Many empirical studies find that financial variables possess a predictive power over real economic activity. To examine this relationship, we adopt two time-series techniques: spectral analysis and a newly developed method, wavelet analysis. The major innovation of this paper is to apply wavelet...

This paper employs a panel vector autoregressive model (PVAR) to study the dynamics of the overall exchange rate volatility. PVAR estimation results, based on panel data for 29 economies, are used in simulating impulse response functions. Since economic shocks may affect high-frequency and...

This paper introduces a class of cointegration tests based on estimated low-pass and high-pass regression coefficients from the same wavelet transform of the original time series data.  The procedure can be applied to test the null of cointegration in a n + k multivariate system with n...

This paper presents a new algorithm for the analysis of spectral properties of short genes using the wavelet transform and the Hilbert–Huang transform (HHT). A wavelet subspace algorithm combined with the empirical mode decomposition (EMD) is introduced to create subdivided intrinsic mode...

In his celebrated 1966 Econometrica article, Granger first hypothesized that there is a ‘typical’ spectral shape for an economic variable. This ‘typical’ shape implies decreasing levels of energy as frequency increases, which in turn implies an extremely long cycle in economic...

In a recent paper Leong-Huang:2010 {Journal of Applied Statistics 37, 215Ӳ33} proposed a wavelet-correlation-based approach to test for cointegration between two time series. However, correlation and cointegration are two different concepts even when wavelet analysis is used. It is known that...