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Higher-order effects of climate change on human society are most commonly expressed in terms of economic cost, though other metrics may also be employed (e.g. numbers of persons affected or at risk of potential negative impacts – Parry et al., 1998). This guidance provides only partial consideration of higher-order effects, although their assessment is necessary for a full understanding of future impacts.

In a recent review of economic assessments of adaptation costs in Europe for the ClimateCost project, Watkiss and Hunt (2010) observe that the boundary between assessment of impacts (damage) and adaptation costs is drawn differently depending on the study authors. They also identify a number of variations in approaches to assessment, including whether:

• future socio-economic change is adequately accounted for in cost estimates for future impacts;
• climate changes are sufficiently distinguished from present-day climate variability and the so-called “current adaptation deficit”, which relates to the (in)effectiveness of current adaptation to account for ongoing climate variability;
• costs of climate change should be weighed against possible benefits and reported as “net costs” (e.g. where increased energy costs of summer cooling are assessed alongside reduced costs of heating).

Some of the main methods of assessment of economic costs, examples of their application, along with their advantages and other issues are summarised in Table 3 5.

Table 3 5: Methodological frameworks and models for economic assessment of climate change
and adaptation. Source: Modified from Watkiss and Hunt (2010)

Approach	Description	Examples	Advantages	Issues
Economic Integrated Assessment Models (IAM)	Aggregated economic models. Values in future periods, expressed £ and %GDP and values over time (PVs)	Global studies (e.g. de Bruin et al., 2009a) that provide outputs for Europe.	Provide headline values for raising awareness. Very flexible – wide range of potential outputs (future years, PV, CBA).	Aggregated and low representation of impacts, generally exclude extreme events and do not capture adaptation in any realistic form. Not suitable for detailed national planning.
Investment and Financial Flows (I&FF)	Financial analysis. Costs of adaptation (increase against future baseline)	Global studies (e.g. UNFCCC, 2007; Parry et al., 2009). National studies, e.g. Sweden (SOU, 2007) uses I&FF type approach.	Costs of adaptation in short-term policy time-scale. Easier to apply even without detailed analysis of climate change.	No specific linkage with climate change or adaptation (though can be included). No analysis of adaptation benefits or residual impacts.
Computable General Equilibrium models (GCE)	Multi-sectoral economic analysis.	National level – Germany (Kemfert, 2007); EU review (Osberghaus and Reif, 2010).	Capture crosssectoral linkages in economy wide models (not in other approaches). Can represent global and trade effects.	Aggregated representation of impacts and only capture adaptation in market form. Issues with projections of sectoral inkages. Omits non-market effects. Not suitable for detailed national planning.
Impact assessment (scenario based assessment)	Physical effects and economic costs of CC with sectoral models in future periods, and costs and benefits of adaptation or in costeffectiveness analysis	Multi-sectoral PESETA study (Ciscar et al., 2009). National scale: Flooding in the UK (Thorne et al., 2007) and Finland (Perrels et al., 2010)	More sector specific analysis. Provides physical impacts as well as economic values – therefore can capture gaps and non-market sectors.	Not able to represent cross-sectoral, economy-wide effects. Tends to treat adaptation as a menu of hard (technical) adaptation options. Less relevant for short-term policy.
Impact assessment - shocks	Use of historic damage loss relationships (statistics and econometrics) applied to future projections of shocks combined with adaptation costs (and sometimes benefits)	Sector level, e.g. EAC study (NAO, 2009) in the UK and FINADAPT study in Finland (Perrels et al., 2005)	Allow consideration of future climate variability (in addition to future trends)	Issues of applying historical relationships to the future. Issues with high uncertainty in predicting future extremes
Impact assessment - econometric based	Relationships between economic production and climate parameters derived with econometric analysis and applied to future scenarios – and to consider adaptation. Ricardian analysis relates regional land prices to climate and other factors.	National level Household level or sector. Ricardian analysis has been applied in agriculture (e.g. Lippert et al., 2009)	Can provide information on overall economic growth and allow analysis of longerterm effects. Provide greater sophistication with level of detail.	Mostly focused on autonomous or nonspecified adaptation. Very simplistic relationships to represent complex parameters. No information on specific attributes. Issues on whether relationships are applicable to future time periods.
Risk management	Current and future risks to climate variability. Probabilistic approach.	Flood risk studies (coastal and river).	Well suited for current and future risks and uncertainty, Often used with Costeffectiveness. Has been applied in adaptive management and iterative analysis.	Extra dimension of complexity associated with probabilistic approach. Limited applicability: focused on thresholds (e.g. risk of flooding).
Adaptation assessments	Risks over a range of policy / planning horizons. Often linked risk management and adaptive capacity.	No real economic examples. Emerging number of adaptation assessments.	Stronger focus on immediate adaptation policy needs and decision making under uncertainty and greater consideration of diversity of adaptation (including soft options) and adaptive capacity.	Less explored in relation to economic assessment

 

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Risk management
	CATSIM
Adaptation assessments
	Economic impact analysis
	Economic Optimisation