In this paper an attempt is made to assess the hypothesis of re- gional club-convergence, using a spatial panel analysis combined with B-Splines. In this context, a 'convergence-club' is conceived as a group of regions that in the long-run move towards steady-state equilib- rium, approximated in...

There is growing literature in macroeconomics, especially on business cycle synchronization, employing different methods of time series clustering. However, even as an unsupervised learning method, this technique requires making choices that are nontrivially influenced by the nature of the data...

The data mining technique of time series clustering is well established in many fields. However, as an unsupervised learning method, it requires making choices that are nontrivially influenced by the nature of the data involved. The aim of this paper is to verify usefulness of the time series...

A clustering procedure is introduced based on the Hausdorff distance as a similarity measure between clusters of elements. The method is applied to the financial time series of the Dow Jones industrial average (DJIA) index to find companies that share a similar behavior. Comparisons are made...

In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i; j), which...

Many papers have highlighted that some macroeconomic time series present structural instability. The causes of these remarkable changes in the reduced form properties of the macroeconomy is a debated argument. In literature this issue is handled with three main econometric methodologies:...