By Alexander Perepechko

Published on March 11, 2017

In the part 1 of this paper we discussed the Machiavellian intelligence approach in elitology. According to this theory, when we must act under uncertainty (a state of mind) with incomplete information about risks (the world is almost out of control) our “non-logical” conduct follows from a particular belief about the world in conjunction with a particular sentiment, desire or psychic state. This conduct is guided by two permanent sets of assumptions associated with two particular ways of life shaped by evolution. The two specific cultural and personological patterns, developed over time to help us withstand different risks during upswings and downswings of socio-economic and political development, influence our experiences of uncertainty into one of two fixed ways. In a competitive individualist environment a “fox” can discover snares. In a time of resource scarcity or crisis a “lion” can terrify the wolves.

We already learned (see figure 32) that a new Pareto long elite cycle started in 2008. It seemed as though the upswing of this new elite cycle could have become more and more synchronized with the new psychosocial health economic cycle (and with the fading IT long economic cycle) in the American economy. Unfortunately, during Obama’s presidency the governing elite was overrun by individuals with the skills and inclination to utilize legal and financial means and ideological persuasion. In Pareto’s language, these skills and proclivities are a deceitful and cunning craft. Overrun by these “foxes,” the governing elite lost its political domination in the 2016 presidential election: the upswing of the new elite cycle, which began in 2008, took a downturn in 2016. The new psychosocial health economic cycle (and the fading IT long economic cycle) and the downswing of the Pareto long elite cycle are asynchronous again…

As we know, downswings are related to an increase in in-group altruism as well as prejudice and suspicion toward out-groups (“others”). During periods of resource scarcity or crisis, risks to social solidarity dominate. This is a good time for Pareto’s “lion,” which can describe the conservative authoritarian personality. We pointed at increasing risks in socio-economic development, at the imbalance in elite circulation, and at political Balkanization as important threats which played to the hands of Donald Trump. We also emphasized that Trump skillfully used uncertainty, pertaining to postmodernist media, social networks, and expert knowledge. He succeeded in presenting himself as an intense realist preoccupied with objective reality and able to restore foundational principles and to develop a strategy for the United States.

But do all these threats and uncertainties for the United States exist? Can they be measured quantitatively? If the answer is positive, Trump’s electoral campaign and the votes of his supporters may be explained in part by Machiavellian intelligence. Furthermore, if this explanation is true, elements of this theory can be used to better understand the current actions of President Trump.

Measuring risk

Recall that fragile states are on the brink of collapse in at least one of three areas: 1) authority over territory and the populace, 2) capacity of the economy and resource mobilization, and 3) effective and responsive governance (see Carment & Samy, 2014; Jenne, 2003). In other words, the state fails because it is seized with internal violence and cannot deliver positive political goods to the population.

The Fragile States Index (hereafter, FSI Index, or Index) highlights pressures experienced by a state. Importantly, this index helps to detect the time when these pressures push a state towards failure (Cast Conflict, 2014; Messner, 2015). Effective 2006, the Fund for Peace (FFP) generates this index for each country every year. The FFP Index measures state fragility based on a total score that summarizes numerous indicators and expresses pressures (conditions) for all countries. The higher the score and FFP Index, the worse the conditions in the country.

A country’s total score and even year-by-year trend can sometimes be misleading. Worsening conditions in some indicators can be masked by improving conditions in others. A disaggregation of the Index to its composite indicators tells a more nuanced story. What are these composite indicators?

The Index is based on the FFP’s proprietary Conflict Assessment System Tool (CAST) analytical platform, developed to assess the vulnerability of states to collapse. Data from multiple public sources is triangulated and subjected to critical review to obtain final scores. Millions of documents from 11,000 sources worldwide are analyzed every year. By applying specialized search parameters, scores are apportioned for every country. These scores are based on 12 key indicators: social (demographic pressures, refugees and internally displaced persons (IDPs), group grievances, and human flight and brain drain), economic (uneven economic development and poverty and economic decline), and political and military (state legitimacy, public services, human rights and rule of law, security apparatus, factionalized elites, and external intervention).

Through integration and triangulation techniques, the CAST platform separates relevant data from the irrelevant. Guided by the 12 primary social, economic, and political and military indicators, a content analysis is performed by using specialized search terms. Results are converted into a score representing the significance of each of the various pressures for a given country.

The content analysis is further juxtaposed against two other key aspects of the overall assessment: quantitative analysis and qualitative inputs based on major events in the country. This “mixed methods” approach also helps to ensure that inherent weaknesses, gaps, and biases in one source are checked by others.

Each indicator is rated on a scale of 1 to 10 with 1 (low) being the most stable and 10 (high) being the most at risk of collapse and violence. To estimate the risk of collapse and violence for a state, 5 categories are established: 0-2 is “excellent,” 2-4 “good,” 4-6 “moderate,” 6-8 “weak,” and 8-10 “poor.”

Fragile state total score

In 2016, pressure assessments were made for 178 countries. With a fragile state total score of 34, the United States had an FSI rank of 159 (figure 34). The U.S. was assigned to the group marked as “stable.” This country was neither in the safest group (“sustainable”), nor in the troubled (“warning”) group or dangerous (“alert”) group of countries. During 2006-2016, America demonstrated worsening. Improvement started in 2007 but soon was interrupted and the trend worsened dramatically after 2008. Improvement again started in 2010 and again was interrupted in 2013. The trend worsened significantly during next year and stabilized after 2014.

Figure 34. Measuring Fragile States: Total score for the United States, 2006-2016. (Source: Generated by the author based on FFP data at http://fsi.fundforpeace.org/).

Social indicators

Among social indicators, “group grievance” in the United States has increased every year since 2007 and is in the “moderate” risk category (4-6) these days (figure 35). This indicator reflects discrimination and racial, ethnic, religious, and other kinds of violence between socio-territorial groups. In 2014, an immigration crisis of undocumented children fleeing the dangerous environment in Central America led to racial, ethnic, and political polarization and street protests. Police actions led to the deaths of several African Americans. These fatalities caused protests, sometimes violent. In August, 2014 law enforcement officials deployed the National Guard in Ferguson, Missouri. The riots were broadcast in the United States and abroad. Old racial, ethnic, and socio-economic cleavages resurfaced and group-based societal tensions and conflicts intensified.

Figure 35. Measuring Fragile States Index (FSI): Social indicators for the United States, 2006-2016. (Source: Generated by the author based on FFP data at http://fsi.fundforpeace.org/)

Even though the indicator of “refugees and IDPs” improved during the last decade, in the assessment of FFP, these factors have grown worse lately. President Trump’s controversial executive orders on foreign “terrorist” entry, on public safety in the interior of the United States, on border security and immigration enforcement, and on transnational organizations and preventing international trafficking (see Rappaport, 2017; Trump’s Executive, 2017) led to disturbance in airports and immigrant communities, fueled protests, and brought about legal fights in courts. Large-scale ICE (Immigration and Customs Enforcement) raids have disrupted the lives of immigrant families throughout the United States. The score for “refugees and IDPs” will definitely worsen in 2017. Naturally, worsening in “group grievance” and “refugees and IDPs” increases the risk of political Balkanization in the United States.

But is the recent refugee crisis a risk (a state of the world)? Or, is this refugee crisis an uncertainty (a state of mind of certain decision-makers)? Let us look at some numbers.

The number of unauthorized immigrants in the United States reached a high point in 2007 at 12.2 million (figure 36) when this group accounted for 4% of the U.S. population (Passel, 2016). There were 11.1 million unauthorized immigrants in the U.S. in 2014. This number has not changed since 2009 and constitutes 3.5% of the country’s population.

Figure 36. Estimated unauthorized immigrant population in the United States rises, falls, then stabilizes. (Source: Passel, 2016)

Since September 11, 2001, all jihadists who have carried out fatal attacks inside the United States were either citizens or legal residents (figure 37). Since September 11, 82% of individuals who were charged with or died engaging in jihadist terrorism or related activities inside the United States have been U.S. citizens or permanent residents. Americans indicted of engaging in the jihadist terrorism abroad are included. Many jihadists inside the United States have been second-generation immigrants (see Berger, Ford, Sims, Sherman, n.d.).

Figure 37. Origin of terrorists since September 11, 2001. (Source: Berger, Ford, Sims, Sherman, n.d.).

The seven Muslim-majority countries singled out in President Trump’s executive order on immigration (in a later, more limited version of the order, unveiled on March 6, 2017, he dropped Iraq from the list of countries (Rhodan, 2017)) were initially identified as “countries of concern” under the Obama administration (Blane & Horowitz, 2017). In December 2015, Obama signed into law a measure placing limited restrictions on certain travelers who had visited Iran, Iraq, Sudan, or Syria on or after March 1, 2011. Two months later, the Obama administration added Libya, Somalia, and Yemen to this list (DHS Announces, 2016; United States Begins, 2016). That was an effort to address the growing threat from foreign terrorists.

Ironically, citizens of these 7 countries have killed zero people in terrorist attacks on U.S. soil between 1975 and 2015 (table 5). Six Iranians, six Sudanese, two Somalis, two Iraqis, and one Yemeni have been convicted of attempting or executing terrorist attacks on U.S. soil during that time period. Zero Libyans and zero Syrians have been convicted of doing the same (Friedman, 2017).

Table 5. Foreign-born terrorist country of origin from the 7 countries, 1975-2015. 

	Iran	Iraq*	Libya	Somalia	Sudan	Syria	Yemen	Total
Terrorists	6	2	0	2	6	0	1	17
Murders	0	0	0	0	0	0	0	0

*In a later executive order, unveiled on March 6, 2017, Trump dropped Iraq from the list of countries. Source: Compiled by the author based on Nowrasteh, 2017.

So, is Trump’s (actually, Obama-Trump’s!) Muslim ban a reaction to a real risk? Or does this ban reflect an uncertainty of mind of decision-makers? What is special about these 7 countries?

In 2016, the Fund for Peace assigned Somalia, Sudan, Syria, and Yemen to the most dangerous (“very high alert”) group of countries. Iraq is assigned to the very dangerous (“high alert”) group of countries, and Libya – to the dangerous (“alert”) group. Iran is in the deeply troubled (“high warning”) group. The FSI Index in Iraq, Libya, Somalia, Sudan, Syria, and Yemen shows worsening. The FSI Index in Iran has not changed but this deeply troubled country is stuck with multiple complex problems.

So, is Trump’s (actually, Obama-Trump’s!) Muslim ban a reaction to a real risk? Or does this ban reflect an uncertainty of mind of decision-makers? What is special about these 7 countries?

During the period of 2012-2016, the cumulative number of refugees to the U.S. from the 7 states increased from 16.5 thousand to 36.3 thousand (figure 38). Iraq, Somalia, and Sudan were the main source of refugees for the U.S. until 2014 with Iraq ahead of all. These days, Somalia and especially Syria have taken the lead with Iraq following them. Since 2014, refugee flows from the 7 countries demonstrated a 35% increase. But why were Libya and Yemen, from which only a few refugees came to the U.S., and Syria, which supplied the U.S. with over 15 thousand refugees (in 2016), added by Obama and then Trump to the same list? An answer to this question will help us to explain the recent brutal actions against illegal immigrants, including their deportation.

Figure 38. Admissions and arrivals of refugees from Iran, Iraq, Libya, Somalia, Sudan, Syria, and Yemen to the United States, 2012-2016. (Source: Generated by the author based on data extracted from the Worldwide Refugee Admissions Processing System (WRAPS) at http://ireports.wrapsnet.org/Interactive-Reporting/EnumType/Report?ItemPath=/rpt_WebArrivalsReports/MX%20-%20Arrivals%20by%20Nationality%20and%20Religion).

The American military theorists William Lind and Gregory Thiele in their brilliant “4^th Generation Warfare Handbook” define terrorism as “a special operation, a single tactical action designed to have direct operational or strategic effect” (2016: 47-48). It seems as though President Trump sees the migration crisis as a network military political operation of radical Islam against the United States. If this is true, Islamists control (at least to the certain degree) migration flows from the 7 failing or failed Muslim-majority countries. This allows Islamic militants to send individually trained terrorists (not groups!) (see Fursov, 2016b: 495) to the United States. Yes, the number of refugees who arrive to the United States from each of the seven countries does matter. Even more important is that this vision of terrorists as imported from the 7 failed states fosters the following assumption: each refugee from any of these countries is a potential terrorist. In other words, the 4 Libyan and 17 Yemeni refugees who came to the United States in 2016 are potential terrorists. Is there any scientific basis in favor of this vision?

Sadly, there is some evidence supporting this vision.

According to the American expert on intrastate conflicts Robert Rotberg (2003), an extreme version of a failed state is a collapsed state, when political goods are obtained only through private or ad hoc means. State authority does not exist in a collapsed state. The citizens are not, in fact, citizens any longer but inhabitants, who team up based on regional, ethnic, religious, or language affinity. These inhabitants stop trusting the state. In search of security and economic opportunity, they increasingly turn to non-state actors – community organizations, criminal gangs, warlords, arms and drug dealers – which become the suppliers of political goods…

The founder of “Facebook” and icon of globalism Mark Zuckerberg (2017) accepts that during late Modernity more and more threats are global. We do not have a global infrastructure to protect us from these risks. A conflict in one country can create a refugee crisis and terrorist threat across continents. Humanity’s current security systems are insufficient to address these issues. As a result problems in a failed or failing state can be exported to neighbors and even across the ocean (see Ahmed, 2017; Kraxberger, 2012: 29-48). When in such a state physical insecurity is combined with economic decline, the threats can hardly be isolated at all.

Economic indicators

Inequality and poverty are hallmarks of America. These economic indicators (figure 39) reflect well-known risks. During the period 2012-2016, the indicator of “poverty and economic decline” fluctuated in response to market dynamics and other factors (. According to the U.S. Census Bureau (see Proctor, Semega, & Kollar, 2016), the poverty rate increased from 12.5% in 2007 to 15.1% in 2010. Then it decreased to 13.5% in 2015. The economic indicator of “uneven development” in the United States improved but remains in the “moderate” risk category (4-6).

Figure 39. Measuring Fragile States Index (FSI): Economic indicators for the United States, 2006-2016. (Source: Generated by the author based on FFP data at http://fsi.fundforpeace.org/)

One needs to be cautious when interpreting these economic indicators in the United States. Why?

In countries that have been leaders in terms of universal suffrage, representative systems, human rights, or equality before the law, a large class of people has been prominent. In ancient Rome, the Greek city, England since the 17^th century, and the United States in 1900 to the 1980s the economic position of this class was to significant degree independent of those who held the most power. These moderately well-to-do people – the middle class – have sufficient means to devote a part of their time to perfecting their culture and pursuing interest in the public good. Individual pride and self-respect are among the major drives which induce these people to selflessly serve their country. The following words, written by a founding father of elitology Gaetano Mosca (1939: 391) 120 years ago, sound prophetic: “the existence of a moderately well-to-do middle class is necessary today for the normal livelihood of the modern representative system. So true is this that in countries and regions where such a class is not very well developed, or is without the requisites for maintaining its prestige and influence, the modern representative system has yielded its worst results. If the decline in question should be accelerated, or merely continue, the forms of our present organization might be observed for some time still, but really we would have either a plutocratic dictatorship, or else a bureaucratic-military dictatorship, or else a demagogic dictatorship by a few experts in mob leadership, who would know the arts wheedling the masses and of satisfying their envies and their predatory instincts in every possible way, to the certain damage of the general interest. Worst still, there might be a combination of two of these dictatorships, or indeed of all three.”

The middle class in the U.S. has been shrinking steadily for almost four decades (figure 40). Since 2000, the middle class lost ground in nearly nine-in-ten metropolitan areas. In addition to two recessions (in 2001 and 2008) longer-run trends such as globalization, the decline of unions, technological change, and the rising cost of health are among factors that limit prospects for many Americans (America’s Shrinking, 2016).

Figure 40. Middle class in Canada, the U.K., and the U.S. and share of American adults living in middle-income households (Source: Generated by the author based on Luxemburg Income Study Database at http://www.lisdatacenter.org/our-data/lis-database/, Pew Research Center analysis of the 2000 decennial census at http://www.pewresearch.org/methodology/demographic-research/data-sources/, and the 2014 American Community Survey at http://www.pewsocialtrends.org/2016/05/11/1-the-american-middle-class-loses-ground-nationally/).

As a percentage of total country wealth, the U.S. middle class accounted for the lowest share of wealth – 19.6% in 2015 – among developed countries as well as several emerging economies (Global Wealth, 2015). In that year, the middle-class comprised 49% of wealth in Japan; 47% in Italy; 40% in Australia, Germany, and the U.K.; 39% in Canada and France; 32% in China; 31% in Brazil; and 23% in India.

The polarization of the middle class in the U.S. is an ongoing long-term trend. The share of American adults in middle-income households decreased from 55% in 2000 to 51% in 2014 (figure 40). Simultaneously, the share of adults in the upper-income tier increased from 17% to 20%. The share of adults in the lower-income tier increased from 28% to 29%. Therefore, the middle class might cease to exist in a few decades. The consequences for American society might be tragic. Mosca (1939: 143) professed: “Laws and institutions that guarantee justice and protect the rights of the weak cannot possibly be effective when wealth is so distributed that we get, on the one hand, a small number of persons possessing lands and mobile capital and, on the other, a multitude of proletarians who have no resource but the labor… In that state of affairs to proclaim universal suffrage, or the rights of man, or the maxim that all are equal before the law, is merely ironical… Even granting that some few individuals do realize those high possibilities, they will not necessarily be the best individuals, either in intelligence or in morals. They may be the most persistent, the most fortunate or, perhaps, the most crooked. Meanwhile the mass of the people will still remain just as much subject to those on high.”

 Political and military indicators

According to FFP data, political and military indicators play the key role in understanding the fragility of the United States. Out of six indicators, “factionalized elites” and “human rights” capture special attention (figure 41).

The score for “factionalized elites” peaked (worsened) in 2013 with the government shutdown due to a disagreement over the Affordable Care Act and has not improved since 2014. According to the Brookings Institution (Vital Statistics, 2017), the 112^th, 113^th, and 114^th Congresses (2011-2017) were the least productive sessions since before 1947 as measured by the number of bills passed into law. As fewer laws are enacted, individual bills tend to grow in length and complexity. Based on ideological scores for House and Senate party coalitions and committees, party unity votes and scores, and roll call votes on bills on which the president has taken an official position, political polarization in Congress has increased.

As often happens, when the indicator of “group grievance” (from figure 35) worsens, the indicator of “factionalized elites” also worsens. The scores for “group grievance” and “factionalized elites” have deteriorated over recent years (figures 35 & 41). Indeed, the correlation between the “group grievance” and “factionalized elites” indicators is positive and very strong (r=0.83). Since these two indicators worsened almost monotonically from the “very low” (0-2) or “low” (2-4) risk category to the “moderate” risk category (4-6), it is unlikely that the change can be attributed to temporal and situational circumstances. Most likely, this change is a sign of systemic risk; it is quite possible that events or processes in a few components of a system can trigger severe instability or collapse of the entire system…

Figure 41. Measuring Fragile States Index (FSI): Political and military indicators for the United States, 2006-2016. (Source: Generated by the author based on FFP data at http://fsi.fundforpeace.org/).

According to FFP data, the indicator of “human rights” improved and since 2009 has consistently stayed in the low (2-4) risk category. But some observers would argue that this score for “human rights” is too optimistic. Indeed, police killings of Alton Sterling in Baton Rouge, Louisiana, and Philando Castile in Falcon Heights, Minnesota, and the killing of 5 police officers in Dallas by a lone gunman in 2014 (see United States. Events, 2016) pushed the indicator of “human rights” toward the “moderate” (4-6) risk zone. In accordance with the humanitarian information portal “ReliefWeb,” the indicator of “human rights” in the United States moved to the “moderate” (4-6) risk category in the fourth quarter of 2016 (Human Rights, 2016). Countries ranked as having “moderate” risk for “human rights” now include the U.S., countries in Southern and Eastern Europe, Argentina, Chile, Uruguay, Botswana, Ghana, Namibia, Japan, South Korea, and Taiwan.

Measuring uncertainty

To measure policy-related economic uncertainty, the American economists Scott Baker, Nicholas Bloom, and Steven Davis (2015; 2016) constructed the Economic Policy Uncertainty Index (hereafter, EPU Index) from three components: 1) newspaper (media) coverage of economic uncertainty related to policy, 2) the number of federal tax code provisions set to expire in upcoming 10 years, and 3) disagreement among economic analysts as a proxy for uncertainty. A higher score and EPU Index reflects higher uncertainty in the country.

Figure 42. Measuring Economic Policy Uncertainty (EPU) in the United States, 1985-2015. (Source: Baker, Bloom, Davis, 2015: 32; Baker, Bloom, Davis, 2016; Economic Policy, 2017).

Compared to recent history, current levels of EPU are at particularly elevated levels (figure 42). There is more uncertainty at the time of a dramatic event, such as war, terrorism, sharp stock market decline, financial collapse, and certain political events such as elections. Since 2008, the EPU has averaged about twice the level of the previous 23 years (Baker, Bloom, & Davis 2015; Baker, Bloom, & Davis, 2016). Several weeks ago, Bloom (2017) reported to the German weekly Spiegel that political uncertainty around the world has more than doubled since the election of Donald Trump. Bloom commented that something comparable happened during the Great Depression when the EPU rose dramatically. It is reasonable to presume that the elevated policy uncertainty in the United States in recent years may have harmed its macroeconomic performance.

Figure 43. Policy-related S&P 500 Index movements in the United States, 1980-2013. (Source: Baker, Bloom, Davis, 2015: 69; Baker, Bloom, Davis, 2016; Economic Policy, 2017).

Baker, Bloom, and Davis (2015; 2016) also found that the number of large movements in the S&P 500 index (defined as a daily change of 2.5% or more) has increased dramatically in recent years relative to the average since 1980. What is more, since 2008 an increasingly larger share of these large stock movements has been caused by policy-related events (figure 43). These scholars also described the considerable impact of policy uncertainty on the cross-sectional structure of stock price volatility, investment rates, and employment growth.

It is not clear whether political uncertainty impacts economic growth or decreasing growth leads to increased political uncertainty. Most likely, the correlation reflects impact in both directions (Bloom, 2017). When Donald Trump said that he wanted to build a wall along the border with Mexico to combat illegal immigration, the stock prices of many U.S. construction companies shot up. When some border experts suggested building a fence instead (Bronstein, Devine, Griffin, 2017) the stocks of these companies plunged…

Figure 44. Market-based volatility of S&P 500 index (VIX) and news-based index of equity market uncertainty from January 1990 to December 2014. (Source: Baker, Bloom, Davis, 2015: 69; Economic Policy, 2017).

We discussed in part 1 of this research paper that the American institutional mass media time and again offer propaganda instead of news. Baker, Bloom, and Davis (2015) created a newspaper-based index of equity market uncertainty – the perception of reality. They compared this index to a market-based index called VIX, a measure of uncertainty in equity returns. The market-based VIX stands for the reality. The resulting newspaper-based index of equity market uncertainty and the monthly average of daily VIX values from 1990 to 2012 were plotted together (figure 44).

The correlation between two series is positive and very strong (r=0.73). The newspaper-based index picks up every major move in the market-based VIX during the sample period but is much noisier (Baker, Bloom, Davis, 2015: 47). The perception of reality is exaggerated, such that the highs seem higher and the lows seem lower than reality…

In the next research essay we will summarize our findings.

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