Fractional integration and business cycle features

Bertrand Candelon and Luis Gil-Alana

No 2001,46, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: We show in this article that fractionally integrated univariate models for GDP may lead to a better replication of business cycle characteristics. We firstly show that the business cycle features are clearly affected by the degree of integration as well as by the other short run components of the series. Then, we model the real GDP in France, the UK and the US by means of fractionally ARIMA (ARFIMA) models, and show that the three time series can be specified in terms of this type of models with orders of integration higher than one but smaller than two. Comparing the ARFIMA specifications with those based on ARIMA models, we show via simulations that the former better describes the business cycles features of the data at least for the cases of the UK and the US.

Keywords: Long memory; Business cycles; Fractional integration (search for similar items in EconPapers)
JEL-codes: C12 C15 C22 (search for similar items in EconPapers)
Date: 2001
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Related works:
Journal Article: Fractional integration and business cycle features (2004)
Working Paper: Fractional Integration and Business Cycles Features (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:200146

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