Recurrence Quantification Analysis of Czech Macroeconomic Time Series

Abstract

The goal of this paper is to analyze a set of Czech macroeconomic time series with the use of Recurrence Quantification Analysis (RQA). We chose RQA because it is suitable for economic time series that are characterized by noise and short data sets. Through RQA we can obtain useful information on the quality and complexity of the hidden structure of the dynamics in an economy. Recurrence is a fundamental property of dynamical systems. At first we estimated the time delay and the embedding dimension, which is needed for the Lyapunov exponent estimation, the phase space reconstruction and for RQA. Finally we used RQA itself. We used recurrence plots (RP) as a powerful tool for visualization and analysis. Generally RP is an advanced technique of nonlinear data analysis. RP is a graphical method designed to locate hidden recurring patterns, nonstationarity and structural changes. We apply RQA in order to provide a classification based on topological aspects of their dynamics. Our considerations on the basis of these analyzes confirm that it could be chaotic behavior in certain macroeconomic time series.