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Direct Multi-Step Forecast based Comparison of Nested Models via an Encompassing Test

Jean-Yves Pitarakis

arXiv 26 Dec 2023 · Econometrics

arXiv:2312.16099 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We introduce a novel approach for comparing out-of-sample multi-step forecasts obtained from a pair of nested models that is based on the forecast encompassing principle. Our proposed approach relies on an alternative way of testing the population moment restriction implied by the forecast encompassing principle and that links the forecast errors from the two competing models in a particular way. Its key advantage is that it is able to bypass the variance degeneracy problem afflicting model based forecast comparisons across nested models. It results in a test statistic whose limiting distribution is standard normal and which is particularly simple to construct and can accommodate both single period and longer-horizon prediction comparisons. Inferences are also shown to be robust to different predictor types, including stationary, highly-persistent and purely deterministic processes. Finally, we illustrate the use of our proposed approach through an empirical application that explores the role of global inflation in enhancing individual country specific inflation forecasts.

Citation extraction

42
references
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appendix boundary found by appendix_titled_section at “Appendix” · 75% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Hansen, P.R., and Timmermann, A (2015) Equivalence between Out-of-Sample Forecast Comparisons and Wald Statistics0.84333100%
2Pitarakis, J (2023) A novel approach to predictive accuracy testing in nested environments self0.81142100%
3Clark, T.E. and McCracken, M.W (2001) Tests of equal forecast accuracy and encompassing for nested models0.73732100%
4Clark, T.E. and McCracken M.W (2005) Evaluating Direct Multistep Forecasts0.73732100%
5Clark, T.E. and McCracken, M. W (2013) Advances in Forecast Evaluation0.73732100%
6McCracken, M.W (2007) Asymptotics for out of sample tests of Granger causality0.64422100%
7Andrews, D.W.K (1991) Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation0.40511100%
8Auer, R. A., Levchenko, A. A., and Sauré, P (2019) International inflation spillovers through input linkages0.40511100%
9Breitung, J., and Demetrescu, M (2015) Instrumental variable and variable addition based inference in predictive regressions0.40511100%
10Breitung, J., and Knüppel, M (2021) How far can we forecast? Statistical tests of the predictive content0.40511100%

Showing the top 10 of 83 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Robust Tests for Factor-Augmented Regressions with an Application to the Novel EA-MD-QD Dataset0.928257
2New Tests of Equal Forecast Accuracy for Factor-Augmented Regressions with Weaker Loadings0.9162610
3On Selection of Cross-Section Averages in Non-stationary Environments0.00011