Forecasting Political Instability

What signals indicate the onset of severe political instability, the worst-case scenario being state-collapse or civil war, with enough lead-time to take preventative action?

This question was asked at the end of the Cold War leading to the creation of the Political Instability Task Force (PITF) in 1994, funded by the Central Intelligence Agency (CIA). The goal was to create a model to determine reliable indicators of instability at least two years prior to the onset of a major crisis.

The PITF devised a model for determining the onset of severe political instability by correlating open-source data variables from over 140 episodes of major instability worldwide stretching back to 1955, and claims an 80% post fact success rate. The model categorizes episodes of major instability as Revolutionary Wars, Ethnic Wars, Adverse Regime Changes, and Genocides and Politicides.

The PITF model* examined hundreds of factors including political, economic, demographic, geopolitical, social, and environmental variables to determine an ‘association with vulnerability to political instability’ through correlating data with the historical record. PITF researchers found that “relatively simple models, involving just a handful of variables and no complex interactions, accurately classify 80% or more of the instability onsets and stable countries in the historical data.”

The main independent variables incorporated by the PITF model includes regime type and political factionalism, infant mortality, neighborhood insecurity, and state-led discrimination.

  • Infant mortality figures provide a reliable standard of living indicator as this reflects a country’s level of socioeconomic development and public wellbeing. This is in turn a product of low levels of governmental effectiveness and quality of political leadership. model confirmed that poorer and underdeveloped states are generally at higher risk of experiencing political instability.
  • The neighboring component refers to general regional instability. The model found that regional security has a measurable impact on the stability of states within the regional system. Part of the risk is that conflict spillover from states experiencing violent conflict may aggravate domestic political tensions in neighboring states. The model also includes other geopolitical risks including the security effects of land-locked states and countries with large land masses.
  • State-led discrimination refers to the degree of institutional, or official political and economic discrimination against specific groups within society. This reflects the nature of communal relations and incorporates religious, ethnic and racial components which may prove divisive.
  • Regime-type refers to the type and nature of states, some of which are more prone to instability than others. This includes regimes along the spectrum of full or partial autocracies, to full or partial democracies. Factionalism refers to social and political polarization linked to the degree of inclusive or exclusive political participation – a leading indicator affecting the probability of unrest and violence.

Jack Goldstone, a former PITF team member explains the salience of regime-type, when anticipating political instability, stating “surprisingly few other factors mattered”.

 Regime Type and Factionalism

As stated, the PITF model found that geopolitical stability, including outbreak of revolutions, ethnic wars, and adverse regime changes (defined as abrupt turns from a more democratic system to one that is more authoritarian), is “overwhelmingly determined by a country’s patterns of political competition and political authority”. Economic conditions, the record of prior instability and conflict, ethnic and regional tensions, and regional security remain secondary, yet important independent, and interdependent variables. The PITF model determined three main dimensions affect regime stability (bullets are direct quotes):

  • the degree of openness and electoral competitiveness in the recruitment of the chief executive (Executive Recruitment);
  • the degree of institutional constraints on the authority of that chief executive (Executive Constraints);
  • and the degree to which political competition is unrestricted, institutionalized, and cooperative rather than repressed or factionalized (Political Competition).

These dynamics are relevant when assessing political risk in all types of regimes as they reflect the degree of inclusiveness, and by extension the probability of opposition to the staus quo.

According to the PITF, factionalism has proven to be the ‘most statistically powerful, precursive condition in modeling the onset of serious political instability’ as this influences ‘patterns of executive recruitment and political participation under those regimes’. The model describes factionalism as occurring when “when political competition is dominated by ethnic or other parochial groups that regularly compete for political influence in order to promote particularist agendas and favor group members to the detriment of common, secular, or cross-cutting agendas.”

Figure A demonstrates the relative importance of aforementioned variables in determining the onset of instability, particularly the risks associated with highly factionalized partial democratic states.

Figure A. Goldstone, J.A., and Ulfelder, J. 2004. How to Construct Stable Democracies. Washington Quarterly 28(1):9-20

Jack Goldstone notes in his writings on revolutions that divisions among elites are not enough to generate instability as competing elites can be managed by an authoritarian leader; however, ‘what is crucial for political crises to emerge is for elites to be not only divided but polarized—that is, to form two or three coherent groupings with sharp differences in their visions of how social order should be structured’.  A good current example would be split between the pro- and anti- socialist camps in crisis-ridden Venezuela.

The high correlation between regime type and insecurity relates to the vulnerability or resilience of certain states when confronted by multiple challenges. According to Goldstone, when the resilience of the state is tested, the “most important factor is elite loyalty and commitment to supporting the existing regime”. The model found that full or consolidated democratic, and fully autocratic regimes exhibit greater levels of stability, while partial, or illiberal democratic states, (called anocracies) characterized by factionalism are most prone to instability. The record suggests that anocracies are least able to weather bouts of severe instability; once a social, political, conflict, or economic challenge becomes unbearable, marked factionalism among elite groups may occur as alternative visions of order emerge, leading to infighting, spoiler politics, opposition and regime sponsored violence against opponents, elevated levels of political instability, and state collapse. Anocracies may remain stable depending upon the degree of elite cohesion: the overall unity and loyalty of high-level political and military elites explains how the Mugabe regime remained in power for over a decade after the country’s economy flat-lined, despite widespread  socioeconomic collapse.

Figure B demonstrates level of instability between the range of regime types defined by the PITF.

Figure B. Regimes and levels of political instability.

Politics in quasi-democratic/anocratic states is frequently seen as a winner-takes-all competition, where state control is the ultimate goal due to the party’s ability to capture the state and manage the distributions of spoils, often building extensive patronage networks that strengthen the regime, or the faction within the regime with access to the levers of power.  The regime may limit the ability of the opposition to mobilize support in order to undermine its prospects for inclusion within government. Inconsequential ‘managed elections’may be permitted, but have limited impact on the selection of the prime minster or president. A national leader may enjoys unlimited power due to the absence of institutional or legal constraints. The regime may lock up or kill the opposition, triggering episodes of mass unrest, contained through state violence. This could have the long term effect of fostering a simmering yet intense opposition to the regime, which may result in civil war as armed conflict remains the only viable option for the opposition.

Politics in fully democratic or autocratic states are generally more stable as political competition (or lack-thereof) is institutionalized and at least tacitly accepted by most major players. While the absence of electoral competitiveness, restraints on the leader, and degree of political participation is restricted in an autocratic regime, contributing to its stability by containing all or most power within a clique that has loyalty instilled by fear, or rented, autocracies are nonetheless prone to violent overthrow, as demonstrated by the fall of the Shah in Iran in 1979. Fully democratic regimes by contrast have established avenues for peaceful political competition, yet are also subject to breakdown owing to changes in ideology, elite composition or other internal/external influences.

Regime types and the nature of political participation can thus be seen as structural causes of instability, while immediate causes include a broad range of factors, such as the lifting of fuel subsidies or imprisoning a popular opposition leader, which are able to trigger a crisis.

Visualizing vulnerability

The Center for Systemic Peace (CSP) continues some of the work of the PITF, and publishes occasional reports on global security. The following map from the CSP (Figure C) lists regime types globally. This presents a global spatial risk model, with states colour-coded along a spectrum from democratic to autocratic. One could say this represents a ‘horizontal’ risk map, as it reflects a current, yet dynamic, political topography. Anocratic regimes in grey and purple indicate highest risk areas.

Figure C. Polity IV Individual Country Regime Trends, 1946-2013.

A ‘vertical’ risk map (Figure D) , based on the historical experience, can be found in the study “State Fragility and Warfare in the Global System 2016,” which lists 328 major episodes of political violence from 1946 to 2016 — including over 30 that are ongoing. This map reflects areas of elevated political instability, using the definitions above.

The World Wars are not included in PTIF model, as the model only began measuring politics since 1956 due to the lack of reliable data before this date. These wars occurred in part due to the changing global geopolitical order, what Halford Mackinder called the post-Colombian era. In this regard, the PTIF model measures the post-colonial world order, many parts of which were beset by violent post-independence struggles, including highly destabilizing factional struggles within new democratic and quasi-democratic regimes. According to the data series, Sub-Saharan Africa was the most unstable part of the world during this period, followed by the Middle East and South Asia.

Figure D. Major Episodes of Political Violence 1946-2016.

Figure D. Major Episodes of Political Violence 1946-2016.

One can question the degree of cause and effect in the development of the model as areas characterized by the prevalence of anocratic regimes may have weak or factitious political systems precisely because of post-independence nation-building related conflict. This suggests the possibility of a vicious circle of instability as renewed bouts of conflict undermine the development of effective governance and elevate militarily successful groups to high office, perhaps the exclusion of others, producing factionalism. Nevertheless, the model attempts to use current indicators to anticipate future instability, and appears well founded in this regard.

The components of the PITF model are useful for gauging country risk conditions by giving the analyst a credible methodology for anticipating bouts of severe political instability. While the model has predictive capacity, it is not able to predict the duration or intensity of conflict or political crisis. It is less useful as a barometer of real-time fluctuations in political risks, which require a more nuanced and complex index or methodology. In this regard, a fusion between the PITF and the World Bank’s 300 odd factor Worldwide Governance Indicators (WGI) could be useful. Experts agree only a combination of matrices, together with the contribution of expert opinion or subject-matter expertise is required to accurately gauge political and country risk.

*The “PITF global model uses a triple-matched, case-control methodology and a conditional logistic regression statistical application to specify key, precursive factors that characterize the imminent risk of the onset of a political instability (state failure) condition in any of 163 countries in the world”. One of the few semi-official publications of the PITF, describing the workings of the model is available here.

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