The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests
Abstract
The Diebold–Mariano (DM) test was intended for comparing forecasts; it has been, and remains, useful in that regard. The DM test was not intended for comparing models. Much of the large ensuing literature, however, uses DM-type tests for comparing models, in pseudo-out-of-sample environments. In that case, simpler yet more compelling full-sample model comparison procedures exist; they have been, and should continue to be, widely used. The hunch that pseudo-out-of-sample analysis is somehow the “only,” or “best,” or even necessarily a “good” way to provide insurance against in-sample overfitting in model comparisons proves largely false. On the other hand, pseudo-out-of-sample analysis remains useful for certain tasks, perhaps most notably for providing information about comparative predictive performance during particular historical episodes.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As emphasized byDiebold (2015), the model-free nature of the Diebold-Mariano test means that it should be interpreted as a comparison of forecasts, not as a comparison of”
From Empirical Asset Pricing via Machine Learning (2020) · cites this paper as Diebold (2015)
Citations
Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Estimating the Dimension of a Model
Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1993) · doi:10.1007/978-1-4899-4541-9 · Cited by 21,230
A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
Hamilton, J. D. (1989) · Econometrica · doi:10.2307/1912559 · Cited by 9,696
Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
Vuong, Q. H. (1989) · Econometrica · doi:10.2307/1912557 · Cited by 5,929
Diebold, F. X., & Mariano, R. S. (1994) · National Bureau of Economic Research · doi:10.3386/t0169 · Cited by 5,498
Self-citationDiebold, F. X., & Mariano, R. S. (1995) · Journal of Business and Economic Statistics · doi:10.1080/07350015.1995.10524599 · Cited by 5,240
Self-citationHansen, P. R., Lunde, A., & Nason, J. M. (2011) · Econometrica · doi:10.3982/ecta5771 · Cited by 2,229
A Reality Check for Data Snooping
White, H. (2000) · Econometrica · doi:10.1111/1468-0262.00152 · Cited by 1,851
Research works printed but not linked: 2
- Durham G., 2013, Journal of Financial Econometrics, 11
- Elliott G., 2006, Handbook of Economic Forecasting, 33, 100
Cited by
Sorted by citations
Empirical Asset Pricing via Machine Learning
Gu, S., Kelly, B., & Xiu, D. (2020) · The Review of Financial Studies · doi:10.1093/rfs/hhaa009 · Cited by 2,545
Electricity price forecasting: A review of the state-of-the-art with a look into the future
Weron, R. (2014) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2014.08.008 · Cited by 1,646
Forecasting: theory and practice
Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babaï, M. Z., Barrow, D. K., Taieb, S. B., Bergmeir, C., Bessa, R. J., Bijak, J., Boylan, J. E., et al. (2022) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2021.11.001 · Cited by 1,187
Recent advances in electricity price forecasting: A review of probabilistic forecasting
Nowotarski, J., & Weron, R. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.05.234 · Cited by 563
Yang, D., Kleissl, J. P., Gueymard, C. A., Pedro, H. T. C., & Coimbra, C. F. M. (2018) · Solar Energy · doi:10.1016/j.solener.2017.11.023 · Cited by 584
Metadata
- Authors
- Diebold, F. X.
- Affiliations
- University of Pennsylvania (US)
- Corresponding author
- Diebold, Francis X.
- Venue
- Journal of Business & Economic Statistics
- Publisher
- Informa UK Limited
- Published
- 2015-01-02
- Volume
- 33
- Issue
- 1
- Pages
- 1-1
- ISSN
- 0735-0015 (ISSN-L)
- 1537-2707
- OpenAlex
- W2007694684
- Cited by
- 496
- References
- 41
- Citations by year
- 2026: 66 · 2025: 60 · 2024: 48 · 2023: 46 · 2022: 39 · 2021: 46 · 2020: 35 · 2019: 34 · 2018: 36 · 2017: 33 · 2016: 20 · 2015: 22
- FWCI
- 46.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Business and Economic Statistics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Monetary Policy and Economic Impact
- Keywords
- Diebold-Mariano test, forecast evaluation, model comparison, prediction accuracy, forecasting model comparison
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
