Reality Checks and Comparisons of Nested Predictive Models
Bibliographic Data
| ID | 19418261 |
|---|---|
| Authors | Todd E Clark (0000-0002-4985-1709, Federal Reserve Bank of Cleveland), Michael W McCracken (0000-0002-7004-1233, Research Division, Federal Reserve Bank of St. Louis, P.O. Box 442, St. Louis, MO, 63166) |
| Year | 2012 |
| Volume | 30 |
| Issue | 1 |
| Pages | 53-66 |
| Publication date | 2012-01-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1198/jbes.2011.10278 |
| OpenAlex | W2057950515 |
| Language | EN |
| Citations received | 8 |
| References cited | 45 |
This article develops a simple bootstrap method for simulating asymptotic critical values for tests of equal forecast accuracy and encompassing among many nested models. Our method combines elements of fixed regressor and wild bootstraps. We first derive the asymptotic distributions of tests of equal forecast accuracy and encompassing applied to forecasts from multiple models that nest the benchmark model—that is, reality check tests. We then prove the validity of the bootstrap for these tests. Monte Carlo experiments indicate that our proposed bootstrap has better finite-sample size and power than other methods designed for comparison of nonnested models. Supplementary materials are available online
Data mining · Econometrics · Monte Carlo method · Nested set model · Predictive power · Sample size determination · Statistics · Computer Science · Financial Risk and Volatility Modeling · Forecasting Techniques and Applications · Mathematics · Monetary Policy and Economic Impact
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| Unique citing works | 8 |
|---|---|
| Citations per year | 0,62 |
| Citation span | 2013 - 2026 (14) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 8 |