Analysis of the macroeconomic development of European and Asia-Pacific countries with the use of connectionist models

Abstract

The paper applies novel techniques for on-line, adaptive learning of macroeconomic data and a consecutive analysis and prediction. The evolving connectionist system paradigm (ECOS) is used in its two versions—unsupervised (evolving self-organised maps), and supervised (evolving fuzzy neural networks—EFuNN). In addition to these techniques self-organised maps (SOM) are also employed for finding clusters of countries based on their macroeconomic parameters. EFuNNs allow for modelling, clustering, prediction and rule extraction. The rules that describe future annual values for the consumer price index (CPI), interest rate, unemployment and GDP per capita are extracted from data and reported in the paper for both global—EU-Asia block of countries, and for smaller groups—EU, EU-candidate countries, Asia-Pacific countries. The analysis and prediction models proof to be useful tools for the analysis of trends in macroeconomic development of clusters of countries and their future prediction.