An artificial neural network based heterogeneous panel unit root test in case of cross sectional independence

  • Authors:

  • Christian de Peretti;Carole Siani;Mario Cerrato

  • Affiliations:

  • Laboratory SAF, ISFA, University Claude Bernard Lyon 1 and DEFI, Faculty of Economics and Management, University of Aix Marseille 2, France;Department of computer Science, University Claude Bernard Lyon 1, France;Department of Economics, University of Glasgow, UK

  • Venue:
  • IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
  • Year:
  • 2009

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Abstract

In this paper we propose an artificial neural network (ANN) based panel unit root test, extending [1] neural test to a dynamic heterogeneous panel context, and following the [2] panel methodology. New asymptotic results are obtained both for the individual ANN-t test statistics for unit root, and the panel unit root test statistic. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided.