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Forecasting Series Containing Offsetting Breaks: Old School And New School Methods Of Forecasting Transnational Terrorism

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Author Info

  • Walter Enders
  • Yu Liu
  • Ruxandra Prodan

Abstract

Transnational terrorism data are difficult to forecast because they contain an unknown number of structural breaks of unknown functional form. The rise of religious fundamentalism, the demise of the Soviet Union, and the rise of al Qaeda have changed the nature of transnational terrorism. 'Old School' forecasting methods simply smooth or difference the data. 'New School' methods use estimated break dates to control for regime shifts when forecasting. We compare the various forecasting methods using a Monte Carlo study with data containing different types of breaks. The study's results are used to forecast various types of transnational terrorist incidents.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Defence and Peace Economics.

Volume (Year): 20 (2009)
Issue (Month): 6 ()
Pages: 441-463

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Handle: RePEc:taf:defpea:v:20:y:2009:i:6:p:441-463

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Related research

Keywords: Bai-Perron test; Nonlinear forecasting; Out-of-sample forecasts; Terrorism; Threshold models;

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Cited by:
  1. Friedrich Schneider & Tilman Brück & Daniel Meierrieks, 2011. "The Economics of Terrorism and Counter-Terrorism: A Survey (Part I)," Economics of Security Working Paper Series 44, DIW Berlin, German Institute for Economic Research.
  2. Sibel Cengiz & Afsin Sahin, 2014. "Modelling nonlinear behavior of labor force participation rate by STAR: An application for Turkey," International Journal of Economic Sciences and Applied Research (IJESAR), Technological Educational Institute (TEI) of Kavala, Greece, vol. 7(1), pages 113-127, April.

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