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ID092937
Title ProperForecasting series containing offsetting breaks
Other Title Informationold school and new school methods of forecasting transnational terrorism
LanguageENG
AuthorEnders, Walter ;  Liu, Yu ;  Prodan, Ruxandra
Publication2009.
Summary / Abstract (Note)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.
`In' analytical NoteDefence and Peace Economics Vol. 20, No. 6; Dec 2009: p. 441 - 463
Journal SourceDefence and Peace Economics Vol. 20, No. 6; Dec 2009: p. 441 - 463
Key WordsBai - Perron Test ;  Nonlinear Forecasting ;  Out - of - Sample Forecasts ;  Terrorism ;  Threshold Models


 
 
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