Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks
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Jari Hännikäinen
Abstract
In this paper, we analyze the forecasting performance of a set of widely used window selection methods in the presence of data revisions and recent structural breaks. Our Monte Carlo and empirical results for U.S. real GDP and inflation show that the expanding window estimator often yields the most accurate forecasts after a recent break. It performs well regardless of whether the revisions are news or noise, or whether we forecast first-release or final values. We find that the differences in the forecasting accuracy are large in practice, especially when we forecast inflation after the break of the early 1980s.
Acknowledgments
I would like to thank the editor, Atsushi Inoue, two anonymous referees, Henri Nyberg, Jari Vainiomäki, Helinä Laakkonen, Markku Lanne, Juhani Raatikainen and the seminar participants in the FDPE Econometrics Workshop and in the XXXV Annual Meeting of the Finnish Economic Association for helpful comments and discussion. Financial support from the FDPE and the OP-Pohjola Group Research Foundation is gratefully acknowledged. All mistakes are mine.
Appendix
Means and Standard Deviations.
| Experiment | ||||||||
|---|---|---|---|---|---|---|---|---|
| News | ||||||||
| 1 | 2.255 | 2.255 | 2.128 | 2.128 | 2.514 | 2.514 | 1.957 | 1.957 |
| 2 | 2.255 | 5.171 | 2.128 | 4.878 | 2.514 | 7.187 | 1.957 | 5.595 |
| 3 | 2.255 | 1.442 | 2.128 | 1.361 | 2.514 | 2.035 | 1.957 | 1.584 |
| 4 | 1.442 | 5.171 | 1.361 | 4.878 | 2.035 | 7.187 | 1.584 | 5.595 |
| 5 | 5.171 | 1.442 | 4.878 | 1.361 | 7.187 | 2.035 | 5.595 | 1.584 |
| 6 | 2.255 | 2.255 | 2.128 | 2.128 | 2.514 | 7.541 | 1.957 | 5.871 |
| 7 | 2.255 | 2.255 | 2.128 | 2.128 | 2.514 | 0.838 | 1.957 | 0.652 |
| 8 | 2.255 | 3.383 | 2.128 | 3.191 | 2.514 | 2.514 | 1.957 | 1.957 |
| 9 | 2.255 | 1.128 | 2.128 | 1.064 | 2.514 | 2.514 | 1.957 | 1.957 |
| Noise | ||||||||
| 1 | 2.000 | 2.000 | 1.887 | 1.887 | 1.732 | 1.732 | 1.879 | 1.879 |
| 2 | 2.000 | 4.000 | 1.887 | 3.774 | 1.732 | 2.268 | 1.879 | 2.460 |
| 3 | 2.000 | 1.333 | 1.887 | 1.258 | 1.732 | 1.549 | 1.879 | 1.680 |
| 4 | 1.333 | 4.000 | 1.258 | 3.774 | 1.549 | 2.268 | 1.680 | 2.460 |
| 5 | 4.000 | 1.333 | 3.774 | 1.258 | 2.268 | 1.549 | 2.460 | 1.680 |
| 6 | 2.000 | 2.000 | 1.887 | 1.887 | 1.732 | 5.196 | 1.879 | 5.636 |
| 7 | 2.000 | 2.000 | 1.887 | 1.887 | 1.732 | 0.577 | 1.879 | 0.626 |
| 8 | 2.000 | 3.000 | 1.887 | 2.830 | 1.732 | 1.732 | 1.879 | 1.879 |
| 9 | 2.000 | 1.000 | 1.887 | 0.943 | 1.732 | 1.732 | 1.879 | 1.879 |
The table presents the means and standard deviations of the first-release
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©2017 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Research Articles
- Regression Discontinuity with Errors in the Running Variable: Effect on Truthful Margin
- A Simple Estimator for Dynamic Models with Serially Correlated Unobservables
- Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks
- Discriminating between (in)valid External Instruments and (in)valid Exclusion Restrictions
- Competing Risks Copula Models for Unemployment Duration: An Application to a German Hartz Reform
- Intercept Homogeneity Test for Fixed Effect Models under Cross-sectional Dependence: Some Insights
- Practitioner’s Corner
- Root-n Consistent Kernel Density Estimation in Practice
- Linear Model IV Estimation When Instruments Are Many or Weak
- Additive Nonparametric Instrumental Regressions: A Guide to Implementation
- Teaching Corner
- Teaching Size and Power Properties of Hypothesis Tests Through Simulations
Articles in the same Issue
- Frontmatter
- Research Articles
- Regression Discontinuity with Errors in the Running Variable: Effect on Truthful Margin
- A Simple Estimator for Dynamic Models with Serially Correlated Unobservables
- Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks
- Discriminating between (in)valid External Instruments and (in)valid Exclusion Restrictions
- Competing Risks Copula Models for Unemployment Duration: An Application to a German Hartz Reform
- Intercept Homogeneity Test for Fixed Effect Models under Cross-sectional Dependence: Some Insights
- Practitioner’s Corner
- Root-n Consistent Kernel Density Estimation in Practice
- Linear Model IV Estimation When Instruments Are Many or Weak
- Additive Nonparametric Instrumental Regressions: A Guide to Implementation
- Teaching Corner
- Teaching Size and Power Properties of Hypothesis Tests Through Simulations
