The unclear impacts of climate policies on household incomes and especially the distribution of these impacts are particularly problematic. They depend on a variety of often under-researched factors. However, the elucidation of these factors is important regardless of their existence and implementation problems in international carbon finance projects. For low carbon development strategies, developing countries will likely be dependent upon international assistance to some extent. However, multilateral assistance will not be able to fundamentally change the incentive structure and determine how much renewable energy is used over the next decades. National policies are needed to supplement climate finance in setting the incentives towards low carbon energy sources. However, as a critical review of the catchy green or low carbon growth slogans show, many problems await for those countries, which are planning to go down the road of climate policies. Much of the political discussion on low carbon development focuses on abstract discussions with limited substantial analytical value and policy guidance. This is surprising, considering that the economic literature can deliver analytical tools to access complicated topics, such as the incidence of market-based
8 Introduction environmental policies. These instruments, putting a price on GHG emissions either in the form of taxes or emission permits, will have to play a major role in any ambitious decarbonization process. Like any other policy, putting a price on carbon will produce winners and losers. The identification of these groups and quantifying the impacts are a highly needed deliverable by the scientific community that this work tries to contribute to.
Fullerton (2008, 2011) discusses six distributional effects, which are worth looking at in more detail and guide the way for the subsequent chapters in this work. Market based climate mitigation policies try to correct for the environmental externalities created by the polluting fossil fuels. The public economics literature has much to say on the general distributional effects of taxes, but environmental policies are in fact more complicated and interesting as Fullerton (2011) points out. The reasons behind this are that environmental policies are not exclusively taxes but also include quantity regulations, such as emission trading schemes or command and control policies. Specifically, the different effects are (1) higher prices of carbon intensive products, (2) changes in relative returns to factors like labor, capital, and resources, (3) allocation of scarcity rents from a restricted number of permits, (4) distribution of the benefits from improvements in environmental quality, (5) temporary effects during the transition, and (6) capitalization of all those effects into the prices of land, corporate stock, or house values. With the exception of effect (3), which only holds for an emission trading scheme, all of these effects are also present in the cases of carbon or energy taxes.
Under particular circumstances, all these single effects can be regressive (a higher burden as a fraction of income for the poor compared to the rich) or progressive and the overall effect is a priori unknown. A discussion of these effects and the available evidence in detail is helpful in understanding their importance and the current state of research.
First, prices of fossil fuel-intensive products are likely to rise, which will affect the consumption costs of households, the so called “uses” side. In developed countries, the uses side is found to be dominantly regressive since poor households spend relatively more on high carbon intensive goods, such as electricity and fuels (Grainger and Kolstad, 2010; Mathur and Morris, 2014). How regressive the impact is depends on whether welfare effects are calculated relative to household income or expenditures, the latter usually claimed to better represent lifetime income measures. Expenditure based assessments are found to be less regressive than effects relative to income (Bull et al., 1994; Dinan and Rogers, 2002; Metcalf, 1999). Shah and Larsen (1992) have warned early of applying the standard regressivity result unquestioned to developing countries, as direct use of modern energy can be lower for poor households. In urban areas the electricity grid connectivity is higher, which correlates positively with income. Private motorized transport expenditures are closely tied to the ownership of motorized transport vehicles, again positively correlated with income. Also
1.3 Distributional effects: decisive for the feasibility of climate policy 9 modern fuels for cooking, such as gas, are unlikely to be used more by the poor who often depend on traditional biomass fuels such as wood and dung for cooking. The uses side incidence of energy and carbon taxes may therefore be progressive in developing countries.
Finally, the extent to which higher prices are passed through to consumers will depend on the shape of their demand curve. Since energy markets are usually dominated by international market forces and national regulation, it is very likely that energy price increases are entirely passed through to consumers. The substitution between fuels is then ultimately deciding on the monetary burden from taxation.
Second, depending on how factor demand changes through the price increase, the income of workers or capital owners will be affected through the “sources” side. If energy or fossil fuel intensive goods can best be replaced by new capital intensive technologies, relative wages will fall, returns to capital rise and the policy will be regressive. On the other hand, a carbon tax may be more burdensome to capital-intensive industries and disproportionately reduce the return to capital. If so, and if capital provides a higher share of income for richer households, then the sources side incidence may be progressive. In particular, the effect on the sources side depends on the elasticities of substitution in production for polluting industries, elasticities in labor supply and demand, and capital market conditions. There is very little empirical literature on this question, which forces modelers of simulation studies to use “plausible values”. The results in this branch of literature are naturally mixed. Fullerton and Heutel (2007) describe the effects of carbon taxation on the different factor prices and conclude they depend critically on the substitutability of capital, labor, and emissions. In a follow-up paper, Fullerton and Heutel (2011) show that the incidence of a carbon tax on the uses side is regressive, the incidence on the sources side can be progressive, U-shaped, or regressive, depending on the parameters. Rausch et al. (2010) find that under certain circumstances, the progressive impacts of a carbon tax on the sources side exceed the regressive impacts on the uses side, which in sum leads to a mildly progressive effect even without recycling of the revenues. Fullerton and Monti (2013) show that even when accounting for potential progressivity on the uses side, the burden a carbon tax places on the lowest income cohort can never be offset completely. Concluding, results on the sources side are sensitive to parameter values in numerical simulation models and remain an unresolved subject of empirical research. For labor abundant developing countries, the chances of progressive effects through capital intensive renewable energy installments are relatively low as put forward for Africa by Collier and Venables (2012).
If the climate policy is a quantity based instrument, there will be a third effect consisting of scarcity rents following the hand out of pollution permits which will benefit the individuals who own those firms. In the first phase of the European Emission Trading Scheme (EU ETS),
10 Introduction almost all emission permits have been grandfathered to companies. Since emission permits are afterwards traded and therefore worth the resulting market price, consumers face rising energy prices while financing the permits with their taxes (Dinan and Rogers, 2002; Parry, 2003). The only immediate beneficiaries are the stockholders of the polluting companies, which are unlikely to sit at the bottom of the income distribution. Plain and simple, giving permits away for free is a way of combining environmental policy with redistribution from the bottom to the top.
Fourth, climate policies have the ultimate goal to reduce greenhouse gas emissions, and the associated environmental improvements may lead to a heterogeneous effect in the population. Air quality improvements through less fossil fuel intensive electricity generation, road transport, and industry production is likely to affect the urban more than the rural population. In this case, the distributional impact depends on the spatial distribution of income in polluted and less polluted areas. Although this intra-country distribution hasn’t been analyzed in the literature thus far, in a cross country comparison Markandya et al. (2009) report large health benefits of low carbon electricity generation in poor countries like India.
Agricultural productivity, which is already lower in less temperate regions of the world, would further decrease in poor countries with climate change. Developing countries with large agricultural shares in their gross domestic product would benefit more from climate mitigation efforts than developed countries in temperate world regions. Dell et al. (2009) come to the conclusion that higher temperatures reduced income growth in poor but not in developed countries. Beyond an increase in temperatures, the possible increase in extreme events and natural disasters may also hurt the poor more than the rich. In this case, the difference may not be entirely explained by agricultural activities, also non-agricultural growth is affected (Fomby et al., 2013; Raddatz, 2009). The benefits of climate mitigation would therefore likely be progressive, also within these countries.
Fifth, the transition towards a low carbon economy may have very different effects on poor and rich households. With imperfect mobility of production factors, returns to capital or wages are not the only effects on the sources side. Additionally, large disruptive changes in employment and capital degradation might occur. Deschenes (2010) analyzes the effects of electricity prices on labor demand for the US and finds a low, but negative cross-price elasticity. As with other effects, the time horizon used for the analysis is critical. Short-term effects as calculated by Deschenes (2010) ignore a firm’s innovation responses to higher energy prices (Popp, 2002; Popp et al., 2009), which may change the story dynamically over time; but literature for developing countries is neither available for static nor for dynamic effects. The other side of the coin, the creation of “green jobs” is often hailed as the ultimate win-win case of climate policy and green growth. There is little empirical evidence of this