In this paper we try to identify manufacturing and service clusters in Spain, using data from Mercantile Registers of 2006. The proposed methodology partially follows contributions of Duranton and Overman (2005), Brenner (2003 and 2004) and Ellison and Glaser (1997), but departing from them we...

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...

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...

This paper presents a procedure for studying industrial performance and related issues such as changes in the wage structure. This procedure combines cluster analysis and discriminant analysis as a package, and applies this package to time series data. This enables us to organize industrial data...