A Test for Superior Predictive Ability
Open accessAbstract
We propose a new test for superior predictive ability. The new test compares favorable to the reality check for data snooping (RC), because the former is more powerful and less sensitive to poor and irrelevant alternatives. The improvements are achieved by two modifications of the RC. We employ a studentized test statistic that reduces the influence of erratic forecasts and invoke a sample dependent null distribution. The advantages of the new test are confirmed by Monte Carlo experiments and in an empirical exercise, where we compare a large number of regression-based forecasts of annual US inflation to a simple random walk forecast. The random walk forecast is found to be inferior to regression-based forecasts and, interestingly, the best sample performance is achieved by models that have a Phillips curve structure.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Politis, D. N., & Romano, J. P. (1994) · Journal of the American Statistical Association · doi:10.1080/01621459.1994.10476870 · Cited by 2,649 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Li, W., Wang, X., Wang, Z., & Yang, M. (2023) · Journal of Accounting and Finance · doi:10.33423/jaf.v23i4.6453 · Cited by 2 · see citing works
- Authors
- Hansen, P. R.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Hansen, Peter Reinhard
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2004
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W3126029843
- Cited by
- 99
- References
- 1
- Citations by year
- 2024: 1 · 2023: 2 · 2022: 1 · 2020: 6 · 2019: 2 · 2018: 2 · 2017: 4 · 2016: 6 · 2015: 4 · 2014: 1 · 2013: 11 · 2012: 8
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- SSRN Electronic Journal (acceptedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Monetary Policy and Economic Impact
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Diverse Scientific and Economic Studies
- Keywords
- superior predictive ability, reality check, data snooping, forecast evaluation, inflation forecasting, random walk forecast, Phillips curve
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
