FORECASTING SERIES CONTAINING OFFSETTING BREAKS: OLD SCHOOL AND NEW SCHOOL METHODS OF FORECASTING TRANSNATIONAL TERRORISM

Walter Enders, Yu Liu and Ruxandra Prodan ()

Defence and Peace Economics, 2009, vol. 20, issue 6, 441-463

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.

Keywords: Bai-Perron test; Nonlinear forecasting; Out-of-sample forecasts; Terrorism; Threshold models (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (4)

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DOI: 10.1080/10242690802425772

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