explanatory conditions, a total of 16 rows are possible.
Second, the empirically relevant combinations are identified.173 When the values of the explanatory combination are consistently more than the outcome condition, they can be said to be a superset of, or a necessary condition for, the outcome. The neces-sary condition is only valid, however, when the distance between the outcome values and the explanatory combination is small; the greater the distance, the more trivial the condition is for explaining the outcome.174 In other words, when the coverage is low it can explain much but is unspecific. The sufficiency of the combinations can also be assessed by identifying combinations that hold values that are consistently lower than the outcome condition, that is, a subset of the outcome. When the consistency scores are high they are said to pass the set-theoretic consistency cut-off point (Ibid, p. 135).175 A substantial consistency score is considered to be more than 75 per cent (Ragin 2008a, p. 136).
Third, the combinations that are consistent are then simplified using Boolean al-gebra to produce a solution for the outcome.176 This process of Boolean minimization is based on the following rule:
If two Boolean expressions differ in only one causal condition yet produce the same outcome, then the causal condition that distinguishes the two expres-sions can be considered irrelevant and can be removed to create a simpler, combined expression.
Ragin (2008b, p. 38) The strategy one takes when dealing with logical remainders – the possible condi-tions that are not accounted for empirically – determines the complexity or parsimo-ny of the outcome. When the logical remainders are not included in an analysis the
‘most complex solution’ is achieved, and when logical remainders are subject to
173 With 10 cases and 4 explanatory conditions, it is difficult to fill all possible combinations of conditions. The logical remainders can be dealt with either through a counterfactual analysis – which produces parsimonious and intermediate solutions – or by choosing not to incorporate the logical remainder, which produces a most complex solution.
174 While the cut-off point for coverage ought to be drawn on a substantive and theoretical basis, any figure below 75 per cent is generally considered to be increasingly trivial (Ragin 2008a, p. 136).
175 Consistency is expressed in the following formula: (Xi ≤ Yi) = ∑ [min Xi, Yi] ∑ (Xi). The operator ‘min’ stands for the lower of the two values; Xi stands for the degree of membership in the causal combination; and Yi is the degree of membership of the outcome condition (Ragin 2008a, p. 134).
176 For example, there might hypothetically be a consistent combination for low DRM coopera-tion expressed as: ~IPD∗EXP+~IPD∗~EXP ≤ ~DRM. This can be reduced to an intermediate solution (~IPD∗(EXP+~EXP) ≤ ~DRM) and finally to a simplified form: ~IPD ≤ ~DRM. In order to reduce any risk of miscalculations, the fsQCA 2.0 software performs these algebra simplifications.
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terfactual analysis, a ‘most parsimonious solution’ is achieved. An ‘easy’ counterfactu-al is the theoreticcounterfactu-al and substanticounterfactu-al assertion that a logiccounterfactu-ally possible combination of explanatory conditions would, or would not, produce the outcome.177 For example, it can be argued that according to the case selection criteria, a regional organization that does not have an intra-regional trade bias (not interdependent) would be unlike-ly to exist.178 However, as this statement is based on a theoretical assumption – that no interdependence will make DRM cooperation highly unlikely – it would obfuscate the results of the analysis if the aim of this chapter is to test the theoretical assump-tions of neoliberal institutionalism. Given this position, inserting ‘easy’ counterfactu-als are not included. However, including all logical remainders as potential counter-factuals can still be useful for identifying a possible parsimonious solution in addition to the complex solution (cf. Ragin 2008a, p. 173).The following section is divided into three main categories. The first analyses the extent to which there is a general systemic threshold that needs to be passed in order to motivate states to cooperate on regional DRM. The explanatory conditions are thus compared to the level of cooperation when each regional organization began to coop-erate on DRM, which is generally at the nascent level of cooperation. The second sec-tion repeats the same analysis for when DRM passes the threshold from a nascent to an advanced level. That is, when states agree to cooperate at the operational level in addition to information sharing (cf. Annex 6.3). The purpose of this second analysis is to test whether the explanatory conditions hold continual power in explaining the emergence of DRM cooperation from a nascent to an advanced level. This is based on the assumption that as the incentive structure changes, the level of cooperation will also increase. The third section looks at the general increase or decrease in the level of explanatory conditions over the full period of investigation, from 1970-2009. This serves the purpose of verifying and cross-checking the importance of the conditions in explaining the outcome, where it is expected that a similar trend in the outcome and explanatory conditions will occur over time.
177 In contrast, a ‘hard’ counterfactual is the assertion that despite pre-given theoretical as-sumptions, an explanatory condition is argued to be (un)necessary for the outcome (Ragin 2008a, p. 162).
178 The scope conditions of the selection of cases are confined to multi-dimensional regional organizations. This excludes organizations such as NATO or the Shanghai Cooperation Organ-ization that are organized around security issues.
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3.2.2.1. Nascent DRMThe nascent level of regional DRM cooperation, which corresponds to the level of DRM cooperation when each regional organization began to cooperate, is defined by the extent to which each regional organization officially declares the need to cooper-ate and instigcooper-ates knowledge sharing and information exchanges on DRM activities.
That is, the membership in the set of DRM cooperation is low (≤0.5). It is shown here that a weak combination of interdependence, expectations and asymmetrical risk can explain the outcome for a nascent level of DRM cooperation.
Table 3.15 Nascent regional disaster management cooperation
Regional Source: EM-DAT 2011b, UNU-CRIS RIKS 2011, World Bank 2012, cf. Tables 3.10, 3.11, 3.12, 3.13. * The available values for the STI, EXP and ASY are from the period 1970-2008. A small-er numbsmall-er of years are thus used to acquire the avsmall-erage for cases that include values past
2008.179
Table 3.15 depicts the raw figures from the four explanatory conditions and their corresponding fuzzy values according to each qualitative breakpoint.180 The raw fig-ures were taken from the average value of the preceding five year period before the establishment of regional DRM cooperation. The purpose of this is to provide for a more general figure that would presumably have had the most direct relevance for the
179 The raw ITS value for AU, for example, is based on the average from 2004-2008 rather than 2004-2009.
180 As expressed earlier in this chapter, these breakpoints are based on substantive and theo-retical arguments. The breakpoints for the interdependence condition (STI) is 0.90, 0.45, 0.00. The breakpoints for the expectations condition (EXP) is 1.00, 0.50, 0.00. The break-points for the asymmetrical risk condition (ASY) is 458, 98, 0. The breakbreak-points for intra-regional power disparity (IPD) is 8100, 2500, 100.
A rational explanation