Why Worry About Climate Change? A Research Agenda

econstor A Service of zbw Make Your Publications Visible. Leibniz-Informationszentrum Wirtschaft Leibniz Information Centre for Economics Tol, Richard S.J. Working Paper Why Worry About Climate Change? A Research Agenda Nota di Lavoro, No. 136.2006 Provided in Cooperation with: Fondazione Eni Enrico Mattei (FEEM) Suggested Citation: Tol, Richard S.J. (2006) : Why Worry About Climate Change? A Research Agenda, Nota di Lavoro, No. 136.2006, Fondazione Eni Enrico Mattei (FEEM), Milano This Version is available at: http://hdl.handle.net/10419/73981 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Documents in EconStor may be saved and copied for your personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Tol, Economic and Social Research Institute Research unit Sustainability and Global Change, Hamburg University and Centre for Marine and Atmospheric Science, Institute for Environmental Studies, Vrije Universiteit Engineering and Public Policy, Carnegie Mellon University This paper can be downloaded without charge at: The Fondazione Eni Enrico Mattei Note di Lavoro Series Index: http://www.feem.it/Feem/Pub/Publications/WPapers/default.htm Social Science Research Network Electronic Paper Collection: http://ssrn.com/abstract=945044 The opinions expressed in this paper do not necessarily reflect the position of Fondazione Eni Enrico Mattei Corso Magenta, 63, 20123 Milano (I), web site: www.feem.it, e-mail: [email protected] Why Worry About Climate Change? A Research Agenda Summary Estimates of the marginal damage costs of carbon dioxide emissions suggest that, although climate change is a problem and some emission reduction is justified, very stringent abatement does not pass the cost-benefit test. However, current estimates of the economic impact of climate change are incomplete. Some of the missing impacts are likely to be positive and others negative, but overall the uncertainty seems to concentrate on the downside risks and current estimates of the damage costs may have a negative bias. The research effort on the economic impacts of climate change is minute, and should be strengthened, with a particular focus on the quantification of uncertainties; estimating missing impacts, interactions between impacts and higherorder effects; the valuation of biodiversity loss; the implications of extreme climate scenarios and violent conflict; and climate change in the very long term. Keywords: Climate Change, Impacts, Valuation, Cost-benefit Analysis JEL Classification: Q54 Address for correspondence: Richard S.J. Tol Economic and Social Research Institute 4 Burlington Road Dublin 4 Ireland E-mail: [email protected] 1. Introduction Tol (2005a) reviews the literature on estimates of the marginal damage costs of carbon dioxide emissions, the main cause of climate change. He finds that the estimated Pigou tax is relatively small: For a 3% utility discount rate, the median estimate in the literature is $7/tC. This estimate is higher than the actual price of carbon in most countries. However, only the most optimistic studies of the costs of emission reduction suggest that $7/tC would buy substantial abatement (Weyant, 1993, 2004). I am not aware of any serious study that suggests that this carbon tax would buy atmospheric stabilisation. Indeed, cost-benefit analyses of climate change show only modest emission reduction (Nordhaus, 1991; Nordhaus and Yang, 1996; Tol, 1999). Do economists such as Tol (2005a) therefore conclude that we should not worry about climate change? This paper argues not. Tol (2005a) is a literature review and meta-analysis. The quantified part of the climate change impacts literature suggests that we should not worry too much (see Pearce et al., 1996 and Smith et al., 2001, for a survey). However, before reaching a conclusion from an estimate, one needs to consider the completeness of that estimate. Damage cost estimates are incomplete. There are reasons to assume that some of the omitted impacts are substantial and negative, but other omitted impacts may be positive. This paper does not argue “we don’t know and therefore …”. Rather, it surveys the missing climate change impact estimates, speculates why we should worry about them, and sketches what research will need to be done to quantify these impacts. I do not adopt a more risk averse, or prudent, or precautionary standpoint because there is a long history of worrying about the unquantified impacts of climate change. Initially, people were worried about widespread starvation (Hohmeyer and Gaertner, 1992), about extreme sea level rise (Schneider and Chen, 1980), or about infectious diseases killing millions (Haines and Fuchs, 1991). Later studies showed the initial worries to be exceedingly pessimistic (Darwin et al., 1995; Nicholls and Tol, 2006; McMichael et al., 2003). At the moment, there is concern about water resources (Arnell, 2004) and the thermohaline circulation (Rahmstorff, 1994), but here as well the concern may be overstated (Mendelsohn and Bennett, 1997; Link and Tol, 2004). Another argument against a precautionary approach is that climate change is a two-sided risk, not a one-sided one. Gradual emission reduction is probably cheap, but stringent, rapid emission reduction may well be expensive, even if implemented in a cost-effective manner (Weyant, 2004). Governments may not adopt cost-effective abatement policies, which would increase costs substantially. Currently, the price of carbon permits in Europe is higher than economic models suggest it should be (e.g. Viguier et al., 2003), another reason for caution on the abatement side. Nonetheless, the policy suggested by cost-benefit analysis – emission reduction, but not enough to stabilise emissions let alone concentrations – is intuitively wrong. It cannot be the case that the best policy is to let the world get warmer and warmer and warmer still. An obvious reason is that the human body fails if it gets too hot (Parker, 2000, suggests a limit of 43ºC), and if the ambient concentration of carbon dioxide is too high (the US Occupational Safety and Health Administration has a provisional exposure limit of 10,000 ppm; see NIOSH, 2001). But common sense suggests that climate change should be stopped at a lower level. Our best estimates challenge the common sense, but it is as yet unclear whether our research findings are superior to our gut feelings. Having worked in this field for 15 years, I do not know. There are two other reasons to challenge the recommendations of cost-benefit analyses of climate change. The first is uncertainty. Uncertainties are vast, and negative surprises are more likely than positive surprises. Qualitatively, such uncertainty almost always calls for more stringent action. However, quantitatively, the uncertainties are unknown (CBO, 2005) but perhaps very large (Tol, 2003). The second reason is equity. The largest (smallest) emitters of greenhouse gases are least (most) vulnerable to climate change. Cost-benefit analysis of climate change with inequity aversion typically recommends higher emission abatement (Tol, 2001, 2002a). However, in other arenas, equity is not an important argument, so why would it be in climate change? This paper is structured as follows. In Section 2, I review estimates of the economic impacts of climate change. I discuss direct costs, both total and marginal, and indirect costs. I particularly emphasize the quality and completeness of the assumptions. In Section 3, I survey four reasons why the economic impact would be higher than currently estimated. These are biodiversity loss, extreme climate scenarios, violent conflict, and the very long term. Section 4 concludes the discussion. 2. A review of the economic impacts of climate change 2.1. Total costs The first studies of the welfare impacts of climate change were done for the USA (Cline, 1992; Nordhaus, 1991; Titus, 1992; Smith, 1996). Although Nordhaus (1991; see also Ayres and Walter, 1991) extrapolated his US estimate to the world, the credit for the first serious study of the global welfare impacts goes to Fankhauser (1994, 1995). 1 Other global estimates include those by Nordhaus (1994a,b), Tol (1995), Nordhaus and Yang (1996), Plambeck and Hope (1996), Nordhaus and Boyer (2000), Mendelsohn et al. (2000a,b), Tol (2002b), Maddison (2003), Hope (2006), Rehdanz and Maddison (2005) and Nordhaus (2006). This is a rather short list of studies, and an even shorter list of authors. 2 Although most fields are dominated by a few people, dominance is here for want of challengers. The effect of this is hard to gauge. The reasons are lack of funding (this work is too applied for academic sources, while applied agencies do not like the typical results), lack of daring (this research requires making many assumptions, and taking on well-entrenched incumbents) and lack of perspective (generalists have a hard time building a career). Table 1 shows some characteristics of these studies. A few insights emerge. First, the welfare impact of a doubling of the atmospheric concentration on the current economy is relatively small. Although the estimates differ, impacts are not more than a few percent of GDP. The estimates of Hope (2006), Mendelsohn et al. (2000a,b) and Tol (2002b) even point to initial benefits of climate change. 3 With such estimates, it is no surprise that cost-benefit analyses of climate change recommend only limited greenhouse gas emission reduction – one of the more contentious findings of the climate economics literature. Second, although the impact is relatively small, is not negligible. A few per cent of GDP in annual damage is a real concern. Third, climate change may initially have positive impacts. This is partly because the higher ambient concentration of carbon dioxide would reduce water stress in plants and may make them grow faster. Another reason is that the global economy is concentrated in the temperate zone, 4 where a bit of warming may well be welcomed because of reductions in heating costs and cold-related health problems. Even though initial impacts are positive, it does not necessarily follow that greenhouse gas emissions should be subsidized (see below). The climate responds rather slowly to changes in emissions, so the initial impacts cannot be avoided. Impacts turn negative roughly at the same time as climate change can be influenced by present and future emission reduction (Hitz and Smith, 2004; Tol, 2002c; Tol et al., 2000). The fourth insight is that relative impacts are higher in poorer countries (see also Yohe and Schlesinger, 2002). This is because poorer countries have a lower adaptive capacity (Adger, 2006; Alberini et al., 2006; Smit and Wandel, 2006; Yohe and Tol, 2002), particularly in health (Tol, 2005b), and have a greater exposure to climate change, particularly in agriculture and water resources. Furthermore, poorer countries tend be hotter and therefore closer to temperature limits and short on spatial analogues should it get warmer still. This has two policy implications. Any justification of stringent emission abatement is an appeal to consider 1 Hohmeyer and Gaertner (1992) earlier published some low quality estimates. This problem is worse if one considers that Nordhaus and Mendelsohn are colleagues; that Fankhauser, Maddison and Tol all worked with David Pearce; and that Rehdanz works with Maddison and Tol. Hope’s estimates are averages of Fankhauser’s and Tol’s. 3 Studies published after 1995 all have regions with net gains and net losses due to global warming, whereas earlier studies only find net losses. 4 At the same, the world population is concentrated in tropics. 2 the plight of the poor and the impacts imposed on them by the rich (Schelling, 1992, 1995). While this makes for wonderful rhetoric and fascinating research (e.g., Tol, 2001), reality shows little compassion for the poor by the rich. Furthermore, if poverty is the root cause for vulnerability to climate change, one may wonder whether stimulating economic growth or emission abatement is the better way to reduce impacts. Indeed, Tol and Dowlatabadi (2001) and Tol and Yohe (2006) argue that the economic growth foregone by stringent abatement more than offsets the avoided impacts of climate change, at least for malaria, while Tol (2005b) shows that development is a cheaper way of reducing climate-change-induced malaria than is emission reduction. The agreement between the studies is remarkable if one considers the diversity in methods. The studies of Fankhauser, Hope, Nordhaus, and Tol all use the enumerative method: ‘physical’ impact estimates are obtained one by one, multiplied with its price, and added up. Mendelsohn’s work is based on direct, empirical estimates of the welfare impacts; this is still done per sector, but physical modelling and benefit transfer are avoided. Nordhaus (2006) uses empirical estimates of the aggregate economic impact, while Maddison (2003) looks at patterns of consumption. Rehdanz and Maddison (2005) also empirically estimate the aggregate impact, but use self-reported happiness as an indicator. The variety of methods enhances confidence, not in the individual estimates, but in the range. The shortcomings of the estimates are at least as interesting. Welfare losses are approximated with direct costs (see below). In the enumerative studies, impacts are assessed independently of one another, even if there is an obvious overlap as between water resources and agriculture. Estimates are often based on extrapolation from a few detailed case studies. Valuation is based on benefit transfer. Realistic modelling of adaptation is problematic. Many impacts are unquantified (see below). The uncertainties are unknown – only 4 of the 14 estimates in Table 1 have some estimate of uncertainty. These problems are gradually solved, but progress is slow. Indeed, the above list of caveats is similar to those in Fankhauser and Tol (1996, 1997). 2.2. Marginal costs Although the number of studies of the total costs of climate change is small, a larger number of studies estimate the marginal costs. The marginal damage cost of carbon dioxide is defined as the net present value of the incremental damage due to an infinitesimally small increase in carbon dioxide emissions. If this is computed along the optimal trajectory of emissions, the marginal damage cost equals the Pigou tax. Marginal damage cost estimates derive from total cost estimates – the fact that there are more estimates available, does not imply that we know more about the marginal costs than we do about the total costs. In fact, some of the total cost estimates (Maddison, 2003; Mendelsohn et al., 2000a,b; Nordhaus, 2006; Rehdanz and Maddison, 2005) have yet to be used for marginal cost estimation, so that the empirical basis is actually smaller. Tol (2005a) reviews 103 estimates from 28 studies. A number of new studies have appeared since (Ceronsky et al., 2005; Downing et al., 2005; Guo et al., 2006; Hope, 2006; Wahba and Hope, 2006) – all in response to the faux pas of HM Treasury (Clarkson and Deyes, 2002; cf. Pearce, 2003). Tol (2005a) also overlooked the older studies of Nordhaus (1982) and Haradan (1992, 1993), and the papers of Cline (2004), Hohmeyer (2004), Hope (2003, 2005), Link and Tol (2004), Manne (2004), Uzawa (2003) appeared or came to my attention. There are now 210 estimates from 49 studies. Tol (2005a) combines the estimates to a joint probability density function (PDF), assuming that all estimates that do not report some measure of uncertainty have the same coefficient of variation. This assumption emphasizes lower estimates at the expense of higher ones. Therefore, Figure 1 shows the PDF of the best guesses, weighted by the quality of the study and the importance that the authors attach to a particular estimates; cf. Tol (2005a) for details. According to Figure 1, there is a 2% chance that the marginal damage cost is less than $0/tC, a 54% change that it is less than $25/tC, a 68% chance that it is less than $50/tC, an 81% chance that it is less than $100/tC, and a 95% chance that it is less than $250/tC. If only those estimates are included that use a pure rate of time preference of 3%, then the estimate lies below $100/tC with virtual certainty (99.98%), and it lies below $15/tC with a 50% chance. If the pure rate of time preference is 0%, there is a 17% chance that the estimate lies below $50/tC, and a 26% chance that it is greater than $250/tC. There is no chance that the marginal cost is negative with even a 1% pure rate of time preference. Partly, this demonstrates the power of discounting. 5 However, a high discount rate also dampens the uncertainty of future development and climate; and it may be that authors who advocate lower discount rates would also be more alarmed about climate change. Figure 1 also shows the difference between all studies and the studies that do not use equity weighting (cf. Azar and Sterner, 1996; Fankhauser et al., 1997, 1998). Equity weighting tends to increase the marginal damage cost estimate, as the impacts on poorer, more vulnerable regions attain greater weight. The chance that the marginal damage cost is less than $25/tC ($50/tC) rises to 64% (75%) if equity-weighted estimates are excluded. This highlights that climate change is an ethical issue. Emissions of one generation cause problems for the next generations, and richer countries emit more while poorer countries suffer more damage. In an academic study, using lower discount rates or equity weights is straightforward. In reality, decision makers do not necessarily care that much about other generations and faraway lands (cf. Schelling, 1992, 1995). 2.3. Indirect and higher order effects The literature reviewed above is limited to estimates of the direct costs. The direct cost equals price times quantity. This is a reasonable approximation of the welfare impact of small changes. However, if the quantity change were larger, one would need to look at price changes too, as well as at the implications for other markets. Studies about the general equilibrium effects of climate change are now emerging. In addition, climate change may have an effect on development as well. General equilibrium studies of the effect of climate change on agriculture have a long history (Kane et al., 1992; Fischer et al., 1993, 1996; Darwin et al., 1995; Tsigas et al., 1996). Studies show that market adaptation matters, and may even reverse the sign of the initial impact estimate. General equilibrium models have now entered other areas as well. Bosello et al. (2004) and Darwin and Tol (2001) show that sea level rise would change production and consumption in countries that are not directly affected. Ignoring the general equilibrium effects leads to small negative bias in the global welfare loss, but differences in regional welfare losses are much greater and may be negative as well as positive. Similarly, Bosello et al. (2006) show that the direct costs are biased towards zero for health, while Berrittella et al. (2006) emphasize the redistribution of impacts on tourism through markets. Generally, richer countries are less vulnerable to climate change than are poorer countries (see above). A cross-sectional analysis of per capita income and temperature may suggest that 5 Some recent studies (Nordhaus and Boyer, 2000; Newell and Pizer, 2003, 2004; Guo et al., 2006) use declining discount rates, as advocated by Gollier (2002a,b) and Weitzman (2001). Declining discount rates lead to higher (lower) marginal damage costs estimates than if the discount rate is held constant at its initial high (eventual low) level. people are poor because of the climate (Nordhaus, 2006; van Kooten, 2004; see below for further discussion). This would suggest that warming would cause economies to shrink or grow slower. This would increase the damages of climate change. As poverty implies higher impacts, this would drag the economy down further. Tol (2003) finds that the utility equivalent of the impacts of climate change may be infinitely negative (see also Yohe, 2003). The mechanism is that climate change slows economic growth, which increases impacts; this negative feedback eventually reverses economic growth and drives the economy to subsistence level. The welfare loss may be infinite. However, as shown in Fankhauser and Tol (2005) and Tol (forthcoming), only very extreme parameter choices would imply such a scenario. 6 An extreme scenario would dominate other, less extreme scenarios only under particular assumptions about utility and welfare (Tol, 2003) and about international aid (Tol and Yohe, 2005). While these assumptions are defensible from an academic perspective, they do not seem to be applicable in the real world. Furthermore, one should not over-interpret cross-sectional analyses of dynamic processes. The work by Nordhaus (2006) and van Kooten (2004) explicitly relates to climate change, but other papers investigate the relationship between geography and development (Gallup et al., 1999; Masters and McMillan, 2001). Easterly and Levine (2003) shows convincingly that the conclusion of Gallup et al. (1999) are not robust, and that institutions are a better explanation of income difference than is geography and climate. Acemoglu et al. (2002) reach the same conclusion. However, Acemoglu et al. (2001) argue for climate as a root cause of development, via the route of the mortality of European settlers. Future climate change will not affect history, though. The demo-economic models that follow Galor and Weil (1999) also put mortality 7 centre stage. In their models, the difference between Malthusian stagnation and exponential growth is determined by the quality-quantity trade-off for children, which is partly driven by infant mortality. A risk-averse parent would opt for more children, so as to increase the chance of old-age care; a large number of inadvertently surviving children would reduce the money spent on their education. These children would become poor adults, unable to afford health care for their offspring. Should climate change increase the prevalence of malaria and diarrhoea, then the poverty trap would widen. This mechanism has not been studied for climate change. 2.4. Missing impacts The impacts of climate change that have been quantified and monetised include the impacts on agriculture and forestry, water resources, coastal zones, energy consumption, air quality, and human health. Obviously, this list is incomplete. Also within each impact category, the assessment is incomplete. Studies of the impacts of sea level rise on coastal zones, for instance, typically omit saltwater intrusion in groundwater (Nicholls and Tol, 2006). Some of the missing impacts are most likely negative. Diarrhoea impacts have been quantified recently (Link and Tol, 2004). Like malaria, diarrhoea is a disease that is driven by poverty but sensitive to climate. Including diarrhoea tightens the link between development and climate policy. Increasing water temperatures would increase the costs of cooling power plants (Szolnoky et al., 1997). Redesigning urban water management systems, be it for more of less water, would be costly (Ashley et al., 2005), as would implementing the safeguards 6 Kemfert (2002; see also Roson and Tol, 2006, and Kemfert, 2006) finds large dynamic impacts, but she assumes that climate change impacts crowd out investment; this assumption is questionable for market impacts, and indefensible for non-market impacts. 7 albeit of infants, not of grown settlers from distant places against the increased uncertainty about future circumstances. Roads and bridges would suffer from weather conditions for which they were not designed; this would imply either disruption of traffic or expensive retrofits. Extratropical storms may well increase, leading to greater damage and higher building standards (Dorland et al., 1999). Expenditures on these things are relatively small. Even if climate change would double or triple the cost, the impact would be small. Ocean acidification would reduce marine biodiversity, and may well harm fisheries (Kikkawa et al., 2004). Ocean fisheries are only a small, and declining fraction of GDP, while there are ready substitutes for wild fish protein (notably fish farming). The value of biodiversity is unclear (see below). Other missing impacts are probably positive. Higher wind speeds in the mid-latitudes would decrease the costs of wind and wave energy (Breslow and Sailor, 2002; Harrison and Wallace, 2005). Less sea ice would improve the accessibility of arctic harbours, would reduce the costs of exploitation of oil and minerals in the Arctic, and may even open up new transport routes between Europe and East Asia (Wilson et al., 2004). Warmer weather would reduce expenditures on clothing and food, and traffic disruptions due to snow and ice (Carmicheal et al., 2004). Also in these cases, the impact of climate change is likely to be small relative to the economy. Some missing impacts are positive in some places, and negative in others. Tourism is an example. Climate change may well drive summer tourists towards the poles and up the mountains (Hamilton et al., 2005a, b). People, however, are unlikely to change the time and money spent on holiday making. The effect is a redistribution of tourist revenue (Berrittella et al., 2006). The global impact is close to zero, but regional impacts are measured in tens of billions of dollars – positive in temperate, rich countries, and negative in tropical, poor countries. This exacerbates the already skewed distribution of climate impacts. Some ski resorts may go out of business, and others would need expensive snowmaking equipment (Elsasser and Buerki, 2002; Scott et al., 2003). Other ski resorts would profit from the reduced competition. Although regional impacts may be substantial, at the global scale positives and negatives cancel. Other impacts are simply not known. Some rivers may see an increase in flooding, and others a decrease (Kundzewicz et al., 2005). At the moment, only a limited number of rivers have been studied in detail, and it is unclear how to extrapolate to other rivers. It is clear though, that land use and water management may greatly increase or reduce impacts. Although river floods wreak substantial havoc and damages of a single event can reach substantial numbers, average flood damage is in fact small relative to the economy (Tol et al., 2003). Tropical storms do more damage, although a substantial share of the impact is due to bad planning rather than bad weather (Burton et al., 1993). Nonetheless, tropical storms may prevent capital accumulation and the plantation of lucrative tree crops such as banana (Ennos, 1997; Mulcahy, 2004). Unfortunately, it is not known how climate change would alter the frequency, intensity, and spread of tropical storms (McDonald et al., 2005; Pielke et al., 2005). 3. Reasons for concern / Gaps in knowledge 3.1. Biodiversity loss Climate change would have a profound impact on nature. The distribution of plants and animals is partly determined by temperature and precipitation; while organisms that are relatively robust to climate change may be affected through competitors, parasites, pests, preys, and predators that are more sensitive to climate change. Most species would shift their distribution and change their abundance; this implies local extinctions and new introductions. Some species would be unable to adapt fast enough and go extinct, globally (Gitay et al., 2001). From an economic policy perspective, there are three major problems. First, there are few quantitative studies of the impacts of climate change on ecosystems and biodiversity. Large-scale dynamic vegetation models were build to study the carbon cycle, and have a very crude resolution for plant species (20 types at most) while ignoring animals altogether (Sitch et al., 2003). Studies which are rich in species detail are few in number, and confined to small groups of species and at best continental in scale (Burkett et al., 2005; Harrison et al., 2003; Termansen et al., 2006). The reasons are that quantitative ecology is still in its infancy, and that there are very many species to be modelled. Although ecosystem impacts may be important, there is little hard material to go by. Second, climate is not the only thing that is changing. Changes in land use, changes in the nutrient cycles, alien invasions and acidification all have large-scale and profound effects on nature. These effects are synergistic rather than additive. This hampers interpretation of past observations (and hence model building), complicates making projections of the future, and muddles the attribution of impacts to causes (Parmesan and Yohe, 2003; Root et al., 2003). Third, valuation of ecosystem change is difficult. Great strides have been made in the valuation literature, but methods and applications have grown more specific, focussing on a single issue in a particular locality (e.g., Champ et al., 2003). The benefit transfer literature reinforces this, demonstrating that values are heterogeneous and contextual (Ready et al., 2004). Wide-spread change that is hard to detect and to attribute is beyond current valuation methods. Furthermore, climate-change-induced ecosystem change is unlikely to be marginal – a challenge for economic methods in general. 3.2. Extreme climate scenarios Extreme climate scenarios are widely considered to be a main reason for concern about climate change. Examples are a shutdown of the thermohaline circulation (e.g., Marotzke, 2000), a collapse of the West-Antarctic Ice Sheet (Vaughan and Spouge, 2002), and massive releases of methane from the permafrost (e.g., Harvey and Huang, 1995). These scenarios have a number of things in common. First, they would lead to rapid changes in the natural system. Second, impacts have hardly been studied. Third, the mechanism is only partially understood. Fourth, the probability is unknown but probably low. Rapid climate change would be a problem, as there would be little time to adapt. This suggests that impacts would be large, but there has been little research. This is partly because output data is few and not readily available from climate models on extreme climate change. Another reason is that impact models have been designed for more gradual climate change. Nicholls et al. (2005), for instance, had to go back and reformulate their models of erosion and coastal protection and redo the input before considering sea level rise faster than 1 metre per century. That study reports an order of magnitude increase in the impacts of sea level rise should the West-Antarctic Ice Sheet collapse in less than 200 years. If adaptation is more difficult than assumed in the model (as suggested by Olsthoorn et al., 2005), impacts may be even be worse. Link and Tol (2004) estimate the impacts of a shutdown of the thermohaline circulation. In their scenario, a THC shutdown slows global warming, at least over land. Unsurprisingly, they report benefits of a THC shutdown. Working with a finer spatial resolution and a most drastic scenario, Link and Tol (2006) find a small negative effect on the global scale, but much larger negative effects in some countries. Ceronsky et al. (2005) also run more drastic scenarios than do Link and Tol (2004), also finding negative impacts of abrupt climate change. The policy implications are unclear. In a decision analysis, what matters is impact times probability. It is hard to estimate probabilities because the mechanisms are still unclear, and measurements are difficult. The thermohaline circulation, for instance, depends on the vertical transport of water to great depth, which is hard to observe (Baehr et al., forthcoming; Keller et al., forthcoming). The fate of the West-Antarctic Ice is determined at the interface of the ice and the bedrock on which it rests (Vaughan and Spouge, 2002), that is, far below the surface. The uncertainties about the mechanisms also hamper policy analysis in another way: It is not clear whether greenhouse gas emission abatement would reduce the probability of a WAIS collapse or a THC shutdown. It may be that these things would happen anyway, or that the threshold has been crossed already, and even that climate change would reduce the probability of collapse. These questions are firmly in the realm of the natural science, and firm policy conclusions cannot be drawn before these questions are answered. The few available policy analyses (Baranzini et al., 2003; Gjerde et al., 1999; Guillerminet and Tol, 2005; Keller et al., 2004) therefore focus on methodological issues. 3.3. Violent conflict Research into the determinants of violent conflict concludes that resource scarcity is at best a contributing factor to, and never a cause of war (Alesina and Spolaore, 2005; Collier and Hoeffler, 1998, 2005; Homer-Dixon, 1991, 1992; Homer-Dixon et al., 1993; Maxwell and Reuveny, 2000). The corollary is that climate-change-induced resource scarcity would not lead to war either, although it may intensify pre-existing conflicts. It is therefore impossible to estimate the impact of climate change on violent conflict without a scenario with background conflicts. Such scenarios do not exist; all future scenarios for climate change are nice and peaceful (Nakicenovic and Swart, 2001). Constructing scenarios of conflict would be hard, but not impossible; such scenarios would necessarily be stochastic (Geller and Singer, 1998). Clearly, an intensification of conflict would be something to worry about. Despite the conclusions of studies quoted above, it is possible to imagine a scenario in which climate change does cause violent conflict. One example may be prolonged drought, perhaps in the Horn of Africa (Held et al., 2006), followed by mass migration. There are three reasons to assume that this is unlikely. First, migration results from a complex of push and pull factors, not from a single push factor (McGregor, 1994; McLeman and Smit, 2006). Second, drought is only a real problem for the poor; a scenario like this would happen only if warming and drying are faster than development. If not, food imports (Reilly and Schimmelpfennig, 1999) or desalination (Zhou and Tol, 2005) may be the preferred options. Third, drought is a slow-onset disaster. It may exhaust people before they move. Poor and exhausted people are unlikely to take up arms, and if they do, they are probably not very effective. The human suffering would be substantial nonetheless. A potentially more serious example is rapid sea level rise in the major deltas of Asia and Africa. Coastal plains are often fertile and hence densely populated (Nicholls and Small, 2002). Without coastal protection, inundation, erosion and saltwater intrusion would drive many people to higher grounds (Nicholls and Tol, 2006). They may resettle peacefully, or start quarrelling with their new neighbours. One can speculate about the consequences of large-scale migrations today. In West Africa, for instance, the situation is already so tense that additional refugees are unlikely to do any good – but note that the coast of Cameroon, Gabon and Nigeria are most vulnerable to sea level rise. Similarly, forced migration of large numbers of Bengali from the coastal plain to the hills of northern Indian and Bangladesh would not be without problems either, and may even escalate to nuclear war. However, these impacts will not be on today’s world. Sixty-four years ago, Western Europe was at war. In 2070, South Asia and West Africa may be stable and prosperous. Terrorism is another unknown. Sea level rise will lead to the evacuation of a number of islands (Nicholls and Tol, 2006). Forcibly moved populations may harbour resentment. Sometimes, this is very strong, and a small minority may turn violent (e.g., van Amersfoort, 2004). It may well be that a Maldivian terrorist will try and blow up the headquarters of ExxonAramco. As with the other scenarios above, one can think of the plot and make it sound plausible. With the current state of conflict research, however, it is impossible to compute, even bound probabilities and intensities. As a further complication, although climate change may contribute to violent conflict and terrorism, it does not follow that slowing climate change is the best response. Addressing the other roots of violence may be easier or cheaper, and would have substantial co-benefits. 3.4. The very long term During this century, the world will probably run out of conventional oil and gas, the two most important energy sources of today (Moomaw et al., 2001). If conventional oil and gas will be replaced by renewable and nuclear energy sources, there will not be much of a climate problem. If unconventional oil and gas take over, climate change will continue. If coal takes over, climate change will be substantial (Nakicenovic and Swart, 2001). Energy is an essential input to the economy, so the resource problem will have to be solved. This requires a complete overhaul of the energy sector. Solving the climate problem also requires a complete overhaul of the energy sector (Richels and Edmonds, 1995). Given the scale of the energy sector and the longevity of its capital stock, it would make sense to overhaul the energy sector only once, and solve the resource problem and the climate problem in one go. Perhaps, the energy security problem can be solved at the same time. Put differently, the energy system is heading towards to a bifurcation. There are various solutions to the resource problem: coal; unconventional oil and gas; or renewables and nuclear. If climate change is enough of a concern, the future of energy is renewable and nuclear. From this perspective, we do not want to know the marginal costs of carbon dioxide emissions. Instead, we want to know the difference in impacts between three radically different futures, and compare it to the difference in energy costs between the alternative futures. Unfortunately, we do not know the difference in impacts. The first problem is that most of the tools of economics are designed for analysis at the margin, that is, small change. That is adequate for most problems, where policy makers indeed tinker at the margin. It may not be adequate for climate change. The second problem is that most static impact analyses are for 2xCO2 only, while most dynamic impact studies stop at 2100. The choice between a renewable and nuclear future and a coal future is the choice between 2xCO2 on the hand and 4x, 6x, perhaps 8xCO2 on the other. 8 Because of the inertia in the energy and climate systems, these scenarios will be still be relatively close to one another in 2100, but the gap would widen between 2100 and 2500. We have not even begun to study the impacts of climate change in the very long term. 9 If 2xCO2 leads to an equilibrium warming of 2.5°C, then 8xCO2 would imply 7.5°C warming – radiative forcing and warming are logarithmic in CO2 concentrations. Sea level rise would not stop at 2-3 m, but may go up to 10 m or so. Using Nordhaus’ (1994a) quadratic damage 8 Current estimates have that there is not enough fossil fuel to drive the atmospheric concentration of carbon dioxide much above 2200 ppm (Moomaw et al., 2001) 9 Indeed, only a few climate change scenarios have been published (e.g., Lenton et al., 2006). function, 2.5°C warming would lead to a welfare loss equivalent to a 1.3% income loss; 7.5°C warming would lead to a damage of 11.7% of world income – but only in a distant future. Does the difference justify the extra costs of renewables, nuclear, and carbon capture and storage? Answering that question requires redoing this back-of-the-envelope calculation with proper carbon cycle, climate and impact models, based on proper scenarios of development in the long run. 7. Discussion and conclusion This paper reviews what is known and what is not known about the economic impacts of climate change. What is known suggests that climate change is a problem that requires a serious effort to reduce greenhouse gas emissions. However, the impact estimates do not support drastic action. The marginal damage costs of carbon dioxide lies probably below $50/tC – a tax like this would stimulate energy efficiency improvements but only minor fuel switching. Higher estimates require that the discount rate is lowered below what is common, or that an uncharacteristic weight is placed on the plight of developing countries. What is known is only a small part of what matters. Many climate change impacts have been identified but not estimated, and there are undoubtedly yet to be identified impacts too. Some of these impacts are clearly negative, and some clearly positive. It is impossible to say with any kind of certainty whether current impact estimates have a positive or a negative bias. Yet, countries like Canada, Finland, Iceland, Norway and Sweden are cold but prosperous. Warming would reduce costs and lift constraints and thus accelerate economic growth, but it is hard to imagine that warming would unleash very rapid growth. At the same time, tropical countries clearly suffer from violent storms, prolonged droughts, and the presence to tropical diseases. Further warming would not be good, and subjecting more places to such conditions cannot be positive either. Although not quantified, one can more easily imagine a scenario in which warming has dramatic consequences than a scenario is warming has large positive effects. So, at the least, the great many unknowns imply that the uncertainty is skewed to the negative; and that, if anything, current impacts estimates are positively biased. This suggests that greenhouse gas emission reduction should be more stringent than suggested by costbenefit analysis. Policy should not fly blind, however. If the above diagnosis is correct, it would most of all call for a vigorous research programme. Although some countries propose to spend billions of dollars on emission reduction, and other countries pretend that climate change is a problem that can safely be ignored, little effort is spent on supporting these courses of action by research into whether climate change is a serious problem or not. Climate science is wellfunded, but climate impact research much less so. Furthermore, the climate change impact research community is focussed on incremental improvements on what is known, ignoring the big unknowns. The number of senior economists who do serious research on the impacts of climate change can be counted on two hands. This is in no proportion to the alleged seriousness of the climate change problem. Future research should focus on: • the quantification of uncertainties; • the estimation of missing impacts; • the interactions between impacts of climate change; • the higher-order economic effects of the impacts of climate change; • ecosystem change and biodiversity loss and their welfare implications; • the impact of extreme climate scenarios; • violent conflict; and • the impact of climate change in the very long term. This research agenda is not limited to the discipline of economics, but economists can and should contribute to every single point. Only after answering these questions we can with some confidence state that climate change is not a dramatic problem or justify the drastic emission reductions proposed by some policy makers. Acknowledgements Discussions with Steve Pacala, Rob Socolow and Bob Williams helped to shape this particular paper. 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(2005), ‘Evaluating the Costs of Desalination and Water Transport’, Water Resources Research, 41 (3), W03003. 0.9 0.8 0.7 no equity weighting all 3% PRTP 1% PRTP 0% PRTP fraction 0.6 0.5 0.4 0.3 0.2 0.1 0.0 <0 0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 >50 dollar per tonne of carbon 0.9 no equity weighting all 3% PRTP 1% PRTP 0% PRTP 0.8 0.7 fraction 0.6 0.5 0.4 0.3 0.2 0.1 0.0 <0 0-25 25-50 50-75 75-100 100125 125150 150175 175200 200225 225250 >250 dollar per tonne of carbon Figure 1. Histogram of the best estimates of the marginal damage costs of carbon dioxide emissions, in bins of $5/tC (top panel) and $25/tC (bottom panel), for the entire sample and various subsamples. Table 1. Impact estimates of climate change; numbers in brackets are either standard deviations or confidence intervals. Study Nordhaus (1994a) Nordhaus (1994b) Warming 3.0 3.0 Fankhauser (1995) Impact Minimum Maximum 2.5 -1.3 -4.8 (-30.0 to 0.0) -1.4 -4.7 China -0.7 Tol (1995) 2.5 -1.9 -8.7 Africa -0.3 Nordhaus and Yang (1996)a Plambeck and Hope (1996)a Mendelsohn et al. (2000)a,b Nordhaus and Boyer (2000) Tol (2002) 2.5 -1.7 -2.1 2.5 -2.5 (-0.5 to –11.4) 0.0 0.1 -1.5 -8.6 (-0.6 to -39.5) -3.6 -0.5 -3.9 Developing countries Asia (w/o China) 2.3 (1.0) -0.1 -0.4 -4.1 (2.2) -14.6 -23.5 0.9 (-0.2 to 2.7) -0.9 (0.1) -2.6 (-0.4 to 10.0) 2.5 2.5 1.0 Maddison (2003)a,c Rehdanz and Maddison (2005)a,c Hope (2006)a 2.5 1.0 Nordhaus (2006) 2.5 a 2.5 Africa Africa Africa South America Sub-Saharan Africa Asia (w/o China) Note that the global results were aggregated by the current author. The top estimate is for the “experimental” model, the bottom estimate for the “cross-sectional” model. c Note that the national results were aggregated to regions by the current author for reasons of comparability. b 0.9 Eastern Europe and the former Soviet Union Eastern Europe and the former Soviet Union Former Soviet Union 0.0 (-0.2 to 1.5) 4.0 1.7 0.7 Eastern Europe and the former Soviet Union Eastern Europe and the former Soviet Union Russia 3.7 (2.2) 2.5 12.9 0.3 (-2.5 to 0.5) Western Europe Western Europe South Asia Eastern Europe and the former Soviet Union NOTE DI LAVORO DELLA FONDAZIONE ENI ENRICO MATTEI Fondazione Eni Enrico Mattei Working Paper Series Our Note di Lavoro are available on the Internet at the following addresses: http://www.feem.it/Feem/Pub/Publications/WPapers/default.html http://www.ssrn.com/link/feem.html http://www.repec.org http://agecon.lib.umn.edu NOTE DI LAVORO PUBLISHED IN 2006 SIEV 1.2006 CCMP 2.2006 CCMP KTHC 3.2006 4.2006 SIEV 5.2006 CCMP 6.2006 PRCG SIEV CTN CTN NRM 7.2006 8.2006 9.2006 10.2006 11.2006 NRM 12.2006 CCMP KTHC KTHC CSRM 13.2006 14.2006 15.2006 16.2006 CCMP 17.2006 IEM CTN 18.2006 19.2006 CCMP 20.2006 SIEV 21.2006 CCMP 22.2006 NRM 23.2006 NRM 24.2006 SIEV 25.2006 SIEV 26.2006 KTHC 27.2006 CCMP 28.2006 IEM 29.2006 KTHC ETA 30.2006 31.2006 IEM 32.2006 NRM 33.2006 CTN 34.2006 IEM ETA 35.2006 36.2006 Anna ALBERINI: Determinants and Effects on Property Values of Participation in Voluntary Cleanup Programs: The Case of Colorado Valentina BOSETTI, Carlo CARRARO and Marzio GALEOTTI: Stabilisation Targets, Technical Change and the Macroeconomic Costs of Climate Change Control Roberto ROSON: Introducing Imperfect Competition in CGE Models: Technical Aspects and Implications Sergio VERGALLI: The Role of Community in Migration Dynamics Fabio GRAZI, Jeroen C.J.M. van den BERGH and Piet RIETVELD: Modeling Spatial Sustainability: Spatial Welfare Economics versus Ecological Footprint Olivier DESCHENES and Michael GREENSTONE: The Economic Impacts of Climate Change: Evidence from Agricultural Profits and Random Fluctuations in Weather Michele MORETTO and Paola VALBONESE: Firm Regulation and Profit-Sharing: A Real Option Approach Anna ALBERINI and Aline CHIABAI: Discount Rates in Risk v. 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TOL: Klum@Gtap: Introducing Biophysical Aspects of Land-Use Decisions Into a General Equilibrium Model A Coupling Experiment Avner BEN-NER, Brian P. McCALL, Massoud STEPHANE, and Hua WANG: Identity and Self-Other Differentiation in Work and Giving Behaviors: Experimental Evidence Aline CHIABAI and Paulo A.L.D. NUNES: Economic Valuation of Oceanographic Forecasting Services: A CostBenefit Exercise Paola MINOIA and Anna BRUSAROSCO: Water Infrastructures Facing Sustainable Development Challenges: Integrated Evaluation of Impacts of Dams on Regional Development in Morocco Carmine GUERRIERO: Endogenous Price Mechanisms, Capture and Accountability Rules: Theory and Evidence Richard S.J. TOL, Stephen W. PACALA and Robert SOCOLOW: Understanding Long-Term Energy Use and Carbon Dioxide Emissions in the Usa Carles MANERA and Jaume GARAU TABERNER: The Recent Evolution and Impact of Tourism in the Mediterranean: The Case of Island Regions, 1990-2002 Carmine GUERRIERO: Dependent Controllers and Regulation Policies: Theory and Evidence John FOOT (lxxx): Mapping Diversity in Milan. Historical Approaches to Urban Immigration Donatella CALABI: Foreigners and the City: An Historiographical Exploration for the Early Modern Period Andrea BIGANO, Francesco BOSELLO and Giuseppe MARANO: Energy Demand and Temperature: A Dynamic Panel Analysis Anna ALBERINI, Stefania TONIN, Margherita TURVANI and Aline CHIABAI: Paying for Permanence: Public Preferences for Contaminated Site Cleanup Vivekananda MUKHERJEE and Dirk T.G. RÜBBELKE: Global Climate Change, Technology Transfer and Trade with Complete Specialization Clive LIPCHIN: A Future for the Dead Sea Basin: Water Culture among Israelis, Palestinians and Jordanians Barbara BUCHNER, Carlo CARRARO and A. Denny ELLERMAN: The Allocation of European Union Allowances: Lessons, Unifying Themes and General Principles Richard S.J. TOL: Carbon Dioxide Emission Scenarios for the Usa NRM 118.2006 SIEV 119.2006 SIEV 120.2006 CCMP 121.2006 ETA 122.2006 KTHC 123.2006 PRCG 124.2006 SIEV 125.2006 SIEV 126.2006 CTN 127.2006 SIEV 128.2006 CCMP 129.2006 IEM 130.2006 PRCG 131.2006 IEM 132.2006 ETA 133.2006 KTHC 134.2006 CCMP 135.2006 CCMP 136.2006 Isabel CORTÉS-JIMÉNEZ and Manuela PULINA: A further step into the ELGH and TLGH for Spain and Italy Beat HINTERMANN, Anna ALBERINI and Anil MARKANDYA: Estimating the Value of Safety with Labor Market Data: Are the Results Trustworthy? Elena STRUKOVA, Alexander GOLUB and Anil MARKANDYA: Air Pollution Costs in Ukraine Massimiliano MAZZANTI, Antonio MUSOLESI and Roberto ZOBOLI: A Bayesian Approach to the Estimation of Environmental Kuznets Curves for CO2 Emissions Jean-Marie GRETHER, Nicole A. MATHYS, and Jaime DE MELO: Unraveling the World-Wide Pollution Haven Effect Sergio VERGALLI: Entry and Exit Strategies in Migration Dynamics Bernardo BORTOLOTTI and Valentina MILELLA: Privatization in Western Europe Stylized Facts, Outcomes and Open Issues Pietro CARATTI, Ludovico FERRAGUTO and Chiara RIBOLDI: Sustainable Development Data Availability on the Internet S. SILVESTRI, M PELLIZZATO and V. BOATTO: Fishing Across the Centuries: What Prospects for the Venice Lagoon? Alison WATTS: Formation of Segregated and Integrated Groups Danny CAMPBELL, W. George HUTCHINSON and Riccardo SCARPA: Lexicographic Preferences in Discrete Choice Experiments: Consequences on Individual-Specific Willingness to Pay Estimates Giovanni BELLA: Transitional Dynamics Towards Sustainability: Reconsidering the EKC Hypothesis Elisa SCARPA and Matteo MANERA: Pricing and Hedging Illiquid Energy Derivatives: an Application to the JCC Index Andrea BELTRATTI and Bernardo BORTOLOTTI: The Nontradable Share Reform in the Chinese Stock Market Alberto LONGO, Anil MARKANDYA and Marta PETRUCCI: The Internalization of Externalities in The Production of Electricity: Willingness to Pay for the Attributes of a Policy for Renewable Energy Brighita BERCEA and Sonia OREFFICE: Quality of Available Mates, Education and Intra-Household Bargaining Power Antonia R. GURRIERI and Luca PETRUZZELLIS: Local Networks to Compete in the Global Era. The Italian SMEs Experience Andrea BIGANO, Francesco BOSELLO, Roberto ROSON and Richard S.J. TOL: Economy-Wide Estimates of the Implications of Climate Change: A Joint Analysis for Sea Level Rise and Tourism Richard S.J. TOL: Why Worry About Climate Change? A Research Agenda (lxxviii) This paper was presented at the Second International Conference on "Tourism and Sustainable Economic Development - Macro and Micro Economic Issues" jointly organised by CRENoS (Università di Cagliari and Sassari, Italy) and Fondazione Eni Enrico Mattei, Italy, and supported by the World Bank, Chia, Italy, 16-17 September 2005. (lxxix) This paper was presented at the International Workshop on "Economic Theory and Experimental Economics" jointly organised by SET (Center for advanced Studies in Economic Theory, University of Milano-Bicocca) and Fondazione Eni Enrico Mattei, Italy, Milan, 20-23 November 2005. The Workshop was co-sponsored by CISEPS (Center for Interdisciplinary Studies in Economics and Social Sciences, University of Milan-Bicocca). (lxxx) This paper was presented at the First EURODIV Conference “Understanding diversity: Mapping and measuring”, held in Milan on 26-27 January 2006 and supported by the Marie Curie Series of Conferences “Cultural Diversity in Europe: a Series of Conferences. 2006 SERIES CCMP Climate Change Modelling and Policy (Editor: Marzio Galeotti ) SIEV Sustainability Indicators and Environmental Valuation (Editor: Anna Alberini) NRM Natural Resources Management (Editor: Carlo Giupponi) KTHC Knowledge, Technology, Human Capital (Editor: Gianmarco Ottaviano) IEM International Energy Markets (Editor: Matteo Manera) CSRM Corporate Social Responsibility and Sustainable Management (Editor: Giulio Sapelli) PRCG Privatisation Regulation Corporate Governance (Editor: Bernardo Bortolotti) ETA Economic Theory and Applications (Editor: Carlo Carraro) CTN Coalition Theory Network