A new unit root analysis for testing hysteresis in unemployment

Olaoluwa Yaya, Ahamuefula Ogbonna, Fumitaka Furuoka and Luis Gil-Alana

MPRA Paper from University Library of Munich, Germany

Abstract: This paper proposes a nonlinear unit root test based on the artificial neural network-augmented Dickey-Fuller (ANN-ADF) test for testing hysteresis in unemployment. In this new unit root test, the linear, quadratic and cubic components of the neural network process are used to capture the nonlinearity in the time-series data. Fractional integration methods, based on linear and nonlinear trends are also used in the paper. By considering five European countries such as France, Italy, Netherland, Sweden, and the United Kingdom, the empirical findings indicate that there is still hysteresis in these countries. Among batteries of unit root tests applied, both the ARNN-ADF and fractional integration tests fail to reject the hypothesis of unemployment hysteresis in all the countries.

Keywords: Unit root process; Nonlinearity; Neuron network: Time-series; Hysteresis; Unemployment; Europe; Labour market. (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2019-10-19
New Economics Papers: this item is included in nep-big, nep-cmp, nep-ecm, nep-eec, nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/96621/1/MPRA_paper_96621.pdf original version (application/pdf)

Related works:
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:pra:mprapa:96621

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().