Predictive and Descriptive Qualities of Different Classes of Models for Parallel Economic Development of Selected EU-Countries

In this paper, we extend and modify our modelling [presented in the conference paper (Komorník and Komorníková, Predictive and descriptive models of mutual development of economic growth of Germany and selected non-traditional EU countries. In: ITISE 2015, International Work-Conference on Time Series, pp. 55–64. Copicentro Granada S.L, 2015)] of the parallel development of GDP of Germany (as the strongest EU economy), the so-called V4 countries (Poland, the Czech Republic, Hungary, Slovakia) and Greece (as the most problematic EU economy). Unlike in Komorník and Komorníková (Predictive and descriptive models of mutual development of economic growth of Germany and selected non-traditional EU countries. In: ITISE 2015, International Work-Conference on Time Series, pp. 55–64. Copicentro Granada S.L, 2015), we analyse the data provided by OECD (freely available from http://​stats.​oecd.​org/​index.​aspx?​queryid=​218) that are expressed in USD (using the expenditure approach) and covering a longer time interval than our former data from EUROSTAT (http://​appsso.​eurostat.​ec.​europa.​eu/​nui/​show.​do?​wai=​true&​data-set=​namq_​10_​gdp) (expressed in EUR using the output approach). The best predictive quality models were found in the class of multivariate TAR (Threshold Autoregressive) models with aggregation functions’ type thresholds. On the other hand, the best descriptive quality models were found in the competing classes of one-dimensional MSW (Markov Switching) and STAR (Smooth Transition Autoregressive) models.