Elsevier

Ecological Economics

Volume 62, Issue 2, 20 April 2007, Pages 330-340
Ecological Economics

ANALYSIS
Why economic dynamics matter in assessing climate change damages: Illustration on extreme events

https://doi.org/10.1016/j.ecolecon.2006.06.006Get rights and content

Abstract

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.

Introduction

Modelers who assess economic impacts of climate change face a dilemma that has been very frankly presented by William Nordhaus (1997): “After 500 years, [global average temperature] is projected to increase by 6.2 °C over the 1900 global climate. While we have only the foggiest idea of what this would imply in terms of ecological, economic, and social outcomes, it would make most thoughtful people – even economists – nervous to induce such a large environmental change. Given the potential for unintended and potentially disastrous consequences, it would be sensible to consider alternative approaches to global warming policies.” It is thus not only outsiders of mainstream economics (e.g., Azar and Schneider, 2003) who question the legitimacy of the very low percent of GDP losses estimated by the published assessments of climate change damages (e.g., Peck and Teisberg, 1992, Nordhaus, 1998, Mendelsohn et al., 2000, Tol, 2002a, Tol, 2002b), and the consequently unambitious optimal abatement trajectories suggested by these studies.

Part of the problem comes from the fact that the quantification of impacts is still in its infancy. First, many important sectors and types of impact are not treated by published studies (IPCC, 2001a). Second, most studies evaluating optimal abatement trajectories envisage only certainty cases, in which we know exactly the future climate. Hedging strategy approaches show that inserting uncertainty about climate sensitivity and the possibility of singularities in the damage function suffices to justify significant departures from reference emissions trends, even if the most-likely damage level remains moderate (Ambrosi et al., 2003, Yohe et al., 2004).

But another part of the problem may lie in the description of the dynamics of the economic growth. Since resorting to long-term growth model is made necessary by the time horizon of the climate change issue, economists unsurprisingly rely on extensions of the Solow model (e.g., Nordhaus, 1994). These models, however, describe economies moving along balanced pathways and do not examine their readjustment in response to exogenous shocks. They consequently neglect the fact that welfare losses resulting from a given amount of climate change impact may be drastically different, would it fall on prosperous economies or on economies weakened by various disequilibria or experiencing inertia in their readjustment process.

This paper aims at framing the orders of magnitude at stake. It compares economic consequences of a given climate impact falling on economies similar in all respects, except that one follows an equilibrated growth pathway while the other experiences transient disequilibria. We take extreme events in Europe as an example, because they are one of the most documented channels through which climate and economy interact, and because the order of magnitude of this interaction is significant enough to support an aggregate analysis.

In the first section we present a model, NEDyM (Non-Equilibrium Dynamic Model), which reproduces the behavior of the Solow model over the long term, but which allows for disequilibria during transient phases. The second section explains how available information about large-scale extreme weather events can be translated in economic terms. The third section describes the calibration and validation of NEDyM and the three following sections apply NEDyM and present comparative exercises.

Section snippets

A dynamic model to capture unbalanced growth pathways

NEDyM models a closed economy, with one representative consumer, one producer, and one good, used both for consumption and investment3. This aggregate representation presents the drawbacks of the absence of sector-based or geographical differentiation, but has the advantage of being similar to the Solow model. This makes it easy to reproduce the ‘after shock’ behavior of a Solow

Modeling economic impacts of Large-scale Extreme Weather Events (LEWE)

There is no strict scientific definition of Large-scale Extreme Weather Events (LEWE); they are rather characterized by their media impact and their capacity to generate sudden and large social concerns9. We will define them as rare climate events causing important capital destructions over time period ranging from one day (cyclones) to several weeks (floods).

Less media-impressive gradual

Calibration and validation: the economic amplification ratio

To validate these modeling options, a disaster was applied to the economy at steady state in the NEDyM model, with the set of hypotheses summarized in Table 2. This disaster destroys the stock of productive capital by an amount equivalent to 2.5% of GDP. This amount is comparable (in relative terms) with the 1999 Marmara earthquake, the consequences of which have been well documented and estimated between 1.5 and 3.3% of GDP (World Bank, 1999, OECD, 2003).

Fig. 4 shows the economic responses to

The macroeconomic costs of LEWEs

In this section, we conduct numerical experiments to assess how the macroeconomic costs of LEWEs depend on the way they are represented and the way the “growth engine” of the economy is modeled. First, we do so under assumptions of stable LEWE distribution and second, under changing distributions. This requires the use of a 400 years time period, because we need a representative set of very rare LEWEs. Obviously, the aim is not to reproduce a realistic economic trajectory over such a long

Conclusions

The basic message of this paper is that the assessment of climate change damages depends strongly on assumptions about the functioning of the economy on which the impacts will fall. This demonstration is made through a modeling framework capable of representing (i) non-equilibrium dynamics in a way that makes the model equivalent to the neoclassical Solow growth model over the long-term; (ii) realistic short-term constraints on the post-disaster reconstruction process.

This exercise also allowed

Acknowledgments

The authors wish to thank Carlo Carraro, Frédéric Ghersi, Jonathan Koehler, Tom Kram, Mike Mastrandrea and Richard Tol for their helpful comments and remarks. Conversations with Michael Ghil were also very fruitful and enriching. We would like to mention the stimulating role of the Trieste Workshop on Integrated Climate Models organized by Carlo Carraro and funded by the Ecological and Environmental Economics Program. This work was supported by the European Commission's NEST project “Extreme

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    CESP is a laboratory of the Stanford Institute for International Studies.

    2

    CIRED is a EHESS–CNRS–ENPC–ENGREF laboratory.

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