Typology of State Types: Persistence and Transition

Abstract

Research on state fragility has seldom examined questions of persistence and transition of states. We develop a sixfold typology of states to examine how key structural features of states evolve and contribute to successful exits from fragility in some cases and persistence in others. Particularly worrisome is the lack of positive transition among the weakest states. Our findings are derived from a minimalist construct of a refined time series data set involving state indicators of authority, legitimacy, and capacity. Case studies of some of the more turbulent examples support our state trajectories. Additionally, changes in legitimacy most often led state transitions into or out of fragility. Implications of intervention policy for transitioning states out of fragility are addressed, and these are given particular focus since fragile states experience at least twice the intensity/incidence of internal armed conflict compared to other states.

KEYWORDS:

• armed conflict
• authority
• capacity
• failed states
• foreign policy
• legitimacy

Notes

¹ See www.carleton.ca/cifp and Carment, Prest, and Samy (2008, 2009) for detailed development of the A-L-C construct.

² See http://ffp.statesindex.org/fsi-trends-2013.

³ See http://www.brookings.edu/research/reports/2008/02/weak-states-index.

⁴ See http://data.worldbank.org/about/country-classifications.

⁵ Although all indicators correlated significantly with one another, the average intracorrelation of r = 0.75 was markedly higher than the average intercorrelation of 0.52.

⁶ Military expenditure was considered as an additional indicator of capacity, but data were insufficient. However, the correlation between GDP total, which was used, and military expenditure based on 116 states in the study was significant at r = 0.94, indicating that economic size can serve as a proxy for military expenditure.

⁷ Mean indicator values of the years 2000 and 2002 were used to estimate the missing single indicator values for 2001, which is equivalent to applying infinite imputation using random estimates. Linear regression was applied to estimate HDI for the years 2001 through 2004 bounded by the values at 2000 and 2005 assuming monotonicity. We tested HDI data for monotonicity using values from 2005 through 2010 inclusive by conducting a correlational analysis of the regressed values against the reported values. A high degree of monotonicity was indicated with a total of 89.3% significant correlations and an overall average correlation of r = 0.93. We also tested the consequence of assuming random HDI values for the years 2001 through 2004, also bounded by the values at 2000 and 2005. This exercise, which did not ensure monotonicity, did not change the state categorizations as tabled in the online appendix “STATE CATEGORIZATION” under the assumption of HDI monotonicity. This invariance to the method of imputation is due to the relatively small difference between the scaled 2000 and 2005 HDI values (average of 0.023) compared to the min–max range of the entire data set (0.682). Thus, our assumption of HDI monotonicity from 2000 to 2005 not only concurs with the observed trend from 2005 to 2010 but does so without biasing state categorization.

⁸ Log-transformation is similarly applied to the income component of HDI (see https://data.undp.org/dataset/Table-2-Human-Development-Index-trends/efc4-gjvq).

⁹ This ensured that state performance over time would be judged by relative changes to itself against an all-inclusive fixed baseline.

¹⁰ STATISTICA® K-means Cluster with a specification of six groups.

¹¹ In the case of Yemen, borderline scores of A and C (5.99 and 6.00 respectively) indicated a change in FI that was opposite to the changes in A and C.

¹² Also see https://www.gov.uk/government/publications/future-character-ofconflict.

¹³ For example, increased domestic expenditure by Saudi Arabia has been dubbed the “national bribe” (Lesch 2012). Also, 2010 GDPpc of Bahrain ($16.7K in constant 2005 US$), Saudi Arabia ($16.0K), and UAE ($24.2K) greatly exceed that of the conflict-troubled Arab states (Algeria [$3.1K], Egypt [$1.6K], Tunisia [$3.9K]) and Syria ($1.7K, estimated). GDP source: http://datacatalog.worldbank.org/.

¹⁴ China is considered as such, given its high GDP (2010 $3.84e12 in constant 2005 US$ despite a modest GDPpc ($2.9K).

¹⁵ See http://www.foreignaffairs.com/articles/58437/gareth-evans-and-mohamed-sahnoun/the-responsibility-to-protect.

¹⁶ There is no general causal relationship between state fragility and incidence of armed conflict—that is, certain states are either fragile (for example, Cote d’Ivoire, DRC) or become fragile (for example, Nepal) when conflict breaks out (see tables in online appendices “STATE CATEGORIZATION” and “ARMED CONFLICT”).