Data Analysis and Applications 2

4 Analysis of Dependence among Growth Rates of GDP of V4 Countries Using Four-dimensional Vine Copulas

We analyzed seasonally adjusted quarterly data for the V4 countries, Czech Republic (Cz), Hungary (Hu), Poland (Pl) and Slovakia (Sk), for the period 1995/Q1–2016/Q3. We investigated parallel changes in GDP of these countries using four-dimensional Vine copula models. We applied ARIMA–GARCH filters to logarithms of the data of above-mentioned countries. The obtained residuals have pairwise Kendall’s correlation coefficients in the interval (0.1, 0.2) (the maximal value was achieved for the couple (Cz, Sk)). Subsequently, we applied to those residuals (country specific) monotone transformations in order to map them in the unit interval. The results served as inputs to calculations of 4-dimensional Vine copulas. The optimal Vine copulas help to obtain more insight in the detailed development of the investigated GDPs.

4.1. Introduction

We analyzed seasonally adjusted quarterly data (provided by EUROSTAT) for the V4 countries, Czech Republic (Cz), Hungary (Hu), Poland (Pl) and Slovakia (Sk) (that underwent similar historical and economic development during the last 70 years), for the period 1995/Q1–2016/Q3. We investigated parallel changes in GDP of these countries using four-dimensional Vine copula models. We applied ARIMA–GARCH filters to logarithms of the data of above-mentioned countries. The obtained residuals have pairwise Kendall’s correlation coefficients in the interval ...