IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability

6.5 Costs and other socio-economic aspects

The costs, benefits and other socio-economic consequences of climate variability and change for coastal and low-lying areas have been determined for many aspects, including heat stress and changes in plant and animal metabolism (see Chapter 4, Section 4.2 and Box 4.4), disease (see Chapter 8, Section 8.5), water supply (see Chapter 3, Section 3.5), and coastal forests, agriculture and aquaculture (see Chapter 5, Section 5.6). The following section focuses on evaluating the socio-economic consequences of sea-level rise, storm damage and coastal erosion.

6.5.1 Methods and tools for characterising socio-economic consequences

Since the TAR there has been further progress in moving from classical cost-benefit analysis to assessments that integrate monetary, social and natural science criteria. For example, Hughes et al. (2005) report the emergence of a complex systems approach for sustaining and repairing marine ecosystems. This links ecological resilience to governance structures, economics and society. Such developments are in response to the growing recognition of the intricate linkages between physical coastal processes, the diverse coastal ecosystems, and resources at risk from climate change, the many ecological functions they serve and services they provide, and the variety of human amenities and activities that depend on them. Thus a more complete picture of climate change impacts emerges if assessments take into account the locally embedded realities and constraints that affect individual decision makers and community responses to climate change (Moser, 2000, 2005). Increasingly, Integrated Assessment provides an analytical framework, and an interdisciplinary learning and engagement process for experts, decision makers and stakeholders (Turner, 2001). Evaluations of societal and other consequences combine impact-benefit/cost-effectiveness analytical methods with scenario analysis. For example, a recent analysis of managed realignment schemes (Coombes et al., 2004) took into account social, environmental and economic consequences when evaluating direct and indirect benefits.

Direct cost estimates are common across the climate change impact literature as they are relatively simple to conduct and easy to explain. Such estimates are also becoming increasingly elaborate. For example, several studies of sea-level rise considered land and wetland loss, population displacement and coastal protection via dike construction (e.g., Tol, 2007). Socio-economic variables, such as income and population density, are important in estimating wetland value but are often omitted when making such estimations (Brander et al., 2003b). But direct cost estimates ignore such effects as changes in land use and food prices if land is lost. One way to estimate these additional effects is to use a computable general equilibrium (CGE) model to consider markets for all goods and services simultaneously, taking international trade and investment into account (e.g., Bosello et al., 2004). However, the major economic effects of climate change may well be associated with out-of-equilibrium phenomena (Moser, 2006). Also, few CGE models include adequate representations of physical processes and constraints.

Given the recent and anticipated increases in damages from extreme events, the insurance industry and others are making greater use of catastrophe models. These cover event generation (e.g., storm magnitude and frequency), hazard simulation (wind stresses and surge heights), damage modelling (extent of structural damage), and financial modelling (costs) (Muir-Wood et al., 2005). Stochastic modelling is used to generate thousands of simulated events and develop probabilistic approaches to quantifying the risks (Aliff, 2006; Chapter 2).

Methodologically, many challenges remain. Work to date has insufficiently crossed disciplinary boundaries (Visser, 2004). Although valuation techniques are continually being improved, and are now better linked to risk-based decision making, they remain imperfect, and in some instances controversial. This requires a transdisciplinary response from the social and natural sciences.