Annex 3. Economic methods toolkit
Direct, indirect and induced effects
Economic impacts can be categorised by direct, indirect and induced effects. Direct effects represent changes in economic outcomes for businesses directly impacted by the designation of an MPA and/or proposed management measures. Indirect effects refer to changes in economic outcomes in the supply chain of directly affected businesses. Induced effects stem from the changes in spending levels in the economy associated with the direct and indirect effects. Table 2 provides a hypothetical example of potential direct, indirect and induced effects for an MPA.
Change in local commercial fishing employment
Change in commercial fishing supply chain employment
Change in commercial fish and fish processing employees' retail expenditure
Opportunity cost relates to the foregone benefits of choosing one option over other options. When predicting the impacts of a proposal it will be important to consider opportunity costs. For example, opportunity costs may arise if proposals result in foregone revenues to some stakeholders. Further guidance on estimating opportunity cost is available in HM Treasury's Green Book.
Direct, indirect and induced effects can be estimated using multipliers, in terms of GVA, employment and income. Type I multipliers sum together direct and indirect effects while Type II multipliers also include induced effects. The latest multipliers for Scotland are available on the Scottish Government's website. The Supply, Use and I-O tables provide different multipliers which allow the estimation of different effects. For example, GVA multipliers can be used to estimate wider GVA effects while employment multipliers can be used to estimate wider employment effects. The use of multipliers should be clearly presented with reference made to the specific multipliers used.
Displacement is the extent to which the economic effects that occur in one area or industry are offset by economic effects in another area or industry. In the case of an MPA, this may relate to the displacement of fishing effort from within the proposed area to outside of its boundary. Indeed, evidence suggests this often occurs when fisheries management measures are introduced. The scale of the likely displacement of economic activity as a result of proposals should be detailed in the analysis.
Substitution may occur when firms or individuals change their behaviour in response to proposals. For example, previous analysis of the socio-economic impacts of MPAs in Scotland suggests that substitution has occurred between fishing gear types where restrictions on the use of certain gear applies. The capacity for substitution will depend on the specific characteristics of the area under study and the content of proposed management measures.
Cumulative effects are changes that are caused by an action in combination with other actions. The designation of an individual MPA site may have a relatively small effect, but in combination with other planned developments and management measures in close proximity this effect may be amplified. Cumulative effects may be positive or negative.
Cumulative impacts can arise from:
- the interaction between MPA measures and other projects in the same area
- the interaction between the various impacts within a single MPA.
Where cumulative effects are expected to be a feature of an MPA, it is recommended that specific analysis is undertaken to identify the causes, pathways and consequences of the effects.
Optimism bias is the demonstrated systematic tendency for appraisers to be over-optimistic about key project parameters, including capital costs, operating costs, project duration and benefits delivery. Over-optimistic estimates can lock in undeliverable targets.
To reduce this tendency appraisals should make explicit adjustment for optimism bias. The Green Book recommends applying overall percentage adjustments at the outset of an appraisal. It is recommended that these adjustments be based on data from past projects or similar projects elsewhere, and adjusted for the unique characteristics of the project in hand. In the absence of a more specific evidence base, the collection of data to inform future estimates of optimism is advised, and in the meantime use the best available data. Ideally adjustments should be based on an organisation's own evidence base for historic levels of optimism bias. In the absence of robust organisation-specific estimates generic values may be used. For further guidance consult the UK Government's Green Book supplementary guidance: Optimism Bias.
Sensitivity analysis explores the sensitivity of the expected outcomes of an intervention to potential variations in key input variables, due largely to risk and uncertainty. In other words, how much does an outcome value fluctuate with a small change to an input value. Examples where using sensitivity analysis to explore the effects associated with changing variables are:
- Values given to time
- Wage rates used
- Costs associated with proposals
- The multiplier effect applied to the economic impact of an investment or scheme
- Environmental impacts
Techniques to deliver sensitivity analysis may include simple spreadsheet calculations, Monte Carlo simulation modelling or the use of qualitative decision trees.
Distributional impacts describe the distribution of impacts resulting from the project across different individuals, groups or businesses. This is a main feature of the social impact assessment but should also be a consideration in the economic impact assessment. For example, impacts may vary at the geographic level or by size of business.
Distributional weighting of impacts is possible but is often very challenging and can be highly subjective, any attempt of this should be presented clearly and transparently. In the absence of weighting, expected distributional impacts should be presented qualitatively through narrative and any analysis disaggregated to the appropriate groups or levels where possible, for example industry turnover by size of business.
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