Terrorism risk, resilience and volatility : a comparison of terrorism patterns in three Southeast Asian countries


Autoria(s): White, Gentry; Porter, Michael D.; Mazerolle, Lorraine
Data(s)

2013

Resumo

Objective This article explores patterns of terrorist activity over the period from 2000 through 2010 across three target countries: Indonesia, the Philippines and Thailand. Methods We use self-exciting point process models to create interpretable and replicable metrics for three key terrorism concepts: risk, resilience and volatility, as defined in the context of terrorist activity. Results Analysis of the data shows significant and important differences in the risk, volatility and resilience metrics over time across the three countries. For the three countries analysed, we show that risk varied on a scale from 0.005 to 1.61 “expected terrorist attacks per day”, volatility ranged from 0.820 to 0.994 “additional attacks caused by each attack”, and resilience, as measured by the number of days until risk subsides to a pre-attack level, ranged from 19 to 39 days. We find that of the three countries, Indonesia had the lowest average risk and volatility, and the highest level of resilience, indicative of the relatively sporadic nature of terrorist activity in Indonesia. The high terrorism risk and low resilience in the Philippines was a function of the more intense, less clustered pattern of terrorism than what was evident in Indonesia. Conclusions Mathematical models hold great promise for creating replicable, reliable and interpretable “metrics” to key terrorism concepts such as risk, resilience and volatility.

Identificador

http://eprints.qut.edu.au/68789/

Publicador

Springer

Relação

DOI:10.1007/s10940-012-9181-y

White, Gentry, Porter, Michael D., & Mazerolle, Lorraine (2013) Terrorism risk, resilience and volatility : a comparison of terrorism patterns in three Southeast Asian countries. Journal of Quantitative Criminology, 29(2), pp. 295-320.

Fonte

School of Mathematical Sciences; Science & Engineering Faculty

Palavras-Chave #010400 STATISTICS #160200 CRIMINOLOGY
Tipo

Journal Article