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Complex Dynamics in Macroeconomics: A Novel Approach

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New Trends in Macroeconomics

Summary

In this work we employ the Recurrence Quantification Analysis (RQA) framework, effective in discovering evidence of non-linear determinism and complex dynamics in short, noisy and irregular signals. We apply RQA to a set of US macroeconomic time series and simulated sequences in order to provide a classification based on topological aspects of their dynamics. Through RQA we can in general obtain useful information on the quality and complexity of the structure of the dynamics in an economy, as this is embedded in its macroeconomic time series.

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Author information

Authors and Affiliations

  1. Department of Economics, University of Macedonia, Egnatia str. 156, 54006, Thessaloniki, Greece

    Catherine Kyrtsou

  2. Durham Business School, University of Durham, Mill Hill Lane, Durham, DH13LB, UK

    Constantinos E. Vorlow

Authors
  1. Catherine Kyrtsou
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  2. Constantinos E. Vorlow
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Editors and Affiliations

  1. BETA/CNRS, Faculty of Economics, University of Strasbourg I, 61 Avenue de la Forêt Noire, 67085, Strasbourg Cedex, France

    Claude Diebolt (Directeur de Recherche au CNRS) (Directeur de Recherche au CNRS)

  2. Department of Economics, University of Macedonia, Egnatia Street 156, 54006, Thessaloniki, Greece

    Catherine Kyrtsou

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Kyrtsou, C., Vorlow, C.E. (2005). Complex Dynamics in Macroeconomics: A Novel Approach. In: Diebolt, C., Kyrtsou, C. (eds) New Trends in Macroeconomics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28556-3_11

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