4. Uncertainty and worst-case risks
Climate change entails relatively predictable, reasonably bad expected or average outcomes — and catastrophically worse outcomes that are unlikely but not impossible. How should economics incorporate uncertainty about catastrophic worst-case risks?
Economics of climate change under uncertainty: Benefits of flexibility
Jon Anda, Alexander Golub and Elena Strukova
Energy Policy (2009) 37(4): 1345-1355.
The selection of climate policy has to be made in an extremely uncertain environment: both benefits and costs of a particular climate policy are unknown and in the best case could be described by the probability distribution of various outcomes. The expected value approach to cost-benefit analysis relies on the aggregated estimation of various outcomes of climate policy weighted and averaged by probabilities. The variance, skewness, and kurtosis are important characteristics of uncertainties but can be easily lost in the process of aggregation. Real option analysis explicitly accounts for both the expected value of underling assets and the variance of the expected value (as well as skewness and kurtosis that are important to describe a fat tail phenomenon). In the paper, we propose an application of real option analysis in order to formulate rules for the selection of a climate policy (emission target) and estimate the economic value of the future flexibility created by interim climate policy, which may be corrected in the future in response to new knowledge that hopefully reduces uncertainties. The initially selected interim policy has an option value and methodology for its valuation presented in the paper.
Integrating economic analysis and the science of climate instability
Darwin C. Hall and Richard J. Behl
Ecological Economics (2006) 57(3): 442-465.
Scientific understanding of climate change and climate instability has undergone a revolution in the past decade with the discovery of numerous past climate transitions so rapid, and so unlike the expectation of smooth climate changes, that they would have previously been unbelievable to the scientific community. Models commonly used by economists to assess the wisdom of adapting to human-induced climate change, rather than averting it, lack the ability to incorporate this new scientific knowledge. Here, we identify and explain the nature of recent scientific advances, and describe the key ways in which failure to reflect new knowledge in economic analysis skews the results of that analysis. This includes the understanding that economic optimization models reliant on convexity are inherently unable to determine an "optimal" policy solution. It is incumbent on economists to understand and to incorporate the new science in their models, and on climatologists and other scientists to understand the basis of economic models so that they can assist in this essential effort.
Why economic dynamics matter in assessing climate change damages: Illustration on extreme events
S. Hallegatte, J.-C. Hourcade
Ecological Economics (2007) 62(2): 330-340.
Extreme events are one of the main channels through which climate and socioeconomic systems interact, and it is likely that climate change will modify the probability distribution of the losses they generate. The long-term growth models used in climate change assessments, however, cannot capture the effects of such short-term shocks. To investigate this issue, a non-equilibrium dynamic model (NEDyM) is used to assess the macroeconomic consequences of extreme events. This exercise allowed us to define the economic amplification ratio, as the ratio of the overall production loss due to an event to its direct costs. This ratio could be used to improve the cost-benefit analysis of prevention measures. We found also that, unlike a Solow-like model, NEDyM exhibits a bifurcation in GDP losses: for each value of the capacity to fund reconstruction, GDP losses remain moderate if the intensity and frequency of extremes remain under a threshold value, beyond which GDP losses increase sharply. This bifurcation may partly explain why some poor countries that experience repeated natural disasters cannot develop. Applied to the specific issue of climate change, this model highlights the importance of short-term constraints in the assessment of long-term damages, and shows that changes in the distribution of extremes may entail significant GDP losses in absence of specific adaptation. It suggests, therefore, that to avoid inaccurately low assessments of damages, researchers must take into account the distribution of extremes instead of their average cost and make explicit assumptions on the organization of future economies.
Uncertainty and economic analysis of climate change: A survey of approaches and findings
Sonja Peterson
Environmental Modeling and Assessment (2006) 11: 1-17.
The analysis of climate change is confronted with large uncertainties that need to be taken into account to arrive at meaningful policy recommendations. The main contribution of economics to this interdisciplinary task is to provide formal frameworks and techniques for analyzing climate policy in the context of uncertainty. This paper will give an overview of existing approaches and findings to provide a broad picture of what economics can contribute to the debate.
Uncertainty and Climate Change Policy
John Quiggin
Economic Analysis and Policy (EAP) (2008) 38(2): 203-210.
The paper consists of a summary of the main sources of uncertainty about climate change, and a discussion of the major implications for economic analysis and the formulation of climate policy. Uncertainty typically implies that the optimal policy is more risk-averse than otherwise, and therefore enhances the case for action to mitigate climate change.
Climate change policy: quantifying uncertainties for damages and optimal carbon taxes
Tim Roughgarden and Stephen H. Schneider
Energy Policy (1999) 27: 415-429.
To calculate an “optimal” control rate or carbon tax a climate-economy model can be used on estimates of climate damages resulting from warming scenarios. The dynamic integrated climate-economy (DICE) model, in its original specification, suggested that an efficient policy for slowing global warming would incorporate only a relatively modest amount of abatement of greenhouse gas emissions, via the mechanism of a small carbon tax. Here, the DICE model is reformulated to incorporate several alternate damage estimates, resulting in a significantly more aggressive optimal policy than that suggested by the original model. In addition, statistical distributions of these damage estimates are constructed and used in a probabilistic analysis of optimal carbon tax rates, resulting in mostly much larger (but occasionally smaller) carbon taxes than the DICE defaults. In view of the large uncertainties in estimates of climate damages, a probabilistic formulation that links many of the structural and data uncertainties is essential to policy analysis, since point values or “best guesses” deny policy makers the opportunity to consider low probability, but policy-relevant, outliers.
Is the uncertainty about climate change too large for expected cost-benefit analysis?
Richard S. J. Tol
Climatic Change (2003) 56: 265-289.
Cost-benefit analysis is only applicable if the variances of both costs and benefits are finite. Finiteness is hard to prove; the opposite is easier to establish as one only needs to show that there is one possible climate change scenario with infinite variance. The paper shows that all relevant current variables of the FUND climate economics model have finite variances. However, there is a small chance that climate change reverses economic growth in some regions. In that case, the discount rate becomes negative and the present value of benefits of greenhouse gas emission reduction become so large that the variance is unbounded. One could interpret this as an indication that cost-benefit analysis is invalid. Alternatively, one could argue that the infinity is present in both the base case and the policy scenario, and therefore irrelevant — implying that cost-benefit analysis remains a valid tool.
Optimal climate policy is a utopia: from quantitative to qualitative cost-benefit analysis
Jeroen C.J.M. van den Bergh
Ecological Economics (2004) 48: 385-393.
The dominance of quantitative cost-benefit analysis (CBA) and optimality concepts in the economic analysis of climate policy is criticised. It is based in a misplaced interpretation of policy for a complex climate&-economy system as being analogous to individual inter-temporal welfare optimisation. The application of quantitative CBA and optimality concepts to climate policy reflects an overly ambitious approach that does more harm than good. An alternative approach is to focus the attention on extreme events, structural change and complexity. A qualitative rather than quantitative CBA that takes account of these aspects can support the adoption of a minimax regret approach or precautionary principle in climate policy. This means: implement stringent GHG reduction policies as soon as possible.
On modeling and interpreting the economics of catastrophic climate change
Martin L. Weitzman
Review of Economics and Statistics, (2009) 91(1): 1-19.
With climate change as prototype example, this paper analyzes the implications of structural uncertainty for the economics of low-probability, high-impact catastrophes. Even when updated by Bayesian learning, uncertain structural parameters induce a critical “tail fattening” of posterior-predictive distributions. Such fattened tails have strong implications for situations, like climate change, where a catastrophe is theoretically possible because prior knowledge cannot place sufficiently narrow bounds on overall damages. This paper shows that the economic consequences of fat-tailed structural uncertainty (along with unsureness about high-temperature damages) can readily outweigh the effects of discounting in climate-change policy analysis.