The paper refers to capacity utilisation, applying a short-cut that is sometimes used in business cycle research to yearly GDP and investment data from 1960 to the present for 22 countries. The basic idea is that the empirical short-run fluctuations of the capital output ratio v are mainly due...

The paper applies methods of functional data analysis – functional auto-regression, principal components and canonical correlations – to the study of the dynamics of interest rate curve. In addition, it introduces a novel statistical tool based on the singular value decomposition...

In this paper we propose a new test statistic that considers multiple structural breaks to analyse the non-stationarity of a panel data set. The methodology is based on the common factor analysis in an attempt to allow for some sort of dependence across the individuals. Thus allowing for...

A method of principal components is employed to investigate nonlinear dynamic factor structure using a large panel data. The evidence suggests the possibility of nonlinearity in the U.S. while it excludes the class of nonlinearity that can generate endogenous fluctuation or chaos

This paper considers a factor model in which independent component analysis (ICA) is employed to construct common factors out of a large number of macroeconomic time series. The ICA has been regarded as a better method to separate unobserved sources that are statistically independent to each...

This paper uses dynamic factor analysis to investigate the sources of foreign shocks and the propagation mechanism of these disturbances into two small open economies, Australia and Canada. Panels including a variety of foreign and domestic series for each country are used to estimate the...

We consider the estimation of a large number of GARCH models, say of the order of several hundreds. Especially in the multivariate case, the number of parameters is extremely large. To reduce this number and render estimation feasible, we regroup the series in a small number of clusters. Within...