AN ANALYSIS OF THE IMPACT OF INSTITUTIONAL ENVIRONMENT ON TERRORISM RISK
2. Definitions, Datasets, and Variables To establish the link between the level of
risk of terrorist attacks and selected institutional characteristics theoretically described in [3], [12], [9], the authors have obtained selected data from the Governance Matters and Terrorism Risk Index databases. To analyse institutional characteristics of selected countries, the World Bank project has been used for evaluating and comparing the quality of
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administration (Governance Matters) by means of six variables. The first variable officially designated as Voice and Accountability (VA) assesses the quality of administration in compliance with the evaluation of the level of political, civil and human rights in individual countries. The second variable, Political Stability and Violence (PSNV), assesses the probability that violence takes place in the given country or the level of political instability in the country. Government Effectiveness (GE), i.e. the third variable, comprises the public service quality assessment, the level of bureaucracy and reliability of the government in the given country. The next variable Regulatory Quality (RQ) assesses the regulatory burden of the country, and Rule of Law (RL) or the legal order quality, and comprises the assessment of public trust in social norms and the level of conformity to them. The last variable monitored within the Governance Matters research project is Control of Corruption (CC) variable describing the level of corruption in individual countries. The above variables can range from −2.5 to 2.5 on the scale where the higher value of the variable is interpreted as lower occurrence of the negative aspect of the given variable. To assess the level of terrorism risk, the authors have examined data from the Terrorism Risk Index classifying countries into 4 groups (extreme risk − ER, high risk − HR, medium risk − MR, low risk − LR). Out of a total of 141 countries subjected to the analysis, 16
countries have been assessed, pursuant to the Terrorism Risk Index, as extreme terrorism risk countries, 10 as high terrorism risk countries, 24 as medium risk countries, and 91 as low terrorism risk countries. A detailed list of the countries, including their classification, is given in Table 1. The purpose of this article is to analyse the link between regulatory quality of selected economies and terrorism risk and to find out to what extent it is possible to classify terrorism risk according to the six variables. Hypotheses published in [9] predict higher terrorism risk in countries with a lower level of political stability, lower quantified quality of democracy and a higher level of corruption. The quantified characteristics of regulatory quality and their link with terrorism risk measured by means of the classification of countries into resulting groups are given together with their basic descriptive characteristics (local extremes, median, lower and upper quartiles) in Figure 1. A more detailed comparison of the values determined for countries differing in the level of terrorism risk shows that the highest median levels are characteristic for groups assessed as low risk countries (the median levels are as follows: Voice and Accountability (VA) 0.31, Political Stability and Violence (PSNV) 0.27, Government Effectiveness (GE) 0.14, Regulatory Quality (RQ) 0.30, Rule of Law (RL) 0.10 and Control of Corruption (CC) 0.05.
Table 1 Classification of countries on the basis of the Terrorism Risk Index Source:[18]
Extreme Risk:
AFGHANISTAN, CENTRAL AFRICAN REPUBLIC, COLOMBIA, CONGO, INDIA, IRAQ, ISRAEL, LAOS, PAKISTAN, PHILIPPINES, RUSSIA, SOMALIA, SUDAN, THAILAND, UGANDA, YEMEN.
High Risk:
AFGHANISTAN, CENTRAL AFRICAN REPUBLIC, COLOMBIA, CONGO, INDIA, IRAQ, ISRAEL, LAOS, PAKISTAN, PHILIPPINES, RUSSIA, SOMALIA, SUDAN, THAILAND, UGANDA, YEMEN.
Medium Risk:
GREECE, IRAN, KENYA, MYANMAR, NEPAL, NIGERIA, SENEGAL, SPAIN, TANZANIA, TURKEY.
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Low Risk:
ALBANIA, ANDORRA, ARGENTINA, ARMENIA, AUSTRALIA, AUSTRIA, AZERBAIJAN, BAHAMAS, BAHRAIN, BELARUS, BELGIUM, BOLIVIA, BOSNIA-HERZEGOVINA, BOTSWANA, BRAZIL, BULGARIA, BURKINA FASO, CAMBODIA, CAMEROON, CANADA, CHINA, COSTA RICA, CROATIA, CUBA, CYPRUS, CZECH REPUBLIC, DENMARK, DOMINICAN REPUBLIC, ERITREA, ESTONIA, FINLAND, GERMANY, GHANA, GUINEA, GUYANA, HAITI, HUNGARY, ICELAND, IRELAND, ITALY, JAMAICA, JAPAN, JORDAN, KAZAKHSTAN, KOREA, NORTH, KOREA, SOUTH, KOSOVO, KUWAIT, KYRGYZSTAN, LATVIA, LIBERIA, LIBYA, LIECHTENSTEIN, LITHUANIA, LUXEMBOURG, MACEDONIA, MADAGASCAR, MALAYSIA, MALTA, MEXICO, MONGOLIA, MOROCCO, MOZAMBIQUE, NAMIBIA, NETHERLANDS, NEW ZEALAND, NICARAGUA, NORWAY, OMAN, PANAMA, POLAND, PORTUGAL, QATAR, ROMANIA, SIERRA LEONE, SLOVAKIA, SLOVENIA, SOUTH AFRICA, SURINAME, SWEDEN, SWITZERLAND, TAJIKISTAN, TUNISIA, TURKMENISTAN, UKRAINE, UNITED ARAB EMIRATES, URUGUAY, UZBEKISTAN, VIETNAM, ZAMBIA, ZIMBABWE.
Figure 1: Box & Whisker Plots
Source: The graphs were drawn by the authors
The biggest differences between the low risk countries group and the extreme risk countries group are apparent for the variables Voice and Accountability (VA) (median LR 0.3 and median ER −0.83), Political Stability and Violence (PSNV)
(0.27 vs. −1.52) and Control of Corruption (CC) (0.05 vs. −1.07).
The results of descriptive statistics indicate that the median values of the variables Voice and Accountability (VA), Political Stability and Violence
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(PSNV), and Control of Corruption (CC) are lowest for countries classified according to the Terrorism Risk Index into the high terrorist risk group.
The results of descriptive statistics are further specified by adding the classification of individual countries into groups by means of a logit analysis. It is an advantage of this classification in comparison with the results of descriptive statistics that it is a multivariate statistical technique so that it is possible to take into consideration simultaneously all six variables when making the classification of a given country. The logit analysis also makes it possible to take into account the statistical links between individual institutional characteristics and last but not least the logit analysis allows us to determine the probability of classification of individual countries into each of the risk groups: extreme risk (ER), high risk (HR), medium risk (MR), and low risk (LR). In the event that the probabilities of classification into individual groups are very close, the probabilities determined in the above manner enable us to arrive at the
conclusion that even though the classification into the given group is the most probable, the classification into another group can be highly probable too. It means that it will not be possible to classify some countries into a given risk group unequivocally on the basis of the institutional characteristics with regard to the probability of classification (even though the highest) for this group. This fact is an advantage of the classification because the actual classification of the selected country into a given risk category does not necessarily have to be unambiguous on the basis of six selected institutional characteristics only.
The logit analysis principle lies in the fact that the probability pj that the given country with the values of institutional characteristics VA, PSNV, GE, RQ, RC belongs to the risk category
j , j= LR, MR, HR and ER is modelled as a logistic function of linear combination of these institutional characteristics VA, PSNV, GE, RQ, RC, CC and unknown parameters. The model is described by the equation:
(
)
{
}
{
}
∑
= ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + = = = 4 1 6 5 4 3 2 1 0 6 5 4 3 2 1 0 CC RC RQ GE PSNV VA exp CC RC RQ GE PSNV VA exp CC RC, RQ, GE, PSNV, VA, i i i i i i i i j j j j j j j j j p p β β β β β β β β β β β β β β .The unknown parameters β are to be jk
determined by means of the maximum likelihood method (see [6]).
The outcomes of the logit analysis are discussed in the below paragraph.
The comparison of the classification results performed on the basis of the Terrorism Risk Index with the classification results made by means of the logit analysis based on the six institutional variables make it possible to analyse the deviations between both original classifications, i.e. between the
original classification and the classification by means of the logit analysis and to interpret the deviations with regard to individual variables observed.
3. Results
Table 2 shows the logit analysis results demonstrating the brief comparison of classifications in the case when we restricted the classification of risk and low risk countries to the basic classification, i.e. we pooled the ER and
79 HR categories and MR and LR
categories. This comparison reveals that the classification of countries based on the Terrorism Risk Index and on the analysis of accompanying variables characterizing the institutional quality of the countries performed by means of the logit function shows 89.36 % of countries classified in the same way in contrast to the original classification. Different classification concerns 10 countries (Central African Republic, Congo, Kenya, Laos, Nepal, Russia, Senegal, Spain, Tanzania, Turkey) that have been classified into the MR or LR category in comparison with the original classification ER or HR, and similarly 5 countries (Bangladesh, Egypt, Ethiopia, Guinea, Syria) have been classified into the ER or HR category, where original classification was MR or LR.
In contrast to the original classification of countries into four categories, the below countries have been classified with a high degree of probability (more than 0.75) into different terrorist risk groups on the basis of the logit analysis: Angola, Chile, Ecuador, France, Honduras, Rwanda, Singapore, Congo, Laos and Tanzania – see Table 3. Out of these countries the first seven (Angola, Chile, Ecuador, France, Honduras,
Rwanda, and Singapore) have been classified into the low terrorist risk category (in the original classification pursuant to the Terrorism Risk Index they were in the medium risk category). Out of a total 4640 terrorist acts recorded under the Global Terrorism Database, 16 acts (0.34 %) which claimed 10 lives were committed in these differently classified countries. From the point of view of institutional characteristics which have indicated the largest differences between the low risk and extreme risk countries (Voice and Accountability (VA), Political Stability and Violence (PSNV) a Control of Corruption (CC)), we can see that Chile (1.04) and France (1.22) only achieve higher values of the Voice and Accountability (VA) variable than the median value. As to the Political Stability and Violence (PSNV) variable, we can see that all these countries demonstrate higher than median values. As regards the Control of Corruption (CC) variable, Chile (1.50), France (1.39), Rwanda (0.48) and Singapore (2.18) demonstrate higher values than the median.
Table 2 Logit classification Source: The table was created by the authors
Observed Predicted ER or HR Predicted MR or LR ER or HR 16 10 MR or LR 5 110
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Table 3 Misclassification result of logit analysis Source: The table was created by the authors
Classification under Terrorism Risk Index
Logit
Classification Prob 1 Prob 2 Prob 3 Prob 4
ANGOLA MR LR 0.005214 0.014075 0.068925 0.911786 CHILE MR LR 0.000045 0.009658 0.165087 0.825210 CONGO ER LR 0.003138 0.027611 0.096952 0.872299 ECUADOR MR LR 0.004805 0.059118 0.105118 0.830959 FRANCE MR LR 0.000184 0.029200 0.172242 0.798374 HONDURAS MR LR 0.027777 0.037408 0.171113 0.763701 LAOS ER LR 0.007926 0.019611 0.149703 0.822761 RWANDA MR LR 0.000022 0.001263 0.155498 0.843218 SINGAPORE MR LR 0.000001 0.000144 0.073539 0.926316 TANZANIA HR LR 0.001359 0.023945 0.086153 0.888543
The logit analysis results classify the remaining countries (Congo, Laos, and Tanzania) into the low risk category, which is in sharp contrast to their original classification into the extreme risk group (Congo, Laos) and high risk group (Tanzania). The Global Terrorism Database shows that in total, 15 terrorist
acts were committed in these three countries in 2010 which, however, claimed 99 lives. In comparison with the other falsely classified countries, the enormous death toll was due to 5 terrorist attacks only (for more details see Table 4 carried out in Congo in 2010.
Table 4 Terrorist acts Source:[8]
Incident Summary: Fatalities
09/01/2010: On Wednesday morning at about 1000, in the village of Kilambo near an unspecified city in North Kivu, Congo (Kinshasa), unidentified armed militants attacked one plane at a runway by unknown means and took hostage one Ukrainian and one Congolese pilot. Two soldiers and one civilian were killed and the plane was damaged in the attack. Congolese government troops, responding to the attack, killed two militants. The hostages were released on 09/24/2010. No damage was reported and no group claimed responsibility, but the militant group Mai Mai was thought to be responsible for the attack.
5
08/18/2010: On Wednesday morning, in the village of Kirumba near Mabenga, Nord-Kivu, Congo (Kinshasa), around 50 unidentified assailants attacked a United Nations Mission in the Democratic Republic of Congo (MONUSCO) base, killing three Indian MONUSCO peacekeepers and injuring seven others with machetes and knives. No damage was reported and no group claimed responsibility for the attack, although two suspects, identified as Justin Kambare and Tembea Mumbere, have been arrested in connection with the attack.
3
06/28/2010: On Monday morning, in the village of Mutwanga, North Kivu, Congo (Kinshasa), unknown assailants attacked by unknown means and looted the entire town, killing 16 civilians, kidnapping a security guard, burning and damaging a house and the vehicle of a local chief. The assailants were targeting Edwardo Nyamwisi, the brother of Congo minister Mbusa Nyamwisi. Nyamwisi was able to escape unhurt. No group claimed responsibility, but the militant group Allied Democratic Forces (ADF) were thought to be responsible for the attack. The status of the hostage is unknown.
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03/27/2010: On Saturday, in Kiruhura near Rutshuru, Nord-Kivu, Congo (Kinshasa), unidentified militants attacked and looted the village by unknown means. This incident was one of two linked attacks that also targeted the village of Burahi. It is unknown if the attack caused any property damage. The casualties for the attacks were listed cumulatively as one civilian killed; two soldiers and one person wounded. No group claimed responsibility for the attack but the Democratic Forces for the Liberation of Rwanda (FDLR) are suspected.
1
02/02/2010: On Tuesday, in the village of Kpanga near the Niangara, Orientale, Congo (Kinshasa), assailants burned homes, attacked and killed at least 74 civilians by unknown means and kidnapped an unknown amount of civilians. No group has claimed responsibility for the attack, but the group Lord's Resistance Army (LRA) is thought to be responsible for the attack. The status of the hostages is unknown.
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The reasons for classifying Congo, Laos and Tanzania into the low terrorist risk group on the basis of the logit analysis are apparent from Figure 2 showing median values of low and extreme risk countries. This figure shows high values of the Political Stability and Violence (PSNV) variable for all these differently classified countries Congo (−0.24), Laos (−0.22), Tanzania (−0.008). The high value of this indicator in comparison with the remaining countries classified pursuant to the Terrorism Risk Index indicates a higher level of political stability of these countries. A more detailed analysis of this variable reveals that according to [7], Political Stability and Violence (PSNV) indicates the probability of the government
destabilization or overthrow including terrorist threat which is the main focus of the classification pursuant to the Terrorism Risk Index. Institutional characteristics as an indicator of terrorism risk cannot be perceived as their general prerequisite and it is possible that the quantified variables of selected institutional characteristics and their structures concerning selected countries can lead to different classifications in comparison with the original classification reflecting terrorism risk without the influence of the institutional environment of the given countries. All calculations were processed by Statistica software and application STAT1 (see [16]).
Figure 2: Scatterplot
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4. Conclusions
Terrorism can be considered one of the greatest security threats at the beginning of the 21st century. It is therefore not surprising that the majority of developed countries invest considerable sums of money in counter-terrorism efforts which accelerated especially after the attacks in 2001. The term terrorism can be explained as the pre- mediated use or threat to use violence by individuals or subnational groups in order to attain a political or social objective through the intimidation of a large audience beyond that of the immediate victims. Terrorism risk is different in different countries and its probability can be affected by various motives of terrorist attacks, such as political, religious or ideological motives. This article analyses the influence of institutional variables on terrorism risk in selected 141 countries. To assess the level of terrorism risk in the countries subject to the analysis in 2010, we have used the Terrorism Risk Index data classifying the 141 countries into 4 groups (extreme risk, high risk, medium risk, low risk). Out of the total 141 analysed countries 16 countries have been assessed as extreme terrorism risk countries, 10 as high terrorism risk countries, 24 as medium risk countries, and 91 as low terrorism risk countries on the basis of the Terrorism Risk Index. To assess the institutional characteristics of the selected countries, we have used data from the Governance Matters characterizing the institutional environment by means of 6 variables (Voice and Accountability (VA), Political Stability and Violence (PSNV), Government Effectiveness (GE), Regulatory Quality (RQ), Rule of Law (RL) and Control of Corruption (CC). The analysis of links among these variables and the classification of countries pursuant to the Terrorism Risk
Index indicates that the highest median values (higher values of variables from the Governance Matters database are considered to be a better result) concern groups assessed as the lowest terrorism risk countries (the median values are as follows: Voice and Accountability (VA) 0.31, Political Stability and Violence (PSNV) 0.27, Government Effectiveness (GE) 0.14, Regulatory Quality (RQ) 0.30, Rule of Law (RL) 0.10 and Control of Corruption (CC) 0.05. The level of voice and accountability, political stability, the rule of law or control of corruption as variables assessing the institutional environment is therefore different in countries differing in terrorism risk. The purpose of this article was to make an alternative classification of countries by means of a logit analysis and compare the results with those of the original classification. Pursuant to this analysis, 141 countries have been classified into the above 4 risk groups where differences with the original classification are apparent in 10 countries, the probability of the classification of which into the given group is higher than 0.75 (Angola, Chile, Ecuador, France, Honduras, Rwanda, Singapore, Congo, Laos and Tanzania). Similarly Angola, Chile, Ecuador, France, Honduras, Rwanda, and Singapore have been classified into the low terrorism risk group pursuant to the logit analysis (according to the Terrorism Risk Index they were classified into the medium risk group). Out of the total recorded terrorist attacks carried out in 2010, 0.34 % occurred in these countries, which does not exceed the values typical for countries classified according to the original classification into the low terrorism risk group. The reasons for classifying Congo, Laos and Tanzania into the low terrorism risk group in compliance with
83 the logit analysis results are apparent
from the highest values of Political Stability and Violence (PSNV) for these countries (low risk of the government destabilization or overthrow and low terrorism risk). However, according to the information about recorded terrorist acts committed in these three countries in 2010, their death toll reached 99. The institutional environment quality therefore does not necessarily have to be
a prerequisite for terrorism risk and expert estimates of this data do not reflect the real danger of terrorist acts in all countries, which is especially apparent as concerns the groups of countries characterized by a long-term instability which can have an adverse effect on the security environment of the given country throughout the year and cannot be reliably reflected in a single figure per the whole calendar year.