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The sanctions assessment methodology is presented here in five steps, and is summarized in schematic form in figure 7. The methodology can be used to assess potential humanitarian consequences in advance of, during or following sanctions (see section 5.5). The five steps can also be applied to assess potential impacts of different types of sanctions (section 5.6).
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Identify the measures covered by sanctions, the nature and scope of humanitarian exemptions (if applicable), and provisions for selective approval of exempt goods. These actions—for example, a prohibition on air travel for a particular country, or a ban on the sale and export of diamonds—constitute a starting point for the assessment. |
Chapter 4 provides guidance on indicators and data sources |
To monitor humanitarian conditions investigators must identify potential indicators and associated data sources. Indicators of humanitarian conditions should span the “4 + 4” human security subject area. The four CORE subject areas of human security relate to: health, food and nutrition, water and sanitation, and education; while the four SYSTEMIC subject areas relate to governance, economic status, physical environment and demography. |
| Box 6 |
The choice of which indicators to use is based on the type of sanctions, available data, capacity and ability to collect original data, previous studies, and indicators already used by humanitarian agencies in the country. Box 6 outlines some priority indicators of PROCESS and OUTCOME in each of the human security subject areas. |
| Guidelines for baseline assessment, section 5.3 and “Checklist” in box 5 |
Using these indicators of humanitarian conditions, carry out a baseline assessment of conditions prior to, or at the onset of, sanctions. This should follow the guidelines outlined in section 5.3 (and box 5) to provide a starting point against which to track changes in conditions.
If the assessment is undertaken prior to the imposition of sanctions, current and historical conditions will serve as a baseline. If the assessment is being undertaken during sanctions, and a previous baseline does not exist, then a retrospective baseline drawing on historical data sources should be elaborated. |
| See section 5.3.1 |
This baseline should include an assessment of the humanitarian vulnerability of the population prior to sanctions. In addition to considerations of population groups most at risk from changes in economic and social conditions in general, this should include an analysis of how previously lowvulnerability groups may experience significant additional exposure to risk as a direct or indirect result of sanctions. |
| See “Creating a model of the chains of causa tion” section 3.4 |
Identify possible causal pathways and intermediate variables linking the sanctions measures to the potential effects (changes to humanitarian conditions as measured by indicators selected in step I) in each subject area. |
| For indicators in each of the eight human security subject areas, see annex II |
Begin with the four core subject areas (health, food and nutrition, water and sanitation, and education), as this will assist in identifying intervening variables for other subject areas. The PROCESS indicators in each of the subject areas in the table of indicators (annex II) and box 6 represent possible intermediate variables. Construct causal models (see box 2) tracing forward from individual sanction measures and tracing backwards from humanitarian conditions (to identify intermediate causes). For each “node” or junction along the pathways identify each possible significant cause. Use the criteria of causation to confirm causal relationships between variables. |
| For “Criteria of causation”, see section 3.4 |
| Another example of a causal model is presented in figure 4. |
For example, in the economic sector, tracing forward from sanctions on statecontrolled mining operations may identify a reduction in government revenue from this source due to sanctions as the next link in the chain. A collateral link in the chain (again in this economic sector) may be the reduction of employment among miners. Each of these intermediate causes can then be traced to the next step. Reduced government revenue may reduce funding for social services and health care. In this way, a weblike set of linkages between the sanction measures and humanitarian conditions is constructed. |
Section 4.6 |
Step I of the methodology included the identification of indicators for determination of humanitarian conditions prior to sanctions (i.e. for “baseline” assessment). Once the causal model associated with each human security subject area has been constructed (step III above), identify sources of quantitative and qualitative information for each of the PROCESS indicators associated with the intermediate steps in the chain of events and for the OUTCOME indicators that have been identified as possible areas of humanitarian impact in the causal models. Some of these OUTCOME indicators may be the same as those identified in step I. Previously they were used for identifying conditions at baseline, and now they will be used to measure changes in those conditions. |
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If this effort points to gaps in available information and data, and time and resources permit, then investigators should consider collecting original data to address this deficiency. Collect the information and data from the identified sources using the guidelines presented in chapter 4. When gathering data, ensure that the resulting PROCESS and OUTCOME indicator values reflect the vulnerabilities of particular population groups to changes due to sanctions.
Following completion of this step, the investigator should have data sources and information available for each “node” or step in the causal models constructed under step III.
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| Figure 2 |
The causal models and associated indicators and data sources that have been constructed in the preceding four steps provide the basis for extracting the contribution of sanctions to changes in humanitarian conditions, which is the final step in the methodology.
To do this, repeat the following process for each of the eight causal models (one for each human security subject area):
- Starting with the sanction measure(s), trace a path through the causal model for a human security subject area one intermediate step at a time. Using the simple causal model shown previously in figure 2 as an example, this would involve tracing through the steps from “trade sanction” to “increased malnutrition”.
- At each intermediate step, use the quantitative and qualitative information associated with the PROCESS indicators (gathered in step IV) to identify how much of an influence the sanction(s) has on that particular intermediate step. In some instances it may indeed be possible to calculate the contribution of sanctions to the intermediate effect in a quantitative manner (e.g. “Trade sanctions resulted in the elimination of 5,000 jobs in sector X, representing a Y per cent increase in the prevailing unemployment rate in the formal sector.”) However, in many cases, the investigator must make an informed estimate about the mechanisms, and the level of importance of each, of the contribution of sanctions to the variable of interest based on available data.
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| Sections 4.6 and 4.7 |
- At each of these intermediate steps, take measures to enhance the reliability of the assessment by: (i) assigning a level of confidence to the assessment of the impact of sanctions at each individual step (not purely a statistical measure) (see section 4.7); (ii) using multiple data sources to “triangulate” for accuracy; and (iii) using qualitative information to better inform your judgement of how much sanctions impact the particular step (see section 4.6).
- Proceeding along the intermediate steps in each causal model, catalogue the contribution of sanctions, at each intermediate step in the causal model. This can be done by simply compiling a list of the assessed consequences of sanctions at each intermediate step.
- When this process of tracing finishes at the OUTCOME indicators of humanitarian conditions (the final step in the causal model), the impact of sanctions on those conditions can be expressed as the cumulative impact of sanctions at each of the intermediate steps leading to that outcome. Box 7 presents a simple example to demonstrate this cumulative effect.
- Finally, present the findings as a direct sanctionoutcome relationship, and also as a linked process. For the former, summarize the impact of sanctions on specific humanitarian conditions by directly linking the sanction measure with those conditions that have been shown to be affected. For example, in the education subject area: “Sanctions on mining activities contributed to a decline in school enrolment rates for children aged 1016 by 20 per cent nationwide.” For the same example, reporting of the process highlights the intermediate steps: “Sanctions on mining activities resulted in the loss of 10,000 jobs each paying approximately US$ 2/day. Qualitative information and surveys confirm that this resulted in increased engagement of those child dependants of displaced workers in informal sector employment. This accounts for most of the 20 per cent reduction in school enrolment."
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Once these five steps have been completed the results of the assessment are compiled and explained in an assessment report (for guidelines on the key elements of the assessment report, see section 6.6).
One approach that can assist the investigator in isolating the effects of many factors on a single outcome is to conduct a survey of humanitarian practitioners in the country to get their input on the relative “weighting” or importance of the sanction measures’ contribution to a given effect.
The survey can ask participants to rank the multiple causes to a common effect, or to make a comparison between pairs of variables (referred to as pairwise comparison). For example, experts in the field could be asked:
“What in your view has contributed more to the raised incidence of preventable diseases among children, inadequate maternal and childcare practices OR poor access to safe water and sanitation?”
The results of these surveys can then be consolidated into a table of weighting factors for the relevant causes.
This process of pairwise comparison and expert survey has been used effectively to reduce the subjectiveness of investigatordominated judgements. The methodology has been formalized by scholars and practitioners in the domain of strategic decisionmaking in a technique known as the Analytical Hierarchy Process (AHP).33 Ranking a variable based strictly on the scores given by a regular survey of experts is common in many fields and referred to as a Delphi Method. It is useful for synthesizing a great deal of qualitative information into a quantitative measure that can be tracked over time. While this does not eliminate the possibility for subjective judgements (it merely averages many individual opinions), it can highlight areas of consensus on what factors lead to what outcomes.
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