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

Author

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  • 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.

Suggested Citation

  • Walter Enders & Yu Liu & Ruxandra Prodan, 2009. "Forecasting Series Containing Offsetting Breaks: Old School And New School Methods Of Forecasting Transnational Terrorism," Defence and Peace Economics, Taylor & Francis Journals, vol. 20(6), pages 441-463.
    • Handle: RePEc:taf:defpea:v:20:y:2009:i:6:p:441-463
    DOI: 10.1080/10242690802425772
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    1. repec:diw:diwwpp:dp1050 is not listed on IDEAS
    2. repec:diw:diwwpp:dp1049 is not listed on IDEAS
    3. Sibel Cengiz & Afsin Sahin, 2014. "Modelling nonlinear behavior of labor force participation rate by STAR: An application for Turkey," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(1), pages 113-127, April.
    4. Friedrich Schneider & Tilman Brück & Daniel Meierrieks, 2010. "The Economics of Terrorism and Counter-Terrorism: A Survey (Part II)," Discussion Papers of DIW Berlin 1050, DIW Berlin, German Institute for Economic Research.
    5. Luo, Shikong & Yan, Xinyan & Yang, Haoyi, 2021. "Let’s take a smooth break: Stock return predictability revisited," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 300-314.

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