ERADICATING POVERTY IN FRAGILE STATES: PROSPECTS OF REACHING THE “HIGH-HANGING” FRUIT BY 2030 that share some of the same elements contained within the four CPIA clusters, including the level of democratization, gender empowerment, government administrative capacity, and government corruption. The IFs capacity index combines the ability of governments to mobilize revenues as a portion of GDP with the level of corruption reduction. The IFs inclusion index combines democratization with gender empowerment. We use a simple average of the IFs capacity and inclusion indices to represent institutions, and for convenience, we label the resulting value the “institution index”. In the FCS list, conflict is represented by the presence of either a UN political mission or peacekeeping mission within the country. For our analysis, we use the IFs security index, which combines an estimate of the probability of intrastate conflict with a sub-index representing overall governance performance and the risk. Both the IFs institution and security indices are based on historical data and we calculate them in the model for each fragile state and can adjust their component values for our scenarios.

Our two optimistic scenarios for institutions and security (referred to as “improved institutions” and “improved security” scenarios) are framed around standard deviation improvements in the IFs institutions index and the IFs security index. A standard deviation is calculated from the IFs institution index for all fragile states in 2010, and the same process is repeated for the IFs security index.

To determine whether our scenario interventions are reasonable, we check our magnitudes of improvement against the thresholds for good governance developed in Pritchett and de Weijer (2010). While Pritchett and de Weijer do not use any indicators directly comparable with the IFs security index, their threshold values for governance lie slightly above the world average. An increase of one standard deviation in the average value of fragile states on the IFs institution index would put that grouping slightly above the world average, supporting our choices with respect to the scale of the improvements.

We next calibrate the rate of improvement in our scenarios against an optimistic scenario methodology. Pritchett and de Weijer (2010) investigate the gains that have been made by developing countries in improving institutions from 1985 to 2009, in terms of bureaucratic quality, corruption, and the role of the military in politics. Those authors then compare the length of time it would take fragile countries to reach a qualitatively designated “good enough” level of governance if they were to improve at 1) their current rate, 2) the average rate of all developing countries, 3) the rate of the fastest 20 countries, and 4) the rate of the top performer. The “fastest 20” rate of improvement is used as the optimistic scenario, and the authors conclude that, at this rate, the average fragile state can achieve a threshold (“good enough”) level of bureaucratic quality in around 24 years. Given that our time horizon is a little less than two-thirds the horizon used in Pritchett et al., a comparable rate of improvement in the IFs indices would produce roughly 60% of a full standard deviation improvement by 2030. Thus our pursuit of a full standard deviation improvement by 2030 is quite an aggressive scenario for reduction in fragility.

Our scenarios assume that improvements in government revenues, gender empowerment, democracy (as measured by the Polity autocracy-democracy index scores) and reductions in government corruption begin in 2015 and ramp up steadily through 2030. Our interventions are not equally weighted; most gains in the aggregate institution index were purposefully made through the decrease of government corruption and increase of polity levels, based on the assumption that corruption and lack of political freedom are greater short-term impediments to state capacity-building in fragile states than revenue collection or gender empowerment.<sup>25</sup> Similarly, the interventions made with respect to the two underlying variables of the IFs security index (intrastate violence and government risk) were not equally weighted in our pursuit of a standard deviation improvement in security. Instead we fully eliminated intra-state conflict and then further reduced government performance risk to achieve the desired overall improvement in the security index for the fragile state grouping.

> 25 The relative weights of the different interventions are based on preliminary scenario analysis; with this in mind, the configuration of the IIS scenario could be disaggregated and its individual effects studied further in subsequent work.

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