Detalle Publicación

ARTÍCULO
Recovering cointegration via wavelets in the presence of non-linear patterns
Autores: Martínez Compains, J. (Autor de correspondencia); Rodríguez Carreño, Ignacio; Gencay, R.; Trani, Tommaso; Ramos Vilardell, D.
Título de la revista: STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS
ISSN: 1081-1826
Volumen: 25
Número: 5
Páginas: 255 - 265
Fecha de publicación: 2021
Lugar: WOS
Resumen:
Johansen's Cointegration Test (JCT) performs remarkably well in finding stable bivariate cointegration relationships. Nonetheless, the JCT is not necessarily designed to detect such relationships in presence of non-linear patterns such as structural breaks or cycles that fall in the low frequency portion of the spectrum. Seasonal adjustment procedures might not detect such non-linear patterns, and thus, we expose the difficulty in identifying cointegrating relations under the traditional use of JCT. Within several Monte Carlo experiments, we show that wavelets can empower more the JCT framework than the traditional seasonal adjustment methodologies, allowing for identification of hidden cointegrating relationships. Moreover, we confirm these results using seasonally adjusted time series as US consumption and income, gross national product (GNP) and money supply M1 and GNP and M2.