Working Group II: Impacts, Adaptation and Vulnerability

Other reports in this collection Ensuring Equity

All of the complications outlined in Section lead to a sad conclusion: Economics may be able to highlight a large menu of distributional issues that must be examined, but it has trouble providing broad answers to measuring and accounting for inequity, particularly across nations. Recourse to ethical principles clearly is in order.

2.5.6. Alternative Metrics for Measuring Costs

Application and extension of the economic paradigm certainly focuses attention on cost measures that are denominated in currency, but practitioners have been criticized on the grounds that these measures inadequately recognize nonmarket costs. Schneider et al. (2000), for example, have listed five numeraires or metrics with which the costs of climate change might be captured. Their list includes monetary losses, loss of life, changes in quality of life (including a need to migrate, conflict over resources, cultural diversity, loss of cultural heritage sites, etc.), species or biodiversity loss, and distributional equity. Chapter 19 recognizes the content of these diverse numeraires in exploring magnitudes and/or rates of climate change that might be dangerous according to three lines of evidence: threatened systems, distributions of impacts, and aggregate impacts. The implications of the fourth line of evidence, large-scale discontinuous events, are then traced along these three dimensions.

When all is said and done, however, costs denominated in one numeraire must be weighed, at least subjectively, with costs denominated in another—and there are no objective quantitative methods with which to do so. A survey conducted by Nordhaus (1994a), however, offered some insight into 15 researchers' subjective views of the relative importance of several different measures along three different "what if" scenarios. Table 2-1 displays some of the results in terms of anticipated cost denominated in lost world GDP, the likelihood of high-consequence impacts, the distribution of costs across the global population, and the proportion of costs that would be captured by national income accounts. The survey results shows wide disagreement across the first three metrics; this disagreement generally can be explained in terms of a dichotomy of views between mainstream economists and natural scientists. Nonetheless, Nordhaus (1994a) reports that a majority of respondents held the view that a high proportion of costs would be captured in national accounts. It would seem, therefore, that natural scientists think that mainstream economists not only underestimate the severity of nonmarket impacts but also that the implications of those impacts into the monetized economy do not follow.

Multi-attribute approaches also could be applied in climate impact analysis. They have not yet found their way into the literature, however, except to the degree to which they are captured in indirect methods outlined above. Chapter 1 also notes that cultural theory can serve as a valuation framework.

Table 2-1: Subjective expert opinion on climate change (Nordhaus, 1994a).

Cost metric Scenario Aa Scenario Bb Scenario Cc
a) Loss in gross world productd
- Mean 1.9 4.1 5.5
- Median 3.6 6.7 10.4
- High 21.0 35.0 62.0
- Low 0.0 0.0 0.8
b) Probability of high-consequence evente

- Mean 0.5 3.0 5.0
- Median 4.8 12.1 17.5
- High 30.0 75.0 95.0
- Low 0.0 0.2 0.3
c) Top to bottom ratio of impactsf

- Mean 4.2
- Median 3.5
- High 10.0
- Low 1.0
d) Percentage of total in national accounts      
- Mean 62.4 66.6 65.6
- Median 62.5 70.0 80.0

a Scenario A postulated 3°C warming by 2090.
b Scenario B postulated scenario A continuing to produce 6°C warming by 2175.
c Scenario C postulated 6°C warming by 2090.
d Percentage of global world product lost as a result of climate change.
e Likelihood of a high-consequence event (a loss of 25% of gross world product, comparable to the Great Depression).
f Proportion of loss felt by the poorest quintile of income distribution relative to the loss felt by the richest quintile; a value of 1 signifies an equal distribution of burden.

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