A systematic review of the evidence on decoupling of GDP, resource use and GHG emissions, part II: synthesizing the insights

Although neo-classical economic growth models (see Aghion and Howitt 2009) do not include energy as a production factor, the relationship of energy use and economic growth has gained significant attention in recent research. Recognizing that standard regression methods are insufficient with regard to avoiding spurious correlation,¹⁰ cointegration and Granger causality tests have been the predominant approaches for time-series statistical analysis from the 1970s onwards (Stern 2011). Cointegration testing identifies long-term equilibria between two or more non-stationary variables (Enders 2014). Granger causality tests analyze the direction of causality, i.e. whether one time series is useful in forecasting another (Granger 1969).

Using these well-established methods, this large body of literature finds that long-run primary energy-GDP cointegration exists across a wide range of temporal and geographic scales. However, the direction of the energy-GDP Granger causality is inconclusive, as directionalities differed according to the considered regions, timeframes and methods used (Ozturk 2010, Stern 2011, Kalimeris et al 2014, Omri 2014, Tiba and Omri 2017). Besides the lack of directionality, energy-GDP Granger causality testing itself is somewhat controversial. For example, Bruns et al (2013) suggest there is a prevalence of model misspecification and publication bias.¹¹ Other scholars criticize the 'speculative and exploratory' nature of the Granger causality debate (Beaudreau 2010) and that the same methodological approaches continue to be applied although they have proven to be inadequate for resolving the question of directionality (Karanfil 2009, Ozturk 2010, Kalimeris et al 2014, Tiba and Omri 2017).

Stern (Stern 1997, 2011) argues that regardless of whether econometric approaches find empirical evidence for causality in one or another direction, energy is always an essential factor of production. This viewpoint is corroborated by several studies reviewed in section 3.2 and has long been voiced by 'biophysical economists' (Hall et al 1986, Cleveland 1987, Kümmel 2011). Based on a synthesis of energy-based and mainstream models of economic growth, (Stern 2011) finds that energy scarcity imposes a strong constraint on economic growth. He also identifies factors that could affect the linkages between energy use and economic output, and are therefore key to gauging the extent of a possible decoupling of GDP from energy use: substitution between energy and other inputs such as capital and labor, technological change, and shifts in the composition of energy inputs and in the economic structure.

Around 80% of global GHG emissions originate from combustion of fossil fuels. Given the historical coupling between primary energy and GDP, we might expect a similar coupling relationship between territorial CO₂ emissions and GDP at the global level (Bassetti et al 2013, Stern 2017). The empirical evidence supports that assertion: global GDP (constant $US2010) grew at 3.5%/year from 1960–2014, while CO₂ emissions grew at 2.5%/year on average (World Bank 2019a); i.e. globally there is relative but no absolute decoupling. Between 2000 and 2014, the relationship was even tighter, as both CO₂ emissions and GDP (constant $US2010) grew at 2.8%/year on average.

At the international level, studies examining the relationships between territorial CO₂ emissions and GDP typically also find weak or relative decoupling (Vollebergh et al 2009, Longhofer and Jorgenson 2017, Stern et al 2017, Sarkodie and Strezov 2019). A few studies find absolute decoupling (Azam and Khan 2016, Roinioti and Koroneos 2017, Chen et al 2018, Madaleno and Moutinho 2018), but these are usually relatively small, short-term reductions of CO₂ emissions (Li et al 2007). A few country-level GDP-CO₂ studies find empirical support for an Environmental Kuznets Curve (EKC) type relationship, whereby CO₂/capita rises and then falls with rising GDP/capita, i.e. income (Stern 2017). National-level studies (Peters and Hertwich 2008, Kander et al 2015, Azam and Khan 2016, Hardt et al 2018, Moreau and Vuille 2018, Moreau et al 2019, Wood et al 2019a) emphasize the role of 'offshoring' emissions (e.g. related to imported goods) and changes in economic structure (e.g. shrinking carbon-intensive industry, larger contributions from service sectors) in distorting the GDP-CO₂ relationship in one or the other direction. Variability in primary energy composition and different stages in renewable energy deployment are also seen as key reasons for differing results regarding the existence of an EKC for CO₂ (Chien and Hu 2007, Fang 2011, Menegaki 2011, Tiwari 2011, Salim and Rafiq 2012, Tugcu et al 2012, Yao et al 2019).

Socioeconomic energy flow analyses trace the flow from primary energy extracted from the environment (e.g. crude oil or solar radiation) to final energy put to use in production or consumption (e.g. gasoline or electricity) to useful energy actually performing a specific function (e.g. mechanical work or heat). While data on primary and final energy are readily available from statistical sources in reasonably standardized manner (IFIAS 1974, IPCC 2014), data on useful energy (i.e. the energy actually performing useful work) must be inferred and are only exceptionally reported. Exergy evaluates the thermodynamic quality of these energy flows by quantifying the maximum amount of work (mechanical energy) that a given amount of energy can provide. For example, as electricity can be completely converted into work (i.e. it is equivalent to mechanical work), 1 kWh of electricity has an exergy of 1 kWh. By contrast, the exergy of 1 kWh of heat at 80ºC in an environment at 20ºC is only 0.17 kWh. Data on exergy are not reported by statistical bodies, therefore the community interested in the relation between exergy and economic activity needs to calculate exergy equivalents of primary, final or useful energy flows (Ayres et al 2003).

Research on the relationship between final energy and economic growth is often motivated by questions on energy efficiency. Energy efficiency is usually defined as GDP per unit energy used (see Hu and Kao 2007, Marcotullio and Schultz 2007, Jakob et al 2012, Borozan 2018, Cunha et al 2018, Moreau et al 2019) or its inverse, energy intensity (see Ang and Liu 2006, Duro et al 2010, Liddle 2012, Mulder and de Groot 2012). Some studies find strong linkages between final energy use and GDP (e.g. Kim 1984, Stjepanović 2018), while others find evidence for some degree of decoupling, mostly at the national scale (e.g. Jakob et al 2012, Liddle 2012, Mulder and de Groot 2012, Naqvi and Zwickl 2017). Several studies argue that the observed decoupling can be attributed to structural changes in the economy and outsourcing of energy-intensive activities (e.g. Moreau et al 2019). A recent scenario suggests that low primary energy demand is compatible with staying well below 2 °C and providing services that enable wellbeing for all (Grubler et al 2018) .

Regarding the wealth of studies investigating the energy-GDP relationship applying cointegration and causality tests based on primary energy consumption (see section 3.1), it is somewhat surprising that there are hardly any studies applying such methods to final energy or exergy and GDP. Among the few exceptions are Antonakakis et al (2017) and Belke et al (2011). Both find evidence for bi-directional causality, i.e. for final energy consumption being a driver for GDP as well as vice versa.

The number of studies analyzing exergy flows is comparatively small (see table 1b). Most studies investigating exergy flows find relative decoupling of GDP from primary and final exergy (e.g. Ayres et al 2003, Warr et al 2010, Serrenho et al 2014, Guevara et al 2016, Jadhao et al 2017). In contrast, no significant improvements in intensities or long-term decoupling were found for useful exergy. Some studies even found increasing useful exergy intensities, in particular during periods in which the contribution of industry to GDP respectively industry's share in final energy use rise (e.g. Warr et al 2008, 2010, Guevara et al 2016); others did not detect a clear trend (e.g. Serrenho et al 2014, 2016). Exergy studies found considerable gains in the conversion efficiency from primary to useful exergy (exergy efficiency), but also a slowdown of efficiency gains since the 1970s (Ayres et al 2003, Warr et al 2010).

Several macro-economic models use (useful) exergy in addition to capital and labor as factors of production (Warr et al 2008, Warr and Ayres 2012, Santos et al 2018, Sakai et al 2019); these models can generally explain past GDP growth very well, without resorting to residual factors such as autonomous technological growth (Ayres and Warr 2009, Warr and Ayres 2012). This would explain the strong long-term coupling between useful exergy and GDP. Seen from that perspective, the decoupling of primary or final energy/exergy and GDP can be interpreted as an 'economic growth engine' under conditions of scarce resources (Ayres and Warr 2009, Sakai et al 2019). Raising the conversion efficiency of primary to final exergy or final to useful exergy then results in relative decoupling for the former properties while the ratio of useful exergy to growth does not improve substantially—in other words, increases in conversion efficiency drive GDP growth rather than reducing energy use (Ayres and Warr 2009, Sakai et al 2019).

Studies analysed in this section are based on the social metabolism concept (Fischer-Kowalski 1998); i.e. are studies that comprehensively trace flows of biomass, mineral resources, fossil fuels and many other materials respectively energy sources (Wiedenhofer et al 2020). In addition to fossil fuels used for the supply of technical energy, biomass used as food and feed also constitutes an important part of a society's energy metabolism (Haberl 2001). Material decoupling is also sometimes denoted as dematerialization (Bernardini and Galli 1993, Cleveland and Ruth 1998, Schandl and Turner 2009). We find very few dematerialization studies prior to the 1990 s (table 2). As also discussed in part I, many of these studies are concerned with compiling MEFA data (MEFA is an extension of MFA that consistently accounts for material and energy flows; see part I) rather than with advanced statistical or econometric analyses, and only 11 econometric dematerialization studies are in our sample of 835 articles.

Long time series of harmonized MEFA data now enable researchers to analyse the interplay between political-economic and material development of countries. Especially at the national level, this analysis commonly analyse how trajectories of material use relate to major phases of socioeconomic or political development, including incisive political events such as the dissolution of the Soviet Union (Krausmann et al 2016) or China's admittance to the World Trade Organisation (Velasco-Fernández et al 2015). At the country level, decomposition analyses (Muñoz and Hubacek 2008, Wenzlik et al 2015, Plank et al 2018) have identified economic growth (of absolute or per capita GDP and/or monetary final demand) as the most important driver of consumption-based measures of resource consumption. (Yu et al 2013) identified technological progress as the most important driver for China, while other drivers were found to have no significant impact on resource use (e.g. Rezny et al 2019 for innovation). The links between GDP growth and material use are also the subject of global studies, covering either aggregated world regions (Behrens et al 2007, Schaffartzik et al 2014) or representative large (> 100) samples of countries (e.g. Steinberger and Krausmann 2011, Steinberger et al 2013, Pothen 2017). At the global scale, a period of relative decoupling after the 1970 s was followed by a period starting 2000 in which global material use accelerated at a similar pace as GDP (Krausmann et al 2018). While many of the studies analyzed in this section apply production-based accounting principles, a substantial and rising fraction analyze resource flows from a consumption-based (or 'material footprint'; Wiedmann et al 2015) perspective.

From country case studies based on simple data description to advanced statistical analyses of global samples, relative decoupling has been identified mainly for regions or countries with intermediate economic growth (e.g. USA, European countries) or in countries that experienced socio-economic and political turmoil with corresponding restructuring of their economies (Kovanda and Hak 2007, Raupova et al 2014). Absolute reductions of material flows are generally only found in periods of very low economic growth or even recession (Steinberger and Krausmann 2011, Shao et al 2017, Wu et al 2019). Accelerated industrialization and high rates of economic growth, as observable in China in the last decades, often coincide with a growth of material use matching or even outstripping economic growth (Xu and Zhang 2007). The post-World War II boom in the world's wealthiest economies is not widely analysed, with most studies relying on data that does not reach further back than 1970. Hence there is little opportunity to compare the rapid growth phase in the 1950 s found by long-term studies (e.g. Krausmann et al 2011, Gierlinger and Krausmann 2012, Infante-Amate et al 2015) with the currently similarly high growth rates in some countries. Better understanding the role of such rapid growth phases for the following phase of slowed growth in domestic extraction and production in the 1970s (Schaffartzik et al 2014, Giljum et al 2014b) would be beneficial.

At the same time, it appears that reductions or stagnation in the use of the domestic resource base is often associated with rising importance of trade. In contrast to those measures of decoupling based on territorial indicators, consumption-based perspectives unveil a reversal of trends with efficiencies deteriorating instead of improving and no evidence even for relative decoupling (Giljum et al 2014a, Pothen and Schymura 2015, Wiedmann et al 2015). The integrated, more holistic perspective achieved by considering trade-offs over longer periods as well as across spatial scales is important in assessing the possibilities of and necessary conditions for any future (relative or absolute) decoupling. Currently, decoupling appears to depend on prior use and accumulation of materials and on extractive expansion and rising material flows elsewhere. As long asthis is the case, decoupling cannot be achieved in the long-term or universally.

Reporting of territorial CO₂ emissions from fossil fuel combustion and industrial processes such as cement manufacture is rather straightforward because these emissions can be calculated stoichiometrically from fuel use respectively cement production data. These emissions have been reported for a long time, and are readily available from sources such as CDIAC (Carbon Dioxide Information Analysis Center, https://cdiac.ess-dive.lbl.gov/) for many countries and the global total. Hence, there is a large literature on the decoupling of GDP from territorial CO₂ emissions (section 3.1). By contrast, full GHG accounts also need to quantify emissions from land-use and land-cover changes (LULUCF) as well as highly uncertain and strongly context-dependent emissions such as those of CH₄ and N₂O. The quantification of 'carbon' respectively GHG footprints (i.e. consumption-based accounts of carbon or GHG emissions) started a bit over a decade ago (Peters and Hertwich 2008, Hertwich and Peters 2009, Peters et al 2011, Lenzen et al 2013),¹² and up to now these studies generally include only fossil-fuel and industrial-process related emissions, whereas LULUCF emissions of carbon (i.e. changes of the carbon balance of ecosystems resulting from land use, land-use change or forestry) are not systematically accounted for in these databases.

Five studies (Lozano and Gutiérrez 2008, Valadkhani et al 2016, Bampatsou et al 2017, Beltran-Esteve and Picazo-Tadeo 2017, Wang et al 2019) use Data Envelopment Analysis techniques, a method providing efficiency rankings of countries, which show that most countries could reduce their emissions if catching up with the most efficient ones, but does not directly deliver insights on decoupling. Studies searching for an EKC often find no indication for the existence of a turning point (Li et al 2007, Koirala et al 2011), not even a large-scale study of 129 countries (Sanchez and Stern 2016) as well as a global study (Fernandez-Amador et al 2017). A study of 27 EU countries found differently shaped EKCs, but only four countries with an inverted U shape (Jesus Lopez-Menendez et al 2014). A study on Australia 1970–2007 found some evidence for an EKC related to energy, and a declining trend for GHG per GDP (Sarkodie et al 2019). Another study predicts an EKC for Russia (Yang et al 2017), another an EKC for CH₄ for Sub-Saharan Africa (Zaman et al 2017). Overall, however, there is little support for the inverted U-shape hypothesis.

A considerable number of studies used descriptive trend analyses, generally finding relative decoupling, for example for the OECD 1970–2001 (Guillet 2010), the Czech Republic (Solilová and Nerudová 2015) and China (Cohen et al 2019). A study of OECD countries covering 1999–2012 found that GHG emissions were constant while GDP grew on considerably (Gupta 2015). A study for Greece (Angelis-Dimakis et al 2012) found that GHG emissions were highest around the year 2000 and then declined somewhat. Decomposition analyses generally find GDP to be an upward driver of GHG emissions. For example, Duarte et al (2013) find that GDP-induced demand growth overwhelmed technology-induced GHG emission reductions in 11 industrialized countries 1995–2005; similar results were reported for the Baltics (Streimikiene and Balezentis 2016). Xu et al (2014) show that in China 1996–2011, GDP growth was the most important driver of rising emissions. By contrast, from 1999–2009 the EU-27 overall slightly reduced energy use and CO₂ emissions through structural change and improved energy/CO₂ efficiency; GDP growth counteracted but not annihilated these efficiency improvements (Cruz and Dias 2016). In Australia, total GHG emissions have been slightly reduced, whereas industrial CO₂ emissions continued to increase, which was achieved by reductions in LULUCF/agricultural emissions (Leal et al 2019). Econometric studies are rare, examples include Knight and Schor (2014), Khan et al (2017), Bader and Ganguli (2019).

Footprint studies often find that territory-based emissions grow more slowly or even fall while consumption-based emissions increase (e.g. UK 1992–2004, see Baiocchi and Minx 2010; global: Simas et al 2017). There are, however, necessarily also countries where the situation is reversed, e.g. Norway 1980–2000 (Faehn and Bruvoll 2009). In 29 high-income countries for the period 1991–2008, GDP was found to drive both territorial and consumption-based emissions; relative decoupling existed for territorial but not for consumption-based CO₂ (Knight and Schor 2014).

Decoupling was found to be insufficient for reaching climate targets in a study of 120 countries for 2005–2015 (Fanning and O'Neill 2019). Absolute decoupling is found in a footprint-study of GHGs for Sweden 2008–2014 (Palm et al 2019). Most noteworthy is a study of 18 countries with declining CO₂ emissions (both consumption and production-based) that is discussed in more detail in section 5 (Le Quéré et al 2019). Overall, the studies summarized in table 3 suggest that very recently, absolute decoupling between GDP and CO₂ or GHG emissions can be found in some countries, but even in those cases decoupling is so far insufficient to address stringent climate targets, and it is driven by policies promoting renewable energy and energy efficiency (Le Quéré et al 2019).

The large body of literature focused on the causal interrelations between energy and GDP uses econometric time-series and causality testing methods, for example Granger causality, but often shows little interest in the energy indicators analyzed or in actual thermodynamic basis of their hypotheses (see part I, Wiedenhofer et al 2020). While no robust conclusion can be drawn on the direction of causality, these studies show that energy and GDP are strongly related. Stern (2011) has argued that energy is an important factor of production, hence energy scarcity imposes restrictions on economic growth, which supports results from biophysical economics (Kümmel 2011). We found no evidence in the reviewed literature that would question this assertion.

The second group of articles (section 3.2) pays a lot of attention to the meaning of the energy indicators used. Many of the authors in this community come from energy analysis and regard themselves as analysts of 'biophysical economics' (Cleveland 1987, Hall et al 2001, Kümmel 2011). Their conviction is that energy use is a key factor of production (Ayres 2016), and that the quality of energy is hence crucial for assessing the role of energy in the economy (Hall et al 1986, Giampietro 2006, Haberl 2006). The main conclusions are that useful exergy and GDP are tightly coupled and that at the useful stage of energy use there is no evidence for relative decoupling. However, this does not mean that decoupling is not possible between primary energy and GDP, which is important because GHG emissions and extraction of energy resources are linked to primary energy, not useful exergy (Haberl 2006). The conclusion from this literature is that primary energy use can be decoupled from GDP only to the extent to which conversion efficiency from primary energy to useful exergy can be increased.

The review of social metabolism studies based on MEFA methods (Haberl et al 2004, Fischer-Kowalski et al 2011, Krausmann et al 2017a) exemplifies the richness of measures of resource use and their different specific meanings (section 3.3). This community is well aware of the importance of a rich set of indicators, in particular of the difference between production-based and consumption-based accounts. This literature suggests that production-based relative decoupling is frequent, although countries exist in which use of physical resources grows faster than GDP. This seems to happen especially at early stages of the agrarian-industrial transition when large stocks of infrastructures and buildings are accumulated, as well as in export-oriented countries where production of raw materials and early processing stages are dominant. Absolute decoupling is rare and generally only occurs during periods of low GDP growth (Steinberger et al 2013). At the global level, only relative decoupling can be observed (Krausmann et al 2017b). In recent years several global multi-regional input-output models have been established which allow allocating extracted primary resources to final demand of any economy (Inomata and Owen 2014, Wiedmann and Lenzen 2018). Consumption-based analyses suggest that decoupling of production-based material flows is often contrasted by increases of material footprints that are similar to those of GDP (Giljum et al 2014a, Pothen and Schymura 2015, Wiedmann et al 2015).

Current trajectories of material and energy use, whether suggesting decoupling of resource use from economic growth or not, cannot be correctly interpreted without considering past material and energy flows on which they are also based. Current stagnation in per capita territorial/production-based resource use (Fishman et al 2016, Bleischwitz et al 2018a), for example, depends on past material flows (Mayer et al 2017) and entail a substantial legacy for the future (Krausmann et al 2017c). Since some materials enter the socio-economic system to be consumed for their energy content while others are for building up stock (manufactured capital) (Haas et al 2015), it may well be that different strategies are needed to observe, analyse, and set targets for decoupling material use of these two streams. Therefore, more insights can be expected by moving from studies of the decoupling of GDP from one resource or emission indicator to analysing interdependencies between GDP and multiple resources flows, respectively material stocks and resource or emission flows (Haberl et al 2017, Krausmann et al 2017c).

In recent years, a hypothesized S-shaped curve of material growth suggesting a notion of 'saturation', i.e. a stable level of materials use, has gained prominence. In the MEFA community, the idea of saturation has recently attracted more attention than the EKC. This would imply sustenance of a stable, perhaps high, level of materials use coinciding with a continued growth of GDP and perhaps other socioeconomic indicators, in accordance with the 'steady state economy' discourse (Daly 1973, O'Neill 2015). However, so far, no consensus could be achieved on many important conceptual questions. It remains unclear whether saturation should be defined as country totals or per capita, whether consumption- or production-based flows (or material stocks) should be stabilized, and whether saturation should be achieved at the same level for all countries (Müller et al 2011, Pauliuk et al 2013, Chen and Graedel 2015, Fishman et al 2016, Cao et al 2017, Bleischwitz et al 2018a). Moreover, stabilization at a high level may fall short of achieving many sustainability and climate targets.

The literature on CO₂ and other GHG emissions is large and growing fast (Wiedenhofer et al 2020). Most of the studies on territorial CO₂ use econometric methods, and many are based on the EKC framework (section 3.1). Empirical support for the existence of an EKC-type inverted U-shape of the relation between CO₂ emissions and GDP is seldom found (Sarkodie and Strezov 2019). This also holds for total GHG emissions (section 3.4). Even when the data seem to suggest such a curve, the downward-bent part of the curve is usually too far in the future to be of use in reaching ambitious climate targets such as the Paris accord. The GHG emission literature reviewed in section 3.4 suggests a similar pattern as for material use: relative decoupling is the norm rather the exception, but cases of absolute decoupling are rare. A recent study, however, has identified and analyzed 18 'peak-and-decline' countries in which CO₂ emissions are falling in both territorial and consumption-based system boundaries (Le Quéré et al 2019). The study concludes that emissions in these 18 countries fell by a median −2.4%/year (25–75 percentile: −1.4% to −2.9%/year) over the period 2005–2015. Almost half of that reduction has been due to a decline in the share of fossil fuels in final energy use. A bit over one-third resulted from reductions of energy use. The study provides evidence that these reductions were a result of targeted policies to promote renewables and raise energy efficiency, but also profited from relatively low GDP growth rates between 1%–2%/year, which is similar to decoupling rates observed in MEFA studies (Steinberger et al 2013). It also noted that rates of CO₂ reduction achieved so far fell short from those required to comply with stringent CO₂ reduction targets as those implied by the Paris climate accord.

Because the analysis of the literature has yielded only limited aggregate insight into elasticities between GDP and resource/emission indicators due to the variety of measures used in the literature to describe (de)coupling, we summarize some information on the last decade in figure 2. Elasticities were calculated as OLS log regressions over 10 years using the formula log(resource/emission) = α + β log(GDP) + . A median elasticity of CO₂ of 0.4 in the higher income class (top panels in figure 2) means that for 1% of GDP growth, production-based CO₂ emissions grew by 0.4%. Elasticities below zero indicate absolute decoupling and elasticities >1 that resources/emissions grew faster than GDP. Results should be interpreted with caution in particular for those parts of figure 2 where data were only available for few countries (see sample sizes in blue font color). Median values of elasticities are close to one for most of the indicators in the low-income class, while they are often substantially lower than one for the higher income class. For the higher income class, elasticities of consumption-based (CB) indicators are highest for material use and substantially lower for CO₂ and GHG. For the lower income class, the highest median values are found for production-based emissions. Negative elasticities, indicating absolute decoupling, are most frequent for production-based GHG emission accounts and consumption-based TPES and CO₂ accounts for high income countries. For other indicators, instances of absolute decoupling also exist in the group of high-income countries, but are very rare for lower income countries. Thus, the results from our regression analysis over a 10-year timeframe are largely consistent with the main findings from our literature review.

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What, then, are the conclusions for the prospects to achieve absolute decoupling in the future? The analyzed literature provides ample evidence that a continuation of past trends will not yield absolute reductions of resource use or GHG emissions. So far, environment and climate policies have at best achieved relative decoupling between GDP and resource use respectively GHG emissions (Kemp-Benedict 2018, Haberl et al 2019). Exceptions include a group of 18 countries that have reduced CO₂ emissions in the last decade (Le Quéré et al 2019), and a few national cases, most of which are due to specific circumstances that probably should not be generalized (e.g. when falling resource use stems from economic crises; Shao et al 2017). This observed absolute decoupling, however, falls short from the massive decoupling required to achieve agreed climate targets (Jackson and Victor 2016). Of course, rare occurrence of absolute decoupling in the past does not represent proof that it cannot become more common in the future—and perhaps intensifying the policies implemented in 18 peak-and-decline countries could yield sufficient decoupling of GDP and GHG emissions to achieve climate targets. Even if rapid deployment of renewable energy could be achieved, however, the world's addiction to material resources would likely not wane, as harnessing renewables also requires substantial investments into large-scale buildings (e.g. hydropower plants), machinery (e.g. wind turbines, photovoltaic power plants) and infrastructures (e.g. expansion and reinforcement of electric transmission grids; Beylot et al 2019, Watari et al 2019).

In any case, meeting the goals of the Paris Agreement will require new and more effective policies than those deployed so far. These need to be based on absolute—not relative—reduction goals for GHG emissions, which could strongly benefit from curbing growth of resource use (Krausmann et al 2020). The IPCC 1.5 °C report (IPCC 2018) shows that even if high hopes are placed in future deployment of negative emission technologies, fast and deep cuts in global GHG emissions are required in order to address the 2.0 °C target agreed upon in the Paris climate accord, and even more so for reaching 1.5 °C. Currently, targets for reducing resource use or emissions are commonly framed as improvements of e.g. energy/GDP ratios. For example, SDG 7.3 aims at doubling the rate of energy intensity (energy/GDP) reduction, from approx. −1.5%/year to −3.0%/year. However, such targets allow substantial increases of resource use in absolute numbers if GDP growth is sufficiently fast (Heun and Brockway 2019). Hence, absolute GHG reduction goals can only be achieved if absolute goals for emission reductions are agreed upon. The analysis of policies and strategies (section 4) shows that decoupling research is so far poorly equipped to deal with this challenge. Only a tiny fraction of the decoupling literature in our random sample adopted a 'degrowth' perspective, which we have defined very broadly as a worldview allowing to question the priority of GDP growth over environmental goals. Whether one follows the viewpoint that a decoupling of GDP from environmental impacts is impossible (Ward et al 2016, Hickel and Kallis 2019) may be less important than accepting the need to achieve absolute reductions of emissions regardless of GDP trajectories. Similar considerations apply to the use of many other biophysical resources (Green and Denniss 2018, Lazarus and van Asselt 2018).

A recent review suggest that strategies towards efficiency have to be complemented by those pushing sufficiency (Parrique et al 2019), that is, 'the direct downscaling of economic production in many sectors and parallel reduction of consumption' (p 3). Although concrete political strategies towards sufficiency—or degrowth—are still fragmented and diverse, they may include restrictive supply-side policy instruments targeting fossil fuels (instead of relative efficiency improvements), redistribution (of work and leisure, natural resources and wealth), a decentralization of the economy or new social security institutions (that complement the growth-oriented welfare state). Recently suggested policies include moratoria on resource extraction and new infrastructures (e.g. coal power plants, highways, airports), bans on harmful activities (e.g. fracking, coal mining), the reduction of working hours and redistributive taxation, instead of just putting a price on resources and emissions (Schneider et al 2010, Kallis 2011, Koch 2013, Sekulova et al 2013, Jackson 2016, Green and Denniss 2018, Hickel and Kallis 2019). A new study suggests, however, that even energy sufficiency actions may be associated with rebound effects and negative spillovers (Sorrell et al 2020).

In any case, recent research suggests that states have so far refrained from strategies of sufficiency as these may contradict their claimed structural dependence on economic growth for the generation of tax revenue, employment and consumption-based political legitimacy. A strategic turn towards sufficiency that involves reductions in overall consumption levels and may lead to a degrowing economy might therefore pose a fundamental challenge to contemporary states—and liberal democracies (Pichler et al 2018, Hausknost 2019, Koch 2019). Studies in sustainable consumption increasingly argue that a decisive turn towards 'strong sustainable consumption governance' (Lorek and Fuchs 2013), that is, a clear focus on reducing the volume of the materials and energy resources consumed while maintaining levels of well-being, will be a key required for deep decarbonization.

Another recent strand of literature is focused on overcoming GDP as key target indicator of economic policy (Hoekstra 2019). This debate suggests that GDP may be becoming an increasingly irrelevant measure of welfare, as it was only loosely coupled with wellbeing in OECD countries over the last 40 years (Hoekstra 2019). In this view, GDP should be replaced or at least complemented by measures of wellbeing and planetary health, as suggested in the dashboard approach of the Sen-Stiglitz-Fitoussi-report (Stiglitz et al 2009), and in the Sustainable Development Goals. Scholars increasingly focus more on improving social wellbeing rather than GDP growth. One conceptual angle is the 'stock-flow-service' nexus approach (Haberl et al 2017, 2019) suggesting that designing currently resource-intensive systems to provide for key contributions to social wellbeing (e.g. access/transport, housing/shelter, provision of food) in a resource-sparing manner in the first place can deliver these services at much lower levels of resource inputs than now. An example would be spatial patterns of settlements and work places that minimize the need for commuting, and foster commuting by environmentally friendly means such as walking, cycling or use of public transit. Such a focus on demand-side measures consistent with provision of services that are vital for social well-being is at the core of a currently emerging research community (Cullen et al 2011, Creutzig et al 2016, 2018, Brand-Correa and Steinberger 2017, Carmona et al 2017, Lamb and Steinberger 2017, Vita et al 2019). Perhaps the question to what extent GDP can be decoupled from resource use or emissions will turn out to be less important than the question how a good life for all on the planet can be organized within the planet's environmental limits (O'Neill et al 2018). Reductions in resource use and emissions commensurate with climate and sustainability goals (IPCC 2018, TWI2050 2018) may still be achieved by turning towards sufficiency and other transformative strategies.