A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates

Christian de Peretti, Carole Siani and Mario Cerrato

Working Papers from Business School - Economics, University of Glasgow

Abstract: This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

Keywords: Artificial neural network; panel unit root test; bootstrap; Monte Carlo experiments; exchange rates. (search for similar items in EconPapers)
JEL-codes: C12 C15 C22 C23 F31 (search for similar items in EconPapers)
Date: 2010-03
New Economics Papers: this item is included in nep-ecm and nep-ets
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.gla.ac.uk/media/media_143746_en.pdf (application/pdf)

Related works:
Working Paper: A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates (2010)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gla:glaewp:2010_05

Access Statistics for this paper

More papers in Working Papers from Business School - Economics, University of Glasgow Contact information at EDIRC.
Bibliographic data for series maintained by Business School Research Team ().