47
1. Owners of carbon-intensive businesses (fossil fuel firms, the steel and cement industries) that have excess or idle production capacity, leading to lower- than-expected returns.
2. Workers in energy-intensive industries who might lose jobs or face lower wages.
3. Owners of fossil resources in situ, who may not be able to extract and sell their products due to lower demand or lower market prices.
4. Households and consumers who spend a relatively high share of their income on energy-intensive goods and services.
The cost for firms often plays a prominent role in public debate about carbon pricing, prompted by their concerns over maintaining global competitiveness, since unilateral policy puts additional costs on domestic business, potentially affecting profits and employment (the impact on relocation of emissions, i.e. leakage, is discussed below). However, the cost to capital owners and workers is only transitory as investment and employment adjust in the long run, without substantial costs resulting from depreciation (capital) and retirement (employment). While costs for firms have been found, on average, to be rather low (Dechezleprêtre and Sato, 2017), they can be high in carbon-intensive firms that would be particularly affected by phasing out fossil fuel subsidies or by higher carbon prices (Jenkins, 2014; Aldy and Pizer, 2015; OECD, 2015, Rentschler et al., 2017). If firms face strong international competition, their ability to pass on higher energy costs to consumers is limited, and this increases their compliance costs.
A common compensation approach is to grant support that is both targeted and time-limited, e.g. exemptions or transfers (Aldy and Pizer, 2015). Allocating permits based on past emissions (known as ‘grandfathering’) in trading systems, as occurs in the European Union ETS, can mitigate economic losses and prevent industry relocation. However, it also undermines policy effectiveness (Flues and Van Dender, 2017a) and can result in substantial overcompensation for a given carbon leakage risk, as Martin et al. (2014) show for the European Union ETS. Reduced corporate income or capital taxes as part of broader fiscal reforms can reduce or even offset the carbon pricing burden on firms (Carbone et al., 2013; Goulder and Hafstead, 2013; Williams III et al., 2014; Rausch and Reilly, 2015). Providing additional training and transitional benefits for workers of affected industries is a more cost-effective way of compensating them than providing direct support to employers, in the longer term (Frondel et al., 2007).
Losses for fossil fuel resource owners due to long- term carbon pricing represent a permanent wealth loss and can be substantial. Ambitious mitigation policies consistent with the 2°C target are estimated to reduce discounted fossil resource rents by roughly 40 percent, compared with a no climate policy scenario (Bauer et al., 2016). However, state revenues from carbon pricing would likely outweigh the losses for fossil resource owners (Kalkuhl and Brecha, 2013; Bauer et al., 2016).
Higher energy prices can affect lower-income or rural households disproportionally (Flues and Thomas, 2015; Levinson and O’Brien, 2018) and may increase energy- poverty risk (Flues and Van Dender, 2017b; Atansah et al., 2017). Carbon pricing tends to be progressive in developing countries, while it is more likely to be regressive in middle- and high-income countries as relatively low-income households have higher expenditure shares on energy-intensive goods and services (Dorband et al., 2018; Ohlendorf et al., 2018). However, middle and high-income countries often have the institutional capacities to overcome these adverse effects by pursuing compensation policies. Transfers on an equal per capita basis are highly beneficial for poor households (Klenert and Mattauch, 2016), but targeted transfers leave more revenue for other purposes. Targeted investment in low-income neighbourhoods (e.g. in public transport, access to clean energy or income tax reductions for poorer households) can mitigate adverse equity effects (Chiroleu-Assouline and Fodha, 2014; Edenhofer et al., 2017; OECD, 2017; Klenert et al., 2018b). Table 6.1 lists examples of measures that have been successfully implemented to protect the poorest households.
6.3.2 Carbon leakage under unilateral policies
A country that unilaterally increases the price of carbon could see emission-intensive production relocate to other countries, which would undermine the effectiveness of carbon pricing (World Bank, 2015). This is known as carbon leakage, which can be fixed by trade and non-trade measures (Jakob et al., 2014). These trade measures include tariffs or charges imposed on countries that do not have comparable carbon prices (‘carbon tariffs’). Trade policies can be used strategically to incentivize trade partners to adopt domestic climate policy measures or to increase or maintain a coalition of countries with ambitious climate policies (Barrett, 1997; Lessmann et al., 2009; Nordhaus, 2015). Non-trade policies to reduce the risk of carbon leakage include the grandfathering of emission permits and output-based rebates to energy-intensive and trade-exposed firms.
Border carbon adjustments are a specific form of carbon tariff that involve levying taxes on imported goods according to their carbon footprint and removing the carbon price component of exported goods. Border carbon adjustments aim to level the playing field between domestic and foreign firms by imposing the same economic burden on emissions (Mehling et al., 2018). Introducing border carbon adjustments to carbon prices on domestic emissions is a consumption-based method for pricing emissions. However, implementing border carbon adjustments requires substantial (and accurate) information on production-side emissions and on the direct or implicit carbon prices in exporting countries. Improved monitoring, reporting and verification systems can therefore help make border carbon adjustments more accurate. Moreover, the impact of border carbon adjustments on reducing leakage can be weakened through induced changes in trade and production patterns (Jakob and Marschinski, 2013).
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112
