How’s Life in Latin America?

Measuring Well-being for Policy Making

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28 October 2021

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4. Resources for future well-being in Latin America

Abstract

Latin America is home to much of the world’s biodiversity. However, its biodiversity is declining twice as fast as the OECD average, eroding the natural capital upon which the region’s current and future well-being depend. The risks to human capital include the rapidly rising prevalence of overweight and obesity and the large number of youth who are not in education or employment. Slow investment growth implies a weak foundation for future well-being, while the high burden of repaying foreign debt is a persistent risk. Multiple social uprisings in 2019 clearly indicated the fragility of the social contract in the region, which is confirmed when looking at dwindling support for electoral democracy, low trust in government and in others, and high levels of perception of corruption, discrimination, and an unfair distribution of income. The COVID-19 pandemic is compounding pressures on all types of capital that underpin future well-being.

Introduction

This chapter provides an overview of four different types of resources that help to support well-being over time. Following the OECD Well-Being Framework (OECD, 2020[1]), these resources are expressed in terms of four types of capital (i.e. stocks that last over time but are also affected by decision-making today. Natural Capital encompasses natural assets that are renewable (e.g. forests, fishes) or non-renewable (e.g. minerals) as well as ecosystems (e.g. ocean coral reefs, wetlands, forests, soil and the atmosphere) and the services they provide. Economic Capital includes both man-made and financial assets. Human Capital refers to the skills and future health of individuals. And Social Capital refers to the social norms, shared values and institutional arrangements that foster co-operation (OECD, 2020[1]). In addition to considering capital stocks and flows, some key risk and resilience factors that might affect the well-being value of those stocks and flows in the future are also discussed. Each section below also highlights the key statistical gaps to be addressed in order to improve the measurement of resources for future well-being.1

As noted in previous chapters, the COVID-19 pandemic has radically changed people’s lives. It has unveiled new vulnerabilities while exacerbating others, and it has created a new focus on the need to “build forward better”, through more resilient and sustainable forms of development. At the time of writing, the available data do not yet show the full impact of the crisis and its long-term consequences. When available, the chapter also presents relevant evidence on how the COVID-19 crisis is affecting these resources.

Natural Capital

Natural Capital consists of naturally occurring assets and ecosystems (OECD, 2020[1]). “Environmental assets” are individual components of the environment, while “ecosystems” refer to the joint functioning of, or interactions among, different environmental assets within a specific spatial area. According to the United Nations Statistical Commission’s System of Environmental and Economic Accounting (SEEA), whose central framework is an international standard (UNSC, 2014[2]), there are seven sets of natural and environmental assets: mineral and energy resources; land; soil resources; timber resources; aquatic resources; other biological resources (excluding timber and aquatic resources); and water resources.

Some of the well-being benefits of natural assets can be felt “here and now” (e.g. breathing clean air or drinking safe water), and some of them are included in the “Environmental quality” dimension covered in Chapter 3 (on quality of life). However, many of the benefits provided by natural assets come from their role in generating services for future generations as well as for other capitals (e.g. providing the physical space, energy and raw materials for economic activities, or water and food to sustain human capital) (OECD, 2015[3]).

Latin America contains 60% of the world’s biodiversity (UNEP-WCMC, 2016[4]), as well as a wide variety of climatic regions, topographies and land-use patterns. The Amazon Basin alone is home to some 40% of the world’s remaining tropical forest and contains one of the Earth’s richest assortments of biodiversity (UNFCCC, 2007[5]). Biodiversity underpins ecosystem services upon which people depend and helps ensure resilience (i.e. increased diversity helps ecosystems to continue to provide services and be more resilient to pressures). Due to its abundant natural resources, Latin America stands out as a major player in the development of renewable energy, in particular hydropower, though since 2000 hydropower has declined as a share of the region’s total energy mix. Despite this, per capita greenhouse gas (GHG) emissions, when including land use change, are close to world average levels: with 8.5% of the world’s population, the region accounts for 8.3% of global GHG emissions. The region is also highly vulnerable to the effects of climate change, in particular in the water, agriculture and health sectors, the Andean glaciers, the Amazon and other regions vulnerable to extreme climatic events and climate variability (changes in temperatures, timing of rain, etc., upset interactions within ecological communities). The critical challenge is to preserve this unique natural wealth from the effects of climate change, harmful forms of commercial exploitation, urban sprawl, subsistence agriculture, land-use change, overuse of natural resources, pollution and invasive alien species.

The indicators presented here include four stock measures (natural and semi-natural vegetated land cover; intact forest landscapes; and both terrestrial and marine protected areas); one flow measure (material footprint per capita); one resilience factor (renewable energy consumption); and three risk factors that put pressure on natural stocks (threatened species; greenhouse gas emissions per capita; and water stress).

Biological resources and biodiversity

“Biological diversity” or “biodiversity” stands for “the variability among living organisms from all sources including, inter alia, terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; this includes diversity within species, between species and of ecosystems” (UNEP, 2006[6]). The current use of terrestrial ecosystems is not sustainable (United Nations, 2020[7]; OECD, 2021[8]). Loss of biodiversity and pressures on ecosystem services are among the most pressing global environmental challenges, with changes in land cover and land use being leading contributors of terrestrial biodiversity loss (Haščič and Mackie, 2018[9]). The unprecedented rate of the worldwide destruction of natural capital is posing significant but often overlooked risks to the well-being of current and future generations, the economy and the financial sector. The emergence of infectious diseases such as COVID-19, of which land-use change and wildlife exploitation are key drivers, is just one example of the various risks associated with the mismanagement of natural capital (OECD, 2021[8]). The Convention on Biological Diversity, signed by 150 government leaders at the 1992 Rio Earth Summit, has been conceived as a practical tool for translating the principles of Agenda 21 into reality. It , recognised that not only is biological diversity about preserving plants, animals and microorganisms and their ecosystems, but it is also about people and their need for food security, medicines, fresh air and water, shelter, and a clean and healthy environment in which to live. Additionally, Sustainable Development Goal 15 addresses the need to “Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss”, while Goal 14 emphasises the need to “Conserve and sustainably use the oceans, seas and marine resources for sustainable development”.

Natural land cover

Land cover is the observed physical and biological cover of the Earth’s surface, including natural vegetation, abiotic (non-living) surfaces and inland waters (UNSC, 2014[2]). In 2018, 76% of land in Latin America was covered by natural or semi-natural vegetation, only slightly above the OECD average of 75% (Figure 4.1, Panel A). In Colombia, Ecuador and Peru, however, natural or semi-natural vegetation covers more than 80% of the total land, while in Chile and the Dominican Republic that share is below 70%. Between 2004 and 2018, the total land covered by natural and semi-natural vegetation in Latin America remained broadly stable. The highest net gain occurred in Costa Rica, where it increased by more than 3 percentage points, while it dropped by 2 percentage points in Paraguay.

Land use change

Change in land use is a key driver of land degradation. Beyond changes in the net stock of natural land cover, losses and gains in natural and semi-natural vegetation have to be considered separately, as gains in semi-natural areas (that are poor in biodiversity) may not compensate losses in natural areas rich in biodiversity (e.g. loss of primary or old-growth forest) (OECD, 2020[1]). Losses of natural and semi-natural vegetated land can be measured by the percentage of tree cover, grassland, wetland, shrubland and sparse vegetation converted to any other land-cover type. Gains of natural and semi-natural vegetated land are conversions in the opposite direction. The denominator used is the “stock” of natural and semi-natural land at the start of the period. Loss of natural and semi-natural vegetated land is a proxy for pressures on biodiversity and ecosystems.

This regional stability of land cover masks diverging patterns across Latin American countries. Brazil, Argentina, Mexico and Paraguay are among the countries where changes in land cover have been most dramatic:2 since 2004, the loss in natural and semi-natural vegetation has exceeded 10 000 square kilometres in each. Losses are also relatively high in Costa Rica and the Dominican Republic, but were paired with the highest gains in natural and semi-natural vegetation (by more than 4%) among the focal countries,3 which was achieved through afforestation or reforestation4 (Figure 4.1, Panel B).

Note: OECD Total excludes Costa Rica, as it was published prior to Costa Rica joining the OECD.

Source: OECD Land cover in countries and regions (database), https://stats.oecd.org/Index.aspx?DataSetCode=LAND_COVER (Panel A) and OECD Land cover change in countries and regions (database), https://stats.oecd.org/Index.aspx?DataSetCode=LAND_COVER_CHANGE (Panel B).

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Intact forest landscapes

High-level indicators of land cover do not provide information about the biodiversity value of areas lost and gained. Intact forest landscapes are very high-value ecosystems: they are characterised by “unbroken expanses of natural ecosystems within the current forest extent with no remotely detected signs of human activity, and large enough that all native biodiversity, including viable populations of wide-ranging species, could be maintained” (Potapov et al., 2017[10]). Latin America and the Caribbean are home to 36% of the world’s intact forest landscapes. Ten of the focal countries have intact forest landscapes remaining. Brazil has the world’s third-largest intact forest landscape (after Canada and the Russian Federation); together these three countries accounted for two-thirds of the world’s intact forest landscape area in 2016. Compared to 2000, intact forest area fell by around 9% (around 400 000 square kilometres) in Latin America and the Caribbean: half of that loss occurred in Brazil. Losses were high also in Peru (more than 44 000 square kilometres) and Paraguay (a decline of 80%, i.e. around 36 000 square kilometres), while they were lowest in Colombia (0.2 square kilometres).

Other terrestrial and marine ecosystems, such as grasslands and wetlands, are also important for biodiversity and ecosystem services, and they are suffering from considerable pressure in Latin America (e.g. las Pampas). Unfortunately, comparable data is scattered.

Threatened species

Species extinction upsets the balance of nature and makes ecosystems more fragile and less resistant to disruptions (United Nations, 2020[7]). The importance of monitoring threatened species has been internationally recognised in the Convention on Biological Diversity (UNEP, 2006[6]) and Sustainable Development Goal 15, and it is monitored through the Red List Index (indicator 15.5.1), which considers the combined extinction risk for birds, mammals, amphibians, cycads and corals.

The Red List Index for the focal countries has fallen by 3% since 2000, twice as quickly as the OECD average decline (Figure 4.2). The largest falls have occurred in Chile, Ecuador and Mexico, all countries with already high “at-risk” rates.

Note: The Red List Index is a combined indicator of extinction risk for birds, mammals, amphibians, cycads and corals. An RLI value of 1.0 implies that all species qualify as “Least Concern”, i.e. they are not expected to become extinct in the near future. An RLI value of 0 equates to all species having gone extinct. LAC is the regional average for Latin America and the Caribbean as calculated by the UN DESA.

Source: UN DESA Global SDG Indicator Database, indicator 15.5.1, https://unstats.un.org/sdgs/indicators/database/.

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Terrestrial and marine protected areas

The expansion of agricultural production and human incursions into natural areas for logging, mining and other purposes have led to habitat loss and fragmentation as well as to increased contact between humans, livestock and wildlife. This increasing contact also enables the spread of diseases from animal populations to humans who have little or no resistance to them, such as COVID-19 (IUCN, 2020[11]). One policy instrument to conserve species and ecosystems (such as taxes, fees, charges, biodiversity offsets and payments for ecosystem services) is the creation of protected areas, whose importance for sustainability is also internationally recognised by Sustainable Development Goals 14 and 15.5

Latin American and Caribbean countries are stepping up their protection of terrestrial and marine environments but at different speeds across the region. In Latin America and the Caribbean as a whole, 25% of land and 24% of marine areas are protected6 (Figure 4.3). This is above the OECD average of 16% and 22% respectively, and above the international Aichi Biodiversity Target7 11 for 2020 of at least 17% of protected terrestrial areas and 10% of coastal and marine areas, in terms of coverage (UNEP-WCMC, 2016[4]). In 2000, the share of protected terrestrial areas in the focal countries and in the OECD area were very close (10.4% and 9.7%, respectively). Yet between 2000 and 2020, coverage of terrestrial protected areas increased by almost 9 percentage points in the focal countries on average, above the rate of increase for the OECD average (6.3 percentage points). The largest increases (above 14 percentage points) occurred in Brazil, the Dominican Republic and Peru. Over the same period, the share of protected marine areas more than doubled in 10 of the focal countries, with the exception of Ecuador, where the share was the highest among the focal countries in 2000 and remained almost stable over time. Most of the focal countries have achieved the 2020 Aichi Biodiversity Target 11 in terms of coverage,8 except Uruguay (for terrestrial and marine areas), Argentina, Mexico and Paraguay (for terrestrial areas), and Costa Rica and Peru (for marine areas).

Note: OECD Total includes Costa Rica and excludes Turkey, as no protected area data for Turkey is submitted to the UNEP-WCMC and IUCN World Database on Protected Areas (WDPA). In Panel B, LAC 10 and LAC Total exclude Paraguay, as there is no marine area. Additionally to Turkey, OECD Total excludes Austria, the Czech Republic, Hungary, Luxembourg, the Slovak Republic and Switzerland, as there is no marine area.

Source: OECD Protected areas (database), https://stats.oecd.org/Index.aspx?DataSetCode=PROTECTED_AREAS.

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Climate change

Climate change threatens future well-being, and its urgency has been internationally recognised in Sustainable Development Goal 13: “Climate action: Take urgent action to combat climate change and its impact”. Due to their geography, climate, socio-economic structures, demographics and natural assets (such as its forests and biodiversity), all Latin American and Caribbean countries, particularly in Central America and the Caribbean, are heavily affected by climate variations, higher temperatures, rising seas, ocean acidification, and the greater intensity and frequency of climate-related natural disasters (ECLAC/OHCHR, 2019[12]). The year 2019 was the second warmest on record and the end of the warmest decade (2010–2019), a decade characterised by massive wildfires, hurricanes, droughts, floods and other climate disasters across continents. To meet the target of a rise of 1.5°C – or even 2°C – called for in the Paris Agreement, global greenhouse gas emissions must begin falling by 7.6 per cent each year starting in 2020 (United Nations, 2020[7]).

Greenhouse gas emissions

In the six focal countries for which data are available, greenhouse gas (GHG) emissions per capita from domestic production (excluding emissions from land use, land-use change and forestry, LULUCF) are around 5 tonnes of CO₂ equivalent, half the level of the OECD average (Figure 4.4, Panel A). GHG emissions in the worst-performing countries (Argentina and Chile) are more than twice as high as those in the best performers (Costa Rica and Colombia). Since 2000, the moderate increase in the focal country average (0.5 tonne) has been driven by Chile (1.1 tonnes) and Brazil (0.8 tonne), while GHG emissions from domestic production have remained broadly stable in the other focal countries for which data are available.

The region’s total emissions including emissions from land use, land-use change and forestry (LULUCF) increased considerably from the mid-nineteenth century to 1992, the year the United Nations Framework Convention on Climate Change (UNFCCC) was adopted. The emissions growth rate has eased since then, and the post-Kyoto protocol9 period (since 2012) has had the lowest emissions growth rate so far. According to Intergovernmental Panel on Climate Change (IPCC) data, the Latin America and the Caribbean region accounted for 8.3% of global emissions, roughly in line with the region’s share of the world population (8.5%). Yet many countries within the region are in an asymmetrical position in relation to climate change: less responsible for its historical causes, but highly vulnerable to its effects (Bárcena et al., 2020[13]).

The structure of the region’s emissions is also different from that of global emissions. Whereas 70% of the world’s emissions come from the energy sector, in the region the share is only 45%, followed by agriculture and livestock (23%), and changes in land use and forestry (19%). Changes in emissions due to land use significantly add to the total, and results in a per capita average are equal to the global average, despite the region’s clean domestic energy mix, with limited use of coal and extensive use of hydropower (Bárcena et al., 2020[13]).

Renewable energy supply

Electricity generation, notably through the combustion of fossil fuels, is the single largest contributor to global GHG emissions (OECD, 2019[14]). Catalysing change through a sustainable energy sector is therefore a necessary step to achieve GHG emission targets. Thanks to its rich water resources, 35% of the total primary energy supply in the focal countries is from renewable sources, well above the OECD average (11%) (Figure 4.4, Panel B). In Paraguay and Uruguay more than 50% of the total primary energy supply comes from renewable sources. In particular, 100% of the primary energy produced in Paraguay is renewable (and 100% of the energy exports originate from renewable sources of energy: hydropower and charcoal produced in coal bunkers, which is why the value for Paraguay exceeds 100%) (UNCTAD, 2018[15]). On the other side of the spectrum, in Argentina and Mexico the share of renewables is only around 8%. Between 2000 and 2019 the share of renewables in the focal countries’ total primary energy supply fell by almost 4 percentage points, in contrast to the rise of almost 5 percentage points in the OECD average. Gains of more than 4 percentage points were observed in Costa Rica (4.4 percentage points), Brazil (7 percentage points) and Uruguay (with an increase of almost 27 percentage points). Conversely, in most of the focal countries there has been a mix of stability and declines in the share of renewables in the total primary energy supply. The strongest falls occurred in Peru (by almost 12 percentage points) and Paraguay (by almost 65 percentage points). Across the region, the share of hydropower is declining, despite the large investment made in it. This is due in part to the reduction in rainfall, but also to investment in fossil fuels (in shale gas in particular), with some countries in the region carbonising instead of decarbonising. Sunk costs,10 a lack of renewable energy transmission and storage infrastructure, delays in internalising externalities and the importance of hydrocarbons in some countries’ exports are major obstacles in moving away from fossil fuel dependency (Bárcena et al., 2020[13]).

Note: OECD Total excludes Costa Rica, as it was published prior to Costa Rica joining the OECD. In Panel A, the latest available year is 2015 for Mexico; 2014 for Argentina and Colombia; and 2012 for Brazil and Costa Rica. LAC 6 excludes the Dominican Republic, Ecuador, Peru, Paraguay and Uruguay. In Panel B, LAC comprises 23 Latin American and Caribbean countries, including the focal countries

Source: OECD Greenhouse gas emissions (database), https://stats.oecd.org/Index.aspx?DataSetCode=AIR_GHG (Panel A) and OECD Green Growth Indicators: Environmental and resource productivity (database), https://stats.oecd.org/index.aspx?queryid=77867 (Panel B).

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Freshwater resources: Water stress

Water is essential not only to health, but also to poverty reduction, food security, peace and human rights, ecosystems and education, as is internationally recognised in Sustainable Development Goal 6: “Clean water and sanitations: Ensure availability and sustainable management of water and sanitation for all” (United Nations, 2020[7]). Water stress – which occurs when the ratio of fresh water withdrawn to total renewable freshwater resources is above a 25% threshold – can have devastating consequences for the environment and constrain or reverse sustainable development (United Nations, 2020[7]). The global average water stress is 17%, which is considered a “safe” level according to the 2020 SDG report. In the Latin American region, water is available in abundant quantities, but it is distributed unevenly among and within countries. In the focal countries, water stress is only 9% on average, below the OECD average of 20% (Figure 4.5). However, the average regional ratio masks high levels of water stress in the Dominican Republic and Mexico (respectively 44% and 26%), which can lead to water scarcity. In addition, water resources are at risk of severe pathogenic contamination, mainly from domestic sewage, and of saline or nutrient pollution related to unsuitable agricultural practices. In the Andean region, the surface area of glaciers is shrinking, and several have already disappeared, affecting large urban and rural areas. Climate change and ineffective management are leading to the loss of strategic freshwater reserves (ECLAC, 2021[16]).

When considering water resources, access to drinkable water is the main challenge in Latin America and the Caribbean, where only 71% of the population has access to safe drinking water, well below the 95% observed among OECD countries (Chapter 2). Differences within the region are wide: Mexico has the lowest level of access to safe drinking water, covering just 43% of its population, while almost everyone has access to it in Chile. According to the United Nations, the implementation of integrated water resources management (i.e. a global framework covering policies, institutions, management instruments and financing for the comprehensive and collaborative management of water resources) is particularly slow (very low to medium-low) in around 90% of countries across Latin America and the Caribbean (United Nations, 2020[7]).

Note: Data refer to 2014, except for Mexico (2015). LAC comprises 32 Latin American and Caribbean countries, including the focal countries.

Source: World Bank World Development Indicators (database), https://data.worldbank.org/indicator/ER.H2O.FWST.ZS.

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Material footprint per capita

Material footprint refers to the global allocation of raw material extracted to meet the final demand of an economy, including materials used in the production of imported products. These data refer to material resources, i.e. materials originating from natural resources that form the material basis of the economy: metals (ferrous, non-ferrous), non-metallic minerals (construction minerals, industrial minerals), biomass (wood, food) and fossil energy carriers. On a per capita basis, the material footprint in the focal countries is around half of that in the OECD countries (14.4 and 24.8 tonnes, respectively) (Figure 4.6). However, the material footprint increased in all focal countries between 2000 and 2018. The largest increases (exceeding 15 tonnes) were recorded in Uruguay (the country with the highest material footprint per capita in the focal group), Brazil and Paraguay. By contrast, the smallest increase (0.3 tonne) was registered in Mexico.

The use of materials in production and consumption processes has many economic, social and environmental consequences (e.g. pollution, waste, habitat disruption, biodiversity loss). These consequences differ among the various materials and among the various stages of the resource life cycle (i.e. extraction, processing, use, transport, end-of-life management) and often extend beyond the borders of countries or regions, notably when materials are traded internationally.

Note: OECD Total includes Costa Rica.

Source: OECD Material resources (database), https://stats.oecd.org/Index.aspx?DataSetCode=MATERIAL_RESOURCES.

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The impact of COVID-19 on natural capital

Pandemic prevention and containment measures, in particular confinement and social distancing, have drastically changed the behaviour of the world’s population, especially in cities. With more than 80% of the Latin American and Caribbean population living in urban areas, the changes in economic and social activities in cities have had significant impacts on the use of private and public transport, air pollution, greenhouse gas emissions, emissions to water bodies, energy consumption and waste production.

The halt to normal daily activities has limited energy consumption. Global energy demand in the first quarter of 2020 declined by 3.8% (150 million tonnes of oil equivalent (Mtoe)) relative to the first quarter of 2019, reversing all the energy demand growth of 2019 (IEA, 2020[17]). Although energy consumption by household activities has increased, this has been more than offset by the decline in energy consumption in other sectors, such as transport and industry. During the pandemic, two of the largest biofuel markets, Argentina and Brazil, have faced a drop in demand and in prices in their domestic and foreign markets, affecting a sector whose technology is relatively expensive. At the same time, fossil fuel prices have fallen, making biofuels less competitive and challenging the region’s model of a clean energy mix (UNDP Latin America and the Caribbean, 2020[18]).

The sudden drop in transport and industrial activities has led to making significant reductions in emissions into water bodies and the atmosphere, especially in cities, in just a short period of time. Global CO₂ emissions were over 5% lower in the first quarter of 2020, compared to the same period in 2019. This has been mainly driven by an 8% decline in emissions from coal, 4.5% from oil and 2.3% from natural gas. CO₂emissions fell more than energy demand, as the most carbon-intensive fuels experienced the largest declines in demand during the first quarter of 2020 (IEA, 2020[17]).Full-year projections of GHG emissions in 2020 point to a drop by around 7% globally (Friedlingstein et al., 2020[19])and, according to ECLAC, by more in the Latin American region, owing to the sharp decline in its output relative to the rest of the world (ECLAC, 2021[16]).

At the same time, preventive isolation and social distancing policies in the region have not stopped deforestation in Latin America (UNDP Latin America and the Caribbean, 2020[18]). Over the past decade, external threats to the region’s forests from mining, oil, agricultural and forestry companies, cattle ranchers, farmers, illegal groups and land speculators have increased markedly (Walker et al., 2020[20]; Ellis et al., 2017[21]). Meanwhile, government efforts to control illegal incursions into indigenous territories have waned in several countries. With the pandemic, this situation has become even worse, as governments had to limit their monitoring efforts, for both health and budgetary reasons, exacerbating the vulnerability of forests and water and other natural resources in indigenous territories (ECLAC, 2020[22]). An analysis by Open Democracy (2020) indicates that forest fires in Colombia have grown by more than 200% in 2020 compared to the same period in 2019, as trafficking mafias and garimperios (illegal miners) have taken advantage of the health emergency to burn the forest without any impediment or restriction; these increases in forest fires follow the significant declines in deforestation that had been achieved in 2018 and 2019 (López-Feldman et al., 2020[23]). Open Democracy also report, based on data from the National Institute for Space Research (INPE), that deforestation in the Brazilian Amazon increased by 64% in April 2020, the rainy season of the year when river flooding makes it difficult for fires to spread and for humans to act (Open Democracy, 2020[24]). Deforestation in the Brazilian Amazon continued also in the following months (Escobar, 2020[25]). According to Rajão and others (Rajão et al., 2020[26]), just 2% of agricultural estates in El Cerrado and Amazonía are responsible for 62% of all illegal deforestation.

Between 2019 and 2021, no major change has been registered in the share of terrestrial and marine protected areas in Latin America and the OECD.

Despite the great effort to meet the coverage component of Aichi Biodiversity Target 1111 of the Convention on Biological Diversity, the protection of specific areas is not ecologically representative.12 Only half of the biomes (large naturally occurring communities of flora and fauna occupying a major habitat) present in Latin America and the Caribbean reach or exceed 17% protection (Aichi Biodiversity Target 11). Some biomes, such as the Mediterranean forest and scrub or temperate grasslands and savannahs, are particularly under-represented in the region. Evaluating the representativeness of the protected regions, in terms of the protection status of regional species and endemism, is essential to preserve biodiversity. The Red List Index, a broad measure of biodiversity loss, was broadly stable on average across Latin American countries and OECD countries but declined by 1% in Ecuador, Mexico and Chile. In terms of connectivity, the vast majority of Latin American countries are still in the process of meeting the connectivity criteria of Aichi Biodiversity Target 11. Out of the 51 countries and territories in the region, only nine have more than 17% of their land area protected and connected (Aichi Biodiversity Target 11). On average, 33% of the extension of these protected areas are not well connected (i.e. one-third of the protected area in Latin America and the Caribbean) (RedParques et al., 2021[27]).

The loss of biodiversity and of the associated ecosystem services greatly increases the threat of infectious pathogens carried by various organisms and then affecting humans, such as COVID-19 (United Nations, 2020[7]; Gottdenker et al., 2014[28]). Land-use change and wildlife exploitation increase the risk of infectious disease by bringing people and domestic animals into close proximity to pathogen-carrying wildlife, and by disrupting the ecological processes that keep diseases in check (OECD, 2020[29]). A high level of species diversity, a characteristic of healthy ecosystems, regulates the population of those species that act as primary reservoirs of viruses, thereby restraining the transmission of pathogens. Evidence (IPBES, 2020[30]; OECD, 2020[29]) indicates that conserving biodiversity and its ecosystem services is necessary to protect human health both directly and indirectly (ECLAC, 2020[22]) and avoid the next pandemic (close to three-quarters of emerging infectious diseases in humans come from other animals) (OECD, 2020[29]). As such, the COVID-19 pandemic is a wake-up call to recognise the importance of natural capital and the necessity to preserve it. Efforts to build forward better are aligned with climate change objectives. In this context, Latin American and Caribbean governments have increasingly recognised the urgent need to integrate climate action and biodiversity into their pandemic recovery efforts.13

Issues for statistical development

The indicators included in this section have been selected as satisfying some minimum requirements in terms of country coverage, length of time series and timeliness (see Chapter 1). However, progress could be achieved in each of these areas. Some key indicators have not been included as they do not satisfy the minimum requirements (e.g. soil resources) or because data are not available (e.g. municipal waste material recovery rates). The indicator set could be further refined or complemented with data on the quality of the natural resources (e.g. soil, water), in terms of pollution (e.g. total fertiliser inputs, pollution of lakes and rivers, ocean acidification) and sustainable management (e.g. fish stocks, total recycling and composting), species diversity, effective management and enforcement of protected areas, and the benefits of ecosystem services for human well-being. Since patterns of water stress can vary substantially at the subnational level, a valuable additional indicator to be developed is the share of the population exposed to water scarcity, as a supplement to national average rates. Ideally, the breakdown of different greenhouse gases (GHG) would be shown separately, rather than summing them together in weighted carbon equivalent terms, as each gas has different atmospheric effects. Better data on natural disasters should also be developed.

Economic Capital

Economic capital – a country’s stock of produced economic and financial assets – plays a crucial role in supporting material well-being (e.g. housing, jobs, wealth and incomes) and in producing goods and services that people consume. In addition, economic capital serves as store of value that provides a buffer for unexpected income shocks, allowing households, firms and governments to plan for the future, and to ensure that material living standards are sustained over time (OECD, 2015[3]).

Produced capital refers to man-made tangible assets such as roads, railways, buildings and machinery; intellectual property assets resulting from R&D expenditure, investment in computer software and art works; and inventories of final and intermediate goods. Financial capital includes financial assets such as currency and deposits, equity, securities and derivatives, net of liabilities in the form of loans and debt securities (OECD, 2020[1]). The net foreign assets position of a country, as it results from the accumulation of current accounts surpluses or deficits, may translate into pressures on the exchange rate in the event of a sudden reversal of financial flows; these have played an important role historically in the Latin American region.

Information on stocks (of produced fixed assets, including intellectual property assets), flows (investments in gross fixed capital formation, transport infrastructure and R&D), and risk factors that pertain to specific sectors of the economy (such as government and private debt, or the capital adequacy of the banking sector) have implications for the sustainability of the whole economic system. Comparable and detailed indicators pertaining to economic capital stocks, flows and risks are less widely available in Latin America compared with OECD countries. In particular, indicators of the distribution of assets between and within institutional sectors (households, governments, non-financial and financial corporations), which are important for the sustainability of well-being (UNECE, 2013[31]), are not generally available in the LAC region.

The overall picture of economic capital in Latin America is mixed. After the remarkable progress experienced at the turn of the 21st century, economic growth has weakened since 2011 (OECD et al., 2019[32]). Since 2014, the region has experienced the weakest period of growth since 1950, even below the OECD average, with almost no expansion of the economy in 2019 (OECD et al., 2020[33]). The already low potential growth has been explained mainly by employment growth, with little contribution from productivity.14 The competitiveness of most countries in the region reflects ample natural resources and low-skilled labour. This has resulted in a “productivity trap”, a poorly diversified production structure, low value added, and export specialisation in low-technology goods (OECD et al., 2019[32]). While the total value of Produced Fixed Assets in the focal group has increased, the gap with the OECD average value has widened since 2000. Growth in Gross Fixed Capital Formation (GFCF) more than halved in the decade 2009-2019, compared with the 2000-2008 period. In addition, investment in types of economic capital that could contribute to raising productivity and reducing the aforementioned dependence on natural resources and low-skilled labour, such as in Research and Development (R&D) and Transport Infrastructure, remain low. Regarding financial assets, information on the financial net worth of government or on the value of total wealth or total debt at the household level are not available. However, available indicators show that while the ratio of government debt service to GDP has decreased substantially since 2000, government tax revenue still remains low compared with OECD countries, underlining the limited financial resources that governments in the region can mobilise.

Produced fixed assets

Produced fixed assets, such as buildings, machinery, infrastructure and intellectual property assets, shape a country’s capacity to produce goods and services. The average value of the stock of produced fixed assets in the focal countries for which information is available was USD 36 350 per capita in 2018 (Figure 4.7), about one-third of the average level in the OECD (around USD 134 200) – a gap that is broadly in line with that for GNI per capita (see Chapter 2). The stock of produced fixed assets per capita ranges from below USD 20 000 in Colombia to above USD 70 000 in Mexico. Since 2000, this stock increased by 55%, on average, with the strongest gains in the Dominican Republic and Chile (where it has more than doubled) and a drop in Colombia (by 8%). While GDP growth in Latin America and the Caribbean was mainly investment-led between 2000 and 2011, since 2012 it has been led by consumption (private and public in 2012-13, public in 2014-16, and private between 2017 and 2019) (World Bank, 2020[34]; World Bank, 2018[35]; World Bank, 2015[36]).

Note: The latest available year is 2017 for Chile, Colombia and Peru; and 2016 for Costa Rica and the Dominican Republic. LAC 6 excludes Argentina, Brazil, Ecuador, Paraguay and Uruguay. LAC regional average comprises 8 Latin American and Caribbean countries, including the 6 focal countries with available data. OECD 30 excludes Colombia, Iceland, Israel, Mexico, New Zealand, Switzerland and Turkey, due to missing data.

Source: LAKLEMS Crecimiento Económico y Productividad en América Latina 2019 (database), http://www.laklems.net/stats/result.

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Gross fixed capital formation

Gross fixed capital formation refers to the investment in both tangible assets (such as dwellings, buildings and other structures, transport equipment, machinery and equipment, cultivated biological assets, which includes livestock for breeding, dairy, draught, etc., and vineyards, orchards and other trees yielding repeat products whose natural growth and/or regeneration is under the direct control, responsibility and management of institutional units (UNECE et al., 2005[37])) and intangible assets (such as intellectual property, computer software and art works) within a country (OECD, 2020[1]). In 2019, total gross fixed capital formation (GFCF) in Latin America and the Caribbean was around USD 1.1 billion (in 2010 prices), one-tenth of the OECD level (around USD 11 billion), but of similar magnitude when considered as a share of GDP (18% and 21%, respectively). Between 2009 and 2019, GFCF has grown by 17% in Latin America and the Caribbean, below the 31% in OECD countries over the same period. Investment growth between 2009 and 2019 was only one-third of its cumulative growth between 2000 and 2008 (but this was three times more than the OECD over the same 2000 to 2008 period) (Figure 4.8). GFCF is highest in Brazil and Mexico (between USD 0.2 and 0.4 billion), but lowest in Costa Rica, Paraguay, Uruguay (less than USD 0.01 billion). Despite a general slowdown in investment growth between 2009 and 2019 compared to the period 2000-08, GFCF has doubled in the Dominican Republic, where GFCF as a share of GDP has always been among the highest among the focal countries (about 27% in 2019). GFCF growth was more limited among the countries with already high levels of GFCF (i.e. Brazil and Mexico) over the two periods.

Note: : LAC is the regional average for Latin America and the Caribbean as calculated by the World Bank. OECD is the average for the OECD area as calculated by the World Bank. Regions are considered as a single entity, to which each country contributes proportionally to the sum.

Source: World Bank Database, https://data.worldbank.org/indicator/NE.GDI.FTOT.KD?locations=ZJ.

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Investment in transport infrastructure

Transport infrastructure is a produced fixed asset that enables people’s mobility and is crucial to the production and distribution of goods. While there is no internationally agreed definition, the European Commission has taken steps to define transport infrastructure as all routes and fixed installations of transport by rail, road and inland waterways that are necessary for the circulation and safety of traffic (EC Regulation No. 851/2006). Similar regulations or definitions of scope for airport and seaport infrastructure do not exist at international level (ITF, 2013[38]). Comparable data on the stock of transport infrastructure, as well as on its quality, are not widely available for countries in the region, but there is a consensus that transport infrastructure is relatively underdeveloped in Latin America compared to other world regions (Fay et al., 2017[39]; World Economic Forum, 2020[40]). For example, an index of Transport and Tourism Competitiveness developed by the World Economic Forum shows the region scoring about 9% below the global mean on its Infrastructure sub-index (World Economic Forum, 2020[40]). More importantly, the region’s transport infrastructure capacity is judged to be well below its needs, given the importance of tourism to many economies in the region and the need for greater mobility of goods and people to drive economic growth and social development and meet the aspirations of its growing middle class (Fay et al., 2017[39]; World Economic Forum, 2020[40]). It has been estimated that the region faces a transport infrastructure investment gap of more than USD 2.0 trillion in the coming 20 years.15

Building transport infrastructure in Latin America is not straightforward due to a relatively dispersed population and large areas of hard-to-traverse terrain (including mountain ranges and rainforests). The region also has low levels of investment in infrastructure compared to most other developing regions. When taking into account all types of infrastructure (including water and services as well as transport) and both public and private investment, it is estimated that Latin America invests around 3% of GDP on average, well below levels prevailing in developing countries (from 4 to 8%) with the only exception being sub-Saharan Africa.16 Increasing investment alone is not enough; equally important is that spending (particularly of scarce public resources) is well targeted to a country’s needs and that it is efficient (World Economic Forum, 2020[40]).

In the absence of stock measures of transport infrastructure in the region, data on investment levels can provide a sense of the relative priority given to the issue in the different countries. Investment in transport infrastructure comprises capital expenditure on new infrastructure and on the extension of existing infrastructure, including reconstruction, renewal (major substitution work on the existing infrastructure, which does not change its overall performance) and upgrades (major modification work that improves the original performance or capacity of the infrastructure). In the focal countries, investments in transport infrastructure, expressed as a percentage of GDP, fell to 0.92% on average in the period 2014-19, above the OECD average of 0.71% but below the average of 0.97% in the period 2008-13 (Figure 4.9). Peru, Paraguay and Costa Rica are the LAC countries that invested the most in transport infrastructure (more than 1.2% of GDP), more than twice the amounts invested by Brazil (less than 0.2%) and Mexico (0.46%). Compared to 2008-13, investment has more than halved in the Dominican Republic and fell by around one-third in Brazil and Colombia. By contrast, investment increased by a half in Paraguay and by a quarter in Uruguay, compared to 2008-13.

Note: LAC regional average comprises 20 Latin American and Caribbean countries, including the focal countries. OECD Total excludes Chile, Colombia, Ireland, Israel, Korea, the Netherlands and Portugal, as data are not available. Public (at national, regional and local government level, including from State-owned enterprises) investment in transport infrastructure considers capital expenditures (in particular gross fixed capital formation expenditures), measured on an accrual basis whenever possible, on improvement, expansion and replenishment as well as new projects, including pre-investment expenses (such as pre-feasibility and feasibility studies). Data for the OECD refer to total inland infrastructure investment (i.e. investment expenditure on rail, road and inland waterways infrastructure). Data for Latin American countries also include information on investment in air transport and railway transportation rolling stock.

Source: INFRALATAM Database, http://infralatam.info/en/home/ and ITF Transport Infrastructure Performance indicators (database) https://stats.oecd.org/Index.aspx?DataSetCode=ITF_INDICATORS.

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Intellectual property assets: Computer software and databases

Intellectual property assets (a country’s knowledge capital) can improve material living standards in the future through, for example, a more efficient use of resources (productivity gains) or by allowing a country to engage in activities with higher value added. Across the focal countries as a whole, the only comparable data on the stock of intellectual property assets refer to cumulative spending on computer software and databases (thus excluding research and development, mineral exploration and evaluation, entertainment, artistic and literary originals and other intellectual property assets not otherwise specified). In 2018, the per capita value of these assets was USD 170 (Figure 4.10, Panel A), only about 9% of the average level in the OECD average (almost USD 1 900). Spending on these assets was highest in Chile (above USD 600) but much lower in the Dominican Republic, Peru, Colombia and Mexico (below USD 50). Between 2000 and 2018, the average stock of computer software and database assets per capita across the focal countries almost tripled, more than quadrupling in Chile, while falling by about a third in Colombia and by a tenth in the Dominican Republic.

For Costa Rica and Peru only, a fuller picture of intellectual property assets is available, one that includes the value of R&D and other intellectual property assets beyond computer software and databases, as well as spending on mineral exploration and evaluation, entertainment, and artistic and literary originals. When including these additional components, the per capita stock intellectual property assets of Costa Rica and Peru rise to USD 388 and USD 456, respectively, two and nine times higher than when accounting for computer software and databases alone.

Investment in intellectual property assets: Investment in R&D

Investment in research and development (R&D) drives changes in the stock of intellectual property assets.17 Average investment in R&D in the focal countries was 0.43% of GDP in 2018, only one-sixth of the OECD average level (2.56%). Growth in the R&D share since 2000 has been minimal among these countries (0.1 percentage points, Figure 4.10, Panel B), well below gains in the OECD average (0.3 percentage points). With the exception of Brazil, where the growth of investment in R&D reached 1% in 2018, annual investments in the other focal countries ranged from 0.1% to 0.6%.18 Between 2000 and 2018, the share of R&D investment in GDP increased the most in Uruguay (up by 0.3 percentage points, from 0.2% in 2000), while the increase was negligible in Chile, Costa Rica, Mexico and Peru.

When measured by patent applications, in Latin America each percentage point of GDP invested in R&D produces, on average, six new patent applications via the Patent Co-operation Treaty, well below the OECD average of 43 patent applications per each point of GDP invested in R&D (OECD et al., 2019[32]).

Note: In Panel A, LAC 6 excludes Argentina, Brazil, Ecuador, Paraguay and Uruguay, as data are not available. OECD 22 excludes Canada, Chile, Colombia, Finland, Iceland, Ireland, Korea, Luxembourg, Mexico, Poland, the Slovak Republic, Spain, Switzerland, Turkey and the United Kingdom, as data are either not available or incomplete. LAC regional average comprises 8 Latin American and Caribbean countries, including the 6 focal countries with available data. In Panel B, LAC 9 excludes the Dominican Republic and Ecuador, as data are not available. LAC is the Latin America and Caribbean regional average as calculated by the World Bank. Differences in the “propensity to capitalise” expenditures on computer software and databases as well as challenges on the measurement of investment in R&D may play a role in cross-country differences in investment in these intellectual property assets. See discussions in (Ahmad, 2004[41]), (OECD, 2010[42]) and (Eurostat-OECD, 2020[43]).

Source: LAKLEMS Crecimiento Económico y Productividad en América Latina 2019 (database), http://www.laklems.net/stats/result (Panel A) and World Bank Database, https://data.worldbank.org/indicator/GB.XPD.RSDV.GD.ZS (Panel B).

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Debt service as a proportion of exports of goods and services

Debt service (principal and interest payments on public and publicly guaranteed debt), when expressed as a share of exports of goods and services, is a useful measure of the sustainability of public debt particularly in developing countries such as in Latin America19 An increasing debt-to-exports ratio over time, for a given interest rate, implies that debt is growing faster than the economy’s basic source of external income, indicating that the country may have problems meeting its debt obligations in the future (IMF, 2003[44]). In 2018, debt service as a proportion of exports of goods and services was 13% on average in the focal countries and around 11% in the Latin American region (Figure 4.11, Panel A). Debt service was highest in Argentina (33%) and lowest in Paraguay and Peru (below 4%). Compared to 2000, debt service fell by more than 9 percentage points in the focal countries, with the highest drops in Brazil and Peru (by more than 20 percentage points), and small increases in Costa Rica and the Dominican Republic. Debt service as a proportion of exports of goods and services generally decreased from 2000 until 2016, increasing thereafter.

Government tax revenue

Government tax revenues are not “capital” per se, but they are a critical tool to allow governments to deliver a range a public goods and services (with some of these public goods and services contributing to human and social capital). In the focal countries, government tax revenue expressed as a percentage of GDP was 21.4% in 2019, up by 4.1 percentage points relative to 2000 (Figure 4.11, Panel B), but this was still only 60% of the OECD average (33.8%). Tax revenues as a share of GDP range from about 13.5% in the Dominican Republic to 33% in Brazil, very close to the OECD on average. Since 2000, the largest increases occurred in Argentina (9.4 percentage points), Ecuador (8.5 percentage points) and Uruguay (5.8 percentage points), while the lowest rises were in the Dominican Republic and Peru (below 1.5 percentage points). The GDP share among the focal countries is 1.6 percentage points below the regional average for Latin America and the Caribbean, which includes countries with shares of government tax revenue above 23% (Bolivia, Guyana, Jamaica, Nicaragua, Trinidad and Tobago) or even above 30% (Barbados, Belize) and 40% (Cuba).

The tax structure (the composition of tax revenues by different tax types) also informs on the economic and social impact of tax systems in the LAC region. Taxes on goods and services provided the largest share of total tax revenues in the LAC region in 2019, representing half of total taxation on average, compared with around one-third in OECD economies on average. By contrast, the combined share of taxes on income and profits and social security contributions (increasingly private-provided) was much lower in the LAC region than in the OECD. The LAC region is more reliant on revenues from corporate income tax than OECD countries and significantly less reliant on personal income tax (9.1% of the total tax revenues in the LAC region, compared to 23.5% on average in the OECD in 2018). Environmentally related tax revenues amounted to 1.2% of GDP on average in 2019 in the 25 LAC countries for which data is available, below the OECD average of 2.1% (5.7% of total tax revenues in the LAC region compared to 6.4% in the OECD in 2019) (OECD et al., 2021[45]).

Note: In Panel A, LAC is the Latin America and Caribbean regional average as calculated by the UN DESA. In Panel B, LAC is the Latin America and Caribbean regional average as calculated by the OECD, which includes, additionally to the focal countries, Antigua and Barbuda, Bahamas, Barbados, Belize, Bolivia, Cuba, El Salvador, Guatemala, Guyana, Honduras, Jamaica, Nicaragua, Panama, Saint Lucia, Trinidad and Tobago.

Source: UN DESA Global SDG Indicator Database, indicator 17.4.1, https://unstats.un.org/sdgs/indicators/database/ (Panel A) and OECD Revenue Statistics - Latin America and the Caribbean: Comparative tables (database), https://stats.oecd.org/index.aspx?DataSetCode=RSLACT (Panel B).

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Capital adequacy ratio of the banking sector

The capital adequacy ratio helps determine whether the banking sector has enough own capital to cover any losses before becoming insolvent. Monitoring this ratio, and adhering to regulatory requirements to avoid going insolvent, is important to avoid risks that the financial sector may pose to the economic sustainability of a country (International Monetary Fund, 2020[46]). Following the financial crisis of 2008-2009, new international banking regulations were introduced under the Basel III accord setting the minimum requirement of the capital-to-risk weighted assets ratio at 10.5%, which combines with a total capital requirement of 8% and a 2.5% capital conservation buffer (an additional layer of usable capital that can be drawn down when losses are incurred) (Bank for International Settlements, 2019[47]).

In the 10 focal countries for which data are available, the capital adequacy ratio has been fairly stable since the mid-2000s at around 16.6%, which is well above the minimum Basel III requirement. This stability contrasts with the 50% increase in the OECD average over roughly the same period (from 12.7% in 2008 to 19% in 2019, (Figure 4.12). The capital adequacy ratio is highest in Colombia (17.6%), Argentina and Costa Rica (17.5%), although still below the OECD average, and lowest in Chile (12.8%). Regional stability in this ratio since 2005 hides diverging patterns across focal countries, with declines in Paraguay (by almost 3 percentage points) and increases in Costa Rica (by 2 percentage points).

Note: The earliest available year is 2008 for Costa Rica, the Dominican Republic and Uruguay. The latest available year is 2018 for the Dominican Republic and Peru. LAC regional average comprises 13 Latin American and Caribbean countries, including the focal countries. OECD 32 average excludes Denmark, Iceland, Japan, New Zealand and the United States, as data are not available or due to incomplete data. The capital adequacy ratio (or capital-to-risk weighted assets ratio) is a measurement of a bank's available capital expressed as a percentage of a bank's risk-weighted credit exposures. Two types of capital are measured with this indicator: Tier-1 capital can absorb a reasonable amount of loss without forcing the bank to stop its trading, while tier-2 capital can sustain a loss if there's a liquidation. Following the financial crisis of 2008-2009, the international banking regulations introduced under the Basel III accord set the minimum requirement of the capital-to-risk weighted assets ratio at 10.5%, which combines with a total capital requirement of 8% and a 2.5% capital conservation buffer (an additional layer of usable capital that can be drawn down when losses are incurred).

Source: Financial Soundness Indicators (FSI), https://data.imf.org/regular.aspx?key=61404590.

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Beyond avoiding bank insolvency, access to credit and higher liquidity in financial markets are fundamental for the LAC region to escape the “middle-income trap” (i.e. the long-lasting slowdown in the growth of economies that reach middle-income levels). Further financial development in Latin America is necessary to increase investment in certain productive sectors (in particular more knowledge-intensive and technology-intensive) and to promote inclusive growth. It is critical to provide greater access to the banking system for small and medium enterprise (SMEs) and households along with more efficiently regulated financial markets in order to promote inclusive development in the region (Arellano et al., 2018[48]).

The impact of COVID-19 on economic capital

As the COVID-19 pandemic began to impact Latin America and the Caribbean, stringent, multipronged mitigation policies were implemented. Key elements of fiscal stimulus programmes have included direct payments to households, tax relief and deferrals, business lending programmes, and additional health spending. Tax revenues fell precipitously in the first half of 2020 but showed some signs of recovery by year’s end (OECD et al., 2021[45]). Increased public spending has been largely financed by public debt and official lending. The monetary policy response has also been multipronged, including provision of liquidity; temporary loosening of reserve requirements for banks; policy interest rate cuts; foreign exchange market interventions; and, in Chile and Colombia, quantitative easing programmes. Despite these measures, the pandemic has resulted in a 6.9% contraction in GDP in 2020 in Argentina, Brazil and Mexico, the most severe among the six emerging market and developing economy (EMDE) regions identified by the World Bank20 (World Bank, 2021[49]). Fiscal stimulus programmes needed to cushion the economic blow of the pandemic have largely depleted the already limited fiscal space available to the region’s countries. Government debt in the median LAC economy rose from 53% of GDP in 2019 to 69% in 2020 (World Bank, 2021[49]), making Latin America and the Caribbean the most indebted region in the developing world (ECLAC, 2021[50]). High uncertainty and tighter financing conditions during the pandemic have led to delays in infrastructure spending and cuts to research and development, hindering future productivity (World Bank, 2021[49]). To address the region’s development gaps, active fiscal policies, including bolstering progressive taxation, under a well-defined sequence of policies that can be adapted to the different stages of the recovery, supported by a fiscal sustainability framework to finance sustainable development, need to play a key role (particularly in relation to social vulnerability and the productive structure) (OECD et al., 2021[45]; Nieto-Parra, Orozco and Mora, 2021[51]). Failure to pursue policies to boost low productivity, such as investments in new technologies and infrastructure, could dampen and prolong the economic recovery from the pandemic (Beylis et al., 2020[52]).

Issues for statistical development

There is limited availability of indicators of economic capital for Latin America and the Caribbean. Critical information, such as the financial net wealth of the total economy or of general government or the level of household debt, is often missing or incomplete. While some measures of stocks, flows of investments and risk factors have been presented above, country coverage, time series and timeliness are limited. Additionally, the majority of these indicators provide only a high-level perspective on the state of a country’s economic capital. Information on the financial position of different economic sectors (households, general government, financial corporations), as well as information the distribution of assets across different groups, is typically not available. For a more complete picture of the economic resilience and financial stability in the region, a more detailed dashboard of indicators would be needed (Financial Stability Board; International Monetary Fund, 2019[53]).

Human Capital

Human Capital refers to individuals’ health, competencies (including both formal education and tacit knowledge) and skills (OECD, 2015[3]). Health, knowledge and skills have intrinsic value for people’s well-being. Beyond contributing to the creation of other well-being outcomes at a given point in time (OECD, 2020[1]), they also forge people’s future well-being (Exton and Fleischer, forthcoming[54]). While some indicators on the health and skills of the population are described in Chapter 3, the focus of this section is on youths’ skills and health risk/ resilience factors as drivers of future development. Investing in today’s children and youth is the most immediate avenue for assuring the well-being of future generations. Youth’s share of the population in Latin America and the Caribbean (around 160 million young people) will continue to be very substantial in most countries in the coming decades, and these youth face distinctive challenges (ECLAC, 2020[55]).21

Young people’s knowledge and skills

Monitoring the participation of young people in education or employment and their transition from school to work gives a sense of the knowledge and skills that will be available in the future. Young people who are not in employment, education or training are not developing the skills and knowledge needed to ensure their active participation in future society, which would imply a loss of opportunities and resources for future well-being.

The share of youth (people aged 15 to 24) who are not in employment, education or training (NEET) has decreased marginally among the focal countries (to 16% in 2018-19, from 17% in 2008-09) (Figure 4.13, Panel A), i.e. 5 percentage points higher than the OECD average. The decline has not been uniform over time. When looking at the Latin American average, after a drop in 2006-07, which coincided with high GDP growth during the period, the share increased during the 2009 global crisis and, more strongly, around 2014-15, concurrently with a dip in productivity as the boom in commodity prices came to an end. The share of NEET varies widely across the focal 11 countries, from more than 20% in Colombia to 10% in Dominican Republic (below the OECD average of 11%, Figure 4.13, Panel B). Chile experienced the largest drop in the NEET rate (around -7 percentage points in 2019 relatively to 2000), followed by Mexico (around -6 percentage points), while the NEET rate declined only marginally in Argentina, Ecuador and Uruguay (by less than 2 percentage points).

Note: The latest available year is 2018 for Mexico; and 2017 for Chile. The earliest available year is 2001 for Ecuador; 2004 for Peru; 2005 for Paraguay; 2007 for Uruguay and 2014 for the OECD average. Data for Argentina refer to urban areas only. LAC 7 average excludes Brazil, Chile, Costa Rica and the Dominican Republic. LAC is the regional average as calculated by ECLAC. The OECD average excludes Chile, Iceland, Ireland, Japan, Korea, Luxembourg and Switzerland due to incomplete time series. NEET data refer to the percentage of young people aged 15 to 24 not in education or employment or domestic care (or not included in the working-age population). Sourced from household surveys, data have been harmonised by ECLAC to ensure cross-country comparability and then may differ from national estimates. For more information, please refer to https://cepalstat-prod.cepal.org/cepalstat/tabulador/ SisGen_MuestraFicha_puntual.asp?id_aplicacion=1&id_estudio=1&indicador=3469&idioma=i.

Source: ECLAC Statistics, CEPALSTAT database, https://cepalstat-prod.cepal.org/cepalstat/tabulador/ ConsultaIntegrada.asp?idIndicador=3469&idioma=I and OECD calculations based on OECD Transition from school to work (database), https://stats.oecd.org/Index.aspx?DataSetCode=EAG_TRANS..

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The transition of younger people from education to working life is a function of educational opportunities and social and economic contexts. To better grasp the status of young people on the labour market, it is also important to look at the share of youth in vulnerable and informal jobs (ILO, 2015[56]; OECD, 2014[57]; OECD, 2019[58]). As with the NEET rate, the share of youth in informal employment has decreased on average among the focal countries (to 67% in 2019, down by 1 percentage point relative to 2010). This share remains very high in Peru, Ecuador and Paraguay, where more than 80% of employed youth are in informal jobs, compared with a figure of under 40% for Uruguay and Chile. The share of youth in informal employment has increased the most in Ecuador (by almost 11 percentage points), while the largest drops have been registered in Paraguay (by almost 9 percentage points, respectively), Colombia and Peru (by 6 percentage points) (Figure 4.14, Panel A). There is no correlation between the NEET rate and the share of youth in informal employment. Low shares of NEET are associated with relatively high shares of youth in informal employment in Peru, Ecuador and Paraguay, suggesting that informality may act as a stepping stone in the transition from school to work in some countries. On the other hand, in Chile and Uruguay, NEET rates stand close to the regional average and are associated with relatively low shares of youth in informal employment (below 40%). The shares of both NEET and youth in informal employment are above the regional average in Argentina and Colombia (Figure 4.14, Panel B).

Note: In Panel A, the earliest available year is 2011 for Brazil and Colombia; and 2015 for Ecuador. LAC regional average comprises 12 Latin American and Caribbean countries, including the focal countries. In Panel B, NEET data refer to 2019, except for Mexico (2018) and Chile (2017). NEET data refer to the percentage of young people aged 15 to 24 not in education or employment or domestic care (or not included in the working-age population). Sourced from household surveys, data have been harmonised by ECLAC to ensure cross-country comparability and then may differ from national estimates. For more information, please refer to https://cepalstat-prod.cepal.org/cepalstat/tabulador/SisGen_MuestraFicha_puntual.asp?id_aplicacion=1&id_estudio=1&indicador=3469&idioma=i.

Source: ILOSTAT, https://ilostat.ilo.org/data/ and ECLAC Statistics, CEPALSTAT database, https://cepalstat-prod.cepal.org/cepalstat/tabulador/ConsultaIntegrada.asp?idIndicador=3469&idioma=I.

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When considering educational attainment, 70% of young adults (aged 20-24) in the focal countries had completed upper secondary education in 2019, a level almost twice as high as in 2000 (Figure 4.15). The share of young adults with an upper secondary education ranged from just below 60% in Mexico to more than 80% in Chile and Peru. In Uruguay, however, only 4 in 10 young adults have completed upper secondary education. In general, all focal countries for which information is available experienced a strong improvement in youth educational attainment. The improvement was close to 30 percentage points in Ecuador, but only half as large in Argentina and Uruguay (around 13-14 percentage points).

Note: The latest available year is 2017 for Chile; and 2018 for Mexico. The earliest available year is 2001 for Ecuador; 2004 for Peru; 2005 for Paraguay; and 2007 for Uruguay. LAC 7 average excludes Brazil, Colombia, Costa Rica and the Dominican Republic, due to incomplete time series. LAC is the regional average for Latin America and the Caribbean calculated by ECLAC.

Source: ECLAC Statistics, CEPALSTAT database, https://cepalstat-prod.cepal.org/cepalstat/tabulador/ConsultaIntegrada.asp?idIndicador=2119&idioma=i.

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Health risks: Overweight, stunting, smoking and alcohol consumption

Overweight, smoking and alcohol consumption are critical risk factors for future health in Latin America (OECD/The World Bank, 2020[59]). In particular, safe, sufficient nutrition and a balanced diet are necessary for a healthy life (OECD/The World Bank, 2020[59]). Malnutrition can affect health, causing stunting (low height for age) or wasting (recent and severe weight loss) when nutrition is insufficient and unbalanced, or overweight and obesity when it is excessive and unbalanced.

Stunting rates in Latin America are generally lower than in East and Southeast Asia, Central Asia, North Africa-Middle East and sub-Saharan Africa and have decreased over time. One in ten children below age five are stunted in the focal countries (Figure 4.16, Panel A), ranging from below 2% in Chile to almost 13% in Colombia. On average, stunting rates have almost halved since 2000, with the highest drops registered in Paraguay and Peru (by more than 10 percentage points) and the lowest in Argentina and Chile (by 1 percentage point or less), where stunting rates were already below the regional average.

Note: The latest available year is 2018 for Peru, and 2016 for Colombia, Mexico, Paraguay. The earliest available year is 2005 for Argentina and Paraguay, and 2006 for Mexico. The LAC 9 average excludes Brazil, Chile, Costa Rica, the Dominican Republic, Ecuador and Uruguay. LAC is the Latin America and Caribbean regional average calculated by the UN DESA. In Panel B, obesity data refer to 2016.

Source: UN DESA Global SDG Indicator Database, indicator 2.2.1, https://unstats.un.org/sdgs/indicators/database/ and WHO GHO (database), https://www.who.int/data/gho/data/indicators/indicator-details/GHO/prevalence-of-obesity-among-adults-bmi-=-30-(age-standardized-estimate)-(-)

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Overweight is one of the most relevant risk factors for health in Latin America (OECD/The World Bank, 2020[59]). 60% of the population are overweight and 25% are obese in these countries, slightly above the OECD average of 58% and 23%, respectively (Figure 4.17). The problem is especially severe in Mexico, where almost 65% of the population are overweight and 30% are obese (the highest rates in the region), but less so in Paraguay (where 54% of the population are overweight), and in Ecuador and Peru (where about 20% of the population are obese). While increasing overweight and obesity are global phenomena, they have become more common in countries that have recently experienced rapid urbanisation and a shift from protein-rich diets to diets rich in fat and sugar. The prevalence of overweight and obesity has increased in Latin American countries since 2000 (by 10 and 8 percentage points) at a faster pace than in the OECD area (7 and 6 percentage point respectively), especially obesity.22

Note: Data come from health examinations. LAC regional average comprises 33 Latin American and Caribbean countries, including the focal countries.

Source: WHO GHO (database), https://www.who.int/data/gho/data/indicators/indicator-details/GHO/prevalence-of-overweight-among-adults-bmi-=-25-(age-standardized-estimate)-(-) and https://www.who.int/data/gho/data/indicators/indicator-details/GHO/prevalence-of-obesity-among-adults-bmi-=-30-(age-standardized-estimate)-(-).

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The two phenomena (stunting among the very young and overweight among adults) are not unrelated. In the focal countries for which data are available, high stunting rates are associated with low adult obesity rates in Colombia and Peru. Argentina and Mexico feature close to average stunting rates and relatively high adult obesity rates, while Paraguay combines low stunting among children and low obesity rates among adults (Figure 4.16, Panel B). The relationship between undernutrition and overweight is not a coexistence of unrelated phenomena, as undernutrition early in life – and even in utero – may predispose to overweight and non-communicable diseases such as diabetes and heart disease later in life. Overweight in mothers is also associated with overweight and obesity of their offspring (WHO, 2017[60]). Additionally, declining stunting rates among children and rising adult overweight in Latin America and the Caribbean also reflect the shift to more calorie-rich diets and a general rise in the availability of food.

Tobacco use is the second-leading risk factor for early death and disability worldwide, after poor diet23 (OECD/The World Bank, 2020[59]). Close to one in six people aged 15 or above in the focal group of countries smoked daily in 2018. This share almost halved since 2000, reaching a level that is now well below the OECD average (one in four people). The proportion of daily tobacco smokers varies considerably across countries, ranging from 45% of people who smoke daily in Chile to below 10% in Colombia and the Dominican Republic (Figure 4.18, Panel A). The greatest falls in smoking since 2000 were experienced in Argentina and Peru, where the share of tobacco smokers dropped by more than 24 percentage points.

Compared to the OECD average, Latin America also features lower average rates of alcohol consumption (at 5.5 litres per capita in 2018, almost half the 9 litres per capita among OECD countries), partly reflecting Latin Americans’ lower per capita income (WHO, 2018[61]). Alcohol consumption is lowest in Ecuador (just above 3 litres per capita) and highest in Argentina (more than 8 litres per capita) (Figure 4.18, Panel B). The average of the focal countries has fluctuated between 5.4 and 5.8 litres per capita in the period 2000-18, stabilising at 5.5 in the last three years. Alcohol consumption has decreased by around 1 litre per capita in Brazil, the Dominican Republic, Ecuador, Mexico and Uruguay in this period, while it increased by 1.6 litre per capita (26%) in Chile.

Note: LAC 10 excludes Ecuador, due to missing data. In Panel A, LAC is the Latin America and Caribbean regional average calculated by the UN DESA. In Panel B, LAC regional average comprises 33 Latin American and Caribbean countries, including the focal countries.

Source: UN DESA Global SDG Indicator Database, indicator 3.a.1, https://unstats.un.org/sdgs/indicators/database/ and WHO GHO (database), https://www.who.int/data/gho/data/indicators/indicator-details/GHO/alcohol-recorded-per-capita-(15-)-consumption-(in-litres-of-pure-alcohol)

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The impact of COVID-19 on human capital

The impact of COVID-19 on human capital, via its effect on educational and health outcomes, is considerable. The relevant sections in Chapter 3 (Knowledge and Skills, and Health) address these in more detail. These effects also have long-term impacts. It has been estimated that the losses in learning, human capital and productivity may translate into a decline in aggregate earnings for the Latin American and Caribbean region of USD 1.7 trillion, 10% of baseline levels (World Bank, 2021[62]).

The impact of the COVID-19 crisis has been particularly hard on youth employed, who are over-represented in the sectors worst hit by the pandemic, such as retail, hospitality and tourism, and who are already facing difficulties in accessing the formal labour market. LAC countries need to prioritise support for job searching and job counselling, as well as training and apprenticeship programmes that enable capacity-building for the young and help match them with evolving employment opportunities (OECD, 2020[63]).

With lockdowns and school closures, activities have been performed remotely whenever possible. However, despite considerable improvements in recent years, insufficient skills and disparities in Internet access and use across socio-economic groups persist, with COVID-19 widening these disparities. For instance, fewer than half of Latin Americans had enough experience using computers and digital tools to carry out basic professional tasks, effectively excluding more than half of the region’s population from performing remote activities (OECD et al., 2020[33]).

Available evidence indicates that a significant share of adults gained weight during lockdown periods, although this was not the case for everyone, with one study showing that older adults (aged over 60) were at a higher risk of weight loss and potential malnutrition.24 Because of higher body weight, the lockdowns implemented during the COVID-19 pandemic may lead to higher incidence of overweight, obesity and related health-risks as well as other non-communicable diseases. Further studies are needed to assess group-specific impacts, with particular regard to weight gain in younger people and the risk of weight loss, malnutrition and sarcopenia in older adults.

Health risks among the population today may be heightening the human cost of the pandemic: for example, overweight and obese populations could have a higher susceptibility to develop severe complications, especially linked to respiratory illness, such as pneumonia. Obesity has a negative effect on both the respiratory function and the immune function, which are under threat with COVID-19. Adipose tissue dysfunction in overweight and obesity can act as a diseased organ (through chronic inflammation) (Rancourt, Schellong and Plagemann, 2020[64]). In one study of French patients admitted to intensive care units (ICU) for COVID-19 and requiring invasive mechanical ventilation (IMV), the proportion of obese patients was higher than among the population at large,25 with higher rates of patients needing IMV among men with a high body mass index (BMI) (Simonnet et al., 2020[65]). A meta-analysis of obesity and COVID-19 outcomes on PubMed (including MEDLINE) and Google Scholar in May 2020 suggests that obesity is associated with a more severe COVID-19 disease but not with higher mortality (Zhang et al., 2021[66]).

In addition to obesity, underweight is also a risk factor for COVID-19 (Gaiha, Cheng and Halpern-Felsher, 2020[67]), as people who are underweight have poor dynamic lung functions (Azad and Zamani, 2014[68]).According to clinical evidence, tobacco smokers have a greater predisposition (1.4-fold) to developing severe symptoms of COVID-19, and are approximately 2.4 times more likely to be admitted to an intensive care unit (ICU), to need mechanical ventilation or to die compared to non-smokers (Vardavas and Nikitara, 2020[69]). Findings from a US national sample of adolescents and young adults show that e-cigarette use and dual use of e-cigarettes and regular cigarettes are significant underlying risk factors for COVID-19 (Gaiha, Cheng and Halpern-Felsher, 2020[67]). Much is still unknown on how the severity of respiratory viral infections is compounded when risk factors are combined.

Issues for statistical development

Data on education and stunting are scattered, in terms of country and time coverage. Regarding alcohol consumption, the methodology to convert alcoholic drinks to pure alcohol may differ across countries. Moreover, data refer to annual estimates of alcoholic beverage production and trade supplied by national Ministries of Agriculture and Trade to the Food and Agriculture Organization of the United Nations (FAO) (i.e. recorded alcohol), and exclude homemade sources, cross-border shopping and other unrecorded sources (OECD/The World Bank, 2020[59]). The share of youth (aged 15-24) not in employment, education or training (NEET) is not a perfect measure of the underutilisation of skills, as some young people are informally employed or unpaid workers (e.g. volunteering their time in the community or as family caregivers).

Social Capital

Social Capital broadly refers to the networks, norms, trust and shared values that foster co-operation within and between different population groups in a society (OECD, 2020[1]). The literature on Social Capital is wide-ranging, encompassing people’s personal relationships (people’s networks and the social behaviours that contribute to establishing and maintaining those), social support (the emotional, material, practical, financial, intellectual and professional resources that are available to individuals through their personal networks), civic engagement (the activities through which people contribute to civic and community life) as well as trust and co-operative norms (shared values and expectations that underpin societal functioning and enable mutually beneficial co-operation) (Scrivens and Smith, 2013[70]). The two types of trust that are most important for social capital are generalised interpersonal trust (i.e. trust in “others”, including strangers) and institutional trust (i.e. trust in public institutions).

The OECD well-being framework, and this report, distinguishes between social assets that are fostered and “owned” at the individual level (such as personal relationships and social network support) and relational public goods that are available to and shared by society as a whole and can be transmitted across generations (trust and co-operative norms). The former are included in Chapter 3 under the Social Connections dimension, while the latter are the focus of this section.

Trust and co-operative norms have strong and wide-ranging instrumental value and contribute to the functioning of societal systems – market, state infrastructure, social stability – that are essential for many aspects of well-being (OECD, 2017[71]). Norms, values and expectations that encourage co-operation such as solidarity, honesty, generosity, kindness, politeness, equity, social justice or tolerance can generate a range of benefits to the society, from higher productivity to better well-being outcomes. Other norms and expectations, such as corruption or discrimination, will have the opposite effect (Scrivens and Smith, 2013[70]). This section presents information on volunteering, interpersonal trust, institutional trust, perception of corruption in national government, support for democracy, tax morale (willingness to pay taxes), perceptions of discrimination and income inequality.

Overall, on a number of indicators, the focal countries (and Latin America as a whole) show signs of weakening social capital, from an already low starting point. Volunteering rates, trust in government, support for democracy and tax morale are all down from the 2000s, while people’s perceptions of corruption in government have increased. In other indicators, such as interpersonal trust, confidence in police, and the share of people saying they belong to a discriminated group, stability in the focal group or the regional average masks widening differences between countries. The only indicator that shows a clear (but moderate) improvement is the share of people saying that income inequality is unfair. The indicators pertaining to confidence in political systems and institutions are particularly worrying. The social uprisings in Bolivia, Chile, Colombia and Ecuador in 2019 were a stark manifestation of reduced trust in government, which risks being compounded by the COVID-19 crisis.

Volunteering

Volunteering refers to the provision of time and unpaid labour to people outside the immediate household. It can be formal (when undertaken within an established organisation or group) or informal (when provided in an unstructured way, outside the context of formal organisations or groups) (Scrivens and Smith, 2013[70]). Harmonised data on volunteering for Latin American countries are available only for formal volunteering provided through organisations.

In 2017-19, around one in six people in the focal countries volunteered time to an organisation in the past month, close to the OECD average (Figure 4.19). This share ranges from around 14% in Chile and Mexico to around 20% in Paraguay and Peru, and up to 30% in the Dominican Republic. Formal volunteering across the region has slightly decreased (by 1.4 percentage points in the focal countries) since 2006-09, mirroring developments in OECD countries, with the highest drops in Colombia and Costa Rica (by more than 4 percentage points) and modest increases in some other countries (i.e. 1 percentage point in Uruguay and 0.6 percentage point in the Dominican Republic).

Note: This is based on the question, “Have you done any of the following in the past month? How about volunteered your time to an organisation?” The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no” and “don’t know”) and are averaged over a four (2006-09) and three (2017-19) year period. LAC regional average comprises 23 Latin American and Caribbean countries, including the focal countries.

Source: OECD calculations based on the Gallup World Poll (database), https://gallup.com/analytics/232838/world-poll.aspx.

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Trust in others

Trust in others is the foundation of co-operation (Scrivens and Smith, 2013[70]). It refers to people’s perceptions and expectations that others will behave in a trustworthy manner. While most of the available measures on trust are based on people’s self-reports, evidence shows that these measures are significantly correlated to the trustworthiness of people’s behaviour in semi-experimental settings.26

In the focal countries, only 14% of people report that most people can be trusted (Figure 4.20). Trust in others is particularly low in Brazil, where only 4% of people report that most people can be trusted, while in Colombia and Uruguay the percentage is five times higher. Compared to 2000, Mexico experienced the largest cumulative drop (-16 percentage points), although remaining relatively high, followed by Costa Rica and Uruguay (-3 percentage points). On the other side of the spectrum, the largest cumulative increase occurred in Argentina (7 percentage points), followed by Colombia (5 percentage points). Additional data from the World Values Survey (not shown) available for seven of the focal countries and for 30 OECD countries indicate that OECD average trust in others is around four times higher in OECD countries than among the focal group (around 38% and 9%, respectively) (World Values Survey, 2021[72]).

Note: This is based on the question, “Generally speaking, would you say that you can trust most people, or that you can never be too careful in dealing with others?” with response categories “most people can be trusted”, “one can never be too careful when dealing with others” and “don't know”. LAC 10 excludes the Dominican Republic, due to incomplete time series. In Panel A, LAC regional average comprises 17 Latin American and Caribbean countries, including the 10 focal countries for which time series are available. In Panel B, LAC regional average comprises 18 Latin American and Caribbean countries, including the focal countries. The earliest available year is 2004 for the Dominican Republic.

Source: Latinobarometro (database), http://www.latinobarometro.org/latOnline.jsp.

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Trust in institutions: Government and police

Trust in institutions is an important aspect of public governance, affecting people’s willingness to co-operate with public institutions in the pursuit of the common good (Praia Group on Governance Statistics, 2020[73]). Trust in institutions is also affected by people’s perceptions of a number of other dimensions of governance (such as quality of services and integrity of public officials), hence it has a claim to be used as a measure that “takes the temperature” of the overall relation between citizens and policy makers.

One-third of the population in the focal countries trusts their national government (Figure 4.21, Panel A), 10 percentage points less than in 2006-09, and well below the OECD average (45%). Trust in government is lowest in Brazil and Peru, where less than one in four people trust the national government, and highest in the Dominican Republic, Ecuador and Uruguay, where more than 40% of the population trust the national government. Trust in the national government has halved in Brazil, Chile and Colombia since 2006-09. Conversely, trust in national government increased the most (by 4.5 percentage points) in Peru.

Half of the population in the focal countries trusts the local police, 5 percent points higher than in 2006-09 (Figure 4.21, Panel B). Trust in the police is highest in Ecuador and Uruguay, where about 60% of the population trust the police, and lowest in Mexico, where less than 40% of the population do. Compared to 2006-09, trust in the police has increased the most in Ecuador, Costa Rica and Paraguay (by 10 percentage points or more), while the highest drop (by 7.5 percentage points) occurred in Mexico, which fell from just below the regional average to the bottom of the league.

Note: LAC regional average comprises 21 Latin American and Caribbean countries, including the focal countries. In Panel A, this is based on the survey question, “In this country, do you have confidence in each of the following, or not? How about national government?” The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no” and “don’t know”) and are averaged over a four (2006-09) and three (2017-19) year period. In Panel B, this is based on the survey question, “In the city or area where you live, do you have confidence in the local police force or not?” The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no” and “don’t know”) and are averaged over a four (2006-09) and three (2017-19) year period.

Source: OECD calculations based on the Gallup World Poll (database), https://gallup.com/analytics/232838/world-poll.aspx

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Corruption

Integrity is a cornerstone of good governance and assures citizens that the government is working in the interests of all, rather than for a few (OECD, 2020[74]). Measuring corruption is challenging, and available indicators, mainly from expert assessments or household surveys, tend to focus on different aspects of it. While each measure, taken in isolation, may provide a partial but potentially distorted view of the issue at hand, using multiple measures of corruption in combination allows to understand its different facets (Exton and Fleischer, forthcoming[54]).

In the focal countries, 76% of people think that corruption is widespread throughout their national government (Figure 4.22, Panel A); this share increased by 5 percentage points compared to 2006-09 and is well above levels observed across OECD countries (55%). People’s own perceptions of corruption in the government are the highest in Paraguay (87%), Colombia and Paraguay (all above 80%) and lowest in Uruguay where (at 55%) it is in line with the OECD average.

Household survey measures of corruption capture only petty corruption and fail to reveal aspects of corruption that are less visible to households, such as political corruption, lobbying or manipulation of the political process by special interest groups (UNODC, 2018[75]). Information on these aspects can be gathered through measures based on expert assessments, which nevertheless have their own biases. When considering the assessments of experts and business people in Transparency International’s 2019 Corruption Perception Index, the average level of corruption in the public sector among the focal countries was 43, on a scale from 0 (highly corrupt) to 100 (the total absence of corruption), which is below the OECD average level of 67 (Figure 4.22, Panel B). This implies higher corruption among the focal group. By this measure, perceived public sector integrity is highest in Chile and Uruguay (with scores in line with the OECD average or just above) and lowest in the Dominican Republic, Mexico and Paraguay (with scores below 30). The Transparency International regional average has remained stable since 2012, with progress in Argentina and Ecuador (with gains of 10 and 6 points, respectively) and declines in Brazil (a fall of 8 points), followed by Chile and Mexico (5 points).

Note: In Panel A, LAC regional average comprises 21 Latin American and Caribbean countries, including the focal countries. It is based on the question, “Is corruption widespread throughout the government in this country, or not?” The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no” and “don’t know”) and are averaged over a four (2006-09) and three (2017-19) year period. In Panel B, LAC regional average comprises 27 Latin American and Caribbean countries, including the focal countries. Transparency International’s annual Corruption Perception Index (CPI) ranks countries based on how corrupt a country’s public sector is perceived to be by experts and business executives. The CPI is a composite index that combines information from 13 surveys and expert assessments from 12 independent institutions specialising in governance and business climate analysis to arrive at a score from 0 (highly corrupt) to 100 (very clean).

Source: OECD calculations based on the Gallup World Poll (database), https://gallup.com/analytics/232838/world-poll.aspx (Panel A) and on Transparency International Corruption Perception Index 2020 (database), https://transparency.org/cpi2020 (Panel B)

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Support for democracy and tax morale

Electoral democracy is a relatively recent phenomenon for many Latin American countries. The legacy of past autocratic regimes, military coups and foreign interference still linger in public opinion, where just below half (49%) of the population in the focal countries support democracy over all other forms of governance, down by 10 percentage points from 2000 (Figure 4.23, Panel A). Support for democracy is lowest in Brazil and Mexico (below 40%) and highest in Costa Rica and Uruguay (above 60%). In recent years, support for democracy decreased the most in the Dominican Republic, Peru and Uruguay (by more than 20 percentage points). Among all other focal countries, it increased only in Chile and Colombia (by 4 percentage points).

Across Latin American countries, support for democracy strongly correlates with measures of government integrity: correlation with the Corruption Perception Index is 0.80 (Figure 4.23, Panel B). Both measures are comparatively high in Chile, Costa Rica and Uruguay, while they are much lower in Brazil, Mexico and Paraguay. Support for democracy also tends to go hand in hand with trust in the police, while the relation with trust in national governments is not statistically significant.27

Note: This is based on the question, “With which of the following statements do you agree most?” with response categories “democracy is preferable to any other kind of government”, “under some circumstances, an authoritarian government can be preferable to a democratic one”, “for people like me, it does not matter whether we have a democratic or a non-democratic regime” and “don’t know”. The data shown reflect the percentage of respondents answering “democracy is preferable to any other kind of government”. LAC regional average comprises 18 Latin American and Caribbean countries, including the focal countries. The earliest available year is 2004 for the Dominican Republic. In Panel B, data refer to 2018 for support for democracy and to 2019 for the Corruption Perception Index. The Corruption Perception Index (CPI) is a composite index that combines information from 13 surveys and expert assessments from 12 independent institutions specialising in governance and business climate analysis to arrive at a score from 0 (highly corrupt) to 100 (very clean).

Source: Latinobarometro (database), http://www.latinobarometro.org/latOnline.jsp and Transparency International Corruption Perception Index 2020 (database), https://transparency.org/cpi2020

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As with support for democracy, less than half (45%) of the population in the focal countries agree with the statement that it is never justifiable to avoid paying all one’s taxes, down from 65% in 2003 (Figure 4.24, Panel A). Aversion towards complete tax avoidance is highest in Argentina and Uruguay (above 55%) and lowest in Mexico, Paraguay and Peru (below 40%). Compared to 2003, the only improvement occurred in the Dominican Republic (16 percentage points) while the largest falls occurred in Costa Rica, Mexico (‑30 percentage points) and Paraguay (-51 percentage points). Aversion towards complete tax avoidance is strongly correlated with support for democracy (0.69) (Figure 4.24, Panel B), trust in the police (0.65) and government integrity (CPI) (0.64). This is in line with previous studies (OECD, 2019[76]) which also link decreasing tax morale (defined as the intrinsic motivation to pay taxes) with the economic slowdown, rising poverty and inequality and social discontent in Latin America.

Note: This is based on the question, “On a scale of 1 to 10, where 1 means ‘not at all justifiable’ and 10 means ‘totally justifiable’, how justifiable do you believe it is to evade paying taxes?”. The data shown reflect the percentage of respondents answering “not at all justifiable”. LAC regional average comprises 18 Latin American and Caribbean countries, including the focal countries. The earliest available year is 2005 for the Dominican Republic. In Panel B, aversion towards total tax avoidance data refer to 2016 and support for democracy data to 2018. Support for democracy is based on the question, “With which of the following statements do you agree most?” with response categories “democracy is preferable to any other kind of government”, “under some circumstances, an authoritarian government can be preferable to a democratic one”, “for people like me, it does not matter whether we have a democratic or a non-democratic regime” and “don’t know”. The data shown reflect the percentage of respondents answering “democracy is preferable to any other kind of government”.

Source: Latinobarometro (database), http://www.latinobarometro.org/latOnline.jsp.

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Perception of discrimination and unjust inequality

Norms of tolerance and non-discrimination towards people and groups from different backgrounds, appearance or beliefs are essential for fair and inclusive co-operation (Scrivens and Smith, 2013[70]). They also represent critical elements of social capital.

The share of people who declare they belong to a discriminated group in the focal countries stands at 17%, a proportion that is little changed from its 2006 level (Figure 4.25). This share ranges from below 10% in Colombia and Ecuador to almost 30% in Chile. Across the focal countries, average perception of discrimination increased in 2010 and 2011 but reverted to earlier (2006 and 2009) levels in 2015. Compared to 2006, Brazil registered the highest drop (-23 percentage points), although perceptions of discrimination remain among the highest in the region, followed by drops in Colombia and Ecuador, where perception of discrimination is among the lowest. Chile (with the highest perceptions of discrimination) as well as Costa Rica and Argentina registered the strongest increases (10, 9 and 7 percentage points respectively).

Note: This is based on the question, “Would you describe yourself as part of a group that is discriminated against in (country)?” The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no” and “don’t know”). LAC regional average comprises 18 Latin American and Caribbean countries, including the focal countries.

Source: ECLAC Statistics, CEPALSTAT database, https://cepalstat-prod.cepal.org/cepalstat/tabulador/ ConsultaIntegrada.asp?idIndicador=2258&idioma=i.

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Feelings of discrimination on grounds that are beyond an individual’s control translate into dissatisfaction with income inequality: 81% of Latin American respondents report that income distribution is unfair or very unfair, down from 86% in 2001 (Figure 4.26, Panel A). This measure is highest in Brazil and Chile (around 90%) and lowest in Ecuador (below 70%), where it dropped by more than 20 percentage points from 2001, the highest drop in the region. Perceptions of income inequality as unjust dropped by more than 10 percentage points in Paraguay and Uruguay, but increased by 7 and 8 percentage points in Brazil and the Dominican Republic, respectively. Perceptions of discrimination and income inequality significantly correlate (Figure 4.26, Panel B), with both measures particularly high in Chile and Brazil, and relatively low in Ecuador and Uruguay.

Note: This is based on the question, “How fair do you think income distribution is in (country)?” with response categories “very fair”, “fair”, “unfair”, “very unfair” and “don‘t know”. The data shown reflect the percentage of people who replied “unfair” or “very unfair”. LAC regional average comprises 18 Latin American and Caribbean countries, including the focal countries. The earliest available year is 2007 for the Dominican Republic. In Panel B, perception of discrimination refers to 2015 and perception of unfair income inequality to 2018. Perception of discrimination is based on the question, “Would you describe yourself as part of a group that is discriminated against in (country)?”. The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no”, and “don’t know”).

Source: Latinobarometro (database), http://www.latinobarometro.org/latOnline.jsp and ECLAC Statistics, CEPALSTAT database, https://cepalstat-prod.cepal.org/cepalstat/tabulador/ConsultaIntegrada.asp?idIndicador=2258&idioma=i.

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The impact of COVID-19 on social capital

Effectively responding to the coronavirus (COVID-19) pandemic requires co-ordinated action and citizens’ willingness to comply with restrictions and to make necessary behavioural changes on behalf of the public good. The low levels of social capital evidenced by many indicators in this section suggest that the social contract between government and citizens in the region is fragile: prior to the pandemic, there was considerable dissatisfaction with persistent inequalities and with the functioning of the political system, growing distrust of institutions, and low and declining support for democracy (Zechmeister, 2019[77]; ECLAC, 2021[78]). The demand for greater equality and non-discrimination has led, in some cases, to social mobilisations and protests that called for substantive transformations to build fairer and more inclusive societies28 (ECLAC, 2021[78]).

The expansion of the middle-income strata and the consolidation of a citizenry that is more demanding of spaces for participation and less tolerant of inequalities and corruption contributed to these mobilisations and protests. Throughout the region, citizens are increasingly questioning the discrimination and inequality that permeate institutions and social relations. These features are crystallised in a culture of privilege whose roots go back to the continent’s colonial origins, a culture that justifies deep socio-economic, gender, ethnic and racial inequalities (ECLAC, 2021[78]; OECD, forthcoming[79]).

The trend in the region towards reduced support for democracy is particularly worrying. A United Nations policy brief (UN, 2020[80]) set out three ways in which the pandemic is threatening democracy in the region. First, by increasing inequality and further exacerbating the differences in well-being outcomes between social groups, strengthening the perception that democratic governments have not responded adequately to the needs of the most vulnerable. Second, in some cases, emergency measures taken to restrict social interaction may have infringed human rights, by reducing the ability of civil society actors to mobilise and hold governments accountable. They may also have created an opportunity for illegitimate actors (such as armed groups and criminal organisations) to reassert control over territories. Third, the release of large amounts of public funds to undertake action to combat the virus, often in a less than transparent manner, has led to an increase in allegations of corruption and misuse of funds, which is likely to further erode trust in democratic governments.

Perceptions of the performance of the region’s governments during the pandemic vary widely. Results from an opinion poll collecting responses from 371 opinion leaders and prominent journalists who regularly publish their views in the Latin American media reveal that, between April and August 2020, opinion leaders’ approval of the way the government was handling the COVID-19 crisis generally declined in almost all the Latin American countries for which data are available. The largest drop occurred in Peru: from 91% of respondents approving in April 2020 to 23% in August 2020. Mexico is the only country where the opinion leaders’ approval increased: from 7% in April 2020 to a still low 28% in August 2020. Approval was highest in Argentina and Colombia (above 70%), while lowest in Brazil (17%), the country registering the highest number of COVID-19 deaths (ECLAC, 2021[78]).

While there was no statistically significant change between the 2019 Corruption Perception index (CPI) and the 2020 CPI, evidence from the Gallup World Poll, mainly referring to the period between late August 2020 and November-December 2020, shows a general increase in trust in the national government (up by 5 percentage points from 2019) and a drop in perceptions of corruption (down by almost the same amount) across the focal countries (Figure 4.27, Panel A and B), which mirrors developments in the OECD countries.

In 2020, trust in the national government and perception of corruption were strongly correlated (-0.92) (Figure 4.27, Panel C). Trust in the national government is lowest where perception of corruption is highest: in particular, in Peru, fewer than 1 in 5 people trust the government, and more than 90% of the population think that corruption is widespread throughout the government. Conversely, trust in the national government is highest where perception of corruption is the lowest: in the Dominican Republic and Uruguay more than 60% of the population trust the government and less than 55% think that corruption is widespread throughout the government.

The increase in trust in institutions, also observed in OECD countries, carries many elements of a “rallying round the flag” effect, which refers to national unity in the face of common threats. This effect is characterised by temporary surges in public approval for nation states’ governments or political leaders during periods of crisis or war (OECD, 2021[81]).

The mild average increase in trust in the local police across the focal countries (by 3 percentage points) hides diverging patterns (Figure 4.27, Panel D). Trust in the police increased the most in Costa Rica (by 13 percentage points), Uruguay (by 9 percentage points) and Chile (by 7.3 percentage points), while it dropped in Paraguay (7 percentage points).

Note: Trust/confidence in the government is based on the survey question, “In this country, do you have confidence in each of the following, or not? How about national government?”. The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no”, and “don’t know”). Perception of corruption in the government is based on the question “Is corruption widespread throughout the government in this country, or not?”. The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no”, and “don’t know”). Trust in the police is based on the survey question, “In the city or area where you live, do you have confidence in the local police force, or not?”. The data shown reflect the percentage of respondents answering “yes” (the other response categories being “no”, and “don’t know”). LAC regional average comprises 21 Latin American and Caribbean countries, including the focal countries. OECD 35 excludes the Czech Republic and Luxembourg, due to incomplete data. In all the countries of the focal group, the mode of data collection changed between 2019 and 2020 (moving from face-to-face to phone-based interviews). As a result, certain countries may have modified the respondent pool in certain ways that cannot be adjusted via weighting techniques (Srinivasan and Clifton, 2020[82]; Helliwell et al., 2021[83]). More than 500 observations are available for each country. Data collection dates for 2020 are as follows: Sep 7 – Nov 20, 2020 in Argentina; Sep 10 – Nov 11, 2020 in Brazil; Sep 11 – Nov 16, 2020 in Chile; Aug 21 – Oct 27, 2020 in Colombia; Sept 15, 2020 – Jan 4, 2021 in Costa Rica; Sep 24 – Oct 23, 2020 in the Dominican Republic; Aug 26 – Oct 23, 2020 in Ecuador; Sep 08 – Nov 18, 2020 in Mexico; Nov 28 - Dec 28, 2020 in Paraguay; Oct 29, 2020 – Jan 6, 2021 in Peru; and Sep 24 – Nov 30, 2020 in Uruguay.

Source: OECD calculations based on the Gallup World Poll (database), https://gallup.com/analytics/232838/world-poll.aspx.

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Issues for statistical development

Harmonised data on volunteering for Latin American countries are available only for formal volunteering provided through organisations. This means that informal forms are completely neglected. Additionally, no information is available on the amount of time spent on volunteering or its frequency. Data on interpersonal trust are available, but the question wording is not aligned with the recommendations of the OECD Guidelines on Measuring Trust (OECD, 2017[71]). According to the Guidelines, an ideal data set to measure institutional trust should consider, in addition to trust in the political system (i.e. the government, political parties, parliament) and in the judicial system (i.e. the police, military, courts), trust in non-political institutions (i.e. the civil service). Information on this dimension of institutional trust is currently missing for Latin American and Caribbean countries.

Data on corruption are gathered through expert assessments or household surveys focusing on corruption perceptions or experiences of bribery. Household surveys are biased towards petty corruption and miss some less visible aspects, such as revolving doors and undue lobbying, while expert assessments lack transparency and ignore the perspective of citizens (Exton and Fleischer, forthcoming[54]). The United Nations Praia City Group recommends relying on multiple measures of corruption to understand its different facets (Praia Group on Governance Statistics, 2020[73]).

It is only recently that data on norms, values and expectations have been collected more frequently in the region. Country coverage is still limited (to 17 countries, for most indicators), and in some cases timeliness needs to be urgently improved (i.e. the latest available year refers to 4 or 5 years ago).

Even though measuring non-discrimination has been recognised as a fundamental principle and norm in international law on human rights, achieving this is still challenging. One difficulty is that discrimination is seldom directly observable. This has led to the use of different methodologies for its measurement. One is the self-reporting of experiences of discrimination captured through surveys, which has the advantage of approximating the prevalence of discrimination in society with acceptable validity levels, and it allows identifying the groups who feel most affected by discrimination (ECLAC, 2021[84]). The United Nations monitors progress in the achievement of SDG Goal 10.3 through a measure of the proportion of adults who report having personally experienced discrimination or abuse in the past 12 months.

Currently, most National Statistical Offices (NSOs) in Latin America and the Caribbean do not collect the necessary information to produce indicators based on self-reported experiences of discrimination. The webinars organised by the OECD, ECLAC and the European Commission29 in September 2020 compared experiences on the most appropriate modalities to measure discrimination through surveys, stressing the importance of implementing short modules in the multipurpose household surveys carried out by the region’s NSOs.

The recommendations made by the UN Office of the High Commissioner for Human Rights (OHCHR) and the experiences accumulated in academic research, in public opinion studies and in the surveys carried out by some countries in the region are important inputs to advance the measurement of discrimination. Discrimination does not manifest itself in the same way in all contexts, so it is inevitable that differences in measurement exist, but this should not prevent the production of an indicator built on the basis of comparable questions. The paucity of countries collecting this type of information indicates that there is an opportunity to generate dialogue that would allow reaching consensus on a harmonised regional measure (ECLAC, 2021[84]).

Finally, it is also critical that NSOs advance in the production of data that allow disaggregating measures of discrimination by some attributes that allow to adequately identify groups especially vulnerable to discrimination, such as indigenous peoples and Afro-descendants, people with disabilities, migrants and other minorities, as well as the settings in which discrimination occurs. While information on discrimination has increased over time, there is still much room for improvement (ECLAC, 2021[84]).

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Notes

← 1. While these four capitals are discussed mainly at country level, it should be noted that they are systemic by definition, with implications beyond a country’s boundaries (e.g. biodiversity, climate change). Multilateral agreements and international regulations also play an important role in preserving these four types of globally interconnected capital.

← 2. These results are consistent with SDG Indicator 15.3.1 (“Proportion of land that is degraded over total land area”). The indicators of natural land cover and land change have been preferred for the higher cross-country comparability, transparency of construction, and longer and more updated time series.

← 3. Throughout this report, the eleven focal countries refer to Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Mexico, Paraguay, Peru and Uruguay.

← 4. Afforestation is the action of planting trees on an area of land in order to make a forest. Reforestation is the act of planting trees on an area of land that has become empty or spoiled.

← 5. A protected area is “a clearly defined geographical space, recognised, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values” (IUCN Definition 2008).

← 6. The indicators of terrestrial and marine protected areas do not answer important and policy-relevant questions such as the extent to which protected areas are protecting national or global biodiversity (as protected areas are not necessarily sited optimally with respect to biodiversity conservation objectives) or whether protected areas are effectively managed or enforced.

← 7. The Aichi Biodiversity Targets are a set of 20 global targets defined under the “Strategic Plan for Biodiversity 2011-2020”, adopted at the tenth meeting of the Conference of the Parties (COP 10) held in Nagoya, Aichi Prefecture, Japan, from 18 to 29 October 2010. The Conference of Parties, known as COP, is the decision-making body responsible for monitoring and reviewing the implementation of the United Nations Framework Convention on Climate Change. It brings together the 197 nations and territories – called Parties – that have signed the Framework Convention.

← 8. These indicators inform on coverage, but not on effectiveness, equitability, representativity and connectivity, which are also referenced in the Target.

← 9. https://unfccc.int/kyoto_protocol

← 10. Sunk costs are investments that were made in the past and are no longer considered for accounting purposes, but which were essential expenses for current profitability.

← 11. https://www.cbd.int/sp/targets/rationale/target-11/

← 12. Aichi Biodiversity Target 11 states that, “By 2020, at least 17 per cent of terrestrial and inland water, and 10 per cent of coastal and marine areas, especially areas of particular importance for biodiversity and ecosystem services, are conserved through effectively and equitably managed, ecologically representative and well connected systems of protected areas and other effective area-based conservation measures, and integrated into the wider landscapes and seascapes.”

← 13. For example, this was recognised during the Latin America and the Caribbean Climate week 2021 (LACCW21), virtually hosted by the Government of the Dominican Republic in May 2021 (UNFCCC, 2021[88]). This event, co-organised by the UN Climate Change, the United Nations Development Programme (UNDP), the United Nations Environment Programme (UNEP), the World Bank Group (WB), together with regional partners including the Economic Commission for Latin America and the Caribbean (UNECLAC), the CAF–Development Bank of Latin America and the Inter-American Development Bank (IDB), aimed to boost the region’s response to climate change and build regional momentum ahead of the UN Climate Change Conference COP26 in November 2021 in Glasgow (UNFCCC, 2021[89]).

← 14. On average, over the last two decades, 76% of GDP growth was accounted for by employment (as opposed to productivity), compared with 54% in Europe, 36% in the United States and 4% in China (OECD et al., 2020[33]).

← 15. Based on the sum of airport, port, rail and road investment needs for Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Paraguay, Peru and Uruguay as calculated in the Global Infrastructure Hub’s Global Infrastructure Outlook in February 2020 (World Economic Forum, 2020[40]).

← 16. The estimated share of GDP (in %) spent on all infrastructure and through both public and private investment is East Asia and the Pacific (7.7), Central Asia (4.0), Latin America and the Caribbean (2.8), Middle East and North Africa (6.9), South Asia (5.0) and sub-Saharan Africa (1.9) (Fay et al., 2017[39]).

← 17. Estimates of the resources allocated to R&D, available from the World Bank, are affected by national characteristics (periodicity and coverage of national R&D surveys across institutional sectors and industries, use of different sampling and estimation methods). They may differ from National Accounts data, due in part to the different treatments of software R&D in the totals.

← 18. These levels are well below the regional average for Latin America and the Caribbean (0.71%). The latter measure is population-weighted and, as such, gives more weight to Brazil, which is the best performer in the region.

← 19. This measure is one of the IAEG indicators (17.4.1) used to monitor countries’ performance on SDG target 17.4: “Assist developing countries in attaining long-term debt sustainability through co-ordinated policies aimed at fostering debt financing, debt relief and debt restructuring, as appropriate, and address the external debt of highly indebted poor countries to reduce debt distress.”

← 20. The six emerging market and developing economies as identified by the World Bank are the following: East Asia and Pacific (which includes China, Indonesia and Thailand), Europe and Central Asia (which includes Poland, the Russian Federation and Turkey), Latin America and the Caribbean (which includes Argentina, Brazil and Mexico), Middle East and North Africa (which includes Egypt, Iran and Saudi Arabia), South Asia (which includes Bangladesh, India and Pakistan) and sub-Saharan Africa (which includes Angola, Nigeria and South Africa).

← 21. As noted by ECLAC (2020): “The youth population needs a higher level of education, relevant training and better preparation for lifelong learning. In addition to persistent structural divides, inequalities in capacity-building and the sphere of work, which affect the young particularly, will need to be addressed if progress is to be made along the path of sustainability with equality.”

← 22. The WHO define overweight and obesity for adults on the basis of the Body Mass Index (BMI). BMI is a single number that evaluates an individual’s weight in relation to height and is defined as weight in kilograms divided by the square of height in metres. Adults who have a BMI between 25 and 30 are considered overweight. Adults with a BMI of 30 or over are defined as obese.

← 23. Poor diet is defined as a cluster of 14 risk factors comprised of low fruit, nuts, and seeds; high sodium; low vegetables; high processed meat; and other elements (OECD/The World Bank, 2020[59])

← 24. A combined systematic review and a meta-analysis conducted in PubMed®, Scopus®, Web of Science® and EMBASE® databases and 36 observational (35 cross-sectional and one cohort) studies to assess the impact of the first lockdown period (March-May 2020) on body weight and on body mass index (BMI) in both adults and adolescents (>16 years old) revealed that body weight increased in a significant portion of the individuals (11.1-72.4%), although a range of 7.2-51.4% of individuals reported weight loss (Bakaloudi et al., 2021[86]). A significantly higher body weight was observed with a weighted mean between-group difference (WMD) in the post-lockdown period compared to the before-lockdown period. At variance with general trends, one study in older adults (>60 years old) notably reported a significant body weight loss, suggesting a higher risk for lockdown-induced weight loss and potentially malnutrition in the elderly population.

← 25. While the results may not be generalisable to other centres in France or in other countries, depending on the criteria implemented for the indication of IMV in other centres, another study from Lyon University Hospital in France tended to confirm the observation from Lille University Centre of a higher requirement for IMV in severe obesity (BMI ≥ 35) compared with lean patients (Caussy et al., 2020[85]).

← 26. For example, (Knack and Keefer, 1997[87]) refer to the high correlation between levels of trust from the World Values Survey and people returning wallets that had been left on the street as part of an experiment to measure people’s trustworthiness.

← 27. Correlations with people’s own perceptions of corruption in the government are not statistically significant.

← 28. For example, although the immediate trigger for Chile’s October 2019 protests was an increase in public transport costs, a number of mobilisations seeking to improve the population’s quality of life had taken place since 2006. In Ecuador, demonstrations were triggered by discontent arising from the elimination of fuel subsidies, one of the measures taken by the government to reduce the fiscal deficit in order to secure a loan from the International Monetary Fund (IMF) and pay off the country’s external debt. With austerity policies already prompting high levels of public dissatisfaction, the protests were framed by discontent arising from the perception that the government was backtracking on the delivery of social and economic guarantees. After a political agreement was reached to overturn the elimination of the fuel subsidies and to establish mechanisms that would target resources at the neediest sectors, the protests calmed down. They began anew, however, following the adoption of the Organic Law on Humanitarian Support to Combat the Health Crisis arising from COVID-19, which contained a string of new austerity policies, and following the announcement that eight public companies were to be closed (ECLAC, 2021[78]).

← 29. https://www.cepal.org/es/eventos/webinar-la-medicion-la-discriminacion-cuestiones-metodologicas-programa-estadistico-cara-al

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