introduction
      3. 2 Probability Predictions
      4. 3 Evaluation of Binary Event Predictions
      5. 4 Binary Point Predictions
      6. 5 Improving Binary Predictions
      7. 6 Conclusion
      8. Acknowledgments
      9. References
    7. Chapter 20. Advances in Forecast Evaluation
      1. Abstract
      2. 1 Introduction
      3. 2 Modeling and Forecasting Framework
      4. 3 Pairs of Models: Population-Level and Finite-Sample Inference
      5. 4 Unconditional Versus Conditional Evaluation
      6. 5 Evaluation of Multiple Forecasts
      7. 6 Evaluation of Real-Time Forecasts
      8. 7 Small-Sample Properties of Tests of Equal Predictive Ability
      9. 8 On the Choice of Sample Split
      10. 9 Why Do Out-of-Sample Forecast Evaluation?
      11. 10 Conclusion
      12. 11 Asymptotic Derivations for Out-of-Sample Inference: Examples
      13. Acknowledgments
      14. References
    8. Chapter 21. Advances in Forecasting under Instability
      1. Abstract
      2. 1 Introduction
      3. 2 Is the Predictive Content Unstable Over Time?
      4. 3 What is the Relationship Between in-sample and Out-of-sample Forecasting Ability in the Presence of Instabilities?
      5. 4 Empirical Evidence
      6. 5 Conclusions
      7. Acknowledgments
      8. Appendix 1 Critical Value Tables
      9. References
  10. Index