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Assessing security measures reducing terrorist risk: inverse ex post cost-benefit and cost-effectiveness analyses of Norwegian airports and seaports

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Abstract

When the risks of unwanted events and the impacts of countermeasures are well-known, an economic assessment would compare the costs of the measures with the benefits of reduced risk. For evaluating countermeasures against terrorist attacks this is, however, not straight-forward. Both the baseline risk of terrorist attacks and the possible risk-reducing impacts of the security measures adopted are largely unknown. A possible approach to the economic assessment in such cases is to adopt inverse ex post economic analyses. Inverse ex post analysis in our case will be an assessment of already implemented security measures at Norwegian airports/seaports, trying to inversely estimate implicit benefits for estimated terror risks and risk changes due to the implemented measures. Such implicit benefits might be measured as implicit costs of lives saved or, more generally, as an implicit value of what is protected in airports and in seaports. Our analysis indicates that for justifying the costs of the implemented security measures, it implies huge cost per life saved and a quite enormous valuation of what the measures protect. A low estimated baseline risk of terror attacks explains to a large degree these findings. Nevertheless, even if fatalities represent a major societal cost of terrorist attacks, there are other potential costs regarding infrastructure, that to a large degree have been disregarded in our analyses. If all potential societal costs could be included, this would justify a higher level of security spending, but not necessarily the levels that our estimates indicate.

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Notes

  1. This is an approach similar to the common “top-down” risk analysis matching “vulnerability and threat against investment of resources” (Robinson et al. 2010, p 14). Principally the value of the object protected could comprise more than protecting lives.

  2. Enders and Sandler (1993, 2000, 2002) have analysed terrorism development over time, from the US or international perspective, using time series analysis. Kollias et al. (2009) analyse the impact of national security measures in Greece based on Poisson and negative binomial modelling; and although terrorist attacks have been far more numerous in Greece than in Norway, they did not find unambiguous terrorist-thwarting impact of security spending.

  3. Game theoretic modelling may give the opportunity to find optimal strategies of allocating security resources so as to minimize the expected loss to some more or less precise level (Bier 2007). Such modelling is, however, beyond the scope of this paper.

  4. We will apply the default Latin Hypercube simulation method in @RISK which requires a lower number of iterations than a standard Monte Carlo simulation (Palisade 2008). Latin Hypercube simulation differs from the traditional Monte Carlo simulation in the number of iterations required until sampled values approximate input distributions Latin Hypercube sampling forces the samples drawn to correspond more closely to the input distribution and thus converges faster on the true statistics of the input distribution than standard Monte Carlo.

  5. In order to register an event into the GTD2, the following criteria have to be fulfilled: i) The incident must be intentional; ii) the incident must entail some level of violence; iii) the incident must be an act of non-state terrorism (state terrorism is excluded); iv) the act must be aimed at attaining a political, economic, religious, or social goal; v) there must be evidence of an intention to coerce, intimidate, or convey some other message to a larger audience (or audiences) than the immediate victims; and vi) the action must be outside the context of legitimate warfare activities, i.e. the act must be outside the parameters permitted by international humanitarian law (PGIS 2007).

  6. Vi assume that the population ratio is the same in 2008 as in the period of concern. Definition of Europe used by GTD2: Andorra, Austria, Belgium, Corsica, Denmark, East Germany (GDR), Finland, France, Germany, Gibraltar, Great Britain, Greece, Iceland, Ireland, Italy, Luxembourg, Malta, Man, Isle of, Netherlands, Northern Ireland, Norway, Portugal, Spain, Sweden, Switzerland, West Germany, Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Czech Republic, Czechoslovakia, Hungary, Kosovo, Macedonia, Moldova, Poland, Romania, Serbia-Montenegro, Slovak Republic, Slovenia, Yugoslavia (GTD2 Codebook. 2009).

  7. Statistically, more than 70 per cent of the terrorist incidents in Europe between 1970 and 1997 have taken place in Spain, North Ireland, Italy, France and Greece (LaFree et al. 2006).

  8. Personal correspondence with Avinor—the operator of the Norwegian airport network.

  9. This figure is somewhat uncertain, as different ports have placed different costs items under the implementation costs related to the ISPS code. Most of the cost information related to seaport security measures was collected by contacting the port association, Norwegian Ports—Norske Havner (http://www.havn.no/), which has 52 member ports of a total of about 60 public ports in Norway.

  10. This fatality cost is estimated in the context of road traffic accidents, and approximately 20% of the cost is related to ex post medical/administrative costs in case of an incident/accident and 80% is related to the ex ante value of a statistical life (NPRA 2006).

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Acknowledgement

This study was funded by the Research Council of Norway, through the project “Coping with the new risks: understanding, organization and economics”, under the programme “Risk and Safety in Transport—RISIT”. The usual disclaimer applies.

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Correspondence to Juned Akhtar.

Appendix

Appendix

Figure 7
figure 7

Anticipated terrorist attacks per year against the transport sector in Europeector

Table 4 Probability of attack in Europe.

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Akhtar, J., Bjørnskau, T. & Veisten, K. Assessing security measures reducing terrorist risk: inverse ex post cost-benefit and cost-effectiveness analyses of Norwegian airports and seaports. J Transp Secur 3, 179–195 (2010). https://doi.org/10.1007/s12198-010-0046-z

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