|LINKING COMPLEX EMERGENCY RESPONSE AND TRANSITION INITIATIVE|
CERTI Crisis and Transition Tool Kit
Conflict Early Warning and Early Response
For Sub-Saharan Africa
Summary of Working Draft
Center for International Development and Conflict Management (CIDCM)
University of Maryland
Prepared for CERTI byThe Center for International Development and Conflict Management (CIDCM) University of Maryland
This project was made possible through Cooperative Agreement Number HRN-A-00-96-9006 between the US Agency for International Development and Tulane University
The number and magnitude of wars and related disasters increased globally throughout the Cold War, peaked in 1990-1993, and have fallen sharply since then, with both a marked decline in the onset of new wars and an unprecedented success rate in containing or ending existing wars (Marshall, 1998; Ayers, 2000; Gurr, 2000a & b; Davies and Gurr, forthcoming). This success reflects a strengthening of norms, capacity and political will in favor of protecting at-risk minority groups and preventing the escalation and spread of political violence.
There remain significant levels of instability, with new democratic norms and institutions under challenge in many parts of the developing world, and it is these conflicts that continue to dominate the news, rather than successes in conflict management and prevention. Positive trends in Sub-Saharan Africa are in any case more modest, with six high intensity wars still current in early 2000, twenty more minority groups substantially at risk of future wars (Gurr, 2000c), and with the Central African/Greater Horn region yet to share the positive trends experienced elsewhere. Nevertheless, these trends point to an opportunity to provide international support for strengthening capacity for conflict management and prevention throughout this troubled region.
The goal of early warning systems may be conceived as avoiding or minimizing violence, deprivation or humanitarian crises that threaten the sustainability of human development. Human development implies improving quality of life through expanding human and social capital, as required to adapt to change and better satisfy human needs such s those for security, identity/valued relationships and effective participation.
Reliable early warnings buy time not only to prepare for short term containment and relief strategies, but also to design, build support for and implement longer term proactive strategies and development programs that can reduce the likelihood of future disasters. An early warning system is more than the flow of information and reports from those on the ground regarding highly visible or rapidly escalating crises. It should also provide reliable analyses that identify still-latent or low-level conflicts or instabilities before they attract CNN and international headlines, when there is still time for investing in appropriate structural development and building conflict management capacity.
More than that, early warning systems can generate analyses that identify key factors driving the instability, providing a basis from which to assess likely future scenarios, and recommend appropriate options for local and international policy makers oriented toward preventive action. They also should keep track of what preventive strategies have been used in what contexts in the past, to what effect and at what cost.
Such analyses improve the reliability of conflict early warnings (current model-based warnings have been found accurate close to 80% of the timesee below), and can be used to build political will and coalitions among potential responders for appropriately designed preventive action, at a fraction of the cost of reactive humanitarian and peace-keeping initiatives. In addition, these coalitions should include where possible, domestic as well as international, private as well as public sector partners, thereby significantly adding to the strength of civil societies and democratic institutions, and their capacity to manage their own conflicts in the longer term.
Along with disease (AIDS) and natural disasters such as drought, ethnic wars and repression within states constitute an enormous threat to human security in Sub-Saharan Africa. Yet much more needs to be done to develop systems for providing early warning of violent civil conflict and of related phenomena, such as mass killings (genocide or politicide), gross human rights violations, regime failure, refugee and IDP flows, environmental degradation and food shortages.
Three stages of conflict or crisis development will need to be distinguished for purposes of building early warning systems (see e.g., Lund. 1996):
i. Structural tensions or instability: Potential crises at this stage may be identified through tracking background or structural conditions that constitute root causes of tension and crises. Examples include a history of state repression, exclusionary ideologies, lack of democratic experience, increasing gaps in income and economic opportunity, high cohesion and external support for aggrieved groups, land desertification, and increasing population pressures. These structural conditions tend to change slowly, and so form the basis for long-term risk assessments: the probability that a crisis will occur at some time in the next several years or decade, and are needed for preventive peace-building or peace-making initiatives and long-term planning.
ii. Escalation: Potential crises at this critical stage may be identified through tracking dynamic factors or accelerators, which may exacerbate the underlying conditions, driving up tensions. Examples include arms or resource acquisitions, incidents of aggressive posturing or low-intensity violence, new discriminatory and repressive policies, crop failures, and major currency devaluations. These are events that unfold rapidly and provide the basis for dynamic early warnings: indicating the probability of a crisis within the coming months or weeks, as needed for last minute preventive diplomacy and containment efforts, or at least in planning for humanitarian aid and peace-keeping.
iii. Crisis/War: The transition to a full-blown humanitarian crisis or war may be marked by trigger incidents such as a coup attempt, assassination, or declared state of emergency that may act as a match to ignite the flammable mix of dry trees or logs (structural factors) with dry brush or lighter fluid (accelerators). At this stage the opportunity for prevention has passed, but the need for relevant information and (comparatively high-risk, high-cost) reaction is no less urgent.
Early warning and early response systems will require both structural risk assessment processes to point to opportunities for appropriate and well-planned preventive action to address structural problems, and linked dynamic early warnings to flag the need for more immediate containment efforts.
The more conventional approach to early warning among operational agencies has involved the preparation of internal, interpretive reports for policy makers, focusing on the substance of the assessment and the need to package the report to bring out available policy options within the constraints on the agencys capacity to respond. These are typically based on field monitoring and in-country situation studies, supplemented by limited but increasingly systematized sharing of field reports and indicator monitoring, through mechanisms such as UNOCHAs Humanitarian Early Warning System (HEWS) for UN agencies, or its publicly available, internet-based ReliefWeb and African IRIN reports. UNHCRs Center for Documentation and Research similarly has begun to make versions of its more structured country situation assessments for UN interagency meetings also publicly accessible via the web.
A complementary approach is the generation of analytical reports employing explicit structural or dynamic models of crisis phenomena. Models provide an essential complement to field monitoring and indicator monitoring through specifying the combinations of risk factors and sequence of events that are likely to lead to different types of crises, distinguishing between remote and proximate conditions. This approach has been favored by academic researchers, and its advantages include being accessible for systematic testing and progressive refinement and adaptation based on cumulative results, and providing a means for identifying the key factors to be addressed for effective prevention.
These model-based analyses may draw on country or group profiles or databases of structural indicators (e.g., Gurrs, 2000a, Minorities at Risk data), coded assessments by country experts (e.g., Scarborough, 1998; Schmid, 1998), and/or coded analyses of multiple filtered, publicly accessible news and information sources (e.g., Harff and Gurr, 1998). Analysis of data from both risk assessment and dynamic early warning models can make use of powerful statistical tools for complex pattern recognition, such as neural net analysis or time-series impact assessment analysis, to distinguish where and when escalation and crises are likely.
Another rich information source is to be found in episodic databases which profile past conflicts and crises, including information on crisis development and the effectiveness of attempts at crisis prevention or management (e.g., Brecher and Wilkenfeld, 1988; Bercovitch, 1996; Bloomfield and Moulton, 1997). This can provide an empirical basis for recommending early response options which are likely to be more effective in current potential crises.
The most extensive empirical research evaluation of risk assessment and early warning models has been conducted as part of the ongoing White House-initiated State Failure Project (e.g., Esty et al., 1998) and the derivative Genocide Early Warning Center in the Department of State. State failures (including partial failures, with 243 cases between 1955 and 1994) were divided into four categories: revolutionary wars, ethnic wars, genocides and politicides, and adverse or disruptive regime transitions.
Phase 1 of the project compared these with 339 matched control cases, 617 variables were evaluated as potential structural indicators, leading to identification of 31 demographic/social, political, and economic/environmental variables that were significant discriminators of impending state failure at least two years in advance. The best overall risk assessment model (using regression and neural net analyses, and about 70% accurate) combined three of these variables:
i. Openness to international trade (best measure of a countrys integration into the global economy, requiring respect for international norms and rule of law);
ii. Infant mortality (best measure of quality of life); and
iii. Democracy (measuring the conflict inhibiting effects of democratic governance, requiring responsiveness to popular discontents).
More specific models were developed and tested for the three more common forms of state failure: ethnic war, regime collapse and genocide/politicide. Inclusion of variables for the ethnic character of the ruling elite and for the existence of a demographic youth bulge improved accuracy of the ethnic war model to 72-78%, and similar levels of accuracy have since been achieved using more detailed and theoretically grounded models for ethnic war, regime crises and genocide/politicide.
Phase 2 of the project focused on the development and testing of dynamic early warning models to supplement the structural models. These accelerator models are designed for use with cases that have been identified as high risk using the structural models, to track events in order to anticipate when an unstable situation is likely to escalate to full-blown crisis (war, genocide or adverse regime transition) in the following months. These models each allow accurate anticipation of when a crisis will erupt six months in advance, about 78% of the time. The genocide/politicide model is now being tested real time as a project of the Genocide Early Warning Center.
More detailed versions of the ethnic war and genocide/politicide models, both structural and dynamic, are available (Harff and Gurr, 1998; Gurr, 2000a), with guidelines for measuring each variable. More recent research findings will be published shortly, including details of the statistical procedures that are required to take advantage of the power of these models. These procedures and findings, and details of the as yet unpublished regime transition model, should also be available internally to USAID from the State Failure Project.
The structural model for ethnic war, for example, includes factors reflecting group incentives for collective action (lost political autonomy, active political, economic or cultural discrimination); group capacity for collective action (strength of identity, militant mobilization); and opportunities for collective action (recent regime transition, support from kindred groups). In contrast, the structural model for genocide/politicide includes factors such as: history of the regimes reliance on coercion, international economic status, exclusionary ideologies, lack of constraints on security agencies, elite (and target group) fragmentation, and economic hardship that leads to differential treatment of disadvantaged groups.
Research has also been conducted to test risk assessment models for other conflict-related crises such as refugee and IDP flows (e.g., Schmeidl and Jenkins, 1998; Onishi, 1998) and environmental conflicts (e.g., Baechler, 1998). The more specifically targeted models should allow greater accuracy, but require greater investment to the degree that multiple models are needed to anticipate the full range potential crises.
Some success is being achieved through the development of collaborative partnerships or networks that bring together government or IO agencies with NGOs and academic research institutions concerned with conflict and crisis early warning. Examples include the EU-supported Conflict Prevention Network, the OSCEs Conflict Prevention Center, the London-based Forum on Early Warning and Early Response (FEWER), the Utrecht-based European Platform for Conflict Prevention and Transformation, and Center for Preventive Action supported by the New York based Council on Foreign Relations.
FEWER, for example, aims to inform and promote coordinated and early responses to violent conflict through the provision of response-oriented analyses of conflict areas to key actors with relevant conflict prevention capacities. FEWER is a global consortium of NGOs and academic research centers which is building global and regional networks and preventive action partnerships with governmental and IO agencies. Emphasis is placed on utilizing and enhancing the capacities and skills of local member organizations, supported by international members, in developing early warning reports up to international standards, in developing regional conflict prevention tool-boxes appropriate to local conditions, convening strategic roundtables for the development of action plans for peace, convening governmental/inter-governmental contact groups where policy makers are convened to discuss responses to conflict generating factors (as recently for the Djavakheti region of southern Georgia, on the border with Armenia), and pooling non-governmental conflict prevention capacities where needed to respond to urgent escalating situations.
The early successes of such collaborative initiatives, and the empirical research findings reviewed above, point to certain principles and priorities for the development of conflict early warning and response capacity in USAIDs Africa Bureau. These include (see Gurr, 2000c):
i. High priority should be given to identifying and monitoring latent and emerging crises well in advance of the outbreak of war or related forms of humanitarian crisis.
ii. To this end, an inventory of ethnic, religious, national and political groups at risk from adverse discrimination or potential conflict in Sub-Saharan Africa should be compiled. A starting point for this is available from the Minorities at Risk data.
iii. Explicit models specifying what risk factors are known or thought to be associated with what types of conflict or crisis should be used to aid interpretation of available information.
iv. Long-term risk assessments from structural factors should be supplemented by near-real-time tracking of events in unstable (high-risk) areas to anticipate escalation of crises.
v. Monitoring and analyses should be done outside the reach of political control and considerations, to ensure that results are, and are seen to be, objective. This can be accomplished by engaging non-government and academic participants in an early warning network, as well as through ensuring operational independence of analysts within the Africa Bureau.
vi. Use of standard protocols for generating risk assessments and early warnings helps ensure both comprehensiveness and precision in the reports, and allows comparison of assessments both across different locations, and form different sources, as needed for deciding priorities in the allocation of limited resources for response.
vii. It is essential to develop close and regular communications between early warning analysts and officials with operational responsibility for preventive action and humanitarian response. This is required to ensure that early warning reports contain information useful for informed decision making, including drawing out the implications of structural and dynamic analysis into likely future scenarios and identification of a range of early response options which are appropriate to the situation and within operational and policy constraints of potential intervenors. It will also give the early warnings a greater level of credibility, as needed for an early warning system to be effective.
viii. Such contact groups should also be regularly engaged in constructing and reviewing tool boxes of regionally appropriate preventive or early response options, drawing lessons from past applications within the region and elsewhere.
ix. Early warnings and risk assessments should be widely circulated, most urgently to those in a position to contribute to collaborative preventive initiatives, and also to other NGOs, scholars, activists and journalists within and beyond the region as far as is possible without risking the safety of those directly involved. This will help to promote public discussion of the issues, build political support for preventive action, and generate new ideas and action responses.
x. USAID has a responsibility to support the building of local capacity for conflict prevention, as needed for strengthening civil society, democratic norms and sustainable peace and development in the long term. In addition, by engaging local professionals in the early warning process, AID will avoid the resentment and suspicions of bias that would follow release of comprehensive in-house assessments, while still being able to use the reports to mobilize cooperative efforts with broad public support.