Progress towards green growth: An overview

This chapter provides an overview of progress towards green growth in OECD and G20 countries. It builds on a cross-thematic analysis of some central elements of green growth. To that end, it uses a small set of headline indicators describing carbon and material productivity, environmentally adjusted multifactor productivity and population exposure to air pollution. These are complemented by indicators on land consumption by buildings, environmentally related innovation and taxation, and on income levels and inequality. For each aspect of green growth covered, it provides an overview of key developments drawing on results from the substantive chapters of the report.

Cross-thematic summary

OECD countries have come a long way towards green growth. Most countries use the available natural resources and environmental services more productively. They have reduced pollution and hence some of the environmental risks to which their populations are exposed. Many countries have stabilised extraction of renewable natural resources (wood, fish, freshwater), and are advancing towards more sustainable management practices. Numerous examples illustrate that progress achieved towards green growth is compatible with maintaining economic prosperity, and can nurture people’s well-being.

Several countries are at the forefront of the transition towards green growth, but no country leads on all fronts. In fact, countries often advance in one dimension of green growth while standing still on other fronts. Too often, progress has been insufficient as evidenced by the failure to halt further dwindling of the natural asset base and its degradation. Important challenges remain, to better safeguard our natural resources and further reduce the environmental footprints of our consumption and production. Beyond relative decoupling, economic growth must be completely untied from environmental pressures (absolute decoupling).

Analysis of the 46 countries covered indicates that Luxembourg, Iceland, Denmark, Norway and the Netherlands have achieved the best overall results (Figure 1). These countries consistently rank high across most of the green growth dimensions assessed. Denmark, for instance, is a leader in environmental technologies and innovation and also ranks high in using environmental taxation. However, its residents are exposed to more air pollution than those in Norway and Iceland. Luxembourg’s economy has higher material productivity and the country has higher living standards, but performs less well in the distribution of income. Among the non-OECD economies studied, Colombia and Costa Rica lead the way.

Figure 1. Monitoring green growth, relative to the leaders
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Note: Each axis represents the range of observed results among the 46 countries studied. The best result (leader) is located on the outer frontier of each axis, the worst result is located in the origin. For each indicator, performance of an individual country is then assessed as the “distance to the leader”. Overall result is an average across all selected indicators. Countries with missing data are excluded. For more details on the definitions of indicators, see Notes.

Source: OECD (2017), “Green growth indicators”; JRC (2016), “Global human settlement layer”; Solt (2016), “The standardized world income inequality database”; World Bank (2016), “World development indicators”.

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Countries such as Denmark, Estonia, the United Kingdom, Italy and the Slovak Republic achieved the greatest overall improvements towards green growth compared to 2000 (Figure 2). Among these, the United Kingdom and Italy improved most on material productivity, the Slovak Republic and Denmark on carbon productivity, Italy and Estonia on environmentally related taxation, and Denmark and Estonia on environmentally related innovation. The top performers vary substantially according to each of the indicators. Most countries achieved improvements in at least some aspects of green growth. This diversity of achievements between countries underlines the need to assess progress towards green growth across a set of multiple indicators.

Figure 2. Progress towards green growth
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Note: Improvements shown here are determined by comparing results in 2015 to 2000 (as a change in the “distance to the leader”). The black dashed line indicates no change; values below that level indicate deterioration.

Source: OECD (2017), “Green growth indicators”; JRC (2016), “Global human settlement layer”; Solt (2016), “The standardized world income inequality database”; World Bank (2016), “World development indicators”.

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However, multiple indicators can be complex to interpret and must be placed in a broader growth context (Figure 3). Initial results of a correlation analysis1 suggest that higher levels of carbon and material productivity are positively associated with lower population exposure to air pollution from fine particulates (PM2.5). Moreover, multifactor productivity (EAMFP) growth is correlated with lower land consumption (built-up area per capita) and lower income inequality. This indicates that fostering productivity growth can potentially also generate some desirable environmental and social outcomes.

Figure 3. Socio-economic context and characteristics of growth
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Source: OECD (2017), “Green growth indicators”, OECD Environment Statistics (database); Solt (2016), “The standardized world income inequality database”; World Bank (2016), “World development indicators”.

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At the same time, lower land consumption (built-up area per capita) is correlated with higher population exposure to PM2.5. This points to some potentially difficult trade-offs. The data also suggest that countries that rely to a greater extent on environmental taxation and foster innovation through environmental technologies tend to achieve higher levels of carbon and material productivity.

Central elements of green growth in focus

The socio-economic characteristics of growth

Large differences across countries have marked economic growth (Figure 3). Between 2000 and 2015, GDP per capita increased by 17% in the OECD area and by 137% in BRIICS economies. It ranged from -7% in Italy and Greece, to over +100% in Latvia, Lithuania, India and China. In the OECD, the service sectors generate most of the value added (73%, compared to 53% in BRIICS). The highest shares of services are in Luxembourg, Greece, the United Kingdom and France. The contribution of industry is highest in Ireland, Korea and the Czech Republic (about 40%), as well as in most BRIICS. Agriculture contributes relatively little value added in the OECD area (2% on average). The agricultural sector contributes much more in Turkey and New Zealand (9% and 6%) and in most BRIICS (10% on average).

Household income inequality is highest in South Africa, China and Colombia; among OECD countries, it is highest in Chile and Mexico. Inequality is lowest in Norway, Iceland and some other European countries. Income inequality has increased in about half of OECD and G20 countries since 2000. This occurred even when countries were going through periods of sustained economic and employment growth. Inequality increased most in Indonesia, China and India, followed by Slovenia, Austria, Germany and Poland. Rising income inequality poses social, environmental and economic challenges. It needs to be addressed when policies are designed and implemented (e.g. when the distributional effects of a green fiscal reform affect low-income households).

The environmental and resource productivity of the economy

Over the past 25 years, the environmental and resource productivity of OECD countries has grown, but with wide variation across countries and sectors. Multifactor productivity, which accounts for the role of multiple inputs (labour, produced capital, natural capital) and outputs (GDP and pollution) provides an important perspective. It shows that productivity gains have played a key role for sustaining economic growth. In fact, OECD countries have generated growth almost exclusively through productivity gains. BRIICS economies have drawn to a much greater extent on increased use of labour, produced capital and natural capital to generate additional growth.

Natural capital can contribute significantly to output growth. About 23% of its output growth in the Russian Federation since 1994 has been due to extraction of subsoil assets. This raises concerns over dependence on natural resource extraction and the need to identify new sources of growth in the long run. Pollution abatement can also affect growth performance. Some countries have achieved economic growth only at the expense of environmental quality.

From the perspective of single inputs and outputs, both the carbon and material productivity of OECD economies has improved. Today, OECD countries generate more economic output per unit of resources consumed. To generate USD 1 000 of GDP in 2015 (or the most recent year available), OECD countries, on average, consume 416 kg of non-energy materials and 111 kg of energy materials (in oil equivalent) (down from 143 kg in 2000). They also emit 256 kg of CO2 (down from 338 kg in 2000).

Despite a slowdown in the OECD area, global CO2 emissions continued to grow, up 58% from 1990. Some countries managed to reduce the absolute level of emissions. However, most have achieved only a relative decoupling between emissions and economic growth. In other words, CO2 emissions increased at a lower rate than real GDP.

Decoupling demand-based CO2 emissions presents an even greater challenge. Total emissions generated to satisfy domestic final demand in OECD countries have increased faster than emissions from domestic production. As a result, most OECD countries are “net-importers” of CO2 emissions.

Cleaner production (e.g. through cleaner energy use) can help address both production- and demand-based emissions (consumption of cleaner domestic production). Decoupling demand-based CO2 emissions is challenging, however, because embodied CO2 emissions per capita are highly correlated with living standards. Conversely, production-based CO2 emissions more closely reflect the structure and energy intensity of the economy.

These developments are on par with widespread increases in energy productivity. However productivity levels remain low in many of the major energy consuming countries. OECD countries and BRIICS economies continue to be more than 80% reliant on fossil fuels. Renewables still play only a relatively minor role in the energy mix. Several countries have seen fast increases in coal penetration (both OECD and BRIICS). Further, some countries with potentially important renewable energy resources still show low levels of renewables penetration. Energy productivity could be fostered through continued phasing out of government support for fossil fuel consumption and removing barriers to improvements in energy efficiency.

Materials other than energy carriers represent 78% of the materials mix consumption in the OECD and 87% in BRIICS. Productivity gains have been achieved, but material consumption remains high, often driven by construction materials. Raising the recovery rates of construction minerals could significantly improve efficiency. Once indirect flows (raw materials embodied in international trade) are considered, improvements over longer periods are often more moderate.

Many materials, including valuable materials, end up as waste. However, efforts to move from waste to resources are starting to show results. Increasing material recovery (through recycling and composting) is an important complement to waste reduction efforts. In Europe, about one-third of the 13.4 tonnes of materials consumed every year per person end up in waste. About 17% of this amount is subsequently recovered.

The natural asset base of the economy

Countries’ endowment in natural resources varies greatly and intensity of use of many resources is high and rising. Freshwater resources in particular are unevenly distributed and local water scarcity remains of concern. In more than one-third of OECD countries, freshwater resources are under moderate to medium-high stress. Many forests are threatened by degradation, fragmentation and conversion to other types; and many ecosystems have been degraded.

Across the OECD, the conversion of land to artificial surfaces has accelerated. Buildings now cover 30% more land than in 1990. Globally, an area the size of the United Kingdom has been converted to buildings since 1990. Societal changes, population growth and changing urban form (compact vs. fragmented cities) may explain this growth.

Intense urban growth occurs in many already highly urbanised countries. This often brings about a loss of natural resources and agricultural land, soil sealing and negative effects on the water cycle. Land development and the resulting changes in land cover lead to habitat fragmentation and habitat loss. They are thus associated with a decline in the populations of many species and reduced biodiversity. Measures to protect biodiversity and ecosystems such as protected area designations, sustainable resource management, etc. must be complemented with mainstreaming of biodiversity-relevant policy instruments. Environmentally harmful agricultural subsidies must also be phased out.

The environmental dimension of quality of life

Air pollution is the single greatest environmental health risk worldwide. Human exposure to air pollution by fine particulates (PM2.5) remains dangerously high in most OECD countries, despite improvements since 1990. Less than one in three OECD countries meet the WHO Air Quality Guideline for annual average PM2.5 exposure of 10 micrograms per cubic metre. Exposures to PM2.5 continue to rise in China and India and now attain extreme levels. At the same time, there has been little improvement in population exposure to air pollution by ground-level ozone (O3).

Exposure to these two air pollutants has serious consequences for human health. In the OECD area, exposure to outdoor PM2.5 and ozone is estimated to cause around 0.5 million premature deaths each year. This has an annual welfare cost equivalent to 3.8% of GDP. More ambitious policy could thus generate significant benefits.

Economic opportunities from innovation and effective policies

Innovation is a key driver of productivity and economic growth. Efforts to implement green growth policies by encouraging innovation and changes in consumer behaviour are accelerating. Worldwide, the number of inventions in climate change mitigation technologies (especially their applications to buildings, transport and energy generation) have tripled since 2000. At the same time, inventive activity in general (all technologies) has risen only by about 30%.

However, inventive activity has been slowing down across all major environment-related technological domains since 2011. About 90% of green technologies still originate in the OECD, but the contributions of China and India are rising fast. Innovation can help achieve environmental objectives at lower costs and speed up the transition to green growth; it can also lead to new business opportunities and markets.

Providing continuous and long-term incentives for directing innovation towards environmental objectives remains a challenge. Economic instruments are insufficiently used, and policies often lack coherence, thus undermining the transition to green growth.

Research and development budgets are rising in many countries, but the share devoted to environmental and energy objectives remains stagnant. Public budgets for energy-related research, development and demonstration are shifting towards renewables in most OECD countries. Yet, in a handful of countries, support for fossil fuel energy technology keeps rising. In many countries, innovation policies are insufficiently co-ordinated with environmental and resource efficiency policies.

In OECD countries, the share of environmentally related taxes in total tax revenue and compared to GDP is decreasing. Some countries have shifted part of their revenue collection from labour to environmentally related activities. Others have introduced new environmentally related taxes as part of fiscal consolidation. However, most countries have experienced higher increases in their revenue from labour taxes relative to that of the environment. The revenue raise by environmentally related taxes represents only 5.2% of total tax revenue, equivalent to 1.6% of GDP in the OECD area.

At the same time, countries continue to support fossil fuel production and consumption in many ways. This costs more than USD 60 billion per year in the OECD area only, and much more in the rest of the world. Further, there are several impediments to the transition to a low-carbon economy. These include variations in energy tax rates, preferential treatment of diesel fuel and of company cars, exemptions for fuel used in some sectors, and significant gaps in taxation of non-road carbon emissions.

Overall, a better alignment of “green” and “growth” objectives is needed. The main challenges in implementing policy frameworks for green growth include (OECD, 2015):

  1. establishing an explicit price on greenhouse gas emissions through taxation or tradable permit systems

  2. using pricing instruments to change behaviour with respect to water, waste and transport

  3. shifting the tax burden in favour of environmentally related taxation

  4. eliminating environmentally harmful discrepancies in tax systems

  5. managing subsidies to promote green technologies and phasing out environmentally perverse subsidies

  6. supporting the development of green infrastructure

  7. orienting innovation systems to advance green growth priorities

  8. accelerating improvements in energy efficiency.

Notes

Figure 1 and Figure 2 use the following indicators:

  • CO2 productivity (production-based) calculated as real GDP generated per unit of CO2 emitted (USD/kg). For more information, see chapter on Carbon productivity.

  • CO2 productivity (demand-based) calculated as GDP generated per unit of CO2 emitted from final demand (USD/kg). For more information, see chapter on Carbon productivity.

  • Material productivity (production-based) calculated as GDP generated per unit of materials consumed (in terms of Domestic Material Consumption). For more information, see chapter on Material productivity.

  • Environmentally adjusted multifactor productivity growth (EAMFP) calculated using a growth accounting framework that includes labour, produced capital and natural capital as factor inputs, and pollution as undesirable by-product. For more information, see chapter on Environmentally adjusted multifactor productivity.

  • (Low) land consumption is calculated as (the inverse of) built-up area per capita. For more information, see chapter on Land resources.

  • (Low) air pollution exposure is calculated as (the inverse of) mean exposure to outdoor PM2.5. For more information, see chapter on Air pollution, health risks and costs.

  • Environmentally related innovation refers to the share of environmentally related patents on total patents developed by a country’s inventors. For more information, see chapter on Technology and innovation.

  • Environmentally related taxation refers to the share of environmentally related tax revenue on total tax revenue collected in a country. For more information, see chapter on Taxes and subsidies.

  • Gross domestic product (GDP) per capita, is expressed in USD 2010 using PPPs, per inhabitant. For more information, see Glossary.

  • (Low) income inequality is calculated as (the inverse of) the Gini coefficient. For more information, see Glossary.

References

JRC (2016), “Global human settlement layer”, Joint Research Centre, European Commission, http://publications.jrc.ec.europa.eu/repository/handle/JRC97705.

OECD (2017), “Green growth indicators”, OECD Environment Statistics (database), http://dx.doi.org/10.1787/data-00665-en (accessed in March 2017).

OECD (2015), Towards Green Growth?: Tracking Progress, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264234437-en.

Solt, F. (2016), “The standardized world income inequality database”, Social Science Quarterly, No. 97/5, SWIID Version 5.1, July 2016, pp. 1267-1281.

World Bank (2016), “World development indicators”, http://data.worldbank.org/data-catalog/world-development-indicators (accessed in January 2017).

Note

← 1. Partial correlation coefficients from pairwise regressions, controlling for country- and time- specific variation.