Forecasting US output growth with non-linear models in the presence of data uncertaintyClements, M. ORCID: https://orcid.org/0000-0001-6329-1341 (2012) Forecasting US output growth with non-linear models in the presence of data uncertainty. Studies in nonlinear dynamics & econometrics, 16 (1). pp. 1-25. ISSN 1558-3708 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1515/1558-3708.1865 Abstract/SummaryWe consider the impact of data revisions on the forecast performance of a SETAR regime-switching model of U.S. output growth. The impact of data uncertainty in real-time forecasting will affect a model's forecast performance via the effect on the model parameter estimates as well as via the forecast being conditioned on data measured with error. We find that benchmark revisions do affect the performance of the non-linear model of the growth rate, and that the performance relative to a linear comparator deteriorates in real-time compared to a pseudo out-of-sample forecasting exercise.
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