1. How’s Life in Latin America? Introduction and key findings
The gains in well-being in countries in the LAC region between 2000 and 2019 were considerable. However, the pace of progress has slowed considerably since the mid-2010s. Further, many of the natural, human, social and economic capital resources that underpin the sustainability of well-being were already under threat or in decline before the pandemic, and structural problems such as high levels of informality and inequalities persisted to 2019. The COVID-19 pandemic risks reversing many of the well-being gains achieved in recent decades, as well as deepening pre-existing challenges. A well-being approach to policy would support LAC countries in addressing the highly interconnected societal challenges they face, but mainstreaming a well-being approach in Latin America will require broad public and political support, as well as institutional mechanisms that anchor well-being priorities into long-term government operations. Improvements in data on all policy-relevant aspects of well-being are also needed.
How’s Life in Latin America? Measuring well-being for policy making is a joint report produced by the OECD Centre on Well-being, Inclusion, Sustainability and Equal Opportunity (WISE) and the OECD Development Centre (DEV). It represents the culmination of a three-year collaborative project between the OECD, the UN Economic Commission for Latin America and the Caribbean (ECLAC) and the European Commission to identify comparable well-being indicators for the Latin American and Caribbean (LAC) region (see Box 1.1). Since the project began in 2018, the region has experienced extraordinary upheaval: first the wave of social protests beginning in late 2019, swiftly followed by the onset of the COVID-19 pandemic in early 2020 with its subsequent unprecedented socio-economic impacts, affecting the well-being of the most vulnerable populations in particular. Describing well-being developments in the region during this period has been akin to chasing a moving target, with impacts unfolding in real time. However, if anything, these developments that were unforeseen at the start of the project have further underlined the need for a broader view of progress that puts people’s well-being at the centre in order to “build forward better”.
The purpose of this report is threefold. First, it aims to promote a better understanding of well-being outcomes in Latin America by presenting results across a range of dimensions that matter for people’s lives today and into the future. Over four chapters, the report explores indicators of material conditions, quality of life, resources for future well-being and experiences for different population groups. While the LAC average is included for most indicators, the report focuses in particular on eleven Latin American countries – Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Mexico, Paraguay, Peru and Uruguay – which were selected due to their status as high-income and upper-middle-income countries in the context of the EU Facility for Development in Transition as well as, in many cases, their expression of interest and commitment to this project (see Box 1.1). Second, it contributes to the objective of enhancing well-being measurement in the region, by identifying key areas for improvement in data collection and coverage: for each well-being dimension or population group covered, a special section highlights the key issues for statistical development in order to obtain a better pulse of the state of the region. Third, it makes the case that, for well-being measures to be used in policy decision-making, just producing more and better statistics is not enough: institutional, analytical and operational innovation in the way governments approach policy making is also needed. The final chapter of the report addresses this topic in detail, building on previous work looking at the policy use of well-being frameworks in OECD countries, to explore the challenges and achievements in implementing a well-being approach to policy in the LAC region.
This report is the final output of the project Metrics for Policies for Well-being and Sustainable Development in Latin America and the Caribbean, led by the OECD Centre for Well-being, Inclusion, Sustainability and Equal Opportunity (WISE) and the OECD Development Centre, in collaboration with the UN Economic Commission for Latin America and the Caribbean (ECLAC) and the European Commission. The project is part of the European Union Facility for Development in Transition, a regional instrument to support the design and implementation of policies to achieve the Sustainable Development Goals (SDGs) in the LAC region.
The concept of “development in transition” refers to countries that are achieving higher income levels but continue to deal with structural challenges (or “development traps”) related to issues such as inequalities, mobilisation of domestic resources, weak social frameworks, sub-national disparities, limited capacities for innovation and low economic diversification (OECD et al., 2019[1]). See Chapter 6 for a more detailed description of the specific development traps that exist in the LAC region. At the international level, one of the consequences for countries transitioning to higher levels of Gross National Income (GNI) per capita is that they are no longer eligible for Official Development Assistance (ODA), entailing the loss of an important source of external financial support, even as they continue to face complex development challenges. In this context, the Metrics for Policies for Sustainable Development in Latin America and the Caribbean project focuses on the need for broader measures of development, looking beyond income, to inform domestic policies and international co-operation. While the hope is that the measures used in the report could be relevant across the whole region, the data in the descriptive chapters of the report (Chapters 1 to 5) focus on the aforementioned 11 high- and upper-middle-income countries: Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Mexico, Paraguay, Peru and Uruguay.
The overarching aim of the project has been to support the development and use of relevant well-being metrics in policy making for achieving sustainable development in the LAC region. This is both a statistical and a policy task. Over three years, the project has provided multiple platforms for international dialogue between policy agencies and between statisticians and policy makers. Numerous physical and virtual events have fostered the exchange of knowledge and experiences across a regional network of experts during the project, including:
“Metrics that Make a Difference: The Policy Uses of Well-being and Sustainable Development Indicators in Latin America and the Caribbean”, an international conference held in Bogotá in October 2019 (OECD, 2019[2]). More than 50 speakers and 200 participants participated in the conference over two days, showcasing different perspectives and experiences on the policy use of well-being indicators through a technical workshop (Day 1) and a high-level event (Day 2), opened by President Duque of Colombia. The event was co-organised in association with Colombia’s National Statistical Department (DANE), the National Planning Ministry (DNP) and the Universidad del Rosario.
“Towards a Comprehensive Measurement of Well-being”, a series of expert lectures in June-July 2020. Over the course of six online events, this series attracted an international audience for discussion on key topics including experiences in multidimensional survey design, the use of administrative records, and improving the measurement of income inequality. The series, which was co-organised with the Mexican national statistical office, INEGI, also helped to inform the deliberations of the Mexican expert group designing a new national well-being survey.
“Measuring people’s perceptions, evaluations and experiences: Key issues and best practice from Latin America and the world”, a webinar series in September-October 2020. Co-organised with ECLAC’s Statistics Division, these four webinars responded to an emerging interest in the region in the measurement of a range of subjective aspects of people’s life (their perceptions of country-wide developments, their evaluations of key aspects of their life, and their personal experiences in a wide range of fields), and covered methodology for collecting data on subjective well-being, trust and discrimination, as well as exploring country experiences. As a follow-up to these webinars, steps have been taken by the ECLAC Statistical Division to establish a dedicated Working Group (in the context of the Statistical Conference of the Americas) to explore ways to improve the comparative measurement of these aspects across the LAC region.
“Putting well-being at the heart of policymaking in LAC”, which was part of the Development in Transition webinar series held on 7 July 2021. This webinar was a space to present and discuss country experiences in the policy uses of multidimensional tools and well-being frameworks in LAC countries. Its objective was to share the main lessons and current challenges in policy making to achieve an impact on the well-being of citizens in the context of the COVID-19 pandemic. The Development in Transition Days on Latin America & the Caribbean, organised in the framework of the EU Facility on Development in Transition with key stakeholders in the region, was an opportunity to take stock of valuable experiences and ideas for a sustainable and inclusive post-crisis recovery in the LAC.
Measuring well-being means taking a multidimensional and people-focused approach to assessing national developments, rather than focusing uniquely on indicators of economic growth. For many decades, metrics such as Gross National Income (GNI) and Gross Domestic Product (GDP) have acted as proxies for countries’ development levels. This focus on macro-economic indicators has been based, to a large extent, on the assumption that increases in national income (or productivity) lead automatically to improvements in broader social outcomes. However, it is increasingly being recognised that the relationship between economic growth, on one side, and inclusive and sustainable development, on the other, is more complex and that a broader information set is needed to provide a fuller picture.
Efforts to go “beyond GDP” are not generally targeted at replacing GDP with a different single measure, but rather at complementing it with various additional metrics in order to make up for what GDP misses, and what it over-emphasises.1 As argued by Joseph Stiglitz, Jean-Paul Fitoussi and Martine Durand, “what we measure affects what we do. If we measure the wrong thing, we will do the wrong thing. If we don’t measure something, it becomes neglected, as if the problem didn’t exist” (Stiglitz, Fitoussi and Durand, 2018[3]). Since improving people’s well-being in an equitable and sustainable manner is widely recognised as a core objective for policy (one that lies at the heart of the SDGs, to which all UN Member States are signatories), then this implies that a broader set of indicators is needed to assess whether policies are contributing to that end.
The notion that broader perspectives on national progress and development need to look beyond GDP, beyond averages, and beyond individuals and firms is far from being a new idea. Over the last decade and a half in particular, a number of initiatives have helped to give greater visibility to this need to measure well-being and the stocks of resources that underpin it, including in particular greater attention to natural, social and human capital and their roles in sustaining well-being over time and for future generations. The recommendations of the Commission on the Measurement of Economic Performance and Social Progress (set up in 2008, and commonly known as the “Stiglitz-Sen-Fitoussi” report after its chairs, Joseph Stiglitz, Amartya Sen and Jean-Paul Fitoussi) were particularly influential in this regard, setting out a roadmap for necessary statistical development to gain a better picture of people’s lives and the drivers of sustainability (Stiglitz, Sen and Fitoussi, 2009[4]). The OECD has also long stressed the need to broaden the scope of indicators used to assess societal progress beyond traditional macro-economic indicators, and in 2011 it launched its Better Life Initiative to promote the measurement of well-being and to put the notion at the core of policy making. This Initiative encompasses a range of outputs, from the regular publication of How’s Life? (OECD, 2020[5]) to the Better Life Index interactive online tool (http://www.oecdbetterlifeindex.org/), and numerous other reports, methodological guidelines, working papers and articles. At the European level, in September 2009 the European Commission issued a communication on “GDP and beyond”, identifying key actions to improve metrics of progress (European Commission, 2009[6]), and since then European institutions have continued to innovate and reflect on the best way to incorporate a more people-focused perspective into measurement and policy at the regional level (Council of the European Union, 2021[7]; Council of the European Union, 2019[8]).
Many countries around the world have already made efforts to establish multidimensional well-being measurement frameworks with this view in mind. Over half of OECD countries have developed some form of national well-being indicator dashboard, including France, New Zealand, Italy, Israel, the Netherlands, the United Kingdom, Slovenia and Norway (OECD, 2019[9]). LAC countries (including both OECD and non-OECD member countries) have also been pioneering work on well-being measurement for some years now. Concepts such as “Vivir Bien” in Bolivia and “Buen Vivir” in Ecuador embody the principle of sustainable and equitable well-being for all people, and these have been used to inform data collection and policy action. Chile, Colombia, Mexico and many other countries in the region are pushing the boundaries in the development of multidimensional measurement tools encompassing issues such as subjective well-being, crime and safety, quality of life, and other aspects of people’s well-being (see Chapter 6 for details).
The UN 2030 Agenda for Sustainable Development also embodies this paradigm shift, recognising the well-being of people and the planet as the ultimate objectives of development. The 2030 Agenda spans 17 inter-related Sustainable Development Goals (SDGs) and 169 targets, with 231 unique indicators agreed by the international statistical community to monitor progress. The sheer number of indicators exemplifies a key tension when moving “beyond GDP”, i.e. how to balance ease of communication (necessitating a smaller number of indicators, or even a single composite index) with completeness of information (requiring a larger set of indicators). Both aspects are important and, ultimately, the appropriate scope and range of a well-being indicator set will depend on its intended purpose. A review of well-being dashboards developed in 28 OECD countries made a broad distinction between frameworks focused on the measurement, monitoring and reporting of well-being (often, but not always, led by national statistical offices – NSOs) and those developed to support policy applications (often led by treasuries or other departments in the centre of government) (OECD, 2019[9]). Generally speaking, monitoring dashboards tend to be larger (ranging up to 147 indicators in the case of Measures of Australia’s Progress), while policy-oriented dashboards tend to be smaller, with the majority of cases numbering 5-15 indicators (OECD, 2019[9]).
The dashboard presented in this report favours completeness over brevity, presenting 107 indicators to support the measurement and reporting of well-being in the LAC region. However, the policy relevance of the indicators has been an important criterion for selecting indicators (see the later section on the indicator selection process). The hope is that the findings presented in the report will lay the groundwork for the more political process of selecting a more limited indicator set to support policy dialogue among countries in the region and development partners. A preliminary list of 30 candidate headline concepts and accompanying indicators is included in Annex 1.A of this chapter, and these indicators have provided the focus of the online country notes accompanying the report.
The description and analysis in this report are underpinned by the OECD framework, which has been guiding measurement and research on well-being both inside and outside the Organisation for the past decade. This framework conceives of well-being in terms of eleven dimensions of current well-being and four types of resources for future well-being (human, natural, economic and social capital) (Figure 1.1). Reflecting earlier work on the meaning of development and deliberations on the nature of human well-being,2 the OECD framework has four distinctive characteristics:
First, it focuses on people (i.e. individuals and households), their situation and how they relate to others in the community where they live and work. Focusing on people, rather than on the economic system, is important since there are often differences between the economy-wide assessment of a country and the well-being experiences of its inhabitants.
Second, it concentrates on both current well-being outcomes and the resources underpinning well-being in the future. Focusing on outcomes in current well-being (e.g. students’ performance), as opposed to inputs (e.g. educational expenditures) or outputs (e.g. students graduating), is important because outcomes provide direct information on people’s lives.
Third, it considers the distribution of well-being in the population alongside average achievements; this allows the exploration of inequalities across different well-being dimensions, as well as by age, gender, socio-economic status and other characteristics.
Lastly, it looks at both objective and subjective aspects of well-being, because personal experiences and people’s assessments of their life circumstances provide important information alongside objective measures of these circumstances.
Source: OECD (2020[5]), How's Life? 2020: Measuring Well-being, OECD Publishing, Paris, https://doi.org/10.1787/9870c393-en.
The OECD framework does not embody a definitive expression of the “good life”, as what matters the most to people will vary across individuals and national settings, depending on circumstance, culture and many other factors. However, it provides a comprehensive list of “ingredients” for inclusive and sustainable well-being.3 The framework aims to provide a structure for operationalising the notion of well-being in different contexts.4 In this perspective, the framework provided a starting point for identifying a set of comparable indicators for measuring well-being in the LAC region.
Both conceptual and pragmatic considerations played a part when adapting the framework to reflect priorities in the region. In the first instance, it was important to examine whether the OECD framework ignored issues of special importance to Latin Americans or, conversely, over-emphasised topics of less relevance in the region. A number of methods and sources were employed to evaluate the necessary components of a well-being framework for the LAC region, including:
The results of a 2016 consultation with national statistical offices (NSOs) in the LAC region,5 as well as further exchanges with regional NSOs and the Statistics Division of ECLAC.
The content of national development plans and other strategic policy documents, as well as multidimensional measurement frameworks, produced by countries in the region.
Two key documents of an exercise conducted by the Statistical Coordination Group of the Statistical Conference of the Americas of ECLAC.
First, an aspirational proposal for a regional SDG indicator framework comprising 307 indicators, of which 143 were from the UN global indicator framework, 135 were proposed complementary indicators and 29 were new proposed proxy indicators (ECLAC, 2017[10]).
Second, the final report of the prioritisation exercise, which presented the indicators retained from the proposal after extensive discussion amongst members of the Statistical Coordination Group. This report included 154 indicators, of which 120 are from the UN global indicator framework, 30 are complementary indicators and 4 are proxy indicators (ECLAC, 2019[11]).
These documents were important resources, as together they gave a broad overview of the issues needing to be considered for the monitoring of sustainable development, from the perspective of regional measurement experts.
Finally, a number of face-to-face and virtual events through the course of the project (see Box 1.1) provided the opportunity for knowledge sharing and discussion with a wide range of experts on what matters most for measuring well-being for policies in Latin America and the Caribbean.
This research and consultation established that, at the dimension level, the OECD framework adequately encompassed the range of issues seen as important for well-being in the region. However, it also showed that the expression of the dimensions, in terms of the key concepts to emphasise and the resulting selection of indicators, needed to diverge from the OECD approach in some areas. Specifically, while all concepts covered in How’s Life? (OECD, 2020[5]) (the point of reference for the operationalisation of the well-being framework for OECD countries) were also relevant for well-being in LAC countries, a number of issues of great significance for the LAC region were excluded or given less emphasis than necessary. Table 1.1 summarises the key concepts covered in the OECD How’s Life? framework, as well as the additional issues of relevance identified for the LAC region. Not all of these concepts were included in the final dashboard underpinning this report due to data constraints (as discussed in the following section), but the inventory provided an aspirational guide for what would ideally be included in a detailed list of well-being metrics for the region.
Table 1.1 does not include every LAC-specific notion that was identified by the research, but rather focuses on the ones that were highlighted by multiple sources as being relevant in the region. One group of issues omitted in the current version, but that could be considered for inclusion in future versions of the framework, relates to cultural beliefs and practices, which are especially important for Indigenous communities and where data availability also remains a challenge.
After the establishment of the conceptual framework, the next step was to review available data sources to select the most appropriate indicators to populate the dashboard. Guiding the indicator selection was a set of standardised criteria, based on the quality assessment criteria used in the first edition of How’s Life? in 2011 (OECD, 2011[12]), and further refined through a 2019 quality review of the OECD How’s Life? indicator set (Exton and Fleischer, forthcoming[13]). Table 1.2 presents the different criteria (relevance, availability of population breakdowns to compute inequality measures, accuracy, credibility and comparability, timeliness and frequency, interpretability, and working constraints) and explains the key aspects considered for each category.
Together, the quality criteria in Table 1.1 describe the ideal characteristics of a well-being metric, but even in the OECD How’s Life? dashboard, not every indicator fully meets every one of these criteria. For this report, a more pragmatic approach was considered. While all quality aspects were considered important, the following issues were prioritised:
Relevance: the value of the indicator for measuring and monitoring well-being had to be clear, with a high degree of policy relevance, and pertain to either households or individuals (for current well-being) or to the different types of resources relevant for future well-being.
Interpretability: the meaning of the indicator had to be obvious, and a change in the indicator must be unambiguously good or bad.
Timeliness: wherever possible, data should be based on recurrent data collections, with annual time series going back to at least 2000. Wherever possible, data with no more than a two-year lag in data publication were prioritised.
Credibility and comparability: as far as possible, data were sourced only from official statistics based on comparable definitions, or, when these were not available, from well-established instruments. Indicators that allowed for a direct comparison with the OECD average were favoured, in general.
Working constraints: indicators with data coverage for the eleven focal countries (Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Mexico, Paraguay, Peru and Uruguay) were prioritised; as a general rule, an indicator needed to have time-series data for at least seven of the eleven countries to be included.
However, as the purpose of this project was also to give greater visibility to issues that are not generally considered in benchmarking exercises, a number of exceptions to these rules were allowed. In these instances, “next-best” indicators were used as placeholders where the importance of the concept was seen to override the need to fulfil all the quality criteria. For example, in the case of income and consumption, where comparable household-level data are lacking in the region, two indicators derived from national accounts (Gross National Income per capita, and Household Final Consumption Expenditure) have been used as proxies of the measure of Household Disposable Income per capita included in How’s Life? In other cases, data with less-than-ideal timeliness, comparability and country coverage have been used to give an indication of the situation and also to highlight the need for better data in these areas. However, even with this more flexible approach, some important areas for well-being in the LAC region (such as household wealth and wealth inequality, or time use activities beyond paid and unpaid work) lack comparable data. Each section of Chapters 2 to 4 of this report (for each dimension of the framework) and Chapter 5 (for each type of group inequality considered) ends with a discussion of the “Issues for statistical development” in order to improve well-being measurement in the different areas.
A particular mention should be made about the use of Gallup World Poll and Latinobarómetro data for a range of subjective measures in the report. Wherever possible, data have been sourced from international organisations that themselves collect data from NSOs and then harmonise the measures ex post to provide more comparable results. However, although an increasing number of NSOs in the region are collecting subjective indicators across a range of topics, the availability of comparable data is still not sufficient to allow for compiling indicators based on official sources. In these cases, as was done in the past in the OECD How’s Life? series, alternative (yet still high-quality) sources have been used. Both Gallup and Latinobarómetro are well-established polling bodies, with national results based on comparable questions and national sample sizes of at least 1 000 observations.
Finally, an over-arching consideration through the indicator selection process was to use indicators from the SDG indicator framework as much as possible. The following section compares the SDG framework and the OECD well-being framework, explaining the degree of relevance of the indicators used in this report to the SDG framework.
The OECD well-being framework and the UN Sustainable Development Goals have much in common in terms of content and intent, with a shared aim of improving people’s lives across key social, environmental and economic domains. Indeed, all SDGs apart from the process-oriented Goal 17 are represented in the well-being framework (see Figure 1.2). However, there are also important differences. The OECD well-being approach is intended to be a diagnostic, analytic and policy actionable tool, built on a clear conceptual framework. The SDG Agenda, on the other hand, is a series of political and aspirational commitments. The 2030 Agenda emphasises that all targets matter, and that, to be successful, countries should meet all goals and targets. But countries do need to be able to understand how best to sequence policies, which requires a conceptual approach that can help prioritise actions and identify trade-offs and synergies. In this sense, the two approaches are complementary: viewing the SDGs through the lens of well-being can help countries in identifying the most relevant indicators for monitoring progress towards sustainable development.
As far as possible, the indicators used to populate the well-being framework for the LAC region were selected with reference to the SDG indicator framework, taking into account both the official SDG Global Framework (as developed by the United Nations Inter-Agency and Expert Group on SDG Indicators, IAEG-SDGs) (UN Statistics, 2021[14]) and the complementary and proxy SDG indicators for the LAC region identified by the Statistical Coordination Group of the Statistical Conference of the Americas of ECLAC (ECLAC, 2019[11]).
Figure 1.3 sets out the degree of relevance to the SDG indicator framework for the different indicators included in this report. Overall, 37 out of the 107 indicators (just over one-third) have been taken directly from the SDG Global Framework list, and an additional 9 from the prioritised list of SDG indicators for the LAC region. An additional 56 indicators (over half of the set), while being in neither the Global Framework nor the prioritised LAC list, are considered as being directly relevant to an SDG target. For example, the S80/S20 inter-quintile ratio (Chapter 1) and the Gini coefficient of labour income (Chapter 2) have both been included as giving summary information on income and wage inequality respectively, which informs SDG target 10.4 to “Adopt policies, especially fiscal, wage and social protection policies, and progressively achieve greater equality”. Similarly, in the Social Capital dimension, a range of mainly subjective indicators have been used to capture concepts that are relevant to targets 16.5 (“Substantially reduce corruption and bribery in all their forms”), 16.6 (“Develop effective, accountable and transparent institutions at all levels”) and 16.7 (“Ensure responsive, inclusive, participatory and representative decision-making at all levels”). In some cases, the indicators used were the closest available proxies for Global Framework indicators. For example, in the absence of adequate country coverage for data on indicator 10.3.1, the Latinobarómetro data on the share of the population who report belonging to a group that experienced discrimination were used.6
Note: The numbers in parentheses in the labels denote the number of indicators in each dimension. SDG Global Framework refers to the official list of indicators as developed by the United Nations Inter-Agency and Expert Group on SDG Indicators (IAEG-SDGs) (UN Statistics, 2021[14]). SDG LAC refers to the complementary and proxy SDG indicators for the LAC region identified by the Statistical Coordination Group of the Statistical Conference of the Americas of ECLAC (2019[11]). ‘Directly/ not directly related to a target’ refer to the official list of SDG targets (UN Statistics, 2021[14]).
In most cases, the reason for the use of an alternative or complementary indicator rather than one taken from the Global Framework or prioritised LAC list stemmed from one of three considerations. First, the need to focus on summary outcome measures with an unambiguous interpretation. As mentioned already, many SDG indicators are oriented at policies or processes rather than at outcomes. They also often focus on narrow policy issues, rather than emphasising high-level outcomes. Key metrics for monitoring overall societal well-being, such as life expectancy or electoral participation, are not included in the SDG indicator lists, while they are included here. Second, the OECD well-being measurement approach (along with many others) emphasises the value of subjective measures alongside objective measures, while very few subjective measures are included in the SDG indicator lists. Third, despite ongoing progress since 2015, data of sufficient quality, coverage and comparability do not yet exist for all SDG indicators; in these cases, it was necessary to look for the closest alternative indicators available.
Finally, five out of the 107 indicators featuring in this report cannot be linked directly to an SDG target. This applies specifically to all indicators of Social Connections (the share of people reporting they have someone to count on in a time of need) and Subjective Well-being (self-reported life satisfaction, negative affect balance, the share of people with low life satisfaction) and to one indicator of Social Capital (the share of people volunteering). This is a reflection of the conceptual differences between the two frameworks: despite the great degree of overlap, the dimensions considered of importance to inclusive and sustainable well-being are not exactly the same in both. Nonetheless, while not specifically mentioned in any targets, strong social relationships, high levels of subjective well-being, and active civic participation are all aspects of the people-focused sustainable development targets set out in the SDGs.
High-quality, comprehensive and multidimensional indicator frameworks are essential for gaining a more nuanced understanding of the development challenges faced by different countries. . However, producing more and better data on well-being and sustainability is not enough to ensure that these metrics are then used in decision-making, which is the ultimate purpose of this endeavour. For governments to move towards a well-being policy approach, institutional, analytical, and operational innovations are needed alongside statistical improvements. Beyond the statistical review presented in this report, an equally important aspect of the research was to explore how well-being frameworks could be used throughout the policy cycle in the LAC region, building on the experience accumulated in other OECD countries, which is the subject of Chapter 6.
A well-being approach to policy uses well-being evidence in an integrated way throughout the policy cycle – from the agenda-setting stage (through development planning) to policy formulation and budgeting, implementation, monitoring and evaluation – to work towards a more comprehensive, long-term and holistic vision of development. It would firmly focus government action on what matters the most to people and society, rather than on a single (or very narrow range of) objective(s), such as GDP growth. An increasing number of governments around the world are incorporating elements of such an approach (whether or not they use a specific “well-being” label), in recognition of the fact that dealing with today’s major challenges requires moving beyond traditional, short-term and silo-oriented ways of thinking and acting.
Chapter 6 presents knowledge and experience on the policy use of well-being frameworks in LAC countries and other OECD countries. It identifies a range of key lessons for informing national policy and international co-operation:
Taking a multidimensional perspective can support LAC countries in addressing the highly interconnected societal challenges they face, which have been further aggravated by the COVID-19 crisis. By supporting whole-of-government efforts, and focusing governments’ attention on areas of greatest need, multidimensional well-being frameworks can strengthen the effectiveness and efficiency of policy-making processes. During post-COVID recovery, more than ever, LAC governments are called upon to devise policy responses to the crisis that assess and address the multidimensionality of people's well-being.
A well-being approach to policy can guide the process of building forward better in the wake of the COVID pandemic by helping governments reprioritise, redesign, realign, and reconnect in a number of ways. The crisis has highlighted the importance of key challenges for the region such as the universalisation of social protection, citizens’ demands for rethinking a new social contract, and the strengthening of regional integration and international co-operation (OECD et al., forthcoming[15]). A well-being approach can give clarity on goals, priorities and measures of success: articulating what building forward better means in practice. It helps to identify both pre-existing and new or accumulated vulnerabilities to target support more effectively. It addresses topics that are sometimes less visible in policy, but which matter a lot for people’s quality of life and which have been hit hard by the pandemic, such as social connections, mental health and subjective well-being. It builds resilience in systems, including not just in economic and natural systems, but also in social systems (such as institutions and trust). It also contributes to establishing collaborative networks across government departments and agencies so as to more sharply focus on shared outcomes; these are needed to deliver on multidimensional integrated agendas such as will be required to implement inclusive and sustainable COVID recovery plans.
Governments in LAC countries have already taken important steps in adopting a “beyond GDP” approach to policy. While the word “well-being” (or “bienestar”) is not always used, countries in the LAC region are well advanced in incorporating a people-focused and multidimensional approach to measurement and policy (Montoya and Nieto-Parra, forthcoming[16]). For example, many LAC countries have a long history of using the Multidimensional Poverty Index (including for targeting social policies during the COVID-19 crisis), while the region’s statistical offices have fully embraced the SDG agenda and are making great efforts to monitor its achievement. National development plans and other development strategies in the region are also increasingly including a holistic approach to development that takes into account social and environmental goals alongside economic goals.
Participative approaches to developing multidimensional frameworks and establishing societal priorities can help strengthen the social contract between governments and citizens. Wide public engagement in the development and periodic review of multidimensional well-being frameworks is essential to ensure the legitimacy and public support for such frameworks and to mobilise collective action towards the identified societal goals. This is especially important at a time when efforts to strengthen the social contract between governments and citizens are profoundly needed in the region to implement key reforms and achieve a strong, sustainable and inclusive recovery (OECD et al., forthcoming[15]).
While national development plans are increasingly taking a multidimensional view, economic goals remain largely dominant, partly because of information gaps on non-economic goals. Analysis of LAC national development plans (NDPs), which is included in the chapter, has shown that although NDPs increasingly include social and environmental objectives, economic goals still dominate, with less focus on wider well-being dimensions or other forms of capital that are needed to sustain well-being over time, going beyond economic capital.
Stronger links are required between, on the one hand, the multidimensional objectives set out in legal frameworks and national development plans, and, on the other hand, their implementation through budget allocation, policy design and targeting, and other policy mechanisms. Building on existing good practice and strengthening the links between “objectives” and “implementation” – including the budgetary dimension – can make the difference between a national development plan that remains a high-level vision versus one that is grounded in broadly shared societal objectives and that can be operationalised and mobilise collective action to improve lives.
Finally, the report argues that multidimensional frameworks have the potential to guide decision-making at the regional and international level, as well as at the national (and sub-national) level. This is especially important in the context of the COVID-19 crisis and of other global challenges such as climate change and migration. Building forward better will also depend on stronger and more innovative forms of international co-operation and partnership. Agreeing on a shared set of priorities to monitor, with common indicators across the region (a political as much as a technical process), would help LAC countries to identify common priorities and challenges and areas of strength or weakness and to broaden the scope for peer-learning and co-ordinated action. This, in turn, would support the emergence of a wider and more flexible range of international partnership modalities (beyond financial aid alone), more adapted to the needs of countries in an era of Development in Transition (OECD et al., 2019[1]).
The remainder of this chapter presents Key Findings from Chapters 2 to 5 of the report. These key findings provide a high-level overview of trends over time by presenting average time series for the 11 focal countries (Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Paraguay, Peru and Uruguay), as well as for the LAC regional average and the OECD average, where possible. The key findings section summarises overall gains and losses in the different well-being areas across the focal countries (while acknowledging that in many cases the average hides diverging patterns across and within the focal countries, as Chapters 2-5 show in more detail). It also summarises key inequalities in well-being for different population groups covered in Chapter 5 and concludes with a synthesis of the evidence on the impact of COVID-19, as well as issues for statistical development, which are highlighted throughout the report.
Chapters 2 to 5 discuss developments in all areas covered by the OECD well-being framework in more detail:
Chapter 2, on Material conditions, covers Income and Consumption, Work and Job Quality, and Housing, looking at both average (country-level) patterns as well as vertical inequalities (i.e. the overall societal distribution of selected well-being outcomes) and deprivations (i.e. the share of people below a certain well-being threshold);
Chapter 3, on Quality of life, takes the same approach to cover Health, Knowledge and Skills, Safety, Environmental Quality, Civic Engagement, Social Connections, Work-Life Balance and Subjective Well-being;
Chapter 4, on Resources for future well-being, presents indicators on the four capital stocks that are considered in the OECD well-being framework, i.e. Economic, Natural, Human and Social Capital;
Chapter 5, on Well-being inequalities across social groups and territories, looks at horizontal inequalities by gender, age (children, youth and elderly), territory (focusing on urban-rural differences), ethnicity and race (by Indigenous or Afro-descendant status), as well as education.
In each of these chapters, country-level results based on the latest available data are shown for every indicator,7 in comparison with 2000 or the closest year available where adequate time series exist. In most cases, the latest data refer to 2019, and most results describe changes in well-being from the start of the 21st century up to the onset of the COVID pandemic. The results are organised in sections, by well-being dimension in the case of Chapters 2 and 3, by the types of capital stocks for resources for future well-being in Chapter 4, and by the different population groups in Chapter 5. Every section concludes with two special sub-sections on:
The impact of COVID-19 on the dimension, resource or population group under consideration. While, in general, the main bodies of each section do not discuss COVID per se, they do provide evidence on resilience and vulnerability factors that have shaped the impacts of the pandemic in different countries. In addition, this sub-section draws on available research and projections to discuss the likely impact of the pandemic on each issue. Wherever possible, data showing differences between 2019 and 2020 levels are also presented.
Issues for statistical development. These sub-sections review the statistical gaps that need to be addressed and the methodological issues to be considered in order to improve the measurement of different aspects of current and future well-being.
Finally, Chapter 6 explores Policy through a well-being lens: Experiences from LAC and wider OECD countries. As described above, it presents experiences on the policy use of multidimensional well-being frameworks from countries in the LAC region and other OECD countries, as well as lessons for well-being policy at the national and international level.
By 2019, several aspects of life had improved throughout the LAC region relative to 2000. That said, the path of well-being development was not smooth, and significant challenges existed even before the pandemic hit the region in 2020. Among the 11 focal countries, significant gains in material conditions, including falls in absolute poverty and income inequality and improvements in housing conditions, were not always matched by similar improvements in quality of life –- for example, in aspects of safety, social connectedness and civic engagement. The slowdown in economic progress in the mid-2010s had a direct effect on living standards, for example by reducing the availability of formal jobs and increasing unemployment, but it was also associated with falls in people’s satisfaction with their conditions and in their confidence in government.
The sustainability of well-being over time faces global threats to which the region is particularly vulnerable (e.g. biodiversity loss and climate change that affect natural capital) and that will require combined national action and international co-operation to address. Meanwhile, the weak social capital in the region underscores the fragility of the relationship between people and the public institutions that serve them. Human capital is being challenged by persistently high levels of youth in informal employment or “not in employment, education or training” (NEET), and growing levels of obesity. Low but rising economic capital began stalling even before the pandemic struck. A whole-of-government approach to investing in resources for future well-being is essential to ensure that action in one area does not undermine progress in others.
Looking beyond the national average reveals wide variations in people’s experiences. A more granular and localised picture of well-being data is necessary for effective decision-making. Well-being is not equally distributed: overall, women, children and youth, those living in rural areas, Indigenous and Afro-descendant people, and those with less education tend to experience worse outcomes and fewer opportunities, particularly in relation to material conditions. Nevertheless, there are still some areas of strength that exist alongside these disadvantages – for example, higher rates of educational attainment among women on average; strong social connectedness among youth; higher levels of social capital in rural areas; and higher employment rates for Indigenous and Afro-descendant people.
COVID-19 is having a profound impact on well-being in the region and could reverse many of the gains achieved over the past two decades, as well as deepening existing challenges. The pandemic struck at a time when important well-being vulnerabilities were already emerging: income growth and poverty reduction were already tapering; employment was falling and unemployment rising; and people’s satisfaction with their living conditions and their trust in public institutions were declining. In 2020, absolute poverty and unemployment sharply increased, while incomes, employment and labour force participation fell. Poor housing conditions in the region have made it harder to combat the virus, while the digital divide hampers opportunities for remote learning, working and access to services. Sharp falls in life satisfaction and social connections underscore the human cost of the crisis. At the same time, the pandemic has accentuated vulnerabilities across human, social, economic and natural capital and compounded disadvantages facing youth and young adults. This implies a need to redouble efforts to improve well-being, using recovery plans and fiscal stimulus as tools for addressing both pre-existing and new vulnerabilities that have emerged. The pandemic has touched every aspect of people’s lives, emphasising the deep interlinkages between economic, social and environmental outcomes. It has served as a stark reminder that policy success cannot be defined in narrow economic terms alone, and it has highlighted the value of more joined-up, multidimensional Development in Transition approaches.
The two decades prior to the pandemic witnessed considerable gains in average well-being, but also losses in some areas
The two decades prior to the pandemic witnessed several important gains in material well-being in the LAC 11 focal countries (Figure 1.4). From the early 2000s to around 2019, average household final consumption expenditure grew by more than one-third cumulatively, more than the one-quarter gain experienced in OECD countries on average. In around 2006, 1 in 3 people lived in poverty (based on the ECLAC regional absolute poverty line); by 2019 this had fallen to 1 in 5. Analyses across various absolute poverty lines (USD 1.90 per day; USD 3.20 per day; and USD 5.50 per day) indicate that the greatest gains were made in lifting the very poorest out of poverty. Income inequality, while still high in comparison to the OECD average, has fallen: the Gini Index decreased from 0.51 in 2008-09 to 0.44 in 2018-19, and the income share received by the top 20% of the population fell from 15 times that received by the bottom 20% in 2008-09 to 10 times by 2018-19. Several housing and infrastructure indicators also improved. For example, the share of the urban population living in slums, informal settlements or inadequate housing fell from 23% to 17%. While still low, the share of households with access to drinking water services and the Internet also improved (Figure 1.4).
Note: Selected indicators from Chapters 2 and 3. *Full 2000-2019 time-series are not available for several indicators: most notably, the time series for labour market outcomes typically begin in 2011 or 2012. Details of indicator definitions, sources and periods covered are provided in Chapters 2 and 3 of this report.
Source: Chapters 2 and 3, and Figures 1.5 to 1.11 below.
Despite these positive developments, progress on material conditions often slowed, or even reversed, following the end of the commodity price boom. In particular, labour force outcomes and people’s own perceptions of their living standards weakened after 2014, while the pace of reductions in income inequality also tapered (Chapter 2). Growth in GNI per capita and poverty reduction among the LAC focal countries both stalled post-2015, while employment levels among those aged 25 or over declined, and unemployment was rising, even prior to the pandemic (Figure 1.5; Figure 1.6).8 Average levels of informal employment in the LAC 11 fell by 1 percentage point between 2010 and 2019, but remain high. Informality affects more than half of all workers (57%), with a similar share among non-agricultural workers (Chapter 2). Growth in household final consumption expenditure per capita also tapered off after 2014, combined with a fall in people’s satisfaction with their living standards (Figure 1.7).
Note: In Panel A, LAC 8 excludes Brazil, Costa Rica and the Dominican Republic, due to breaks in the time series. Data for Argentina refer to urban populations only. LAC is the regional average for Latin America and the Caribbean as calculated by ECLAC. In Panel B, time series data prior to 2012 are not available. LAC 7 excludes Argentina, the Dominican Republic, Ecuador and Uruguay. LAC is the regional average for Latin America and the Caribbean as calculated by the ILO.
Source: ECLAC Statistics, CEPALSTAT database https://cepalstat-prod.cepal.org/cepalstat/tabulador/ConsultaIntegrada.asp?idIndicador=3328&idioma=i (Panel A) and ILO, https://www.ilo.org/shinyapps/bulkexplorer34/?lang=en&segment=indicator&id=EMP_DWAP_SEX_AGE_RT_A for country data and https://www.ilo.org/shinyapps/bulkexplorer13/?lang=en&segment=indicator&id=EMP_2WAP_SEX_AGE_RT_A for the Latin American and Caribbean regional average (Panel B): For LAC 7 country-level data: ILO non-modelled series, https://www.ilo.org/shinyapps/bulkexplorer22/?lang=en&segment=indicator&id=UNE_DEAP_SEX_AGE_RT_A; for the overall LAC average, ILO modelled series, https://www.ilo.org/shinyapps/bulkexplorer22/?lang=en&segment=indicator&id=UNE_DEAP_SEX_AGE_RT_A
Note: In Panel A, LAC is the regional average for Latin America and the Caribbean as calculated by the World Bank. In Panel B, LAC 7 excludes Argentina, the Dominican Republic, Ecuador and Uruguay, due to breaks in the series. LAC average is the regional average for Latin America and the Caribbean as calculated by the ILO.
Source: World Bank Database https://data.worldbank.org/indicator/NY.GNP.PCAP.PP.KD (Panel A) and ILO, https://www.ilo.org/shinyapps/bulkexplorer22/?lang=en&segment=indicator&id=UNE_DEAP_SEX_AGE_RT_A for country data and https://www.ilo.org/shinyapps/bulkexplorer59/?lang=en&segment=indicator&id=UNE_2EAP_SEX_AGE_RT_A for the Latin American and Caribbean regional average (Panel B)
Note: LAC 10 excludes Uruguay, as data are not available.
Source: World Bank Database, https://data.worldbank.org/indicator/NE.CON.PRVT.PP.KD and OECD calculations based on Gallup World Poll, https://www.gallup.com/analytics/232838/world-poll.aspx
Gains were also made between 2000 and 2019 across several quality-of-life domains in the LAC 11 – notably physical health, educational attainment, homicides and crime victimisation. Average life expectancy at birth increased from 73 years in 2000 to 76.7 in 2018; and mortality rates for the under-5s fell by nearly 50%, while maternal mortality fell by 30%. Despite these gains in physical health, however, suicide rates increased by 5% since 2000. On knowledge and skills, the share of the population with an upper secondary education rose from 34% to 46%, while the share of those with tertiary education increased from 12% to 19%. The homicide rate, while still nearly five times higher than the OECD average, fell by almost one-quarter in the past two decades – though trends within the LAC 11 countries (and across the region more broadly) strongly diverge.9 The average share of the population who report having been victim to a crime in the last 12 months also dropped from 43% in 2001 to 25% in 2018.
Mirroring the downturn in labour market outcomes after 2013, some quality-of-life outcomes – while remaining above the levels attained in the 2000s – started worsening even prior to the pandemic. This is despite continued, albeit weakened, GDP per capita growth during the same period (Figure 1.8, Panel A). For example, although there was a net gain in life satisfaction over the full-time period considered, it peaked at 6.4 in 2013, and fell slightly thereafter (Figure 1.8, Panel A). Similarly, the share of the population reporting low levels of life satisfaction reached its lowest point in 2013, before rising thereafter (Figure 1.8, Panel B). The LAC 11 homicide rate has also increased since 2015.
Note: In Panel B, LAC 8 excludes Chile, the Dominican Republic and Peru.
Source: World Bank Database https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.KD and Gallup World Poll https://www.gallup.com/analytics/232838/world-poll.aspx (Panel A) and UNODC Database, https://dataunodc.un.org/GSH_app and OECD calculations based on Gallup World Poll, https://www.gallup.com/analytics/232838/world-poll.aspx (Panel B)
Some aspects of personal safety and social connectedness have also stagnated over the last two decades. Road deaths and people’s feelings of safety when walking alone at night have remained stable for the LAC 11 on average, in sharp contrast to strong improvements in both indicators for the OECD average. Similarly, there have been some improvements in air quality, but these are small compared to the large gains recorded for the OECD average over the same period: the share of the population in the focal countries who are exposed to dangerous levels of air pollution remains very high, at 91% in 2019. Finally, the share of people with friends and family to count on in times of need hovered between 86% and 87% across the two decades prior to the pandemic.
Sentiment towards the government and some public services worsened for the LAC 11 countries. Health care access (measured by the Universal Health Coverage Index)10 recorded substantial gains between 2000 and 2015, but people’s satisfaction with health care fell –- a trend that predates the pandemic (Figure 1.9). Voter turnout has remained relatively stable since 2000, but fewer people have voiced an opinion to an official (Figure 1.10, Panel A), and an increasing number of people feel that the State is captured by the interests of powerful elites (Figure 1.10, Panel B).
Note: In Panel A, the Universal Health Coverage Index is a composite of coverage rates across 14 essential interventions; the OECD average excludes Costa Rica. In Panel B, data refer to the share of respondents answering “yes” to the question: “Are you satisfied with availability of quality health care in the city or area where you live?”; the LAC regional average comprises 15 Latin American and Caribbean countries, including the focal countries. OECD 33 excludes the Czech Republic, Iceland, Luxembourg and Norway, due to incomplete time series.
Source: UN DESA Global SDG Indicator Database, indicator 3.8.1, https://unstats.un.org/sdgs/indicators/database/ (Panel A) and Gallup World Poll, https://www.gallup.com/analytics/232838/world-poll.aspx (Panel B)
Note: In Panel A, the LAC regional average includes Bolivia, El Salvador, Nicaragua and Venezuela, in addition to the focal group of countries. OECD 30 excludes the Czech Republic, Estonia, Iceland, Latvia, Luxembourg, Norway and Switzerland, due to incomplete time series. In Panel B, data refer to the percentage of the population aged over 18 who believe that the country is governed by powerful groups for their own benefit. 2012 and 2014 are missing since no data are available. The LAC regional average, in addition to the focal group of countries, includes Bolivia, El Salvador, Guatemala, Honduras, Nicaragua, Panama and Venezuela.
Source: Gallup World Poll, https://www.gallup.com/analytics/232838/world-poll.aspx (Panel A) and Latinobarómetro, https://www.latinobarometro.org/latOnline.jsp (Panel B)
The importance of taking a multidimensional perspective is again underscored when considering medium-term developments in the resources that underpin future well-being. While several of these resources increased over the 2000-2019 period, there were also significant losses (Figure 1.11). Performance both within and across the four different types of capitals remains uneven. Some elements of natural and social capital have declined since 2000, but not across the board. Most indicators of economic capital have improved, but they started from a position well below that of OECD countries as a whole. Meanwhile human capital experienced some positive developments in terms of knowledge and skills, but persistent challenges remain when considering youth labour market outcomes, alongside some growing risks to future health (Figure 1.11).
Note: Includes selected indicators from Chapter 4. Full 2000-2019 time-series are not available for several indicators; details of the time periods considered, together with indicator definitions and sources, can be found in Chapter 4.
Source: Chapter 4, and Figures 1.13 to 1.18, below
Latin America and the Caribbean is a region rich in natural resources, but particularly vulnerable in the face of climate change and biodiversity loss. LAC 11 countries started from a position of strength relative to the OECD average on several natural capital indicators, but long-run trends have seen these assets weakening. For example, the region is home to much of the world’s biodiversity, yet among the LAC 11 countries biodiversity is declining twice as fast as the OECD average rate, according to the Red List Index of threatened species. The regional stability of natural and semi-natural land cover for the LAC 11 average between 2004 and 2019 masks diverging patterns across countries (see Chapter 4), and gains in natural land cover (e.g. through reforestation) cannot always replace the biodiversity lost when human intervention causes land cover changes elsewhere. Ten of the focal countries still have intact forest landscapes, accounting for 30% of the world’s total stock (with the wider LAC region accounting for 36%). However, among the 10 focal group countries with available data, their area has declined by 8% since 2000.
When considering emissions, renewables and material footprints, LAC focal countries are better placed than OECD countries on average, but trends are on an unsustainable path. Recent data on greenhouse gas emissions11 per capita are sparse, but among the 5 focal group countries with time-series data, the 2012 average (5.5 tonnes CO2 equivalent per person) was half the level of the OECD countries. However, while OECD per capita emissions fell 16% between 2000 and 2018, among these 5 focal group countries, emissions increased 8% between 2000 and 2012 (Figure 1.12, Panel A). Similarly, the per capita material footprint of the LAC 11, again half that of the OECD in 2000, grew by 39% between 2000 and 2017. The share of renewable energy among the focal group of countries (35%) is three times that of the OECD average (11%), but while renewables are playing an increasing role in the OECD energy supply mix, their role has been shrinking since 2000 in the LAC 11 (down from 39% in 2000) (Figure 1.12, Panel B). By contrast, there has been a substantial increase in the share of terrestrial and marine areas that are protected between 2000 and 2019 (Figure 1.11), a development that mirrors that experienced by OECD countries.
Note: In Panel A, LAC 5 includes Argentina, Brazil, Colombia, Chile and Mexico. OECD 31 excludes Chile, Colombia, Israel, Italy, Korea and Mexico, due to incomplete time series. In Panel B, LAC regional average 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)
Social capital has weakened over the last decade. Recent uprisings signal the fragility of the social contract in the region, with dwindling support for electoral democracy, low trust in government, and high levels of perceived corruption, discrimination and the feeling that the distribution of income is unfair (OECD/CAF/ECLAC, 2018[17]; OECD, 2021[18]). Both trust in the national government and support for democracy reached a peak around 2010, but began to deteriorate thereafter, with the downward trend steepening in the last years (Figure 1.13). The Transparency International corruption perception index has remained relatively stable over the period, but the share of people who think government is corrupt increased from 71% to 76%. In addition, tax morale is low: only half of the population agree with the statement that tax evasion is never justified, and this share has decreased since the early 2000s. Trust in others, a key indicator of social capital, showed some gains between 2000 and 2011, but these have been lost in the decade that followed. Levels of trust in others are around four times lower than for OECD countries on average (see Chapter 4).12
Note: In Panel A, the LAC regional average includes Bolivia, El Salvador, Nicaragua and Guatemala, in addition to the focal countries. OECD 33 excludes Costa Rica, the Czech Republic, Iceland, Luxembourg and Norway, due to incomplete time series. In Panel B, LAC 10 excludes the Dominican Republic, due to incomplete time series. The LAC regional average includes Bolivia, El Salvador, Guatemala, Honduras, Nicaragua, Panama and Venezuela, in addition to the 10 focal group countries with available data.
Source: Gallup World Poll, https://www.gallup.com/analytics/232838/world-poll.aspx (Panel A) and Latinobarómetro (database), http://www.latinobarometro.org/latOnline.jsp (Panel B)
Youth informal employment and high NEET rates remain persistent challenges, while rising obesity threatens future health. Investing in child and youth skills is particularly important for human capital and future well-being (OECD/CAF/ECLAC, 2016[19]). On average among the focal countries, the share of young adults (aged 20-24) having completed upper secondary education increased from 49% in around 2000 to 69% in 2019. However, the share of youth not in employment, education or training (NEET) fell by only 1 percentage point and remains 5 percentage points above the OECD average (Figure 1.14, Panel A). Youth informal employment is still high, and while there was a slight improvement between 2010 and 2016-17, the situation worsened again in 2018-19, even prior to the impact of the pandemic (Figure 1.14, Panel B). In terms of current and future health determinants, between around 2000 and around 2018, child malnutrition rates fell by over one-third, tobacco consumption almost halved, and alcohol consumption fell by 4%. However, obesity increased substantially – affecting 1 in every 4 adults in 2016, up from around 1 in 6 in 2000 (Figure 1.15).
Note: In Panel A, LAC 7 excludes Brazil, Chile, Costa Rica and the Dominican Republic, due to incomplete data or breaks in the series. LAC is the regional average as calculated by ECLAC. OECD 30 excludes Chile, Costa Rica, Iceland, Ireland, Japan, Korea, Luxembourg and Switzerland, due to incomplete time series. In Panel B, LAC 6 refers to Argentina, Brazil, Colombia, Paraguay, Peru and Uruguay; other focal countries are excluded due to incomplete data or breaks in the series. The LAC regional average includes Panama, in addition to the 6 focal countries with available data.
Source: ECLAC Statistics, CEPALSTAT database, https://cepalstat-prod.cepal.org/cepalstat/tabulador/ConsultaIntegrada.asp?idIndicador=3469&idioma=I and OECD Transition from school to work (database), https://stats.oecd.org/Index.aspx?DataSetCode=EAG_TRANS (Panel A) and ILOSTAT, https://ilostat.ilo.org/data/# (Panel B)
By 2019, economic capital indicators were generally faring better than in 2000, but some elements weakened significantly after 2014. Levels of economic capital in the region started from a low base, relative to OECD countries, but some gains were made particularly in the decade prior to 2013. Annual growth in gross fixed capital formation (as a share of GDP) peaked in 2008 and 2012, and while the 2019 value remains higher than it was in 2000, the years since 2014 have seen significant weakening (Figure 1.16, Panel A). The total value of produced fixed assets in the focal group of countries has increased by more than 50% since 2000, but with OECD growth at nearly 40%, the gap between the two groups has widened in absolute terms. Average investment in R&D in the focal countries (at 0.4% of GDP in 2018) remains very low, at one-sixth of the OECD average level (2.6%), and this has grown by only 0.1 percentage points since 2000. Investment in transport infrastructure in the focal countries (0.9% of GDP in 2014-19) has increased slightly (up from 0.8% in 2008), though it remains below the LAC regional average of 1.1%. In the government sector, debt service has fallen by more than one-third overall since 2000 but has risen sharply since 2013 (Figure 1.16, Panel B). Meanwhile, government tax revenues as a share of GDP have increased from 17.2% to 21.4%, though they remain well below the OECD average (33.8% in 2019).
Note: LAC 10 excludes Ecuador, as data are not available.
Source: UN DESA Global SDG Indicator Database, indicator 3.a.1, https://unstats.un.org/sdgs/indicators/database/ (for tobacco use); WHO Global Health Observatory (database), https://www.who.int/data/gho/data/indicators/indicator-details/GHO/alcohol-recorded-per-capita-(15-)-consumption-(in-litres-of-pure-alcohol) and WHO GHO (database) https://apps.who.int/gho/data/view.main.CTRY2430A
Note: In Panel A, LAC is the regional average for Latin America and the Caribbean as calculated by the World Bank, and 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. In Panel B, LAC 9 excludes Chile and Uruguay, as data are not available. LAC is the Latin America and Caribbean regional average as calculated by the UN DESA.
Source: Panel A: World Bank Database, https://data.worldbank.org/indicator/NE.GDI.FTOT.ZS?locations=ZJ; Panel B: UN DESA Global SDG Indicator Database, indicator 17.4.1, https://unstats.un.org/sdgs/indicators/database/, https://w3.unece.org/SDG/Indicator?id=74
A focus on average performance masks important diversity of experience both between and within countries. Chapters 2, 3 and 4 provide country-level data for each country in the LAC 11 focal group. Analysis at the country level shows that there are aspects of well-being on which almost all countries have significantly improved their performance (i.e. by at least half a standard deviation) between 2000 and 2019. For example, performance in Internet access, household final consumption expenditure, absolute poverty, income inequality (measured by the Gini Index), crime victimisation, health care coverage, mortality for children under age five, tobacco use and protected terrestrial areas improved across almost every LAC 11 country with available data. Yet for the majority of indicators, even when the LAC 11 average performance improved, the country-level picture is more uneven, with some countries improving, some experiencing little change and some even worsening. When it comes to areas of declining average performance across the focal countries, the picture is similarly mixed. In fact, there are almost no indicators on which every one of the countries in the focal group worsened significantly (i.e. by at least half a standard deviation) between 2000 and 2019: the only exception is overweight and obesity. Tax morale also weakened in 9 out of 11 of the focal group countries, while perceptions of elite State capture increased in 8 out of the 11 countries.
Inequalities are multidimensional – and different population groups face different sets of challenges to their well-being. Chapter 5 considers the distribution of well-being across a wide variety of different population groups within the focal group of countries – including outcomes at different stages of the life course, outcomes by education, and regional (subnational) variations in well-being (or spatial inequalities). What follows is a summary of selected findings concerning differences in well-being based on gender, race and ethnicity, youth (as compared to middle age) and urban versus rural differences. Overall, the data indicate fewer opportunities, particularly in material conditions, for women, youth, Indigenous people, Afro-descendant people and people living in rural areas. Nevertheless, these population groups also have areas of relative strength – such as education for women, social network support for youth, employment rates for Indigenous people and social capital for people living in rural areas. A key challenge for future development will be to level up opportunities by harnessing these strengths (e.g. women’s education), rather than levelling down (e.g. so that women face the same burden of very long working hours and high rates of job insecurity that men do).
Gender differences in well-being
While significant progress has been made in recent years in improving well-being outcomes for women in the focal group of countries, persistent gender inequalities remain, holding back wider social and economic development. Overcoming gender gaps implies removing several structural barriers, including socio-economic inequality and poverty; discriminatory, violent and patriarchal cultural patterns; the unequal division of labour and care; and the concentration of power and hierarchical relations in the public sphere (ECLAC, 2017[20]).
Women fare worse than men across many aspects of material conditions in the focal countries. On average, women are much less likely to be employed and nearly one-third more likely to be unemployed, and their monthly earnings are 13.7% lower than those of men.13 In addition, more than twice as many women have no income of their own compared to men (Figure 1.17). Women are more likely than men to live in poverty, a gap that has widened over the past two decades, and they are slightly more likely to work in informal jobs. By contrast, more men than women work very long hours in paid work, and more men fear losing their jobs in the next 12 months.
Note: Values refer to the LAC 11 average, but data may not be available in all 11 focal group countries; data refer to the latest available year. For full details, see Chapter 5, Figure 5.1.
Source: Chapter 5, Figure 5.1
Women fare better than men in several education and health outcomes, but they do more unpaid work. Despite experiencing far worse labour market outcomes, women have higher educational attainment rates than men in the focal group of countries. For example, 70% of women have reached at least an upper secondary level of education (compared to 62% of men), and 20% of women have a tertiary education (compared to 18% for men). Women live six years longer than men do, with a life expectancy at birth of 79.8 years. Men are meanwhile three times more likely than women to die from suicide, and eight times more likely to die from homicide. Nevertheless, women face pervasive threats in terms of sexual assault and domestic or intimate-partner violence that are less well measured through comparable statistics. For example, it is estimated that 1 in 4 women aged 15-49 in the focal countries have experienced intimate partner violence in their lifetime. Fewer women feel safe walking alone in their neighbourhood (38% compared to 51% of men). Women perform more than twice the amount of unpaid care and domestic work14 that men do: they spend on average 36.5 hours per week on such work, compared to the 16.2 hours spent by men. This results in a “double day” burden for women in paid employment: working women spend almost 10 hours longer on total work time (including both paid and unpaid work) than men, with an average total work week of nearly 72 hours, compared to 62 hours for men.
Women have less civic and political voice and lower levels of trust than men, while men and women have different risk profiles for human capital. On average among the focal group of countries, the share of seats held by women in national parliaments has doubled in the last two decades to 30% (slightly above OECD average levels). Nevertheless, a lack of gender parity also extends to civic engagement and trust among the general population. For example, fewer women report voicing their opinion to an official in the last 12 months; women express slightly less support for democracy; and fewer women have confidence in their national government. More broadly, women also report lower levels of interpersonal trust, with 13% of women feeling that most people can be trusted, compared to 16% of men. When it comes to risks to human capital, a much higher share of young women (aged 15-24) are not in employment, education or training (21%) relative to young men (11%), meaning they have fewer opportunities to develop knowledge and skills at a critical transition in their lives. Future health risks also differ for men and women: while men are almost twice as likely to use tobacco regularly and drink alcohol heavily, 28% of women are obese, compared to 21% of men.
Age differences in well-being
Youth and young adults face very high levels of unemployment and informality, but also fare worse than the middle-aged in several quality-of-life domains. In a pattern that is common to OECD and LAC countries alike, many youth and young adults (i.e. those aged between 15 and 29) struggle to get a foothold in the labour market (Figure 1.18). As of 2020, youth unemployment in the focal group of countries is three times higher than among the middle-aged, on average, and the share of youth in informal employment is also very high (64% versus 48% for the middle-aged). Younger people report better physical health, with half the prevalence of limitations in daily activities due to health problems, but what little data exist suggests they fare worse than middle-aged adults in mental health, with higher suicide rates. Homicide rates among young people in the LAC 11 countries are nearly 1.5 times higher than for the middle-aged. Patterns of social capital vary little between these two age groups, with the exception of trust in government (where youth have higher rates) and trust in the local police (where youth rates are lower than for the middle-aged). Despite the various challenges faced by youth in the region, social network support and life satisfaction are higher among youth than among the middle-aged, a pattern that tends to hold globally – though falls in life satisfaction in 2020 have been greater for youth than for other age groups (below).
While children in the region face a high prevalence of absolute poverty, child labour and malnutrition, people aged 50 or over face different well-being challenges. Children in the focal group of countries experience poverty rates that are twice as high as adults, on average: in 2019, 31% of children aged 0-14 were living in absolute income poverty, and 9% in extreme poverty, while for 25-54 year-olds the rates were 17% and 4%, respectively. There is still some way to go before child labour is eliminated: 5% of children aged 10-14 were employed across the LAC 11 in 2018, with higher rates among boys and in rural, poorer and Indigenous communities. Stunting rates among children in the focal group of countries have halved since 2000, but the condition continues to affect 1 in 10 children below the age of 5. At ages 5-19, the prevalence of obesity has grown from 22% in 2000 to 31% in 2016, mirroring the trend for adults. At the other end of the age spectrum, those aged 50 or over experience higher hourly earnings from formal employment, lower poverty, lower homicides and higher social capital than adults of other ages on average – but as might be expected, health limitations worsen considerably with age (six times higher than among youth and young adults; nearly three times higher than among the middle-aged). Suicides and informal employment are also slightly more common among people aged 50 or over relative to the middle-aged. For retirees, low pension coverage remains a significant challenge throughout the region: on average across the focal group of countries, only two-thirds of the population of pensionable age receives a social pension compared with near-universal coverage (95%) on average in OECD countries.
Note: Values refer to the LAC 11 average, but data may not be available in all 11 focal group countries; data refer to the latest available year. For full details, see Chapter 5, Figure 5.13. For most of the indicators shown here, “young” refers to youth and young adults aged 15-29; the exceptions are unemployment and informal employment (where the age range considered is 15-24) as well as suicides (where the age range is 20-29). The middle-aged group typically refers to adults aged 30-49, with exceptions in the cases of unemployment and informal employment (25-54); formal hourly earnings (30-54); and homicide (30-59).
Source: Chapter 5, Figure 5.13
Ethnic and racial differences in well-being
Indigenous and Afro-descendant populations face some shared challenges in terms of exclusion, deprivation and discrimination. In Latin America, the concept of ethnicity is most commonly used with reference to Indigenous peoples and the concept of race primarily for Afro-descendants (ECLAC, 2016[21]). On average across the focal countries, 8% of the population identify as Indigenous and 8% as Afro-descendant. The availability and timeliness of well-being data is particularly limited for breakdowns by race and ethnicity, both across well-being indicators and across the focal group countries. Nevertheless, for almost all the available indicators for material conditions, quality of life and social and human capital, Indigenous people tend to have lower well-being outcomes than non-Indigenous people on average, and Afro-descendant people tend to have lower well-being outcomes than non-Afro-descendant people.
Indigenous people in the focal group of countries fare better than non-Indigenous people on employment and unemployment, but generally experience worse outcomes across material conditions, health and education-related indicators. For example, absolute poverty rates (using the ECLAC regional definition) are nearly twice as high among Indigenous people, and extreme poverty is three times higher, compared to non-Indigenous people. This is despite their higher employment and slightly lower unemployment (Figure 1.19). Higher poverty goes hand-in-hand with lower earnings, more overcrowded housing, lower levels of secondary education among young adults and higher levels of illiteracy. While the fear of falling victim to a crime is slightly lower among Indigenous people, the percentage of people reporting having fallen victim to a crime in the previous 12 months is very similar for Indigenous and non-Indigenous people (around 30%). Social capital indicators such as trust in others and trust in government are also similar across Indigenous and non-Indigenous communities. Nevertheless, trust in the local police and support for democracy as the best form of government are slightly lower for Indigenous people. In addition, more than 1 in 4 Indigenous people feel that they belong to a discriminated group, compared to around 1 in 6 non-Indigenous people.
Afro-descendant people experience higher employment rates than non-Afro-descendants, but face multiple challenges across the dimensions of material conditions, quality of life, human and social capital. Across the focal group of countries, 22% of Afro-descendant people live in absolute poverty (using the ECLAC regional definition) and 5.3% in extreme poverty – much higher rates than non-Afro-descendants. Employment rates reach 67.6% (compared to 66.5% for non-Afro-descendants), but unemployment, perceived job insecurity and the share of youth not in employment, education or training are all higher among Afro-descendants. Barriers to opportunity faced by Afro-descendants include lower educational attainment rates at both secondary and tertiary levels and higher rates of infant mortality (around one-third higher) and maternal mortality (three times higher, on average). One-quarter of Afro-descendants also feel they belong to a discriminated group. Trust in others and trust in the national government are very similar for Afro-descendant and non-Afro-descendant people, but voter turnout, trust in the police, support for democracy and tax morale are between 3 and 8 percentage points lower among Afro-descendants.
Note: Values refer to the LAC 11 average, but data may not be available in all 11 focal group countries; data refer to the latest available year. For full details, see Chapter 5, Figure 5.26.
Source: Chapter 5, Figure 5.26
Urban-rural differences in well-being
Opportunities for better lives are not equally distributed between urban and rural areas within the focal group countries. Rural areas feature much poorer housing conditions, higher rates of poverty and lower formal earnings. The share of people living in households without sufficient income to buy a basic food basket (the ECLAC regional definition of extreme poverty) is three times higher in rural areas compared to urban zones, while absolute poverty (according to the ECLAC regional definition) is around 1.5 times higher (Figure 1.20). The employment-to-population ratios are broadly similar, but informal employment is considerably higher in rural areas (65%) compared to urban ones (43%), and average rural earnings (whether in the formal or informal sectors) are only two-thirds the level of urban earnings. Some of the most striking urban-rural differences relate to housing infrastructure and conditions, which limit rural residents’ opportunities to live healthy and digitally connected lives. For example, only around two-thirds of the rural population have access to drinking water services or hygienic toilet facilities (96% and 93% in urban areas, respectively); and just over 1 in 4 rural households have access to the Internet, while more than 1 in 2 urban households do.
Note: Values refer to the LAC 11 average, but data may not be available in all 11 focal group countries; data refer to the latest available year. For full details, see Chapter 5, Figure 5.19.
Source: Chapter 5, Figure 5.19
Knowledge, skills and prospects for youth are also lower in rural areas, but social capital and feelings of safety are higher. In rural areas, only 53% of people have reached at least an upper secondary level of education, while the share of youth not in employment, education or training is also higher (18%) compared to urban ones (15%). By contrast, social capital includes some areas of comparative strength for rural areas: volunteering rates are higher, there is greater trust in both the local police and the national government, and perceived government corruption is slightly lower. People in rural areas also feel safer: while 54% feel safe walking alone in their neighbourhood, only 35% of urban dwellers feel the same way.
The pandemic has touched every aspect of people’s well-being, dealing severe blows to material conditions and quality of life
COVID-19 has struck Latin America and the Caribbean particularly hard. As of 28 June 2021, the region had experienced 1.26 million deaths due to COVID-19, nearly one-third of the world total, despite being home to just 8.4% of the world’s population (ECLAC, 2021[22]). As the health crisis rapidly became an economic and social crisis, there have been far-reaching consequences for people’s well-being. In particular, the impact of the crisis was asymmetric across citizens, affecting particularly the most vulnerable groups. Lockdowns and containment measures to mitigate the pandemic have hit low-paid and informal workers particularly hard. As many as 38% of total workers (and 61% of vulnerable informal workers) do not have access to any kind of social protection. This absence of safety nets puts them at greater risk (OECD, 2020[23]). During the first wave of the pandemic in 2020, Latin American people endured some of the longest lockdowns worldwide (Parkin, Phillips and Agren, 2020[24]) and were subject to some of the strictest mobility and contact restrictions (Alicea-Planas, Trudeau and Vásquez Mazariegos, 2021[25]; Hale et al., 2021[26]; OECD et al., forthcoming[15]), with significant implications for education as schools were closed more often than in other regions (OECD et al., forthcoming[15]). As the pandemic continues, and the sanitary situation has disrupted data collection worldwide, it will take some time before the full extent of its impacts on well-being will be known for many of the statistics gathered in this report.
In 2020, absolute poverty and unemployment sharply increased, while incomes, employment and participation fell. GNI per capita for the focal group of countries fell by 7.4%, and household final consumption expenditure by 8.8%, between 2019 and 2020. Estimates for the whole of the LAC region indicate that the number of people falling below the ECLAC absolute poverty line was 209 million by the end of 2020, 22 million more than in 2019 (ECLAC, 2021[27]). Of these, an estimated 78 million were living in conditions of extreme poverty – an increase of 8 million compared to 2019 (ECLAC, 2021[27]). These changes bring absolute poverty to its highest level since 2008, and extreme poverty to its highest level since 2000. The impacts of the crisis on jobs have also been pronounced: the seven focal countries with available data experienced a 9 percentage-point drop in their average employment rate, and a 3.6 percentage-point increase in unemployment, between 2019 and 2020. Many people of working age also dropped out of the labour force altogether (ECLAC/ILO, 2020[28]), and informal work is projected to rise (Altamirano et al., 2020[29]).
Poor housing conditions in the region have made it harder to combat the virus, and the digital divide hampered opportunities for remote learning, working, telemedicine and more. As community transmission of COVID-19 took hold in Latin America, the greatest risk of exposure has been among individuals living in overcrowded housing, often with little or no access to sanitation and water (Lustig and Tommasi, 2020[30]) – making both physical distancing and additional hygiene practices challenging. Reliable, high-speed Internet access at home is essential for several measures being taken globally to mitigate the effects of confinement on the economy and on people’s well-being, from large-scale teleworking, to home schooling to telemedicine.
The pandemic has had a marked impact on education in the region. By mid-May 2020, more than 160 million students at all levels of education had stopped having face-to-face classes in Latin America and the Caribbean, and the total duration of school closures in the focal group of countries was generally over 41 weeks (UNESCO, 2021[31]). Data from the Gallup World Poll show a clear drop in the share of people satisfied with the educational system in 2020, compared to 2019: the year-on-year drop of 11 percentage points left the average level among countries in the focal group at 52% in 2020, against 67% in the OECD. Remote learning solutions were put in place across the region during school closures, but online delivery is challenging when 46% of children aged 5-12 live in households with no connectivity (ECLAC, 2020[32]), and fewer than 14% of poor students (those living with less than USD 5.5 per day, PPP 2011) in primary education have a computer connected to the Internet at home, in contrast to over 80% among affluent students (i.e. those living with more than USD 70 per day) (Basto-Aguirre, Cerutti and Nieto-Parra, 2020[33]). Furthermore, challenges related to digital skills also affect inclusiveness in the region. Providing disadvantaged schools and students with more computers and ICT is not enough to improve performance – the development of digital skills is key to harnessing the opportunities of broader digital transformation (OECD et al., 2020[34]).
The pandemic has underscored the importance of access to health care, for both physical and mental health conditions. Approximately 25% of the population in Latin America as a whole did not have access to essential health-care services prior to the pandemic: these individuals will have seen their access even more restricted over the course of 2020. Health problems can also have a significant impact on household finances: among the six focal countries for which data are available, approximately 9% of households incurred out-of-pocket health-care expenditures exceeding 10% of their income over the 2010-18 period. While the effects of the COVID-19 pandemic on physical medical conditions have received great attention, there are also concerns about its impact on mental health. For example, one in two Mexicans reported that the pandemic had a negative impact on their mental health (51%), and almost one in four reported suffering from at least one mental health condition (22%) (YouGov, 2020[35]). More widely, 27% of young Latin Americans (aged 13-29) reported feeling anxiety and 15% depression in the previous 7 days during the first months of the pandemic (UNICEF, 2020[36]). Lockdown measures are likely to have increased people’s loneliness, substance use and self-harm (WHO, 2020[37]).
Extended lockdowns in Latin America and the Caribbean kept people off the streets, with mixed consequences for crime. Little comparative data currently exist to assess the impact of the pandemic on personal safety. Worldwide, there have been significant concerns about the likely impact of “stay at home” orders for adults and children living in households at risk of domestic violence. Reports of increased domestic violence in four of the focal group countries (Argentina, Chile, Colombia and Mexico) during the first weeks of confinement bear this out (Statista, 2020[38]). Confinement conditions have likely shifted crime patterns: in the first semester of 2020, 22% of households in Mexico fell victim to robbery, burglary or theft, compared to 35% a year earlier (2019) (INEGI, 2020[39]), while crimes committed outside of private dwellings fell from 17% to 9%. Nevertheless, homicides in Mexico showed little change (Gobierno de Mexico, 2020[40]; UNODC, 2020[41]). COVID-19 may have also opened a window of opportunity for organised crime groups to solidify their local power, by engaging in charitable activities (Felbab-Brown, 2020[42]) and imposing their own restrictions on communities (Asmann, 2020[43]) – while the material hardships caused by the pandemic may provide fertile grounds for criminal recruitment (Nugent, 2020[44]).
The COVID-19 pandemic has disturbed electoral processes in a number of Latin American countries, with elections postponed in Chile, the Dominican Republic, Paraguay and Uruguay. Evidence across 14 parliamentary and presidential elections suggests that the pandemic may have affected voting behaviour in the region (López-Calva, 2021[45]). When comparing the elections that took place during the pandemic to historical averages, voter turnout slightly increased in half of the countries and decreased in the other half. However, when compared with the most recent elections, a majority of these countries (11 of the 14) registered a decrease in voter turnout (López-Calva, 2021[45]).
The pandemic has taken a toll on people’s subjective well-being and their social relationships. Between 2019 and 2020, life satisfaction in the focal group of countries fell by 7% – a drop that has wiped out all life satisfaction gains made in the focal group since 2006-08. Similarly, the share of people reporting very low levels of life satisfaction increased, affecting 1 in 4 people in 2020 compared to around 1 in 5 just one year earlier. Emotional well-being has also suffered: on average, 17% of respondents in focal group countries experienced more negative than positive feelings in a typical day in 2020, roughly 6 percentage points more than in 2019. Both voluntary social distancing and mandatory lockdown policies have had implications for people’s ability to maintain social relationships beyond immediate household members. Across the focal group of countries, the share of people who have friends or family that they can count on in times of need fell from 87% in 2019 to 83% in 2020. This contrasts with the pattern in OECD countries, where a level just above 90% was sustained both before and during 2020.
COVID-19 has accentuated vulnerabilities across human, social, economic and natural capital
The impact of COVID-19 on human capital, via its effect on young people, education and health, is considerable, and likely to result in long-term scars. The World Bank has estimated that losses in learning, human capital and productivity could translate into a USD 1.7 trillion decline in aggregate earnings for the Latin American and Caribbean region, representing 10% of baseline levels (World Bank, 2021[46]). The crisis has also been particularly hard on working youth, who are over-represented in the sectors hardest hit by the pandemic, such as retail, hospitality and tourism –- and who already faced difficulties in accessing the formal labour market before the crisis. Poor health heightens vulnerability to the effects of COVID-19, and an estimated 21% of the population in Latin America have at least one pre-existing health condition that put them at higher risk of severe COVID-19 consequences (LSHTM CMMID COVID-19 working group, 2020[47]).15 High rates of obesity and high levels of exposure to air pollution (above) present further risks (Pozzer et al., 2020[48]; Wu et al., 2020[49]). The role of indoor air pollution, a major issue in low- and middle-income countries, also takes on new significance when more time is being spent at home (Du and Wang, 2020[50]).
Social capital in the LAC region was already weak prior to the pandemic, and this represents a risk factor for the recovery. Even prior to the pandemic, there was considerable dissatisfaction with persistent inequalities and the functioning of the political system, as well as growing distrust of institutions and low and declining support for democracy. In the longer run, these perceptions may be further exacerbated by the pandemic’s role in widening inequalities, by restrictions on personal freedoms, and by the rapid mobilisation of government funds with sometimes limited oversight (UN, 2020[51]). However, in the short run, the focal group countries saw the share of people who have confidence in their national government rise from 32% in 2019 to 37% on average in 2020, while the share of those perceiving government to be corrupt fell from 77% to 72%. This “rallying round the flag” effect has also been witnessed in OECD countries, and appears to reflect a phenomenon of greater national unity in the face of a common threat – though OECD evidence also indicates that this effect may not be long-lasting in relation to COVID-19 (OECD, forthcoming[52]).
Economic capital, already weakening since 2015, will be further undermined by falls in investment. Key elements of fiscal stimulus programmes have included direct payments to households, tax relief and deferrals, business lending programmes and additional health spending. Increased public spending has been largely financed by public debt but also by official lending. The monetary policy response has also been multipronged, including the 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 6.8% contraction in GDP for 2020 across Latin America and the Caribbean (ECLAC, 2021[22]). At the same time, stimulus programmes have largely depleted the limited fiscal space available to countries in the region. Government debt in the median LAC economy has risen from 53% of GDP in 2019 to 69% in 2020 (World Bank, 2021[53]), making Latin America and the Caribbean the most indebted region in the developing world (ECLAC, 2021[54]). High uncertainty and tighter financing conditions during the pandemic have led to delays in infrastructure spending and cuts to research and development – the latter of which is already well below OECD average rates and is key for securing future productivity.
Natural resources have been exposed to greater risk due to difficulties in enforcing protections of certain natural assets during the pandemic. The collapse in economic activity during the pandemic produced a temporary fall in carbon emissions, but this will have little bearing on climate change unless followed up with strong policy action in the recovery – since its impact on the overall stock of greenhouse gas emissions in the atmosphere is very small, and evidence from past crises suggests a strong rebound in emissions when the economy picks up (OECD, 2020[55]). Meanwhile, pandemic restrictions have not stopped deforestation in Latin America (León and Cárdenas, 2020[56]). Over the past decade, external threats to these forests from mining, oil, agricultural and forestry companies, cattle ranchers, farmers, illegal groups and land speculators have increased markedly (Walker et al., 2020[57]; Ellis et al., 2017[58]). Meanwhile, government efforts to control illegal incursions into Indigenous territories have declined in several countries in the region. 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, water and other natural resources in Indigenous territories (ECLAC, 2020[59]).
The pandemic has deepened existing gaps in opportunities and created new vulnerabilities
Men and women have faced different economic, social and health impacts during the pandemic. Men have experienced higher mortality rates so far, but women’s jobs have often put them on the frontline. Latin America has the highest share of female health care workers in the world (half of doctors and more than 80% of nurses) (Inter-American Development Bank, 2018[60]). At the same time, women are also over-represented in sectors that underwent greater disruption and job losses, such as restaurants and hotels, retail and domestic services (ECLAC and ILO, 2020[61]). In the region as a whole, female unemployment is expected to reach 22.2% for 2020, a 12.6 percentage point increase year-on-year (UN ECLAC, 2021[62]). Latin American women also experienced a greater proportional fall in employment (by 18.1%, compared with 15.1% for men), as well as greater exits from the labour market (15.4%, compared with 11.8% for men) (ECLAC and ILO, 2020[61]). In total, the negative impact of the pandemic on women’s labour market participation in Latin America is expected to wipe out a decade’s worth of progress (UN ECLAC, 2021[62]). Higher rates of poverty amongst women even before the pandemic imply fewer opportunities to build savings that could mitigate future income losses. It is estimated that 118 million women in the region will be living in absolute poverty following the crisis (compared with a total poor population of 187 million in 2019) (UN ECLAC, 2021[62]; UN ECLAC, 2021[63]). Finally, lockdowns coupled with economic hardships may have made people living with a violent or abusive household member especially vulnerable.
Prior to the pandemic, youth already experienced considerable disadvantages in the labour market – and these are now being compounded by the crisis. For example, the youth unemployment rate among the focal group of countries was 18% in 2020, three times more than that for prime-aged workers. COVID-19 exposes vulnerable youth in the region to higher risks of disengagement and dropout from education and training and may increase the overall number of NEET youth. Although the reasons for disengagement and dropout are complex and change over time (Aarkrog et al., 2018[64]), COVID-19 may act as a potent multiplier through loss of motivation due to several factors, including breaks in education or training; loss of connections with supportive adults and positive peer interactions; increases in household poverty; and higher household stress (OECD, 2020[65]).
Survey data provide a first glimpse into how people’s psychological states and social supports have held up in 2020. Average life satisfaction in the focal group of countries fell for almost all the population groups shown in Figure 1.21, with the exception of the tertiary educated, who have been more protected from the worst of the pandemic’s effects on living conditions. Greater falls in life satisfaction were experienced by women, rural residents, youth and young adults aged 15-29, and people with lower levels of educational attainment. In the case of social network support, women and rural-dwellers again experienced slightly greater falls than men and urban-dwellers (respectively) between 2019 and 2020. However, the age and education gradients were less clearly delineated for social support: people in middle-age and those with secondary education experienced the greatest falls relative to their younger and older (and primary or tertiary educated) counterparts, though marked falls also occurred for young adults (as shown in Chapter 5).
Note: Data refer to answers (0-10 scale) to the following questions: “Please imagine a ladder with steps numbered from 0 at the bottom to 10 at the top. Suppose we say that the top of the ladder represents the best possible life for you, and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time, assuming that the higher the step the better you feel about your life, and the lower the step the worse you feel about it? Which step comes closest to the way you feel?” LAC 11 excludes Argentina, Colombia, the Dominican Republic, Mexico and Peru, for primary, secondary and tertiary. OECD is OECD 35 for women and men and excludes the Czech Republic and Luxembourg; it is OECD 36 for urban and rural and excludes Luxembourg; it is OECD 28 for age 15 to 29, age 30 to 49 and age 50+ and excludes Australia, the Czech Republic, Finland, Iceland, Italy, Japan, Luxembourg, the Netherlands and Slovenia, as data are not available for both years.
Source: Gallup World Poll (database), https://www.gallup.com/analytics/232838/world-poll.aspx
The poor housing conditions and lack of services that exacerbate pandemic-related challenges are particularly prevalent in rural areas, but the density of urban populations also puts them at high risk. The marked spatial concentration and density of the population in the main Latin American urban areas accelerated the spread of COVID-19, particularly in population segments that experienced significant vulnerabilities and shortages (ECLAC, 2020[66]). Those at higher epidemiological risk, as well as those most vulnerable to the pandemic’s socio-economic impacts, are people living in overcrowded dwellings, without water or sanitation, and in particular those living in slums or informal settlements in urban areas. These are largely informal workers, with limited or no assets, nor social security and often no Internet access. Access to water, handwashing facilities and sanitation are essential to contain the spread of COVID-19, while access to the internet and digital technologies (where available) have been key to accessing remote learning and working, public information and the maintenance of social contacts.
The relative deprivation of both Indigenous and Afro-descendant populations exposes them to a disproportionate level of vulnerability to the consequences of the pandemic. The common challenges faced by the two groups – in terms of poverty, informality, lack of social protection and inadequate housing conditions – increase the risks they experience during the pandemic, both in terms of direct health impacts as well as the broader socio-economic outcomes (ECLAC et al., 2020[67]; ECLAC, 2021[68]). However, there are also differences between the two groups that shape the way these risks can play out, including the large share of Indigenous people who live in rural areas and the primarily urban-dwelling patterns among the Afro-descendant population.
The availability of well-being data remains a significant challenge for the focal group countries, and in Latin America and the Caribbean region more widely. Chapters 2 through 5 of this report highlight a variety of important data gaps for understanding the levels, trends and distributions of well-being outcomes in the region. Overall, the main data challenges can be summarised as follows. There is a need to:
Better understand inequalities across well-being dimensions. This includes building the capacity to disaggregate key well-being measures by gender, age, race and ethnicity, as well as gaining further insights into the geographic distribution of well-being outcomes within countries.
Gain deeper insights into well-being areas of high concern, such as levels and patterns of informal work, time use, the impact of violence and experiences of safety on people’s well-being, and a more nuanced understanding of household financial situations (through better data on household income, wealth and expenditure).
Collect well-being data in a more harmonised way that enables comparisons with other regions and countries and enhances the timeliness of data – since for most of the indicators covered in this report, there is usually a time lag of at least 2-3 years. More timely data are vital for well-being indicators to be integrated more comprehensively into policy decision-making, as the COVID-19 crisis has underlined.
Strengthen the measurement of subjective well-being experiences in LAC countries. The recent wave of protests and social unrest in countries in the LAC region have underlined the need to better understand citizens’ lived experiences when making policy decisions. In the absence of harmonised official statistics for subjective aspects of quality of life and social capital in particular, this report has used non-official data sources, such as the Gallup World Poll and Latinobarómetro, which despite their smaller sample sizes have the advantage of comparable methods used across countries and frequent, recurrent data collections.
Finally, statistical offices within the region could collaborate on developing a priority list of headline indicators for assessing development in transition, beyond GDP. All countries in the region are committed to SDG monitoring activities, and a number of statistical offices and government ministries in the focal group of countries have already embarked on work to measure well-being, including in Mexico, Colombia, Chile and Ecuador (see Chapter 6 for details). In a context of limited resources, not every indicator can be prioritised for frequent, recurrent data collection by national statistical offices. Nevertheless, a small selection of “headline” measures (disaggregated by key population groups of interest) could be agreed by statistical offices and their stakeholders in the region as priorities for capturing development challenges in countries transitioning from low- to high-income status. Based on the analysis and insights in this report, as well as past OECD work, a candidate list is proposed in Annex 1.A. as a starting point for further elaboration and discussion.
The need to look “beyond GDP” is widely recognised by the international community, and this paradigm shift has been embodied by the SDG agenda, as well as in many other national and international efforts on well-being. Using a broader range of policy-relevant metrics to benchmark progress is especially important in the LAC region, and particularly for the group of countries who are experiencing a transition to upper-middle-income and higher-income status, but who continue to face structural challenges. The COVID-19 pandemic and its deep socio-economic impacts have further underlined the need for countries in the region (and elsewhere) to implement recovery strategies based on a multidimensional, people-focused and forward-looking vision of development. Having a shared idea of policy priorities and using a common framework to identify relative strengths and weaknesses can also help to strengthen regional co-operation and to support more effective international partnerships.
The framework of indicators presented in this report has been adapted from the original OECD well-being framework to better reflect issues of special relevance in the region, encompassing material conditions, quality of life, resources for future well-being, and inequalities across groups and territories. Yet the report also emphasises that for metrics to make a difference to policy, institutional, analytical and operational innovations are required, in addition to statistical development. Countries in the LAC region are well advanced in incorporating a people-focused, multidimensional approach to measurement and policy, but (as in other regions) stronger links are required between, on the one hand, the multidimensional objectives set out in legal frameworks and national development plans, and, on the other hand, their actual implementation through budget allocation, policy development and targeting.
In order to move forward to mainstream a well-being approach in measurement and policy at the national and regional level in Latin America, continued discussions between policy actors, statistical agencies and a wide variety of stakeholders across civil society are needed. The findings of this report are intended to contribute to these discussions and to strengthen the foundation for future work and deliberations.
References
[64] Aarkrog, V. et al. (2018), “Decision-making processes among potential dropouts in vocational education and training and adult learning”, International Journal for Research in Vocational Education and Training, Vol. 5/2, pp. 112-129, https://doi.org/10.13152/ijrvet.5.2.2.
[25] Alicea-Planas, J., J. Trudeau and W. Vásquez Mazariegos (2021), “COVID-19 risk perceptions and social distancing practice in Latin America”, Hispanic Health Care International, p. 154041532098514, https://doi.org/10.1177/1540415320985141.
[29] Altamirano, A. et al. (2020), ¿Cómo impactará la COVID-19 al empleo? Posibles escenarios para América Latina y el Caribe, Inter-American Development Bank, Washington, D.C., https://doi.org/10.18235/0002062.
[43] Asmann, P. (2020), What Does Coronavirus Mean for Criminal Governance in Latin America?, https://www.insightcrime.org/news/analysis/criminal-governance-latin-america-coronavirus/.
[33] Basto-Aguirre, N., P. Cerutti and S. Nieto-Parra (2020), Is COVID-19 widening educational gaps in Latin America? Three lessons for urgent policy action, OECD Development Centre, https://oecd-development-matters.org/2020/06/04/is-covid-19-widening-educational-gaps-in-latin-america-three-lessons-for-urgent-policy-action/.
[72] Boarini, R., A. Kolev and A. McGregor (2014), “Measuring Well-being and Progress in Countries at Different Stages of Development: Towards a More Universal Conceptual Framework”, OECD Development Centre Working Paper, No. 325, http://www.oecd-ilibrary.org/fr/economics/oecd-statistics-working-papers_18152031.
[7] Council of the European Union (2021), “Beyond GDP: Measuring what matters”, Issues Paper, European Union, Brussels, https://www.consilium.europa.eu/media/49818/beyond-gdp-measuring-what-matters-issues-paper-19-may-2021-web.pdf.
[8] Council of the European Union (2019), Conclusions of the Council of the European Union on the Economy of Well-being, https://www.europeansources.info/record/conclusions-on-the-economy-of-wellbeing/.
[50] Du, W. and G. Wang (2020), “Indoor air pollution was non-negligible during COVID-19 lockdown”, Aerosol and Air Quality Research, Vol. 20/9, pp. 1851-1855, https://doi.org/10.4209/aaqr.2020.06.0281.
[68] ECLAC (2021), “COVID-19 reports: People of African descent and COVID-19: Unveiling structural inequalities in Latin America”, ECLAC, Santiago.
[54] ECLAC (2021), COVID-19 Special Report No. 10: Financing for development in the era of COVID-19 and beyond: priorities of Latin America and the Caribbean in relation to financing for development policy agenda, United Nations, https://www.cepal.org/sites/default/files/publication/files/46711/S2100063_en.pdf.
[27] ECLAC (2021), Panorama Social de America Latina, https://www.cepal.org/es/publicaciones/46687-panorama-social-america-latina-2020.
[22] ECLAC (2021), The recovery paradox in Latin America and the Caribbean Growth amid persisting structural problems: inequality, poverty and low investment and productivity, https://www.cepal.org/en/publications/47059-recovery-paradox-latin-america-and-caribbean-growth-amid-persisting-structural.
[66] ECLAC (2020), Reconstruction and transformation with equality and sustainability in Latin America and the Caribbean, https://repositorio.cepal.org/bitstream/handle/11362/46130/1/2000652_en.pdf.
[59] ECLAC (2020), The part played by natural resources in addressing the COVID-19 pandemic in Latin America and the Caribbean | Insights | Economic Commission for Latin America and the Caribbean, https://www.cepal.org/en/insights/part-played-natural-resources-addressing-covid-19-pandemic-latin-america-and-caribbean?utm_source=CiviCRM&utm_medium=email&utm_campaign=20200914_natural_resources_bulletin_1.
[32] ECLAC (2020), Universalizing access to digital technologies to address the consequences of COVID-19, https://repositorio.cepal.org/bitstream/handle/11362/45939/5/S2000549_en.pdf.
[11] ECLAC (2019), Report on the Activities of the Statistical Coordination Group for the 2030 Agenda in Latin America and the Caribbean, Statistical Conference of the Americas of ECLAC.
[20] ECLAC (2017), Estrategia de Montevideo para la Implementación de la Agenda Regional de Género en el Marco del Desarrollo Sostenible hacia 2030 [Montevideo Strategy for the Implementation of the Regional Gender Agenda in the context of Sustainable Development to 2030].
[10] ECLAC (2017), Proposal on a regional framework of indicators for monitoring the sustainable development goals in Latin America and the Caribbean (Document prepared by the technical secretariat for the Statistical Coordination Group for the 2030 Agenda in Latin America and the Caribbean) | Publication | Economic Commission for Latin America and the Caribbean, ECLAC, https://www.cepal.org/en/publications/42397-proposal-regional-framework-indicators-monitoring-sustainable-development-goals.
[21] ECLAC (2016), The Social Inequality Matrix in Latin America.
[67] ECLAC et al. (2020), The impact of COVID-19 on indigenous peoples in Latin America (Abya Yala): between invisibility and collective resistance, ECLAC, Santiago.
[28] ECLAC/ILO (2020), El trabajo en tiempos de pandemia: desafíos frente a la enfermedad por coronavirus (COVID-19), https://www.cepal.org/es/presentaciones/trabajo-tiempos-pandemia-desafios-frente-la-enfermedad-coronavirus-covid-19.
[61] ECLAC and ILO (2020), “Employment trends in an unprecedented crisis: policy challenges”, Employment Situation in Latin America and the Caribbean, No. 23, https://repositorio.cepal.org/bitstream/handle/11362/46309/4/S2000600_en.pdf.
[58] Ellis, E. et al. (2017), “Private property and Mennonites are major drivers of forest cover loss in central Yucatan Peninsula, Mexico”, Land Use Policy, Vol. 69, pp. 474-484, https://doi.org/10.1016/j.landusepol.2017.09.048.
[6] European Commission (2009), GDP and beyond: Measuring progress in a changing world, https://ec.europa.eu/eurostat/cros/content/gdp-and-beyond-measuring-progress-changing-world_en.
[13] Exton, C. and L. Fleischer (forthcoming), “The future of the OECD Well-being Dashboard”, Statistics working papers, OECD, Paris.
[42] Felbab-Brown, V. (2020), “Mexican cartels and the COVID-19 pandemic.”, in Mexican cartels are providing COVID-19 assistance. Why that’s not surprising., https://www.brookings.edu/blog/order-from-chaos/2020/04/27/mexican-cartels-are-providing-covid-19-assistance-why-thats-not-surprising/.
[40] Gobierno de Mexico (2020), Informe Anual de Seguridad 2020, https://www.gob.mx/cms/uploads/attachment/file/603367/CPM_Informe_Anual_de_Seguridad_2020__31dic20.pdf.
[26] Hale, T. et al. (2021), “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)”, Nature Human Behaviour, https://doi.org/10.1038/s41562-021-01079-8.
[39] INEGI (2020), Encuesta Nacional de Seguridad Publica Urbana (Septiembre 2020), https://www.inegi.org.mx/contenidos/saladeprensa/boletines/2020/ensu/ensu2020_10.docx.
[60] Inter-American Development Bank (2018), The Future of Work in Latin America and the Caribbean: Education and Health, the Sectors of the Future?, https://publications.iadb.org/en/future-work-latin-america-and-caribbean-education-and-health-sectors-future-interactive-version.
[56] León, D. and J. Cárdenas (2020), Lessons from COVID-19 for a Sustainability Agenda in Latin America and the Caribbean, https://www.latinamerica.undp.org/content/rblac/en/home/library/crisis_prevention_and_recovery/lecciones-del-covid-19-para-una-agenda-de-sostenibilidad-en-amer.html.
[45] López-Calva, L. (2021), The Virus and the Votes: How is COVID-19 changing voter turnout in LAC?, UNDP, https://www.latinamerica.undp.org/content/rblac/en/home/presscenter/director-s-graph-for-thought/the-virus-and-the-votes--how-is-covid-19-changing-voter-turnout-.html.
[47] LSHTM CMMID COVID-19 working group (2020), How many are at increased risk of severe COVID-19 disease? Rapid global, regional and national estimates for 2020, Cold Spring Harbor Laboratory, https://doi.org/10.1101/2020.04.18.20064774.
[30] Lustig, N. and M. Tommasi (2020), Covid-19 and social protection of poor and vulnerable groups in Latin America: a conceptual framework, https://www.latinamerica.undp.org/content/rblac/en/home/library/crisis_prevention_and_recovery/covid-19-and-social-protection-of-poor-and-vulnerable-groups-in-.html.
[16] Montoya, N. and S. Nieto-Parra (forthcoming), Policymaking beyond GDP in Latin America: Case studies and lessons (forthcoming), OECD Development Policy Papers, OECD Publishing, Paris.
[44] Nugent, C. (2020), Why Armed Groups in Latin America Are Enforcing COVID-19 Lockdowns, https://time.com/5870054/coronavirus-latin-america-armed-groups/.
[71] Nussbaum, M. (2001), Women and Human Development: the Capabilities Approach, Cambridge University Press, Cambridge.
[18] OECD (2021), Perspectives on Global Development 2021: From Protest to Progress?, OECD Publishing, Paris, https://dx.doi.org/10.1787/405e4c32-en.
[55] OECD (2020), “COVID-19 and the low-carbon transition: Impacts and possible policy responses”, OECD Policy Responses to Coronavirus (COVID-19), OECD Publishing, Paris, https://doi.org/10.1787/749738fc-en.
[23] OECD (2020), “COVID-19 in Latin America and the Caribbean: Regional socio-economic implications and policy priorities”, OECD Policy Responses to Coronavirus (COVID-19), OECD Publishing, Paris, https://doi.org/10.1787/93a64fde-en.
[65] OECD (2020), “COVID-19: Protecting people and societies”, OECD Policy Responses to Coronavirus (COVID-19), OECD Publishing, Paris, https://dx.doi.org/10.1787/e5c9de1a-en.
[5] OECD (2020), How’s Life? 2020: Measuring Well-being, OECD Publishing, Paris, https://dx.doi.org/10.1787/9870c393-en.
[9] OECD (2019), OECD Economic Surveys: New Zealand 2019, OECD Publishing, Paris, https://dx.doi.org/10.1787/b0b94dbd-en.
[2] OECD (2019), “Summary and Key Messages of the ’Metrics that make a difference’ conference”, Bogotá, October 2019, https://www.oecd.org/statistics/LAC-well-being-metrics-Bogota-2019-summaryandkeymessages.pdf.
[74] OECD (2017), How’s Life? 2017: Measuring Well-being, OECD Publishing, Paris, https://dx.doi.org/10.1787/how_life-2017-en.
[75] OECD (2016), Measuring and Assessing Well-being in Israel, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264246034-en.
[73] OECD (2015), How’s Life? 2015: Measuring Well-being, OECD Publishing, Paris, https://dx.doi.org/10.1787/how_life-2015-en.
[70] OECD (2013), How’s Life? 2013: Measuring Well-being, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264201392-en.
[12] OECD (2011), How’s Life?: Measuring Well-being, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264121164-en.
[52] OECD (forthcoming), COVID-19 and Well-Being: Life in the first year of the pandemic, OECD Publishing, Paris.
[17] OECD/CAF/ECLAC (2018), Latin American Economic Outlook 2018: Rethinking Institutions for Development, OECD Publishing, Paris, https://dx.doi.org/10.1787/leo-2018-en.
[19] OECD/CAF/ECLAC (2016), Latin American Economic Outlook 2017: Youth, Skills and Entrepreneurship, OECD Publishing, Paris, https://dx.doi.org/10.1787/leo-2017-en.
[34] OECD et al. (2020), Latin American Economic Outlook 2020: Digital Transformation for Building Back Better, OECD Publishing, Paris, https://dx.doi.org/10.1787/e6e864fb-en.
[15] OECD et al. (forthcoming), Latin American Economic Outlook 2021, OECD Publishing, Paris.
[1] OECD et al. (2019), Latin American Economic Outlook 2019: Development in Transition, OECD Publishing, Paris, https://dx.doi.org/10.1787/g2g9ff18-en.
[24] Parkin, J., D. Phillips and D. Agren (2020), “Covid warnings ring out as Latin America bids to return to normality”, The Guardian, https://www.theguardian.com/world/2020/sep/19/latin-america-covid-coronavirus-warnings.
[48] Pozzer, A. et al. (2020), “Regional and global contributions of air pollution to risk of death from COVID-19”, Cardiovascular Research, Vol. 116/14, pp. 2247-2253, https://doi.org/10.1093/cvr/cvaa288.
[69] Sen, A. (1999), Development as Freedom, Knopf, New York.
[38] Statista (2020), Growth of domestic violence and sexual abuse reports during the COVID-19 lockdown in selected Latin American countries as of April 2020, https://www.statista.com/statistics/1113975/gender-violence-growth-coronavirus-latin-america/.
[3] Stiglitz, J., J. Fitoussi and M. Durand (2018), Beyond GDP: Measuring What Counts for Economic and Social Performance, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264307292-en.
[4] Stiglitz, J., A. Sen and J. Fitoussi (2009), Report by the Commission on the Measurement of Economic Performance and Social Progress, http://www.stiglitz-sen-fitoussi.fr.
[51] UN (2020), The Impact of COVID-19 on Latin America and the Caribbean, United Nations, https://www.un.org/sites/un2.un.org/files/sg_policy_brief_covid_lac.pdf.
[62] UN ECLAC (2021), COVID-19 Special Report No. 9: The Economic Autonomy of Women in a Sustainable Recovery with Equality, ECLAC, https://www.cepal.org/sites/default/files/publication/files/46634/S2000739_en.pdf.
[63] UN ECLAC (2021), Social Panorama of Latin America 2020, ECLAC.
[14] UN Statistics (2021), SDG Indicators: Global indicator framework for the Sustainable Development Goals and targets of the 2030 Agenda for Sustainable Development, https://unstats.un.org/sdgs/indicators/indicators-list/.
[31] UNESCO (2021), Education: From disruption to recovery, https://en.unesco.org/covid19/educationresponse#durationschoolclosures.
[36] UNICEF (2020), The impact of COVID-19 on the mental health of adolescents and youth, https://www.unicef.org/lac/en/impact-covid-19-mental-health-adolescents-and-youth.
[41] UNODC (2020), Research brief: Effect of the COVID-19 pandemic and related restrictions on homicide and property crime, https://www.unodc.org/documents/data-and-analysis/covid/Property_Crime_Brief_2020.pdf.
[57] Walker, W. et al. (2020), “The role of forest conversion, degradation, and disturbance in the carbon dynamics of Amazon indigenous territories and protected areas”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 117/6, pp. 3015-3025, https://doi.org/10.1073/pnas.1913321117.
[37] WHO (2020), Mental health and COVID-19, https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/technical-guidance/mental-health-and-covid-19.
[46] World Bank (2021), Acting Now to Protect the Human Capital of Our Children : The Costs of and Response to COVID-19 Pandemic’s Impact on the Education Sector in Latin America and the Caribbean, https://openknowledge.worldbank.org/handle/10986/35276.
[53] World Bank (2021), Global Economic Prospects, https://www.worldbank.org/en/publication/global-economic-prospects.
[49] Wu, X. et al. (2020), Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study, Cold Spring Harbor Laboratory, https://doi.org/10.1101/2020.04.05.20054502.
[35] YouGov (2020), How COVID-19 is affecting mental health across the globe, https://today.yougov.com/topics/health/articles-reports/2020/12/10/covid-19-mental-health-global.
Notes
← 1. GDP, in particular, often dominates discourse on progress. While capturing people’s welfare in a broad sense was never the intended purpose of the GDP indicator, its ease of communication, the frequency and timeliness with which it is reported, the well-established national accounts framework on which it is based, and the high level of standardisation in its compilation – coupled with the fact that it summarises information across the whole economy – makes it an exceptionally useful tool for monitoring macro-economic performance. Nevertheless, as a purely economic, system-level measure, GDP conveys no information about social and environmental outcomes that are not traded in markets, yet have great value to people; GDP cannot provide information on the distribution of welfare across a society (thus ignoring inequality aspects); and, crucially, it lacks a forward-looking perspective that can encompass issues of sustainability and inter-generational impact. GDP excludes the value of many unpaid activities that contribute to the economy indirectly (and that are socially indispensable), but that cannot currently be traced through the System of National Accounts, such as unpaid household work, domestic care and volunteering. It also includes the value of other activities that cannot be considered aspects of “progress” or that are even detrimental to well-being and sustainability, such as the cost of increasing policing and prison budgets to tackle rising crime, or clean-up costs after environmental disasters.
← 2. Key influences on the framework include the capabilities approach, as set out in Sen (1999[69]) and Nussbaum (2001[71]) as well as the recommendations of the Commission on the Measurement of Economic Performance and Social Progress, led by Joseph Stiglitz (Stiglitz, Sen and Fitoussi, 2009[4]). In addition to the academic and expert literature, the framework also builds on national and regional experiences, including public consultations, focused on the aim of going “Beyond GDP”, as well as interactions with hundreds of practitioners from all sectors of society in the OECD World Forums on Statistics, Knowledge and Policy held every two or three years since 2004. See the first and second editions of How’s Life? (OECD, 2011[12]) (OECD, 2013[70]) for more on the background and conceptual underpinnings of the framework.
← 3. A comparison of 20 national well-being measurement dashboards with the OECD framework indicators shows that there is a high degree of overlap in most cases (Exton and Fleischer, forthcoming[13]).
← 4. For example, the OECD and the OECD Development Centre produced an adapted framework that reframes some of the dimensions to better take into account developing-country perspectives (Boarini, Kolev and McGregor, 2014[72]). The framework has also been adapted to focus on the specific needs or priorities of regions (https://www.oecdregionalwellbeing.org/), children (OECD, 2015[73]) and migrants (OECD, 2017[74]), as well as being applied in national contexts such as Israel (OECD, 2016[75]).
← 5. Seven national statistical offices from the LAC region (Chile, Colombia, Costa Rica, Ecuador, Mexico, Panama and Uruguay) responded to a questionnaire sent in May 2016 on what would need to be changed about the OECD framework to reflect LAC priorities.
← 6. SDG Global Framework Indicator 10.3.1: Proportion of population reporting having personally felt discriminated against or harassed in the previous 12 months on the basis of a ground of discrimination prohibited under international human rights law.
← 7. With the partial exception of Chapter 5, where due to data limitations, as well as to the need to keep the chapters to a reasonable length, only a small selection of indicators are presented with country-level results and the remainder are summarised with averages for the 11 focal countries (or for the maximum number of focal countries with available data).
← 8. Comparable LAC 11 average data prior to 2012 are not available for the labour force data included here: time series begin in 2012 for employment and unemployment; in 2011-13 for time-related underemployment; and in 2012-13 for informal employment as a share of total employment.
← 9. The average trend is mostly driven by a drastic decrease in Colombia (-42 points), coupled with considerable falls in Paraguay (-12 points) and Ecuador (-9 points). However, there have been substantial rises in Mexico (+18 points), Peru (+8 points) and Uruguay (+6 points).
← 10. This index was developed by the WHO to measure progress towards SDG target 3.8 and is defined as the average coverage of essential services based on tracer interventions that include reproductive, maternal, newborn and child health, infectious diseases, non-communicable diseases and service capacity and access, among the general and the most disadvantaged population. The index uses a unitless scale of 0 to 100, which is computed as the geometric mean of 14 tracer indicators of health service coverage. The tracer indicators are as follows, organised by four components of service coverage: 1. Reproductive, maternal, newborn and child health; 2. Infectious diseases; 3. Noncommunicable diseases; and 4. Service capacity and access. See the 2019 monitoring report for the tracer indicator within each component. For further details, see: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/uhc-index-of-service-coverage
← 11. From domestic production, excluding emissions from land use, land use change and forestry (LULUCF).
← 12. Comparable OECD data are not available for Figure 1.12; this finding is drawn from the World Values Survey (see Chapter 4 for further details).
← 13. The gender pay gap is defined as the difference between the mean monthly earnings of men and women, relative to the mean monthly earnings for men.
← 14. According to the definition provided by ECLAC, unpaid work includes unpaid goods and services produced by household members for their own consumption, as well as domestic, home care, household and community work.
← 15. Prevalence estimates were extracted for the following disease categories by age, sex and country: (1) cardiovascular diseases (CVD), including CVD caused by hypertension; (2) chronic kidney disease (CKD), including CKD caused by hypertension; (3) chronic respiratory disease; (4) chronic liver disease; (5) diabetes; (6) cancers with direct immunosuppression; (7) cancers without direct immunosuppression, but with possible immunosuppression caused by treatment; (8) HIV/AIDS; (9) tuberculosis; (10) chronic neurological disorders; and (11) sickle cell disorders.