DocumentCode
2711400
Title
An artificial neural network based heterogeneous panel unit root test in case of cross sectional independence
Author
De Peretti, Christian ; Siani, Carole ; Cerrato, Mario
Author_Institution
Lab. SAF, Univ. Claude Bernard Lyon 1, Lyon, France
fYear
2009
fDate
14-19 June 2009
Firstpage
2487
Lastpage
2493
Abstract
In this paper we propose an artificial neural network (ANN) based panel unit root test, extending neural test to a dynamic heterogeneous panel context, and following the 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.
Keywords
exchange rates; neural nets; statistical testing; time series; ANN; US Dollar; artificial neural network; bilateral real exchange rate series; cross sectional independence; heterogeneous panel unit root test statistics; Artificial neural networks; Data analysis; Econometrics; Exchange rates; Helium; Linearity; Power generation economics; Statistical analysis; Statistical distributions; Testing; Artificial neural network; exchange rates; panel unit root test;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location
Atlanta, GA
ISSN
1098-7576
Print_ISBN
978-1-4244-3548-7
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2009.5178885
Filename
5178885
Link To Document