The ten selected key emitters and 16 Member States of the European Union (16 EU MS thereafter) jointly commit to a total of around USD 11.1 trillion in fiscal rescue and recovery spending as of May 2021 (Fig. 3). Of this, we identify around USD 3 trillion as fiscal spending with potential GHG emissions impacts for further analysis on its likely emissions impact. The other USD 8.1 trillion represent ‘neutral’ fiscal spending that no potential GHG emissions impact in line with our framework introduced in the ‘Categorisation of fiscal rescue and recovery measures by their level of greenness and their emission impact type’ section.
Level of greenness across key emitters’ fiscal spending
Most countries dedicate fiscal rescue and recovery spending to measures considered ‘supporting the status quo’ to further accelerate climate action (Fig. 4), representing an average of 35% across all countries and up to 73% of fiscal spending for single countries. This spending includes a wide range of measures such as liquidity support for large corporations or general value added tax (VAT) reductions without any conditions for a net zero transition.
Large shares of fiscal rescue and recovery spending further remain ‘unclear’ given lack of detailed information, totalling to almost USD 1.2 trillion across all countries (40% of all fiscal spending with potential impact). This is especially relevant for large fiscal spenders such as the 16 EU MS, the USA, China, the UK, and India. In the case of China, this is for example driven by lack of granularity in China’s 2021 Government Work Report announced in March 2021 available to the authors (O’Callaghan et al., 2021b).
The share of low- and high-carbon fiscal spending differs among the key emitters analysed (Fig. 4), both in absolute terms and relative to GDP. Low-carbon measures represent around USD 641 billion (22% of all spending with potential GHG emissions impact). This finding is in line with the existing literature; O’Callaghan and Murdock estimated that 18.0% of all recovery spending of the 50 largest economies could be considered low-carbon (O’Callaghan & Murdock, 2021); the Green Recovery Tracker estimated that 30% of spending assessed positive (16%) or very positive (14%) in Green Recovery Tracker’s briefing for 16 EU Member States (Green Recovery Tracker, 2021); only 17% to 19% of a total USD 2.25 trillion in announced COVID-19 ‘recovery’ spending as of May 2021 has gone towards green spending, and only 2.5% to 12.1% of total COVID-19 spending has been green or with green co-benefits (O’Callaghan, 2021; OECD, 2021; Vivid Economics, 2021).
The UK, South Korea, Japan, India, and the 16 EU Member States show higher shares of low-carbon spending (30% or more of all rescue and recovery spending with potential GHG emissions impact). Except for Japan, these countries have also committed the highest total amounts of fiscal rescue and recovery spending. Measures explicitly considered high-carbon amount to USD 105 billion (~ 4% of all spending) across all countries. India (30% of its total spending) together with Saudi Arabia (56%) and Indonesia (27%) also spent the highest shares of their domestic rescue and recovery spending on high carbon measures.
The summary results across key emitters show that around 35% of fiscal spending reinforces a current status quo and have not met the pledges to effectively focus economic rescue and recovery measures on low-carbon activities. South Korea and the UK dedicate large shares of their rescue and recovery spending to measures supporting the status quo in their economies, representing 11% and 8% of their GDP, respectively. Across all countries, these measures comprise corporate liquidity support for large corporates (total of USD 212 billion) and airline companies (USD 138 billion), reduction in interest rates (USD 183 billion), road construction (USD 90 billion), or VAT reductions (USD 53 billion)—all without specific conditions for a low-carbon transition or a specific focus on low-carbon products. This suggests that governments might have pursued other socio-economic considerations, especially during the initial rescue phase, and showed limited capabilities or willingness to align all emission-relevant fiscal spending with the Paris Agreement’s objectives.
On a positive note, explicitly low-carbon spending (22%) outweighs high-carbon spending roughly five to one. High uncertainty and a lack of available information remains on many rescue and recovery measures given that unclear spending represents around 40% of all relevant spending with potential GHG emission impact.
Emissions impact type across key emitters’ low-carbon and high-carbon fiscal spending
The emission impact type categorises fiscal rescue and recovery measures according to their expected likely impact on GHG emissions in the period towards 2030. Table 3 in the Appendix introduces several examples for rescue and recovery measures considered direct, enabling and catalytic in this study based on the harmonised dataset of almost 2500 measures. Our analysis across key emitters suggests that most of the low-carbon fiscal spending identified will likely not lead to direct emissions reductions in the short-term as almost two-thirds of the low-carbon spending of a total USD 641 billion can be considered enabling and catalytic low-carbon measures (Fig. 5). The other one-third of all low-carbon spending goes to direct low-carbon measures. Our findings suggest low-carbon fiscal rescue and recovery spending to date will likely unfold its emission reduction impact only over a longer time horizon towards 2030 and beyond. The detailed assessment of the emission impact type of low-carbon and high-carbon measures reveals heterogeneity in spending patterns among key emitters.
In total, all key emitters have spent or announced around USD 230 billion on direct low-carbon measures, representing 36% of total low-carbon spending (USD 641 billion). Except for China (82%), USA (53%), and South Africa (100%), all countries spend less than 50% of their total low-carbon spending on direct measures.
Across all key emitters analysed, USD 345 billion have been spent or announced on low-carbon enabling measures, representing around 54% of total low-carbon spending. Some countries like the UK, Japan, or Brazil dedicate more than 80% of their low-carbon spending to enabling measures. Other countries such as India, the EU16 and the USA dedicate at least 40% of their low-carbon spending to enabling measures.
Low-carbon catalytic measures represent 10% of all low-carbon spending (USD 64 billion). South Korea (47%) represents the only country spending more than 10% of their total low-carbon spending.
Both enabling and catalytic low-carbon measures will play an important role to support the implementation of direct low-carbon measures on a longer time horizon, for example through catalytic R&D and enabling infrastructure investments but might not immediately lead to the implementation of direct measures itself in the short run. Substantial further action will be required to effectively reduce emissions globally in the short to medium run towards 2030.
As for high-carbon spending of USD 104 billion across key emitters, around 42% of all high-carbon spending can be considered direct in nature, with 58% representing high-carbon enabling spending.
A total of USD 43 billion has so far been spent or announced in all key emitters analysed for high-carbon direct measures, representing 42% of all high-carbon spending. Five countries have dedicated all of their high-carbon spending to direct measures, including the UK, Japan, and Brazil. Other countries such as 16 EUMS (79%) and India (45%) have also partially spent on high-carbon direct measures.
High-carbon enabling measures constitute the remaining 58% (USD 61 billion) of high-carbon spending. The USA (100%), South Korea (100%), China (100%), and Saudi Arabia (96%) have dedicated all or almost all their high-carbon spending to high-carbon enabling measures. India (55%), and 16 EU MS (19%) have also spent partially on high carbon enabling measures, while other countries register no spending on this category.
Policy implications of the findings
Our analysis based on the publicly available data as of May 2021 suggests that key emitters collectively may have missed the opportunity to use their fiscal rescue and recovery spending to build back their economy while fully making good on their responsibility to implement a ‘green’ recovery aligned with the Paris Agreement goals. The share of low-carbon spending across all key emitters assessed accounts for only 22% of all spending with potential GHG emissions impact. Governments might still have some leeway to adjust some parts of the fiscal spending not considered as low-carbon (high-carbon, unclear, supporting the status quo), for example by repurposing committed funding to low-carbon activities. Some countries assessed in this study show that such realigned spending can be done. However, they would need to do so in a timely manner.
Explicitly low-carbon spending outweighs high-carbon spending roughly five to one. This generally supports the need to increase the share of low-carbon spending in direct comparison to high-carbon spending to align investments with the Paris Agreement, for example overtaking high-carbon investments in the energy sector globally by around 2025 or before and growing thereafter (McCollum et al., 2018). This, however, has to put into context of around 75% of all rescue and recovery spending either remains unclear (40%) or substantiates current business-as-usual practice in the respective country context (35%).
Another important implication of this study’s findings is that two-thirds of the total low-carbon spending was identified to be of enabling and catalytic nature. This implies that the emission impact of these expenditures would only unfold over a longer time horizon. While global CO2 emissions already seem to have almost fully rebounded to pre-crisis levels of 2019 after experiencing the largest annual percentage decline since World War II (IEA, 2021a, 2021b), it remains to be seen whether and to what extent these expenditures would have an impact on emissions toward 2030 and beyond. Beyond the scope of this analysis, policy makers and researchers ought to enhance the empirical knowledge base on how the fiscal response to the COVID-19 pandemic can be understood in the context of transformational change imperative towards a low-carbon economy, and how national circumstances and barriers influence the process from implemented measures to actual impact on the ground.
While governments’ spending decisions in the context of the COVID-19 economic recovery consider many important national and socio-economic circumstances facing a global health and economic crisis, their collective actions remain inadequate considering both the scientific evidence on the urgency to fight climate change and governments’ own long-term climate commitments.
Limitations and avenues for further research
The analysis for key emitters faces several methodological limitations. First, the refined framework and its application to a large dataset of fiscal rescue and recovery measures across several emitters neither measures the anticipated impact on emissions nor considers the process and timing of transformation in each country context. It allows to classify fiscal measures in terms of their causal effect on emissions but does not provide an underlying theory of transformational change for different types of fiscal rescue and recovery spending. Country-specific contexts crucially matter in several dimensions to assess the latter, for example, specific measure designs, existing barriers, or enabling factors to determine the likely GHG impact on the ground. Such analysis remains outside the scope of this analysis.
The second relates to the data cut-off date; the analysis considered all fiscal rescue and recovery announcements for the key emitters as of May 2021. For this reason, the present analysis only represents a snapshot in time for all key emitters assessed. Moreover, some of the reported response measures included in our analysis are still pending approval: the tracking of fiscal spending of EU Member States by May 2021 built on draft versions of their Recovery & Resilience Plans pending further adjustments final approval by national governments and the Council of the European Union as of May 2021. At the same time, national governments’ fiscal measures may become less driven by the responses to the pandemic as the world gradually shifts toward a post-COVID ‘new normal’. In this regard, we argue that the findings of this study are representative of countries’ fiscal measures, both implemented and planned or under discussion, primarily driven by the pandemic. Data for the EU Member States comes exclusively from the Green Recovery Tracker (E3G & Wuppertal Institut, 2021). This tracker is limited to recovery measures only and exclusively covers EU member states. This difference in scope limits the comparability of results between the 16 EU Member States and the other key emitters covered in this study. As of May 2021, the Green Recovery Tracker only provided data for 16 EU Member States (out of 27 EU Member States in total), not all 27 EU Member States, which determined the selection of the 16 EU Member States. This selection, however, covers all G20 members within the EU (Germany, France, Italy) and other larger economies (Spain, Poland), representing 85% of the EU’s GHG emissions excluding land use in 2019 (Gütschow et al., 2021). Member States left out and with slightly different spending patterns (for example Denmark, The Netherlands, or Sweden with potentially higher shares of low-carbon spending than the average EU Member State) might bias the results for EU Member States to some degree, but not change the overall findings across all emitters analysed.
Third, there was limited or no information on the timeframe of announced investments and the total committed amount for several rescue and recovery measures. For example, only a unitary subsidy value is provided for some measures providing subsidies for activities such as the purchase of electric vehicles, but no estimate of the programme’s total budgetary scope. Furthermore, many measures were announced as part of larger rescue and recovery packages, where a disaggregation of the announced expenditures committed per individual measure was not available. Following the approach by O’Callaghan (2021), we have assumed an even split between measures in some of these cases. Still, we do not have information on the amount committed for 518 measures (18% of measures collected in the database for key emitters analysed). While this uncertainty would not affect the overall findings of our analysis due to a relatively small share of total fiscal spending, any interpretation of our country-level results should consider this limitation.
Fourth, we experience a lack of granularity in applying measure archetypes to a diverse range of rescue and recovery measures with country-specific contexts. Policy options available to governments across the world are similar enough that the application of standardised policy archetypes to categorise public spending allows for a meaningful comparison across countries. However, using such an archetype to code the level of greenness and the emissions impact type of policies across countries may potentially ignore country-specific contexts. For example, the GHG emission impact of electric vehicle investments can be substantially affected by the electricity mix of the country where these investments are rolled out. In other cases, case-by-case judgements had to be made to assign a level of greenness to a rescue and recovery measure archetype: For example, measures catalogued as “other building upgrade support” included green components such as support for “eco-friendly facilities and schools”, while in other cases measures under the same archetype included traditional building upgrades or maintenance investments. In total, we have manually recoded around 100 measures to account for measure-specific information.
Fifth, we encounter limits to the extent we can harmonise the three different datasets with substantial differences in scopes. The basis for our analysis is the Global Recovery Observatory database (O’Callaghan et al., 2021a), which includes both rescue and recovery measures focusing on fiscal spending. This data is used for every country covered except the 16 EU Member States. For six key emitters analysed, we fill identified data gaps in the Global Recovery Observatory database using data from the Energy Policy Tracker (2021). This database exclusively tracks measures that support the energy sector, both fossil and low-carbon energy, and it covers both rescue and recovery measures. While harmonising data from the Energy Policy Tracker with the Global Recovery Observatory database helps to provide a more complete picture, this process required systematic cross-checking to avoid double-counting.
Considering these limitations, we identify two key avenues for future research. First, further research can conceptually embed the fiscal spending—both for regular fiscal budget cycles and fiscal rescue and recovery spending—into the literature on theories of transformational change. Such research substantiates the conceptual understanding of the process of transformation that fiscal spending can contribute to and identify the relevant conditions and barriers determining impact. Second, in-depth country assessments can complement the present cross-country analysis in several meaningful ways empirically assessing the likely or actual impact on transformation processes and emissions over time. A deeper understanding of the specific country contexts allows to better circumvent challenges in data collection and harmonisation outlined above.