  A predictive model of terrorist activity is developed by examining the daily
number of terrorist attacks in Indonesia from 1994 through 2007. The dynamic
model employs a shot noise process to explain the self-exciting nature of the
terrorist activities. This estimates the probability of future attacks as a
function of the times since the past attacks. In addition, the excess of
nonattack days coupled with the presence of multiple coordinated attacks on the
same day compelled the use of hurdle models to jointly model the probability of
an attack day and corresponding number of attacks. A power law distribution
with a shot noise driven parameter best modeled the number of attacks on an
attack day. Interpretation of the model parameters is discussed and predictive
performance of the models is evaluated.
