DOI: https://doi.org/10.30884/jogs/2023.01.05
Alina Khokhlova, HSE University, Moscow
Andrey Korotayev, HSE University, Moscow, Russia; RUDN University, Moscow
Much has been written about the destabilizing factors in the Middle East and North Africa (MENA) (and the Afrasian instability macrozone in general) since 2011; however, the characteristics of its destabilization dimensions have been little discussed. Our principal component analysis based on the CNTS, Global Terrorism and Center for Systemic Peace databases, shows that some MENA countries are the most violently destabilized in the entire world for the period of 1970–2018 compared to all other countries. These results are supported by the mean factor scores of the principal components of socio-political destabilization for four world-system regions for three observation periods which show that both for the 1970–2018 and post-2011 periods, the Afrasian instability macrozone in general, and the MENA region in particular, emerge as the areas with the highest mean values of bloody destabilization factor scores. Moreover, the tests conducted show that MENA is the only region where destabilization component of mass protest is associated with repressions both for the general observation period (1970–2018) and for the post-Arab Spring period (since 2011) while for other regions the correlation with the purges/repressions indicator is insignificant, albeit positive (South America and sub-Saharan Africa) or even insignificant and negative (Western Europe). This seems to imply that in the MENA region protests are much more systematically accompanied by mass repressions than in other parts of the world. On the other hand, for Sub-Saharan Africa we find the presence of a number of terrorist attacks among the significant contributors to mass protest destabilization, suggesting that mass protest destabilization in this part of the world is also of a rather special nature, with a very substantial violent component. Meanwhile, the principal component analysis of destabilization in the MENA region (considered as a semi-peripheral world-system area) in comparison with South America (another world-system area), Western Europe (considered as a part of the world-system core), and Sub-Saharan Africa (considered as a part of the world-system core) has yielded the following results. In general, we find that the highest percentage of destabilization variance is explained by the mass protest principal component for the world-system core (represented by Western Europe); on the other hand, the lowest percentage of the destabilization variance is explained by the bloody destabilization principal component precisely for this part of the world. We also find that the highest percentage of destabilization variance is explained by the bloody principal component for the world-system periphery (represented by sub-Saharan Africa); on the other hand, the lowest percentage of the destabilization variance is explained by the mass protest destabilization principal component precisely for sub-Saharan Africa. The world-system semi-periphery appears here between these poles. The MENA region (which is the core of the Afrasian instability macrozone) ranks second in terms of both mass protest and bloody destabilization, with very high levels of both (while South America occupies an intermediate position between MENA and Western Europe).
Keywords: MENA, the Afrasian instability macrozone, the Arab Spring, the World System, principal component analysis, socio-political destabilization, repressions, Sub-Saharan Africa, Western Europe, Latin America.
Triggered by the Arab Spring, the global wave of socio-political destabilization resulted in a very significant increase in socio-political instability in absolutely all world-system zones in different ways and not entirely synchronously (Grinin and Korotayev 2012; Кorotayev, Meshcherina et al. 2016; Korotayev, Shishkina, Issaev 2016; Akaev et al. 2017; Korotayev, Shishkina, Lukhmanova 2017; Ortmans et al. 2017; Korotayev, Meshcherina, Shishkina 2018; Korotayev, Romanov, Medvedev 2019; Khokhlov et al. 2021; Korotayev, Shishkina, Khokhlova 2022).
The factors of this socio-political destabilization of 2011 in the Middle East and North Africa (MENA) have attracted serious attention from various researchers. The existing studies devoted to the analysis of socio-political destabilization in MENA have shown that the genesis of explosive sociopolitical destabilization in the Arab countries in 2011 was determined by a number of political factors (type of regime, intra-elite conflict, and ineffectiveness of instruments of power transfer), social factors (presence of inter-tribal, inter-confessional, and other social conflicts and contradictions), demographic factors (structural demographic risks, e.g., the ‘youth bulge,’ unemployment among young people with higher education, etc.), historical factors (major conflicts in the recent past), religious factors (in particular, the inclusion of Islamists in the legal political processes), economic factors (e.g., the second wave of agflation which led to an explosive growth in food prices), and some subjective (socio-psychological and cultural-historical) factors (Bilyuga 2017; Butenschøn 2015; Grinin and Korotayev 2012; Grinin, Korotayev, Tausch 2019; Hussain and Howard 2013; Korotayev et al. 2011; Korotayev and Zinkina 2011, 2022; Malik and Awadallah 2013; Slinko et al. 2017; Steinert-Threlkeld 2017).
At the same time, little has been said about dimensions of destabilization and their peculiarities for this region after the Arab Spring. Using descriptive statistical methods, we distinguished between destabilization periods of mass protest in MENA states, observing 19 countries (2011–2013 and since 2016) and destabilization period of terror (2013–2016), coinciding with the rise of radical Islamist terrorism in the region (Korotayev and Khokhlova 2022).
However, it still remains unclear whether MENA will emerge as the most destabilized region, which types of destabilization are typical for it, what are characteristics of these destabilization types and what are their peculiarities in comparison with other world-system zones.
Types of Destabilization Processes
Much has been written on the problem of typology of socio-political destabilization. In general, researchers distinguish between internal and inter-state types of socio-political destabilization, while all acts of violence, conflict situations and contentious socio-political events are treated as destabilization processes (see, e.g., Flanigan and Fogelman 1970; Hibbs 1973; Gurr and Lichbach 1986; Alesina et al. 1996; Benson, and Kugler 1998; de Haan 2007; Jong-A-Pin 2009; Celestino and Kristian 2013; Klomp and de Haan 2013).
The first attempts to apply principal component analysis to indicators of destabilization were made already in the 1960s and 1970s to highlight the main types of destabilization (Tanter 1966; Hibbs 1973). In these studies, limited to the period 1948–1967, researchers tended to identify the ‘anomic violence’ type of destabilization which includes anti-government demonstrations, strikes and riots, and the ‘civil war’ type as the second destabilization dimension, which includes armed insurgencies and assassinations.
Douglas Hibbs's (1973) analysis of aggregate data from 108 nations on the causal structures underlying mass political violence within nations (for the period l948–1967) showed that coups were positively correlated with previous coups experience, and defense expenditure as a proportion of total government expenditure, and negatively correlated with level of development of (non-military) socio-political institutions. He defined the focus of his research as events of domestic violence that are non-systemic in nature, have direct and immediate political significance, and involve collective or mass actions. The variables that fit his theoretical dimensions are Riots, Guerilla Warfare, General Strikes, Assassinations, Deaths from Political Violence, and Anti-Government Demonstrations (Hibbs 1973: 19). Hibbs's (1973) analysis identified two dimensions (factors): the ‘anomic violence’, which included riots, anti-government demonstrations and strikes, and the ‘civil war’ that combined such forms of political violence as armed assaults, murders and assassinations.
Richard Jong-A-Pin (2009) defines the following four types of socio-political destabilization: mass civil protests (demonstrations, riots and strikes); political aggression (civil war, guerilla warfare, revolutions, assassinations, internal conflicts, ethnic conflicts); political institutions instability (strikes, fractionalization, ruling party incumbent period, society polarization, general elections number, governmental crises) and political regime instability (constitutional changes, coups, political regime changes, government change and religious factors).
Elena Slinko and others apply principal component analysis to identify the following four types of socio-political destabilization in their cross-national research using the CNTS database: mass protest destabilization (with the main contributions on the part of anti-government demonstrations, general strikes, and riots); abrupt regime change (predominantly due to coups); bloody destabilization (terror attacks etc.) and intra-elite destabilization (with the main contributions on the part of political crises, assassinations, purges and coups) (Slinko et al. 2018). Slinko and others' analysis of the relationship between socio-political and economic indicators with four types of destabilization shows that each type of destabilization has its own socio-political conditions that contribute to the risk of its occurrence (Ibid.). They also show that different dimensions of socio-political destabilization have different effects on types of destabilization. At the same time, the chronological frameworks of the paper are limited to 2010 because, as they explain, of the ‘structural shift’ (Akaev et al. 2017; Korotayev, Khokhlova and Tsirel 2018) caused by the events of the Arab Spring.
This research aims to contribute to this block of literature with typology study of the world-systems destabilization in order to determine the place of MENA and the Afrasian instability macrozone in the hierarchy of the most destabilized regions of the world for the observation period including 2011–2018 (in contrast to Slinko et al. 2018), and to investigate its specific destabilization dimensions peculiarities.
Research Design, Materials and Method
Immanuel Wallerstein's world-systems approach is pivotal for the present study (Wallerstein 1974, 1979, 1980, 1987, 1988, 2004); according to him, this system consists of the following three components:
1) the ‘core’ (with respect to the modern World System, this component refers to the high-income OECD countries with developed industrial / post-industrial economics and strong state);
2) the ‘periphery’ – countries and regions that specialize in the resource extraction, have a predominantly agricultural economy and a weak state (the most underdeveloped and low-income countries of the Third World);
3) the ‘semi-periphery’ (modernized countries of the ‘second wave’; socialist countries of the twentieth century, all the BRICS countries of the twenty-first century, middle-income countries of the Third World).
According to Wallerstein, the capitalist world-system is based on the non-equiva-lent division of labor and the exploitation of the periphery by the core (of course, today this point needs important qualifications [see, e.g., Grinin, Korotayev 2015; Korotayev, Zinkina et al. 2011; Korotayev, Goldstone, Zinkina 2015). The core countries force the periphery to supply raw materials at lower prices, which contributes to the prosperity of the center and the impoverishment of the periphery (Wallerstein 1974, 1979, 1980, 1987, 1988, 2004).
Thus, following Wallerstein, the countries of Western Europe are taken as an example of the world-system ‘core’, sub-Saharan Africa as the ‘periphery’, and South America and the MENA countries as examples of the ‘semi-periphery’.2
We argue that the ‘semi-periphery’ regions are the most unstable among the three world-system zones mentioned above since the highest risks of socio-political instability are typical for the countries with intermediate values of GDP per capita which are typical of this world-system zone, and not the countries with the highest or lowest values, since it is observed that, up to a certain value of GDP per capita, economic growth predicts an increase in the risks of socio-political destabilization (Bilyuga et al. 2016; Korotayev, Bilyuga, Shishkina 2016, 2017a, 2017b, 2018; Korotayev, Vaskin et al. 2017, 2018, 2021; Korotayev, Khokhlova and Tsirel 2018; Vaskin et al. 2018; Korotayev, Sawyer, Grinin et al. 2020; Korotayev, Sawyer, Romanov 2021; Korotayev, Medvedev, Zinkina 2022). At the same time, the destabilization period after the Arab Spring (2011) produced a serious effect on the socio-political dynamics of the MENA semi-periphery zone (Akaev et al. 2017; Korotayev, Meshcherina, and Shishkina 2018).
So our first hypothesis is as follows:
H#1: Latin America and the MENA region as semi-peripheral zones of the World System are the most unstable of the four for the period before the Arab Spring, while for the entire observation period as well as after 2011 the highest destabilization values are observed for the MENA region due to the Arab Spring effect.
At the same time, taking into account the phenomenon of the Arab Spring and the increase in the rate of terrorism in the MENA region in 2013–2014 with the expansion of Islamic State of Iraq and the Levant (ISIS – banned organization in the Russian Federation) (Korotayev and Khokhlova 2021), we hypothesize that:
H#2: The MENA region countries are the most violently destabilized among the four analyzed regions.
The total 1970–2018 dataset contains 10,133 observations, including 1,201 observations for MENA, 1,244 observations for Western Europe, 588 observations for South America and 2255 observations for Sub-Saharan Africa.
We use the Cross-National Time-Series Database (CNTS [Banks and Wilson 2020]) as the principal database for the present research.3 In addition to the CNTS, we use the Global Terrorism Database (START 2020) for the number of terrorist attacks and the number of people killed in terrorist attacks variables; we take data on the number of coups and coup attempts from the Coups d’Etat 1946–2017 database (Center for Systemic Peace 2020).
To identify the principal components (types of instability) for the whole world, we use a principal components analysis. To extract a sufficient number of principal component eigenvalues, we use a modified version of the Kaiser criterion, which requires the eigenvalue to be greater than 0.95, and Cattell's scree test (Cattell 1966). A detailed description of the principal component analyses that we have performed can be found in the online supplementary material.
Tests
Our principal component analyses identify the following main components of destabilization: (1) ‘bloody destabilization’ with the main contributions from the Number of Deaths in Terrorist Attacks, Number of Terrorist Attacks, and Guerilla Warfare; (2) ‘mass protest destabilization’ with the main contributions from Anti-Government Demonstrations, Riots, and General Strikes; and (3) ‘elite destabilization’ with the main contributions from Governmental Crises, Coups and Coup Attempts, Assassinations, and Purges (see the Online supplementary material for details). In what follows, we pay most attention to the first two main components.
To investigate which countries contribute most to the abovementioned components the most we use averages and provide the top-20 most destabilized countries in the world by mass protests and bloody destabilization factors, see Table 1.1.
Table 1.1 demonstrates that almost half of the world's most violently destabilized countries are in the MENA region: Iraq, Afghanistan, Somalia, Syria, Yemen, South Sudan, Turkey, Algeria, Egypt and Libya. One should also note that Pakistan which is sometimes attributedto the ‘Greater Middle East’ and the ‘Broader Middle East and North Africa (BMENA)’ (see, e.g., Perthes 2004; Latif, Abbas 2011; Markakis 2015), and Nigeria, home to the radical Islamic movement Boko Haram (banned organization in the Russian Federation), which pledged its allegiance to ISIS in 2015, are also among the top-20 most violently destabilized countries. In addition, two MENA countries, Iraq and Afghanistan, occupy the top two spots, followed by Pakistan in the third place. Together, the scores for the MENA countries, which together with Pakistan, Nigeria, and Mali are part of the ‘semi-periphery system’ (see Table 1.2) account for more than 70 per cent of the total violent destabilization factor score points for the world's top-20 violently destabilized countries.
It should also be noted that Pakistan, Nigeria, Mali, Somalia, and South Sudan are all part of the African zone of instability (which, in addition to the Greater Middle East, includes, the Sahel macro zone of sub-Saharan Africa with Nigeria, and highly destabilized countries such as Mali, Somalia and South Sudan). This macro zone has been shown to be characterized by particularly high levels of violent destabilization (Korotayev, Issaev et al. 2016; Korotayev, Grinin, Malkov et al. 2021 etc.). Hence, this study provides additional support for this conclusion.
The world's top-20 violently destabilized countries also include Colombia and Peru, the countries of the South American region, the second ‘semi-periphery zone’. Other countries, namely, India, Ukraine, Philippines, El Salvador and Sri Lanka belong to the regions which we do not analyze in our study (except for the UK which is a Western European state).
Concerning mass protest type of destabilization, it is obvious that is not very typical of the ‘semi-periphery’ zones: only Pakistan, Israel and Egypt occupy the eighth, twelfth and seventeenth places respectively in the top-20 most non-violently destabilized countries. The largest share of this destabilizing factor belongs to Western European countries, India and China. At the same time, we find countries from South America in the world's top-20 non-violently destabilized countries; they are Argentina, Bolivia and Chile.
In the next stage, we divide the observation period into two intervals and analyze how the list of countries changes (see Table 1.2).
Table 1.2 demonstrates that the MENA countries as part of the ‘semi-periphery zone’ account for more than a quarter of all the places in the list of the top-20 most violently destabilized countries in the world prior to 2011; these countries are Iraq, Afghanistan, Algeria, Turkey and Lebanon (with Pakistan as the sixth country if we take into account the BMENA/Afrasian instability macrozone). Moreover, Iraq and Colombia virtually share the top spot as their pre-2011 scores are about the same (3.1 and 3 respectively), while other countries score at least 1.5 times lower.
The South American ‘semi-periphery region’ countries also make up a large proportion of the list: Colombia ranks first and Peru fourth.
After the Arab Spring, the scores for the first two countries (Iraq and Afghanistan) account for almost 45 per cent of all the countries scores. Overall, the MENA countries' score after 2011 account for about 66 per cent of all scores for the top-20 most violently destabilized countries. It should be noted that the first seven rows of the ranking are occupied by the MENA countries, Pakistan and Nigeria, and the list is interrupted by Ukraine, the Philippines and India, which are not included in the four regions of the world-system zones analyzed in this paper. Thus, we see that among the four regions analyzed, MENA is the most violently destabilized. On the other hand, if we consider the Afrasian zone of instability as a whole, we will find out that it includes most of thetop-20 countries.
Table 1.3 demonstrates that, with the exception of Israel, none of the MENA countries appear in the top-20 most non-violently unstable countries in the world before 2011 (in addition to Pakistan from the Afrasian instability macrozone). Serious destabilization of the mass protest type in MENA occurs after the Arab Spring, and predictably affects Egypt, Turkey, Sudan and Bahrain, but together their scores explain 11 per cent of the list of 20 countries.
To sum up, the preliminary results of the factor analysis of socio-political destabilization on the world sample show that the MENA countries, belonging to the ‘semi-periphery’ world-system zone, are the most violently destabilized in the world for the period 1970–2018: together with Pakistan, Nigeria, Somalia and Mali (from the Afrasian instability macrozone) their scores account for more than 70 per cent of the total scores of the top-20 destabilized countries. A serious escalation of bloody destabilization predictably occurs after 2011, when countries in this region account for more than two thirds of values of the world's top-20 violently destabilized states.
The next task is to identify what are the peculiarities of socio-political destabilization factors in the MENA region and which indicators each of the three mentioned dimensions include.
The Middle East and North Africa
In this section, we use principal component (PC) analysis to examine the characteristics of the dimensions of socio-political destabilization in MENA for 1970–2018 (see Tables 2.1 and 2.2).4
The principal components analysis, with factors rotated by the varimax method, gives the following results for MENA in 1970–2018 (see Table 2.2).
Table 2.2 demonstrates that the PC1 of destabilization in MENA in 1970–2018 is the ‘bloody’ one, which, according to Table 2.1, accounts for about 30 per cent of all instability phenomena. We also see that the PC1 is mainly generated by guerilla warfare, the number of terrorist attacks and the number of people killed in those attacks and to a lesser extent by assassinations. The PC2 reflects mass protest destabilization which accounts for 22 per cent of the explained variance. It should be noted that in addition to the indicators typical of mass destabilization in the world sample,5 such as general strikes, riots and anti-government demonstrations indicators, the PC2 for MENA mass destabilization also includes purges/repressions with a load twice as high as that of the PC2 for assassinations in the world sample. This seems to imply that protests in the MENA region are associated with greater repressions than in other parts of the world. The elite destabilization for MENA is split into two components: PC3 and PC4, which together account for 22 per cent of the variance, comparable to the PC2 – mass protest destabilization component.6
Further we analyze the same components after dividing the observation period into two intervals: before and after 2011 (see Tables 3.1 and 3.2).
As we see in Tables 3.1 and 3.2, the loadings of the MENA region's socio-political destabilization indicators before and after the 2011 turbulence have their own peculiarities. Although PC1 is ‘bloody’ for the both periods and PC2 for both periods describes ‘mass protest’ destabilization; PC3 represents ‘elite destabilization’ for both periods (in fact, PC4 for the 2011–2018 observation period primarily reflects elite destabilization), the results are different in terms of the component indicator sets. The assassinations indicator is significant for all of the three dimensions of destabilization with the highest eigenvalues before 2011. Before 2011, PC1 also includes government crises in addition to guerilla warfare, number of terrorist attacks and number of people killed in terrorist attacks (which were typical of the1970–2010 period) and assassinations also includes governmental crises, while this is not the case for PC1 for the period after 2011. It is also possible to look at the growth of guerilla warfare, number of terrorist attacks and number of people killed in terrorist attacks after 2011: the largest escalation is observed for guerilla warfare which grows from 0.304 to 0.903. Predictably, a strong escalation is observed for the loadings of the indicators number of terrorist attacks and number of people killed in terrorist attacks. Thus, this implies a decline in the role of assassinations in bloody destabilization in the MENA region after 2010 and an increase in the importance of guerilla warfare.
The PC2 for MENA includes, in addition to general strikes, riots and anti-government demonstrations,7 assassinations before 2011 and repression after the start of the Arab Spring. After 2011, the PC2 shows other changes: we see that the assassinations indicator is missing for the observation period 2011–2018. Moreover, the loading value for the riots indicator, which includes some violence (see Banks and Wilson 2020), is lower than before 2011. In general, one may observe a decline in the contribution of the assassinations to the mass protest destabilization after 2010 (note that we could observe the same above with the respect to the bloody destabilization component). After 2010, one could also observe the increasing contribution of general strikes and anti-government demonstrations to the mass protest destabilization and the emergence of purges / repressions as a significant contributor. This seems to be related to the fact that after 2010, mass protests in MENA became particularly closely associated with repression (this was not observed, e.g., in Western Europe and South America and quite predictably, repression is not found among the contributors to the respective principal component [see below]).
It is important to note that while the percentage of variance explained for bloody destabilization before and after the Arab Spring barely changed (from 28.43 to 29.91 per cent), this increase in loadings for mass protest destabilization is very significant (from 18.15 to 23.87 per cent).8
As a result, the types of destabilization in the MENA region have their own specificities shown in the indicator sets. It can be observed that the role of assassinations in the bloody destabilization in the MENA region after 2010 declined while the value of guerilla warfare indicator increased. The same trend for assassinations is observed for mass protest destabilization before and after 2010 while the loadings for general strikes and anti-government demonstrations increased significantly. In addition, purges / repressions are observed as crucial contributors to mass protest destabilization after the start of the Arab Spring. It is also shown that the percentage of variance explained for bloody destabilization before and after the Arab Spring has hardly changed (from 28.43 to 29.91 per cent), this increase in value for mass protest destabilization is very significant (from 18.15 to 23.87 per cent).
Western Europe
In the next stage, we repeat the same tests for Western Europe. In Table 4.1 we identify the main components (types of destabilization for the region; we apply the same principal components analysis for 1970–2018 in order to further compare the results with the ones for MENA.
The principal components analysis, with factors rotated by the varimax method, yields the following results for Western Europe in 1970–2018 (see Table 4.2).
Predictably, the world-system core represented by the Western European countries, so far is much more vulnerable to ‘mass protest destabilization’ type (30 per cent) than to ‘bloody destabilization,’ which accounts for half of the first component (15 per cent). It is predictable that the ‘bloody destabilization’ is particularly typical of Western Europe before the twenty-first century, as is elite destabilization type after the last democratic transitions in the region in 1975.9 These hypotheses can be tested after splitting the sample into the two periods before and after 2011 (see Tables 5.1 and 5.2).
The principal components analysis, with factors rotated by the varimax method, yields the following results for Western Europe in 1970–2010 and 2011–2018 (see Table 5.2).
In fact, Tables 5.1 and 5.2 suggest that before the Arab Spring, PC1, although not as obvious as for the MENA sample, represents bloody destabilization with the highest loadings for assassinations, guerilla warfare, number of terrorist attacks, number of people killed in terrorist attacks, accompanied by riots and anti-government demonstrations, this component explains 30 per cent of variance. The indicator of mass protest destabilization is represented by PC2, which explains less than 15 per cent of the variance and is accompanied by assassinations and governmental crisis indicators in addition to general strikes, riots and anti-government demonstrations.11
The results for the post-Arab Spring period are different as PC1 apparently blends with PC2, so that the highest PC1 loadings reflect mass protest destabilization, contributed by general strikes, riots and anti-government demonstrations. The bloody destabilization component for Western Europe for 2011–2018 splits into two while we do not observe a pronounced elite destabilization PC for the region after 2011.
All in all, Western Europe is predictably more unstable than MENA in terms of mass protest destabilization which is accompanied by governmental crises while no purges/ mass repressions are observed for the region after 2010 while this indicator emerges as the key contributor for MENA (and the Afrasian instability macrozone, in general) after the Arab Spring.
South America
In the next stage, we repeat the same tests for the South American region. In Table 6.1 we identify the main types of destabilization for the region using the principal components analysis for 1970–2018.
Tables
6.1 and 6.2 show that as well as for MENA, PC1 for South America reflects the bloody
type of destabilization with typical ‘bloody’ indicators12 such as assassinations,
number of terrorist attacks and number of people killed in them.
PC2 also includes ‘typical’13 indicators of mass protest instability,
including general strikes, riots and anti-government
demonstrations, so this component may be called the ‘mass protest
destabilization’ type. ‘Elite destabilization’ in South America is divided into
PC3 and PC4 and has its own atypical features due to the region's history.14
In the next stage, we look what happens when we divide the observation period into two parts – before and after the Arab Spring.
After dividing the observation period in two (before and after the Arab Spring), we see that the 2011 phenomena had an effect on the socio-political dynamics of South American countries: the percentage of variance for all three types of destabilization increased sharply. As for the MENA countries, PC1 is defined for the both periods as the bloody destabilization component which accounts for 26–30 per cent of the explained variance, mass protest destabilization (PC2) accounts for 19–23 per cent of the variance and ‘elite destabilization’ (PC3 and PC4) accounts for 13–24 per cent of the va-riance explained.
Prior to 2011, the most heavily loaded indicators in PC1 are the same as in MENA: assassinations, guerilla warfare, number of terrorist attacks and number of people killed in terrorist attacks (see Table 2.2). PC2 includes a typical set of indicators15 consisting of general strikes, riots and anti-government demonstrations.
Since 2011, PC1 for South America which reflects bloody destabilization is accompanied by general strikes instead of assassinations; one could also observe some growth in assassinations, guerilla warfare, number of terrorist attacks and number of people killed in terrorist attacks indicators values, the largest escalation is observed for guerilla warfare (from 0.490 to 0.771). There was a small increase in the PC2 (mass protest destabilization) key indicators (general strikes, riots and anti-government demonstrations) is observed. It should be noted that although South America is the ‘semi-periphery’ zone of the World-System, like the MENA region, its PC2 does not include the ‘purges/ mass repressions’ indicator, which the MENA PC2 (‘mass protest’ destabilization component) does.
Sub-Saharan Africa
In the next stage, we replicate the same tests for Sub-Saharan Africa. In Table 8.1 we identify the main principal components (types of instability) for the region for 1970–2018.
From Tables 8.1 and 8.2 it becomes clear that among the four analyzed regions, sub-Saharan Africa is the leader in the percentage of the variance explained by bloody destabilization type for 1970–2018, accounting for 32 per cent of the variance explained, 2 per cent more than for MENA. PC1 includes the highest loadings for guerilla warfare, number of terrorist attacks and number of people killed in terrorist attacks indicators which are ‘typical’ of this type of destabilization for the world sample.16
Mass protest destabilization (PC2) explains only 16 per cent of the variance which is the lowest result for all the four regions. PC2 includes the highest loadings for general strikes, riots and anti-government demonstrations which are ‘typical’ of the mass protest type of destabilization for the world sample.
The test results with the observation period divided into two are presented in Tables 9.1 and 9.2.
Tables 9.1 and 9.2 demonstrate that after dividing the observation period into two parts (before and after the Arab Spring), the percentage of variance explained by bloody destabilization reaches its all-time high of 33 per cent for the 2011–2018 period for the Sub-Saharan African countries. The differences in the percentage of the principal component values for the region before and after the Arab Spring show that the 2011 phenomena for the Sub-Saharan region resulted predominantly in the escalation of bloody destabilization while a relatively small mass protest destabilization escalation is observed.
It should be noted that before 2011, the PC1 for Sub-Saharan Africa has the highest loadings of indicators of mass protest destabilization (which is not typical of the MENA region, the MENA's PC1 reflects bloody destabilization) and includes general strikes, riots and anti-government demonstrations accompanied by the number of terrorist attacks indicator, which is a unique feature for the Sub-Saharan region (where, in fact, the first PC turns out to be a mixture of the mass protest and bloody destabilization). One may say that the presence of the number of terrorist attacks among the significant contributors to mass protest destabilization for Sub-Saharan Africa before 2011 suggests that the mass protest destabilization in this part of the world was of a rather special type, involving a rather substantial violent component.
The second principal component prior to 2011 is the bloody destabilization with the highest values for guerilla warfare, number of terrorist attacks, number of people killed in terrorist attacks and general strikes, which is also not typical of other regions.
After 2011, the principal components for Sub-Saharan Africa coincide with those for MENA, with bloody destabilization type coming as PC1, followed by mass protest destabilization as PC2. After 2011, there is sharp escalation in the loadings of the bloody destabilization indicators, which also include assassinations and anti-govern-ment demonstrations after 2011, but no longer include general strikes.
It is interesting to note that the PC2 indicators set after 2011 are the same as before the Arab Spring for the Sub-Saharan Africa region (of particular interest is that the number of terrorist attacks remains a significant contributor to mass protest destabilization).17
Discussion
Using the results of the above tests on the percentage of variance explained by each type of socio-political destabilization factor for the above four world-system regions in 1970–2018 (see Tables 2.1, 4.1, 6.1 and 8.1), it is possible to provide the next general comparisons (see Figures 5 and 6).
From the figures above we may conclude that bloody and mass protest destabilization types in MENA for 1970–2018 together account for the largest percentage of variance explained among the four regions analyzed (52 per cent), which proves our first hypothesis that the MENA region as the world-system ‘semi-periphery’ zone turns out to be the most socio-politically unstable region in the world. The MENA region is followed by Sub-Saharan Africa (49 per cent), Western Europe (45 per cent) and South America (41 per cent), which shows that South America, on the contrary, as a ‘semi-periphery zone’ like MENA, is the least unstable region of the four regions mentioned above.18
The characteristics of socio-political destabilization in the MENA region may be described by a relatively high level of bloody destabilization accompanied by a relatively high level of mass protest destabilization. For Sub-Saharan Africa, the highest level of bloody destabilization type is accompanied by the lowest level of mass protest destabilization rate. On the contrary, for Western Europe, the highest level of mass protest destabilization is accompanied by the lowest level of bloody destabilization type. Finally, South America is characterized by an intermediate level of bloody destabilization as well as an intermediate level of mass protest destabilization.
Conclusions
The present paper aims to determine the place of MENA (and the Afrasian zone of instability, in general) in the hierarchy of the most destabilized regions of the World System for the observation period including the post-Arab Spring phase (2011–2018) as well as before 2011 and to examine the region's unique destabilization peculiarities.
Our analysis based on the CNTS, Global Terrorism and Center for Systemic Peace databases shows that some MENA countries, belonging to the world-system ‘semi-periphery’ MENA zone are in the list of the top-20 most violently destabilized states in the world for the period of 1970–2018: together with Pakistan, Nigeria, and Mali (belonging to the Afrasian instability macrozone), their scores account for more than 70 per cent of the total scores. In the MENA region, the serious escalation of bloody destabilization predictably occurred after 2011, when countries of this region account for 66 per cent of the factor scores of the world's top-20 violently destabilized states.
In addition, our principal component analysis allows defining the following important patterns in the development of socio-political destabilization in the MENA region.
First, with regard to bloody destabilization in the MENA region, we observe the decline in the role of the assassinations indicator for the region after 2010 and the increase in importance of the guerilla warfare indicator.
Second, with regard to peculiarities of the mass protest destabilization in the MENA region, it is found that after 2010 one could identify the increasing importance of general strikes and anti-government demonstrations compared to the pre-Arab Spring period and emergence of purges / repressions as a significant contributor to the abovementioned component for the region after 2010. The high values of purges/repressions indicator loadings are typical both for the general observation period (1970–2018) and for the period after the Arab Spring (since 2011), while for other regions the values of this indicator loadings are insignificant (South America and Sub-Saharan Africa) or even insignificant and negative (Western Europe for the observation periods 1970–2018 and 1970–2010; for 2011–2018 this indicator is equal to 0). This seems to imply that in the MENA region (and in the Afrasian instability zone in general) protests are accompanied by mass repressions much more systematically than in other parts of the world. On the other hand, we find the presence of a number of terrorist attacks among the most significant contributors to mass protest destabilization for sub-Saharan Africa, which suggests that the mass protest destabilization in this part of the world is of a rather special kind, involving a very substantial violent component.
Finally, it is also important to emphasize that for MENA, while the percentage of variance explained by bloody destabilization before and after the Arab Spring has hardly changed (from 28.43 to 29.91 per cent), the increase in value for mass protest destabilization is very significant: from 18.15 to 23.87 per cent. For Western Europe, the mass protest destabilization component explains much more of the variance than the same factor for MENA for 1970–2018 (30 and 22 per cent respectively), while Sub-Saharan Africa's bloody destabilization component explains slightly more of the variance than for MENA for the same observation period (32 and 30 per cent respectively); however, MENA turns out to be the most destabilized region when the mass protest and bloody destabilization factors are taken together (52 per cent of the variance explained) for 1970–2018. South America's mass protest and bloody destabilization dimensions are both smaller than MENA's for 1970–2018.
In general, we find that the highest percentage of the destabilization variance is explained by the mass protest principal component for the world-system core (represented by Western Europe); on the other hand, the lowest percentage of the destabilization variance is explained by the bloody destabilization principal component precisely for this part of the world.
We also find that the highest percentage of the destabilization variance is explained by the bloody principal component for the world-system periphery (represented by sub-Saharan Africa); on the other hand, the lowest percentage of the destabilization variance is explained by the mass protest destabilization principal component precisely for Sub-Saharan.
The world-system semi-periphery appears here in between these poles. The MENA region (which is the core of the Afrasian instability macrozone) ranks second in terms of both mass protest and bloody destabilization, with very high levels of both (while South America occupies an intermediate position between MENA and Western Europe).
NOTES
1 This research has been supported by the Russian Science Foundation (Project No. 19-18-00155).
2 The lists of countries included in each of the four regions can be found in the online supplementary material (see Part 1 of the online supplementary material).
3 The CNTS database description is provided in Part 2 of the online supplementary material.
4 See para 3 of the online supplementary material to investigate our method of indicators sample formation.
5 See Table 3.2 of para 3 of the online supplementary material.
6 PC3 consists of cnts_domestic1 (assassinations) and cnts_domestic4 (governmental crisis) indicators, while PC4 is presented by coups and coups attempts and repressions. The division of these indicators into two deserves a separate study, so we decided to concentrate only on mass protest and bloody destabilization in this paper. The elite destabilization for all the regions will be discussed in another article.
7 These indicators are of the typical mass protest destabilization according to the tests results for the whole world sample, see Tables 3.1 and 3.2 of online supplementary material para 3).
8 As elite destabilization factor is divided into two components after 2011 (PC3 and PC4) with its own features as PC3 contains only assassinations and governmental crisis indicators while PC4 – repressions, riots and coups and coup attempts, we consider the problem of elite destabilization factor to be a topic for a separate research.
9 Obviously, ‘elite destabilization’ type is represented by a high value of coups and coup attempts as the chronological framework embraces the third wave of democratization in Europe of 1974–1975.
10 Because purges and coups and coup attempts indicators are equal to 0 for Europe after 2011 we have to exclude these indicators from the model for 2011–2018 observation period.
11 Concerning elite destabilization type (PC3) in Western Europe in 1970–2010, it is important to note that it consists of high loadings for repressions and coups and coup attempts indicators – those variables which are absent for the same observations for 2011–2018.
12 See Table 3.2 of para 3 of the online supplementary material.
13 See Table 3.2 of para 3 of the online supplementary material.
14 Where the third principal component is responsible for ‘regime change’ elite destabilization type while PC4 more defines ‘regimes response or its sanctions’ destabilization as it consists of assassinations and repressions. These results are interesting and deserve a separate research.
15 See Table S3.2 of part 3 of the online supplementary material.
16 See Table 3.2 of para 3 of the online supplementary material.
17 Elite destabilization for both observed periods is divided into two and has its own features.
18 We consider these discrepancies to be investigated in a separate study.
REFERENCES
Akaev, A., Korotayev, A., Issaev, L. and Zinkina, J. 2017. Technological Development and Protest Waves: Arab Spring as a Trigger of the Global Phase Transition? Technological Forecasting and Social Change 116: 316–321.
Alesina, A., Ozler, S., Roubini, N., and Swagel, P. 1996. Political Instability and Economic Growth. Journal of Economic Growth 1 (2): 189–211.
Banks, A., and Wilson, K. 2020. Cross-National Time-Series Data Archive. Jerusalem, Israel: Databanks International. URL: http://www.databanksinternational.com.
Benson, M., and Kugler, J. 1998. Power Parity, Democracy, and the Severity of Internal Violence. Journal of Conflict Resolution 42 (2): 196–209.
Bilyuga, S. 2017. Type of Regime and Indices of Sociopolitical Instability: A Quantitative Analysis. Sravnitelnaya Politika 8: 95–112. Original in Russian (Белюга С. Тип режима и индексы социально-политической нестабильности: Опыт количественного анализа. Сравнительная политика 8: 95–112).
Bilyuga, S., Shishkina, A., Zinkina, J., and Korotayev, A. 2016. Global Correlation between GDP Per Capita and the Level of Sociopolitical Destabilization between 1960 and 2014: A Preliminary Quantitative Analysis. In Grinin L., Ilyin I. V., Herrmann P., and Korotayev A. V. (eds.), Globalistics and Globalization Studies: Global Transformations and Global Future. Yearbook (pp. 213–219). Volgograd: ‘Uchitel’ Publishing House.
Butenschøn, N. 2015. Arab Citizen and the Arab State: The “Arab Spring” as a Critical Juncture in Contemporary Arab Politics. Democracy and Security 11: 111–128.
Cattell, R. 1966. The Screen Test for the Number of Factors. Multivariate Behavioural Research 1 (2): 245–276.
Celestino, M., and Kristian, S. 2013. Fresh Carnations or all Thorn, no Rose? Nonviolent Campaigns and Transitions in Autocracies. Journal of Peace Research 50 (3): 385–400.
Center for Systemic Peace. 2020. Coups d'Etat 1946–2018. Vienna. VA: Center for Systemic Peace. URL: http://www.systemicpeace.org/inscr/CSPCoupsAnnualv2018.xls.
De Haan, J. 2007. Political Institutions and Economic Growth Reconsidered. Public Choice 131 (3–4): 281–292.
Flanigan, W., and Edwin, F. 1970. Patterns of Political Violence in Comparative Historical Perspective. Comparative Politics 3 (1): 1–20.
Grinin, L., and Korotayev, A. 2012. Does “Arab Spring” Mean the Beginning of World System Reconfiguration? World Futures 68: 471–505.
Grinin, L. E., Korotayev, A. V. 2015. Great Divergence and Great Convergence. A Global Perspective. Cham: Springer International Publishing.
Grinin, L., Korotayev, A., and Tausch, A. 2019. Islamism, Arab Spring, and the future of democracy. World System and World Values Perspectives. Cham: Springer.
Gurr, T., and Lichbach, M. 1986. Forecasting Internal Conflict: A Competitive Evaluation of Empirical Theories. Comparative Political Studies 19 (1): 3–38.
Hibbs, D. 1973. Mass Political Violence: A Cross-National Causal Analysis. New York: Wiley.
Hussain, M., and Howard, P. 2013. What Best Explains Successful Protest Cascades? ICTs and the Fuzzy Causes of the Arab Spring. International Studies Review 15 (1): 48–66.
Jong-A-Pin, R. 2009. On the Measurement of Political Instability and its Impact on Economic Growth. European Journal of Political Economy 25 (1): 15–29.
Khokhlov, N., Vasiliev, A., Belichenko, A., Kirdyankina, P., and Korotayev, A. 2021. Echo of Arab Spring in Western Europe: A Quantitative Analysis. Mezhdunarodnye Protsessy 19 (2): 21–49. https://doi.org/10.17994/IT.2021.19.2.65.7. Original in Russian (Хохлов Н., Васильев А., Беличенко А., Кирдянкина П., Коротаев А. Эхо арабской весны в западной Европе: опыт количественного анализа. Международные процессы 19 (2): 21–49).
Klomp, J., and de Haan, J. 2013. Political Regime and Human Capital: A Cross-Country Analysis. Social Indicators Research 111 (1): 45–73.
Korotayev, A., Bilyuga, S., and Shishkina, A. 2016. GDP per Capita, Protest Intensity and Regime Type: A Quantitative Analysis. Sravnitelnaya Politika – Comparative Politics 7 (4): 72–94. Original in Russian (Коротаев А. В., Билюга С. Э., Шишкина А. Р. ВВП на душу населения, уровень протестной активности и тип режима: опыт количественного анализа. Сравнительная политика 7 (4): 72–94).
Korotayev, A., Bilyuga, S., and Shishkina, A. 2017a. The Economic Growth and Socio-Political Instability: A Global Analysis. Polis – Politicheskiye Issledovaniya 2: 155–169. Original in Russian (Коротаев А. В., Билюга С. Э., Шишкина А. Р. Экономический рост и социально-политическая дестабилизация: опыт глобального анализа. Полис. Политические исследования 2: 155–169).
Korotayev, A., Bilyuga, S., and Shishkina, A. 2017b. GDP per capita, Intensity of Anti-government Demonstrations and Level of Education. Cross-National Analysis. Politeia – Journal of Political Theory, Political Philosophy and Sociology of Politics 1 (84): 127–143. Original in Russian (Коротаев А.В., Билюга С.Э., Шишкина А.Р. ВВП на душу населения, интенсивность антиправительственных демонстраций и уровень образования. Кросснациональный анализ. Полития: Анализ. Хроника. Прогноз 1 (84): 127–143).
Korotayev, A., Bilyuga, S., and Shishkina, A. 2018. GDP Per Capita and Protest Activity: A Quantitative Reanalysis. Cross-Cultural Research 52 (4): 406–440.
Korotayev, A., Goldstone, J. A., and Zinkina, J. 2015. Phases of Global Demographic Transition Correlate with Phases of the Great Divergence and Great Convergence. Technological Forecasting and Social Change 95: 163–169.
Korotayev, A., Grinin, L., Malkov, S., et al. 2021. Sociopolitical Destabilization in the Countries of the Afrasian Instability Macrozone: Quantitative Analysis and Risk Forecasting. Moscow: Lenand/URSS. Original in Russian (Коротаев А.В., Гринин Л. Е., МалковС. Ю. и др. Социально-политическая дестабилизация в странах афразийской макрозоны нестабильности: Количественный анализ и прогнозирование рисков. М.: Ленанд: УРСС).
Korotayev, A., Issaev, L., Rudenko, M., Shishkina, A., Ivanov, E. 2016. Afrasian Instability Zone and its Historical Background. Social Evolution & History 15 (2): 120–140.
Korotayev, A., Khodunov, A., Burova, A., Malkov, S., Khalturina, D., and Zinkina, J. 2012. Socio-Demographic Analysis of the Arab Spring. In Korotayev, A., Zinkina, J. and Khodunov, A. (eds.), Systemic Monitoring of Global and Regional Risks (pp. 28–76). Moscow: Lenand. Original in Russian (Коротаев А.В., Ходунов А. и др. Социально-демографический анализ Арабской весны. Системный мониторинг глобальных и региональных рисков. Арабская весна / Ред. Коротаев А.В., Зинькина Ю.В., Ходунов А.С. М.: Ленанд).
Korotayev, A., and Khokhlova, A. 2022. Effect of the Arab Spring on Stabilization Capacity of the MENA Monarchies. Journal of Asian and African Studies 57 (2): 289–307.
Korotayev, A., Khokhlova, A., and Tsirel, S. 2018. Unemployment as a Predictor of Socio-Political Destabilization in Western and Eastern Europe. Ekonomicheskaya Sotsiologiya 19 (2): 118–167. Original in Russian (Коротаев А. В., Хохлова А. А., Цирель С. В. Безработица как предиктор социально-политической дестабилизации в странах Западной и Восточной Европы. Экономическая социология 19 (2): 118–167).
Korotayev, A., Medvedev, I., and Zinkina, J. 2022. Global Systems for Sociopolitical Instability Forecasting and Their Efficiency. A Comparative Analysis. Comparative Sociology 21 (1): 64–104. doi: 10.1163/15691330-bja10050
Korotayev, A., Meshcherina, K., Issaev, L., Iskoskov, A., Hern, W., and Kulikova, E. 2016. Arab Spring as a Trigger of Global Socio-Political Destabilization: Experience of Systemic Analysis. In Grinin L. E. et al. (eds.), Systematic Monitoring of Global and Regional Risks: The Arab Spring in a Global Context (pp. 22–126). Volgograd: Uchitel. Original in Russian (Коротаев А. В., Мещерина К. В., Исаев Л. М., Искосков А. С., Херн У. Д., Куликова Е. Д. Арабская весна как триггер глобальной социально-политической дестабилизации: опыт систематического анализа. Системный мониторинг глобальных и региональных рисков: Арабская весна в глобальном контексте. / Отв. ред. Л. Е. Гринин, А. В. Коротаев, Л. М. Исаев, А. Р. Шишкина. Волгоград: Учитель).
Korotayev, A., Meshcherina, K., and Katkova, V. 2019. Arab Spring and its Echo in Sub-Saharan Africa: A Quantitative Analysis. Asia and Africa today 1: 17–24. https://doi.org/10.31857/S032150750003339-4
Korotayev, A., Meshcherina, K., and Shishkina, A. 2018. A Wave of Global Sociopolitical Destabilization of the 2010s: A Quantitative Analysis. Democracy and Security 14 (4): 331–357.
Korotayev, A., Romanov, D., and Medvedev, I. 2019. Echo of the Arab Spring in Eastern Europe: A Quantitative Analysis. Sociologiceskoe obozrenie 18 (1): 31–81. https://doi.org/10.17323/1728-192x-2019-1-56-106. Original in Russian (Коротаев А. В., Романов Д., Медведев И. Эхо «арабской весны» в Восточной Европе: опыт количественного анализа. Социологическое обозрение 18 (1): 31–81).
Korotayev, A., Shishkina, A., Issaev, L. 2016. Arab Spring as a Global Phase Transition Trigger. Polis-Politicheskiye Issledovaniya 3: 108–122. https://doi.org/10.17976/jpps/2016.03.09. Original in Russian (Коротаев А. В., Шишкина А. Р., Исаев Л. М. Арабская весна как триггер глобального фазового перехода? Полис. Политические исследования 3: 108–122).
Korotayev, A., Shishkina, A., and Khokhlova A. 2022. Global Echo of the Arab Spring. In Goldstone, J. A., Grinin, L., Korotayev, A. (eds.), Handbook of Revolutions in the 21st Century: The New Waves of Revolutions, and the Causes and Effects of Disruptive Political Change (pp. 813–849). Cham: Springer. https://doi.org/10.1007/978-3-030-86468-2_31.
Korotayev, A., Shishkina, A., and Lukhmanova, Z. 2017. The Global Socio-Political Destabilization Wave of 2011 and the Following Years: A Quantitative Analysis. Polis. Politicheskiye Issledovaniya 6: 150–168. https://doi.org/10.17976/jpps/2017.06.11 Original in Russian (Коротаев А., Шишкина А., Лухманова З. Волна глобальной социально-политической дестабилизации 2011 и последующих лет: количественный анализ. Полис. Политические исследования 6: 150–168).
Korotayev, A., Sawyer, P., Grinin, L., Romanov, D., and Shishkina, A. 2020. Socio-Economic Development and Anti-Government Protests in Light of a New Quantitative Analysis of Global Databases. Sotsiologicheskiy Zhurnal 26 (4): 61–78. Original in Russian (Коротаев А., Сойер П., Гринин Л., Романов Д., Шишкина А. Социально-экономиче-ское развитие и антиправительственные протесты в свете нового количественного анализа глобальных баз данных. Социологический журнал 26 (4): 61–78).
Korotayev, A., Sawyer, P., and Romanov, D. 2021. Socio-Economic Development and Protests. A Quantitative Reanalysis. Comparative Sociology 20 (2): 195–222.
Korotayev, A., Vaskin, I., and Bilyuga, S. 2017. Olson-Huntington Hypothesis on a Bell-Shaped Relationship Between the Level of Economic Development and Sociopo-litical Destabilization: A Quantitative Analysis. Sociologiceskoe Obozrenie 16(1): 9–49.
Korotayev, A., Vaskin, I., Bilyuga, S., and Ilyin, I. 2018. Economic Development and Sociopolitical Destabilization: A Re-Analysis. Cliodynamics 9 (1): 59–118.
Korotayev, A., Vaskin, I., and Tsirel, S. 2021. Economic Growth, Education, and Terrorism: A Re-Analysis. Terrorism and Political Violence 33 (3): 572–595.
Korotayev, A., and Zinkina, J. 2011. Egyptian Revolution: A Demographic Structural Analysis. Entelequia. Revista Interdisciplinar 13: 139–169.
Korotayev, A., and Zinkina, J. 2022. Egypt’s 2011 Revolution. A Demographic Structural Analysis. In Goldstone, J. A., Grinin, L., and Korotayev, A. (eds.), Handbook of Revolutions in the 21st Century: The New Waves of Revolutions, and the Causes and Effects of Disruptive Political Change (pp. 651–683). Cham: Springer. https://doi.org/10.1007/978-3-030-86468-2_25.
Korotayev, A., Zinkina, J., Bogevolnov, J., and Malkov, A. 2011. Global Unconditional Convergence among Larger Economies after 1998? Journal of Globalization Studies 2 (2): 25–62.
Latif, M. I., and Abbas, H. 2011. US Democracy Promotion and Popular Revolutions in the Middle East: Challenges and Opportunities. Pakistan Horizon 64 (3): 25–42.
Malik, A., and Awadallah, B. 2013. The Economics of the Arab Spring. World Development 45: 296–313.
Markakis, D. 2015. US Democracy Promotion in the Middle East: The Pursuit of Hegemony. London: Routledge.
Ortmans, O., Mazzeo, E., Meshcherina, K., and Korotayev, A. 2017. Modeling Social Pressures toward Political Instability in the United Kingdom after 1960: A Demographic Structural Analysis. Cliodynamics 8 (2): 113–158. https://doi.org/10.21237/C7clio8237313.
Perthes, V. 2004. America's ‘Greater Middle East’ and Europe: Key Issues for Dialogue. Middle East Policy 11 (3): 85–97.
Slinko, E., Bilyuga, S., Zinkina, J. and Korotayev, A. 2017. Regime Type and Political Destabilization in Cross-National Perspective: A Re-analysis. Cross-Cultural Research 51 (1): 26–50.
Slinko, E., Meshcherina, K., Shulgin, S., Zinkina, J., Biluga, S. and Korotayev, A. 2018. Measuring Internal Political Destabilization Processes: Types of Instability and Their Relationship with Socio-Political and Economic Factors. In Grinin L. E. et al. (eds.), Systemic Monitoring of Global and Regional Risks (pp. 95–114). Original in Russian (Слинько Е. В., Мещерина К. В., Шульгин С. Г., Зинькина Ю. В., Билюга С. Э., Коротаев А. В. Измерение внутриполитических дестабилизационных процессов: типы нестабильности и их связь с социально-политическими и экономическими факторами. Системный мониторинг глобальных и региональных рисков / Отв. ред. Л. Е. Гринин, А. В. Коротаев, К. В. Мещерина. Волгоград: Учитель).
START [National Consortium for the Study of Terrorism and Responses to Terrorism]. 2018. Global Terrorism Database. College Park, MD: National Consortium for the Study of Terrorism and Responses to Terrorism. URL: https://www.start.umd.edu/gtd/.
Steinert-Threlkeld, Z. 2017. Spontaneous Collective Action: Peripheral Mobilization During the Arab Spring. American Political Science Review 111 (2): 379–403.
Tanter, R. 1966. Dimensions of Conflict Behavior within and between nations, 1958–60. Journal of Conflict Resolution 10 (1): 41–64.
Vaskin, I., Tsirel, S., and Korotayev, A. 2018. Economic Growth, Education and Terrorism: Experience in Quantitative Analysis. Sotsiologicheskiy zhurnal 24 (2): 28–65. https://doi.org/10.19181/socjour.2018.24.2.5844. Original in Russian (Васькин И., Цирель С., Коротаев А. Экономический рост, образование и терроризм: опыт количественного анализа. Социологический журнал 24 (2): 28–65).
Wallerstein, I. 1974, 1980, 1988. The Modern World-System. 3 vols. New York: Academic Press.
Wallerstein, I. 1979. The Capitalist World Economy. Cambridge: Cambridge University Press.
Wallerstein, I. 1987. World-Systems Analysis. In Giddens A., and Turner J. H. (eds.), Social Theory Today (pp. 309–324). Cambridge: Cambridge University Press.
Wallerstein, I. 2004. World-Systems Analysis: An Introduction. Durham, NC: Duke
University Press.