dorsal/arxiv
View SchemaCluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations
| Authors | M. Gligor, M. Ausloos |
|---|---|
| Categories | |
| ArXiv ID | physics/0607098 |
| URL | https://arxiv.org/abs/physics/0607098 |
| DOI | 10.1140/epjb/e2007-00132-5 |
| Journal | Eur. Phys. J B 57 (2007) 139-146 |
Abstract
The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.
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"abstract": "The statistical distances between countries, calculated for various moving\naverage time windows, are mapped into the ultrametric subdominant space as in\nclassical Minimal Spanning Tree methods. The Moving Average Minimal Length Path\n(MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass\ncenter of the system from the movement of the mass center itself. A Hamiltonian\nrepresentation given by a factor graph is used and plays the role of cost\nfunction. The present analysis pertains to 11 macroeconomic (ME) indicators,\nnamely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital\nFormation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest\nof the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour\nworked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of\ncountries is composed of 15 EU countries, data taken between 1995 and 2004. By\ntwo different methods (the Bipartite Factor Graph Analysis and the Correlation\nMatrix Eigensystem Analysis) it is found that the strongly correlated countries\nwith respect to the macroeconomic indicators fluctuations can be partitioned\ninto stable clusters.",
"arxiv_id": "physics/0607098",
"authors": [
"M. Gligor",
"M. Ausloos"
],
"categories": [
"physics.soc-ph"
],
"doi": "10.1140/epjb/e2007-00132-5",
"journal_ref": "Eur. Phys. J B 57 (2007) 139-146",
"title": "Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations",
"url": "https://arxiv.org/abs/physics/0607098"
},
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