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Netconomics: Novel Forecasting Techniques from the Combination of Big Data, Network Science and Economics

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  • Andreas Joseph
  • Irena Vodenska
  • Eugene Stanley
  • Guanrong Chen

Abstract

The combination of the network theoretic approach with recently available abundant economic data leads to the development of novel analytic and computational tools for modelling and forecasting key economic indicators. The main idea is to introduce a topological component into the analysis, taking into account consistently all higher-order interactions. We present three basic methodologies to demonstrate different approaches to harness the resulting network gain. First, a multiple linear regression optimisation algorithm is used to generate a relational network between individual components of national balance of payment accounts. This model describes annual statistics with a high accuracy and delivers good forecasts for the majority of indicators. Second, an early-warning mechanism for global financial crises is presented, which combines network measures with standard economic indicators. From the analysis of the cross-border portfolio investment network of long-term debt securities, the proliferation of a wide range of over-the-counter-traded financial derivative products, such as credit default swaps, can be described in terms of gross-market values and notional outstanding amounts, which are associated with increased levels of market interdependence and systemic risk. Third, considering the flow-network of goods traded between G-20 economies, network statistics provide better proxies for key economic measures than conventional indicators. For example, it is shown that a country's gate-keeping potential, as a measure for local power, projects its annual change of GDP generally far better than the volume of its imports or exports.

Suggested Citation

  • Andreas Joseph & Irena Vodenska & Eugene Stanley & Guanrong Chen, 2014. "Netconomics: Novel Forecasting Techniques from the Combination of Big Data, Network Science and Economics," Papers 1403.0848, arXiv.org.
  • Handle: RePEc:arx:papers:1403.0848
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    File URL: http://arxiv.org/pdf/1403.0848
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    References listed on IDEAS

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    1. James Crotty, 2009. "Structural causes of the global financial crisis: a critical assessment of the 'new financial architecture'," Cambridge Journal of Economics, Oxford University Press, vol. 33(4), pages 563-580, July.
    2. Rene M. Stulz, 2010. "Credit Default Swaps and the Credit Crisis," Journal of Economic Perspectives, American Economic Association, vol. 24(1), pages 73-92, Winter.
    3. Andreas Joseph & Stephan Joseph & Guanrong Chen, 2013. "Cross-border Portfolio Investment Networks and Indicators for Financial Crises," Papers 1306.0215, arXiv.org, revised Jan 2014.
    4. Stulz, Rene, 2010. "Credit default Swaps and the Credit Crisis," Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 6, pages 157-175.
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    Cited by:

    1. Alexei P Kireyev & Andrei Leonidov, 2016. "A Network Model of Multilaterally Equilibrium Exchange Rates," IMF Working Papers 16/130, International Monetary Fund.
    2. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.

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