Sectoral marine plan for offshore wind energy: social and economic impact assessment scoping report

B.3. Distributional Analysis

The approach to undertaking the social impact analysis ( SIA) is set out in Section 2.10. The distributional analysis forms part of the social impact analysis and involves identifying how any impacts would be distributed across different groups within society.

The first step within the distributional analysis is to identify the social impacts and their likely significance:

Step 1: Identify if there is an impact on each of the value clusters and, if so, which sectors or activities would be affected and provide a description of the direct effects. Table B.3.1 provides the table template that can be used to record this part of the assessment; it is used to record the information from Steps 1 to 3.

Step 2: Consider who would be most affected by the costs associated with a change in GVA, costs or knock-on effects that exceed 5% of turnover, and impacts that have been identified as being significant at the local level and that have been quantified and monetised. The costs are allocated to the value clusters that most closely represent the impacts that would be caused as a result. These can be recorded in Table B.3.1 as quantified/ monetised impacts. Any mitigation in place that would reduce the impacts should also be recorded.

Step 3: Identify the non-quantified impacts (qualitative assessment) and record both magnitude and direction in Table B.3.1 using the definitions set out in Table B.3.2. These range from significant through to minimal effect (positive or negative). A typical (average) impact should be identified and recorded.

Table B.3.1 Table for recording typical impacts by social value cluster

Table B.3.2 Definitions for application to the qualitative assessment

Step 4: identify the distributional consequences of each of the social impacts. Table B.3.3 lists the different groups of people that might be affected. Two tables are used to record these impacts to provide sufficient space for justifications to be included (the example for knock-on effects from loss of traditional fishing grounds is continued in Tables B.3.4 and B.3.5 to illustrate how the tables could work):

• Table B.3.4 is used to record impacts relating to location, age and gender. Where the impact is expected to be larger on a particular group than average, the rating is increased. So, for example, loss of traditional fishing grounds that impacts on fish processing is assigned a '-' in Table B.3.1 against jobs/career/employment. Table B.3.4 requires consideration of where and who might be affected by that impact. Where impacts are more likely to occur in rural areas because that is where the fishing ports are mainly located, the impact is increased to '- -'. The rating is reduced where an impact is less than average for a particular location or group (for urban locations the rating in the example in Table B.3.4 is 0 as no noticeable effects are expected). Impacts that are expected to be the same as average retain the original rating. Where a change to the average impact is made, the tables include a brief reason describing why the change has been made.
• Table B.3.5 is used to record impacts relating to different income groups and particular social groups: crofters, ethnic minorities, those with a disability or who are long-term sick, special interest groups and other (those not picked up elsewhere). Again, the ratings from the first table are used as the basis for the assessment, with ratings increased to reflect that a particular group is likely to be impacted more significantly. The extent of the increase is used to reflect how concentrated the impact would be on a particular group and, hence, how noticeable it is likely to be to them. Reference can be made back to the value clusters of local importance identified in specific areas ( Table 1 in Section 2.10) when completing these tables to ensure that local priorities are taken into account.

Table B.3.3 Groups considered in the distributional analysis

Table B.3.4 Distributional analysis: location, age and gender

Table B.3.5 Distributional analysis: income and social group