Editing IPCC:AR6/SR15/Chapter-4 (section)

== Box 4.8: Investment Needs and the Financial Challenge of Limiting Warming to 1.5°C ==

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Peer-reviewed literature that estimates the investment needs over the next two decades to scale up the response to limit warming to 1.5°C is very limited (see Section 4.6). This box attempts to bring together available estimates of the order of magnitude of these investments, after consultation with the makers of those estimates, to provide the context for global and national financial mobilization policy and related institutional arrangements.

Table 1 in this box presents mean annual investments up to 2035, based on three studies (after clarifying their scope and harmonizing their metrics): an ensemble of four integrated assessment models (here denoted IAM, see Chapter 2), an Organization for Economic Co-operation and Development (OECD) scenario for a 2°C limit (OECD, 2017a) <sup>[[#fn:r1316|1316]]</sup> and scenarios from the International Energy Agency (IEA, 2016c) <sup>[[#fn:r1317|1317]]</sup> . All three sources provide estimates for the energy sector for various mitigation scenarios. They give a mean value of 2.38 trillion USD of yearly investments in the energy sector over the period, with minimum and maximum values of 1.38 and 3.25 respectively. We also report the OECD estimate for 2°C because it also covers transportation and other infrastructure (water, sanitation, and telecommunication), which are essential to deliver the Sustainable Development Goals (SDGs), including SDG 7 on clean energy access, and enhance the adaptive capacity to climate change.

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'''Box 4.8, Table 1'''

Estimated annualized world mitigation investment needed to limit global warming to 2°C or 1.5°C (2015–2035 in trillions of USD at market exchange rates) from different sources. The top four lines indicate the results of Integrated Assessment Models (IAMs) as reported in Chapter 2 for their Baseline, Nationally Determined Contributions (NDC), 2°C- and 1.5°C-consistent pathways. These numbers only cover the energy sector and the second row includes energy efficiency in all sectors. The final two rows indicate the mitigation investment needs for the energy, transport and other infrastructure according to the Organization for Economic Co-operation and Development (OECD) for a Baseline pathway and a 2°C-consistent pathway. Sources: IEA, 2016c; OECD, 2017a <sup>[[#fn:r1318|1318]]</sup> .

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{| class="wikitable"
|-
|
| Energy Investments
| Of which Demand Side
| Transport
| Other Infra-structures
| Total
| Ratio to
MER GDP

|-
| IAM Baseline (mean)
| 1.96
| 0.24
|
| 1.96
| 1.8%
|-
| IAM NDC (mean)
| 2.04
| 0.28
|
| 2.04
| 1.9%
|-
| IAM 2°C (mean)
| 2.19
| 0.38
|
| 2.19
| 2.1%
|-
| IAM 1.5°C (mean)
| 2.32
| 0.45
|
| 2.32
| 2.2%
|-
| IEA NDC
| 2.40
| 0.72
|
| 2.40
| 2.3%
|-
| IEA 1.5°C
| 2.76
| 1.13
|
| 2.76
| 2.7%
|-
| Mean IAM-IEA, 1.5°C
| 2.38
| 0.54
|
| 2.38
| 2.53%
|-
| Min IAM-IEA, 1.5°C
| 1.38
| 0.38
|
| 1.38
| 1.6%
|-
| Max IAM-IEA, 1.5°C
| 3.25
| 1.13
|
| 3.25
| 4.0%
|-
| OECD Baseline
|
| 5.74
| 5.4%
|-
| OECD 2°C
| 2.13
| 0.40
| 2.73
| 1.52
| 6.38
| 6.0%
|}
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The mean incremental share of annual energy investments to stay well below 2°C is 0.36% (between 0.2–1%) of global GDP between 2016 and 2035. Since total world investment (also called gross fixed capital formation (GFCF)) is about 24% of global GDP, the estimated incremental energy investments between a baseline and a 1.5°C transition would be approximately 1.5% (between 0.8–4.2%) of projected total world investments. As the higher ends of these ranges reflect pessimistic assumptions in 1.5°C-consistent pathways  on technological change, the implementation of policies to accelerate technical change (see the remainder of Section 4.4.5) could lower the probability of higher incremental investment.

If we assume the amounts of investments given by the OECD for transportation and other infrastructure for warming of 2°C to be a lower limit for an 1.5°C pathway, then total incremental investments for all sectors for a 1.5°C-consistent pathway would be estimated at 2.4% of total world investments. This total incremental investment reaches 2.53% if the investments in transportation are scaled up proportionally with the investments in the energy sector and if all other investments are kept constant. Comparing this 2.4% or 2.53% number for all sectors to the 1.5% number for energy only (see previous paragraph) suggests that the investments in sectors other than energy contribute significantly to incremental world investments, even though a comprehensive study or estimate of these investments for a 1.5°C limit is not available.

The issue, from a macroeconomic perspective, is whether these investments would be funded by higher savings at the costs of lower consumption. This would mean a 0.5% reduction in consumption for the energy sector for 1.5°C. Note that for a 2°C scenario, this reduction would be 0.8% if we account for the investment needs of all infrastructure sectors. Assuming conversely a constant savings ratio, this would necessitate reallocating existing capital flows towards infrastructure. In addition to these incremental investments, the amount of redirected investments is relevant from a financial perspective. In the reported IAM energy sector scenarios, about three times the incremental investments is redirected. There is no such assessment for the other sectors. The OECD report suggests that these ratios might be higher.

These orders of magnitude of investment can be compared to the available statistics of the global stock of 386 trillion USD of financial capital, which consists of 100 trillion USD in bonds (SIFMA, 2017) <sup>[[#fn:r1319|1319]]</sup> , around 60 trillion USD in equity (World Bank, 2018b) <sup>[[#fn:r1320|1320]]</sup> , and 226 trillion USD of loans managed by the banking system (IIF, 2017; World Bank, 2018a) <sup>[[#fn:r1321|1321]]</sup> . The long-term rate of return (interest plus increase of shareholder value) is about 3% on bonds, 5% on bank lending and 7% on equity, leading to a weighted mean return on capital of 3.4% in real terms (5.4% in nominal terms). Using 3.4% as a lower bound and 5% as a higher bound (following Piketty, 2014) <sup>[[#fn:r1322|1322]]</sup> and taking a conservative assumption that global financial capital grows at the same rate as global GDP, the estimated yearly financial capital revenues would be between 16.8 and 25.4 trillion USD.

Assuming that a quarter of these investments comes from public funds (as estimated by the World Bank; World Bank, 2018a) <sup>[[#fn:r1323|1323]]</sup> , the amount of private resources needed to enable an energy sector transition is between 3.3% and 5.3% of annual capital income and between 5.6% and 8.3% of these revenues for all infrastructure to meet the 2°C limit and the SDGs.

Since the financial system has limited fungibility across budget lines, changing the partitioning of investments is not a zero-sum game. An effective policy regime could encourage investment managers to change their asset allocation. Part of the challenge may lie in increasing the pace of financing of low-emission assets to compensate for a possible 38% decrease, by 2035, in the value of fossil fuel assets (energy sector and indirect holdings in downstream uses like automobiles) (Mercure et al., 2018) <sup>[[#fn:r1324|1324]]</sup> .

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The average increase of investment in the energy sector resulting from Box 4.8 represents a mean value of 1.5% of the total world investment compared with the baselines scenario in MER and a little over 1% in PPP. Including infrastructure investments would raise this to 2.5% and 1.7% respectively. <sup>[[#fn:9|9]]</sup>

These incremental investments could be funded through a drain on consumption (Bowen et al., 2017) <sup>[[#fn:r1325|1325]]</sup> , which would necessitate between 0.68% and 0.45% lower global consumption than in the baseline. But, consumption at a constant savings/consumption ratio can alternatively be funded by shifting savings towards productive adaptation and mitigation investments, instead of real-estate sector and liquid financial products. This response depends upon whether it is possible to close the global investment funding gap for infrastructure that potentially inhibits growth, through structural changes in the global economy. In this case, investing more in infrastructure would not be an incremental cost in terms of development and welfare (IMF, 2014; Gurara et al., 2017) <sup>[[#fn:r1326|1326]]</sup>

Investments in other (non-energy system) infrastructure to meet development and poverty-reduction goals can strengthen the adaptive capacity to address climate change, and are difficult to separate from overall sustainable development and poverty-alleviation investments (Hallegatte and Rozenberg, 2017) <sup>[[#fn:r1327|1327]]</sup> . The magnitude of potential climate change damages is related to pre-existing fragility of impacted societies (Hallegatte et al., 2007) <sup>[[#fn:r1328|1328]]</sup> . Enhancing infrastructure and service provision would lower this fragility, for example, through the provision of universal (water, sanitation, telecommunication) service access (Arezki et al., 2016) <sup>[[#fn:r1329|1329]]</sup> .

The main challenge is thus not just a lack of mobilization of aggregate resources but of redirection of savings towards infrastructure, and the further redirection of these infrastructure investments towards low-emission options. If emission-free assets emerge fast enough to compensate for the devaluation of high-emission assets, the sum of the required incremental and redirected investments in the energy sector would (up to 2035) be equivalent to between 3.3% and 5.3% of the average annual revenues of the private capital stock (see Box 4.8) and to between 5.6% and 8.3%, including all infrastructure investments.

The interplay between mechanisms of financial intermediation and the private risk-return calculus is a major barrier to realizing these investments (Sirkis et al., 2015) <sup>[[#fn:r1330|1330]]</sup> . This obstacle is not specific to climate mitigation investments but also affects infrastructure and has been characterised as the gap between the ‘propensity to save’ and the ‘propensity to invest’ (Summers, 2016) <sup>[[#fn:r1331|1331]]</sup> . The issue is whether new financial instruments could close this gap and inject liquidity into the low-emission transition, thereby unlocking new economic opportunities (GCEC, 2014; NCE, 2016) <sup>[[#fn:r1332|1332]]</sup> . By offsetting the crowding-out of other private and public investments (Pollitt and Mercure, 2017) <sup>[[#fn:r1333|1333]]</sup> , the ensuing  ripple effect could reinforce growth and the sustainability of development (King, 2011; Teulings and Baldwin, 2014) <sup>[[#fn:r1334|1334]]</sup> and potentially trigger a new growth cycle (Stern, 2013, 2015) <sup>[[#fn:r1335|1335]]</sup> . In this case, a massive mobilization of low-emission investments would require a significant effort but may be complementary to sustainable development investments.

This uncertain but potentially positive outcome might be constrained by the higher energy costs of low-emission options in the energy and transportation sectors. The envelope of worldwide marginal abatement costs for 1.5°C-consistent pathways reported in Chapter 2 is 135–5500 USD2010 tCO <sub>2</sub> <sup>−</sup> <sup>1</sup> in 2030 and 245–13000 USD2010 tCO <sub>2</sub> <sup>−</sup> <sup>1</sup> in 2050, which is between three to four times higher than for a 2°C limit.

These figures are consistent with the dramatic reduction in the unit costs of some low-emission technical options (for example solar PV, LED lighting) over the past decade (see Section 4.3.1) (OECD, 2017c) <sup>[[#fn:r1336|1336]]</sup> . Yet there are multiple constraints to a system-wide energy transition. Lower costs of some supply- and demand-side options do not always result in a proportional decrease in energy system costs. The adoption of alternative options can be slowed down by increasing costs of decommissioning existing infrastructure, the inertia of market structures, cultural habits and risk-adverse user behaviour (see Sections 4.4.1 to 4.4.3). Learning-by-doing processes and R&amp;D can accelerate the cost-efficiency of low-emission technology but often imply higher early-phase costs. The German energy transition resulted in high consumer prices for electricity in Germany (Kreuz and Müsgens, 2017) <sup>[[#fn:r1337|1337]]</sup> and needed strong accompanying measures to succeed.

One key issue is that energy costs can propagate across sectors and amplify overall production costs. During the early stage of a low-emission transition, an increase in the prices of non-energy goods could reduce consumer purchasing power and final demand. A rise in energy prices has a proportionally greater impact in developing countries that are in a catch-up phase, as they have a stronger dependence on energy-intensive sectors (Crassous et al., 2006; Luderer et al., 2012) <sup>[[#fn:r1338|1338]]</sup> and a higher ratio of energy to labour cost (Waisman et al., 2012) <sup>[[#fn:r1339|1339]]</sup> . This explains why with lower carbon prices, similar emission reductions are reached in South Africa (Altieri et al., 2016) <sup>[[#fn:r1340|1340]]</sup> and Brazil (La Rovere et al., 2017a) <sup>[[#fn:r1341|1341]]</sup> compared to developed countries. However, three distributional issues emerge.

First, in the absence of countervailing policies, higher energy costs have an adverse effect on the distribution of welfare (see also Chapter 5). The negative impact is inversely correlated with the level of income (Harberger, 1984; Fleurbaey and Hammond, 2004) <sup>[[#fn:r1342|1342]]</sup> and positively correlated with the share of energy in the households budget, which is high for low- and middle-income households (Proost and Van Regemorter, 1995; Barker and Kohler, 1998; West and Williams, 2004; Chiroleu-Assouline and Fodha, 2011) <sup>[[#fn:r1343|1343]]</sup> . Moreover, climatic conditions and the geographical conditions of human settlements matter for heating and mobility needs (see Chapter 5). Medium-income populations in the suburbs, in remote areas, and in low-density regions can be as vulnerable as residents of low-income urban areas. Poor households with low levels of energy consumption are also impacted by price increases of non-energy goods caused by the propagation of energy costs (Combet et al., 2010; Dubois, 2012) <sup>[[#fn:r1344|1344]]</sup> . These impacts are generally not offset by non-market co-benefits of climate policies for the poor (Baumgärtner et al., 2017) <sup>[[#fn:r1345|1345]]</sup> .

A second matter of concern is the distortion of international competition and employment implications in the case of uneven carbon constraints, especially for energy-intensive industries (Demailly and Quirion, 2008) <sup>[[#fn:r1346|1346]]</sup> . Some of these industries are not highly exposed to international competition because of their very high transportation costs per unit value added (Sartor, 2013; Branger et al., 2016) <sup>[[#fn:r1347|1347]]</sup> , but other industries could suffer severe shocks, generate ‘carbon leakage’ through cheaper imports from countries with lower carbon constraints (Branger and Quirion, 2014) <sup>[[#fn:r1348|1348]]</sup> , and weaken the surrounding regional industrial fabric with economy-wide and employment implications.

A third challenge is the depreciation of assets whose value is based on the valuation of fossil energy resources, of which future revenues may decline precipitously with higher carbon prices (Waisman et al., 2013; Jakob and Hilaire, 2015; McGlade and Ekins, 2015) <sup>[[#fn:r1349|1349]]</sup> , and on emission-intensive capital stocks (Guivarch and Hallegatte, 2011; OECD, 2015a; Pfeiffer et al., 2016) <sup>[[#fn:r1350|1350]]</sup> . This raises issues of changes in industrial structure, adaptation of worker skills, and of stability of financial, insurance and social security systems. These systems are in part based on current holdings of carbon-based assets whose value might decrease by about 38% by the mid-2030s (Mercure et al., 2018) <sup>[[#fn:r1351|1351]]</sup> . This stranded asset challenge may be exacerbated by a decline of export revenues of fossil fuel producing countries and regions (Waisman et al., 2013; Jakob and Hilaire, 2015; McGlade and Ekins, 2015) <sup>[[#fn:r1352|1352]]</sup> .

These distributional issues, if addressed carefully and expeditiously, could affect popular sensitivity towards climate policies. Addressing them could mitigate adverse macroeconomic effects on economic growth and employment that could undermine the potential benefits of a redirection of savings and investments towards 1.5°C-consistent pathways.

Strengthening policy instruments for a low-emission transition would thus need to reconcile three objectives: (i) handling the short-term frictions inherent to this transition in an equitable way, (ii) minimizing these frictions by lowering the cost of avoided GHGs emissions, and (iii) coordinating expectations of multiple stakeholders at various decision-making levels to accelerate the decline in costs of emission reduction, efficiency and decoupling options and maximizing their co-benefits (see the practical example of lowering car use in cities in Box 4.9).

Three categories of policy tools would be available to meet the distributional challenges: carbon pricing, regulatory instruments and information and financial tools. Each of them has its own strengths and weaknesses, from a 1.5°C perspective, policy tools would have to be both scaled up and better coordinated in packages in a synergistic manner.

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