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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...
Persistent link: https://www.econbiz.de/10011763799
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...
Persistent link: https://www.econbiz.de/10011885973
We introduce a broad family of generalised self-exciting point processes with CIR-type intensities, and we develop associated algorithms for their exact simulation. The underlying models are extensions of the classical Hawkes process, which already has numerous applications in modelling the...
Persistent link: https://www.econbiz.de/10012853458
The paper identifies the business models followed by banks in the euro area, utilising a proprietary dataset collected in the context of the supervisory reporting of the Single Supervisory Mechanism. The concept of a 'business model' has been neglected by economic theory and is defined here with...
Persistent link: https://www.econbiz.de/10011656196
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...
Persistent link: https://www.econbiz.de/10014156247
We propose a new, computationally-efficient way to approximate the “grouped fixed-effects” (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means objective to regression settings. As the...
Persistent link: https://www.econbiz.de/10014076493
We propose a new, computationally-efficient way to approximate the "grouped fixed-effects" (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means objective to regression settings. As the...
Persistent link: https://www.econbiz.de/10013401747
Persistent link: https://www.econbiz.de/10014251584