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