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Model averaging in markov-switching models: predicting national recessions with regional data

Pierre Guérin () and Danilo Leiva-Leon ()

No 1727, Working Papers from Banco de España, Working Papers Homepage

Abstract: This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In the empirical application, we forecast U.S. business cycle turning points with statelevel employment data. We find that forecasts obtained with our best combination scheme provide timely updates of U.S. recessions in that they outperform a notoriously dicult benchmark to beat (the anxious index from the Survey of Professional Forecasters) for short-term forecasts.

Keywords: business cycles; forecast combination; forecasting; Markov-switching; nowcasting (search for similar items in EconPapers)
JEL-codes: C53 E32 E37 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets, nep-for, nep-mac, nep-ore and nep-ure
Date: 2017-07
References: View references in EconPapers View complete reference list from CitEc
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http://www.bde.es/f/webbde/SES/Secciones/Publicaci ... /17/Fich/dt1727e.pdf First version, July 2017 (application/pdf)

Related works:
Journal Article: Model averaging in Markov-switching models: Predicting national recessions with regional data (2017) Downloads
Working Paper: Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data (2015) Downloads
Working Paper: Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data (2014) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:bde:wpaper:1727

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