Abstract
Climate change is an externality problem—so the challenges that arise in limiting it and dealing with the effects that remain are largely fiscal. The structure of the problem, however, and the uncertainty which surrounds it, make the design of proper policy responses particularly complex. This paper provides a primer on the fiscal implications of climate change, the aim being to provide a (reasonably) quick and comprehensive overview of the main analytical issues and lessons learned.
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Notes
The appendix provides a refresher.
Auerswald et al. (2011) show further that where a unilateral cut in emissions reduces the uncertainty associated with emission-related damages, the net impact may actually be an increase in global emissions.
The International Energy Agency (IEA 2010) estimated that global emissions fell by around 3 percent in 2009; but increased again in 2010 to slightly surpass the 2008 level.
Jones and Keen (2011).
They also identify weaknesses in traditional assumptions regarding the independence of different weather related risks, significantly amplifying concerns regarding potential losses from extreme weather events.
The basic argument is that damages are always bounded so that the fundamental problem in Weitzman (2009), that expected climate damages can be infinitely large, does not apply. A modified argument appears in Weitzman (2011). See also Strand (2009). Kousky et al. (2009) discuss practical, anticipatory, measures to meet the possibility of “mega-catastrophes”.
See for example Pindyck (2000).
To see this: A firm’s profits under such a scheme are \(\varPi =R(X) -C (e,X)- p(e- \bar{e})X\), where R denotes revenue, output is X, emissions per unit output are e, the emissions standard is \(\bar{e}\) and the permit price is p. Rewriting, Π=Π c +sX where Π c =R(X)−C(e,X)−peX would be profits under a carbon price of p and \(s =p \bar{e}\) acts as an output subsidy.
Similar principles apply to other GHGs, but the discussion here follows much of the debate in focusing on mitigating CO2 emissions—the largest (and most rapidly increasing) share of GHG emissions. Burning fossil fuels also generates other pollutants (such as nitrous oxides and particulates) that can cause significant local and regional harm. While carbon pricing can have significant co-benefits in reducing such emissions, they are best dealt with by differential charges related to each pollutant.
The shape of the marginal damage function is not entirely clear cut: damage is convex in temperature increase, but temperature increase is (somewhat counter-intuitively) concave in (linear in the log of) the concentration level.
The carbon price is effectively a royalty on resource extraction.
The World Coal Organization reports that proven coal reserves are adequate for around 118 years at current usage, while proven oil and gas reserves are enough for around 46 and 59 years (http://www.worldcoal.org/coal/where-is-coal-found/).
Bovenberg and de Mooij (1994).
See, for instance, Carraro et al. (1996).
See Jaffe et al. (2002) for a review of the empirical literature.
See, in particular, Greaker and Pade (2008), who show that when the technology projects are mutually reinforcing, the carbon tax should typically start higher, while when projects have the “crowding out” feature, it should usually start lower, relative to the Pigou level.
Strand (2010a) shows that either the “insecure property rights” effect or the “sunk cost” effect can dominate, depending on parameter values.
Carlin (2006) points out, however, that geoengineering has some advantages over mitigation: it preserves, for instance, the beneficial effects of higher CO2 concentrations on some plant growth.
“Can be” rather than “are” because equivalence also requires, for instance, effective competition in both product and permit markets.
This general point is made by Roberts and Spence (1976).
See Strand (2010b).
A number of administrative issues have also emerged. The EU ETS, for example, created opportunities for “carousel” style VAT fraud. This prompted a variety of unilateral responses, with “reverse charging”—imposing the VAT obligation on the buyer—ultimately adopted.
Since carbon pricing would reduce emissions and hence marginal social damage, estimated damage under BAU overstates the corresponding Pigovian charge. Stern et al. (2007), for example, has strong mitigation reducing marginal damage to US$105/tC.
See www.pointcarbon.com.
IAMs combine a wide range of economic and physical processes characterizing the human influence on, and interactions with, the global climate (including both mitigation and adaptation). Their strength in the present context is a relatively detailed modeling of energy use and mitigation opportunities. They (especially MiniCAM) are less well-suited than G-cubed, which is an intertemporal general equilibrium model, to modeling investment, savings, and balance of payment effects. An appendix to IMF (2008b) provides a detailed comparison of these and other models.
Note that the prices in the tables are given per tonne of carbon (/tC); to convert to prices per tonne of CO2, as discussed in the text, multiply by 3.67.
Schemes of “contraction and convergence” (as analyzed for instance in Böhringer and Welsch 2004) envisage a phased shift from the BAU-based allocation to one based on equal per capita emission rights. Here, for sharpness of comparison, there is no transition.
And across generations, too, as discussed in Sect. 2 above.
Hassett et al. (2007) show, however, that, for familiar reasons, regressivity is much less marked when assessed from a lifecycle perspective; and, perhaps more surprisingly, that there is relatively little regional variation in the impact in the US.
Dresner and Ekins (2006), however, argue that the wide variation in energy efficiency make it hard to protect all the poorest against increased energy prices in the UK.
IEA (2010) estimates global subsidies across all fossil fuels at approximately $550 billion per year: about $300 billion for oil, $200 billion for gas, and $50 billion for coal; about $100 billion is subsidized electricity generation inputs, and the rest direct use subsidies. See also Joint Group Report (2010).
See, for instance, the review of experience in Coady et al. (2006).
This result rests on assumptions regarding the elasticity of substitution between clean capital and different labor types, which may also vary across countries.
And £250 for petrol, though comparison is questionable as the dominant externality is in this case congestion.
Including for electricity used in the production of chemicals and metals (two major polluting sectors). These sectors are, however, today covered by the EU-ETS and thereby already subject to a carbon emissions price.
Available at http://www2.oecd.org/ecoinst/queries/index.htm.
CBO (2009b).
Loosely speaking, the gain will be greater the less concave are permit-exclusive profits in emissions; a low elasticity of demand, for instance, is in this respect conducive to larger private gains.
The lower figure partly reflects that fact that firms may also benefit from induced growth in other sectors: many utilities, for example, have direct commercial interests in renewables.
Bovenberg et al. (2008) show that instrument choice may be affected if political economy dictates that firms be compensated: imposing a carbon tax and compensating by lump sum transfers may be inferior to command-and-control measures, for instance, because of the cost of financing those transfers in part (since they must exceed revenue from the carbon tax itself) from distortionary taxation.
For further references and discussion, see ?WB2010.
Conversely, importers of fossil fuels have a collective incentive to use carbon taxes or tariffs to extract rent from exporters; and exporters have a corresponding incentive to manipulate supply. The net outcome could, in principle, be carbon taxes that, from a global climate perspective, are too high rather than too low (Strand 2008). Of course, given the likely damage projected under BAU, this is not now the dominant effect at work.
This is because the optimal response to defection by one of more parties in the case of a small coalition of large emitters—to substantially reduce their mitigation activity—acts as a stronger deterrent than in the case of a large group (where defection by one country affects the optimal effort of remaining signatories only marginally). See, for example, Bloch (1997), Finus (2001), Finus and Rundshagen (2003), Barrett (2003), Rubio and Ulph (2006, 2008).
The scheme proposed by Altemeyer-Bartscher et al. (2010) permits efficiency by considering two negotiators who offer each other take-it-or-leave-it deals on the tax they are to charge and the side-payment to be received; but, unlike the Cramton–Stoft scheme, it is not in general budget neutral.
Kanbur et al. (1995).
They note too that there is no efficiency case for BTAs when counterpart countries nonparticipating countries use cap-and-trade, since they then have no impact on emissions there.
McLure (2011) provides an extensive analysis of the legal issues. Ultimately, the issue will remain moot until some case is brought to the WTO.
Sometimes called “autonomous adaptation.”
Some regional or global cooperation may of course be required in some areas: to improve management of water systems, for example, or strengthen regional weather forecasting.
See, in particular, Tol (2005). This is, however, not always the case—planting mangrove in coastal areas both protects against storms and sequesters carbon, for instance—but is the general tendency.
To see the point more formally, suppose that private welfare is U(E)+λR−TE−D(E,A), where U, strictly increasing and concave, captures the benefits from emissions E, which are taxed at rate T, while R is some item of nonclimate-related public spending with λ its relative value, and damages D are strictly increasing and convex in emissions, strictly decreasing and convex in public spending on abatement A and (derivatives denoting subscripts) with D EA <0. When the government optimally chooses both T (and hence, from U E (E)=T, emissions) and A, subject to TE=A+R, it is straightforward to show that an increase in λ leads to higher T and lower A.
This is the tendency for under-insurance by those who expect external help in the event of adversity: those supplying the help would wish to limit its extent by committing to relatively low support—but their benevolence makes it hard to do so credibly.
See Syroka and Musifora (2010).
IMF (2008b) provides a more general discussion of the role of financial markets in dealing with climate change.
Figure 1 of Obsterghaus and Reif (2010).
This is somewhat higher than previous estimates. An early study by the World Bank (2006) put the cost of climate-proofing existing investments in developing countries at US$10–US$40 billion per annum. UNDP (2007) estimates an annual cost of climate-proofing development investment, by 2015, of around US$44 billion per annum, with an additional US$2 billion to strengthen disaster response—and a further annual US$40 billion in strengthening social safety nets. UNFCCC (2007) estimates suggest an annual investment cost for agriculture, health, water, and coastal protection, of around US$40 billion per annum by 2030.
The argument is made, for instance, in UNDP (2007).
This compares with current bilateral development assistance for mitigation of around $9.4 billion per year in 2008–2009, and multidonor funds with cumulative pledges of around $10 billion (World Bank et al. 2011). Conditions are that developing countries undertake so-called Nationally Appropriate Mitigation Actions (NAMAs), in addition to the adaptation actions to be supported by the Green Climate Fund.
See also Atkinson (2005).
Note, however, that forest biomass used for building materials does not lead to an immediate release of carbon; this occurs only when buildings decay.
Global warming also leads to an increase in ocean water temperatures (which has a feedback effect on land temperatures), but this occurs only very slowly. This implies long lags from an initial climate forcing to a final equilibrium global temperature level.
Relative to average temperatures between 1980–1999.
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Acknowledgements
We are grateful to Ian Parry and two referees for helpful comments. Views and errors remain ours alone, and should not be attributed to the International Monetary Fund or the World Bank Group.
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This is a considerably revised version of IMF (2008a).
Appendix: The science and impact of climate change
Appendix: The science and impact of climate change
Average global temperature increases with the atmospheric concentration of greenhouse gases (GHGs). There are three main GHGs (other than water vapor, which is little affected by human activity and decays rapidly):
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Carbon dioxide (CO2) currently accounts for about 75% of GHG emissions; burning fossil fuels—petroleum, coal and natural gas—contributes about 60%, and deforestation (which releases carbon stored in soil and forest biomass) 15%.Footnote 77
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Methane, mainly from agricultural activity, contributes 15%.
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Nitrous oxides, generated by industrial and agricultural activities (including nitrogen-based fertilizers) account for most of the remaining 10%.
Some man-made factors reduce global warming, most importantly aerosols (particles resulting from sulphur emissions and reflecting sunlight), though these decay relatively quickly and have more localized effects.
The concentration of GHGs in the atmosphere—conventionally measured in parts per million (ppm) of CO2 equivalent (CO2e)—has risen from about 280 ppm in 1750 to around 430 ppm now. It is currently rising by more than 2 ppm per annum, and under “business as usual” (BAU) could increase to around 750 ppm by 2100.
Temperature increases less than linearly with GHG concentration (though climate damage itself is likely convex in the temperature rise). And emissions take some time to have their full temperature effects due to slow heat diffusion processes with oceans.Footnote 78 GHG emissions also decay very slowly: emitted carbon stays in the atmosphere for, on average, about 100 years.
By the best current estimate (IPCC 2007), the global average temperature has increased by about 0.75 degrees Celsius (°C) since 1906 (with the cooling effect of aerosols roughly offsetting the warming effect of GHGs until about 1980). The Intergovernmental Panel on Climate Change (IPCC 2007) projects that, under BAU, the global mean temperature will increase over the next century by 2.8oC, with a 3% chance of rising 6oC or moreFootnote 79 (the latter being roughly the same as the increase since the last ice age).
The physical consequences include changed precipitation patterns, sea level rise (amplified by storm surges), more intense and perhaps frequent extreme weather events, severe impacts on ecosystems, and increased prevalence of vector-borne diseases. The potential economic consequences include productivity changes in agriculture and other climate-sensitive sectors, damage to coastal areas from sea level rise and more severe flooding events, stresses on health and water systems, changes in trading patterns and international investment flows, financial market disruption (and innovation), increased vulnerability to sudden adverse shocks, and altered migration patterns—all with potential implications for external stability.
The risk of catastrophic events—shifts in some basic features of the planet’s geophysical subsystems—have naturally attracted particular attention, in both public debate and the formal literature. Such possibilities include, for instance, loss of the Greenland ice sheet and a shift of the gulf stream. Little is known about the concentrations thresholds at which these become significant risks; some, even though ‘abrupt’ in geophysical terms, involve transitions of decades or more.
Of course not all of these effects are adverse: benefits can be expected from agricultural productivity increases in some northern regions, for instance, and opening of the Northern passage; and at least one technically ’catastrophic’ event—greening of the Sahara—would convey large benefit. Nonetheless, and while views differ on the likely extent of many of these effects, few doubt that they warrant serious and current attention—especially because the worst-affected countries will be those least equipped to deal with them (and with the least historical responsibility for emissions). Assessments of the macroeconomic impact of climate change are reviewed in Jones et al. (2007), and IMF (2008b). For a 3oC rise, benchmark estimates for the loss of global GDP range from zero to 3% (reflecting differing degrees of coverage of market and nonmarket effects, the presumed ease of adapting to changing climates, and the treatment of catastrophic risk). Behind these aggregate losses, it is generally agreed that hotter and lower-lying countries—often already the most vulnerable—are most at risk, with some more temperate countries even benefiting from moderate temperature rise. Most of the likely aggregate damage is expected in the latter part of the century. But events such as Hurricane Katrina, the 2002 drought in East Africa and severe floods in Europe, Pakistan and elsewhere—though not simply attributable to climate change—illustrate the possible severity of near-term challenges. Moreover, since core actions to deal with climate change must be anticipatory, policy responses need to be considered far in advance of the damage to be averted. The impact of biofuel subsidies is a stark illustration of the potential for strong current impacts from climate policies (Mercer-Blackman 2007).
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Jones, B., Keen, M. & Strand, J. Fiscal implications of climate change. Int Tax Public Finance 20, 29–70 (2013). https://doi.org/10.1007/s10797-012-9214-3
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DOI: https://doi.org/10.1007/s10797-012-9214-3