In many respects, people’s well-being has improved in OECD countries since 2010. However, progress has been slow or deteriorated in some dimensions of life, including how people connect with each other and with their government. Large gaps by gender, age and education persist across well-being outcomes. Generally, OECD countries that do better on average tend to have greater equality between population groups and fewer people living in deprivation. The greatest gains in current well-being have often been concentrated in countries that had weaker well-being at the start of the decade. While these gains have sometimes gone hand in hand with recent GDP growth, this has not always been so, underscoring the need to look beyond GDP when measuring progress. Gains in current well-being have often not been matched by improvements in the resources needed to sustain it over time, with systemic risks emerging across Natural, Human, Economic and Social Capital.
How's Life? 2020
1. How’s Life? in OECD countries
Abstract
To understand how people and societies are doing, and to design effective public policies to improve well-being, governments need to look beyond the functioning of the economy, to also consider a diverse range of living conditions. For this, we need data and statistics that reflect people’s lives in areas such as income, health, life satisfaction, safety and social connections. It requires looking beyond average numbers to understand not only whether life is getting better, but also where it is getting better and for whom. Finally, it requires measuring not just well-being today, but also the resources that will help to sustain well-being into the future.
The OECD Well-being Framework, which charts whether life is getting better for people (Box 1.1), has never been more relevant. Concerns around data gaps, and the absence of statistics which speak to the full range of people’s living conditions, were already evident during the decade of moderate GDP growth and low inflation (“the Great Moderation”) prior to 2007. The 2008 financial crisis and the ensuing political disruptions, social dissatisfaction and civil unrest in several OECD countries has further amplified the need for better data about people’s experiences and circumstances. The United Nations Sustainable Development Goals have brought new impetus to policy efforts to put people, their prosperity, peace, partnerships and the long-term health of the planet at the forefront. The importance of well-being is increasingly being recognised by national governments, several of which have designed well-being frameworks similar to the OECD’s. Some OECD governments have also started to develop tools for the integration of people’s well-being into their strategic objectives and agenda-setting, policy analysis and budgetary processes (Durand and Exton, 2019[1]; OECD, 2019[2]; Fleischer, Frieling and Exton, 2020[3]).
So, is life getting better for people in OECD countries? How’s Life? 2020 (Box 1.2) shows that well-being has, in some respects, improved relative to 2010, a year when the impacts of the financial crisis were still being felt in most OECD countries. Across the OECD, people now have a higher disposable income and are more likely to be employed. People are also living longer, are more satisfied with their lives and are less likely to inhabit crowded households. Homicide rates have fallen, and in general, people report that they feel safer.
Yet progress has been slow, or has even deteriorated in other areas, many of which pertain to the quality of personal relationships and to how people connect with each other and with their government. These developments call for closer monitoring and, more fundamentally, policy action: income inequality, the share of income that households in OECD countries spend on housing costs, whether people feel supported in times of need, and voter turnout have stagnated since 2010. Household median wealth, students’ performance on the Programme for International Student Assessment (PISA) science tests, and the time people spend interaction with friends and family have all decreased. Furthermore, stark differences by gender, age and education persist across most aspects of well-being.
OECD countries that are more successful in terms of achieving high levels of average well-being also evidence greater equality between socio-demographic groups (such as by gender, age or education), and between top and bottom performers in each well-being dimension, and they have fewer people living in deprivation. Generally speaking, people in the countries traditionally associated with high well-being, i.e. the Nordic countries, the Netherlands, New Zealand and Switzerland, enjoy both comparatively higher levels of current well-being and lower inequalities. Yet some of the most equal countries have experienced little change, or even widening inequalities since 2010.
The good news is that many OECD countries that initially evidenced poorer well-being have been catching up in the last decade: these countries, many of them in eastern Europe, have experienced the largest number of improvements across the well-being indicators considered in this chapter, and the largest number of reductions in inequalities since 2010. While some of these well-being gains have gone hand in hand with higher GDP growth, this has not always been the case, underscoring the need to look beyond GDP growth as the sole indicator of progress (Box 1.5).
Looking forward, there is no room for complacency and all OECD countries will need to take a more future-oriented approach in order to sustain the well-being of people and the planet in the longer run. This is critical given the challenges that OECD governments are currently facing, in particular warnings of prolonged economic stagnation and the potential for further natural and social disruptions ahead (OECD, 2019[4]). There are clear warning signs with respect to both Economic and Natural Capital, and there has been virtually no progress with respect to Social Capital since 2010. For example, government and household debt have deepened in countries where both were already well below the OECD average. Climate change poses a formidable threat to future well-being, with global greenhouse gas emissions from energy use reaching their highest level ever in 2018. OECD countries are consuming more of Earth’s materials, per capita, than in 2010, and more species are threatened. Trust in government remains low, and gender parity in politics, while creeping forward, continues to be a distant goal.
Despite these risks to future well-being, there have been some gains in Human Capital across the OECD. Since 2010, a growing share of young adults completed upper secondary education (even though performance in test scores points to some declines in the quality of education), fewer workers are unemployed, discouraged or underemployed1, and premature mortality has been reduced. But overall, countries’ advances in current well-being have not always been matched by improvements in resources needed to sustain it over time. In the years to come, OECD countries will need to look beyond maximising well-being today and take a more holistic approach in balancing investments across all facets of well-being.
Box 1.1. The OECD Well-being Framework
How’s Life? provides key statistics on whether life is getting better for people living in OECD countries. Current well-being data focus on living conditions at the individual, household and community levels, and describe how people experience their lives “here and now”. These data are complemented by statistics on the resources needed to sustain well-being in the future: specifically, via “capitals”, countries’ investments in (or depletions of) these capitals, and risk and resilience factors that will shape future changes in well-being. Separate reporting of current well-being and its sustainability helps to assess whether maximising the former comes at the cost of compromising the latter (or vice versa), which can inform intertemporal trade-offs in policy design and indicate the intergenerational outlook of a country’s well-being.
In the OECD Well-being Framework (Figure 1.1), current well-being is comprised of 11 dimensions. These dimensions relate to material conditions that shape people’s economic options (Income and Wealth, Housing, Work and Job Quality) and quality-of-life factors that encompass how well people are (and how well they feel they are), what they know and can do, and how healthy and safe their places of living are (Health, Knowledge and Skills, Environmental Quality, Subjective Well-being, Safety). Quality of life also encompasses how connected and engaged people are, and how and with whom they spend their time (Work-Life Balance, Social Connections, Civic Engagement).
As national averages often mask large inequalities in how different parts of the population are doing, the distribution of current well-being is taken into account by looking at three types of inequality: gaps between population groups (e.g. between men and women, old and young people, etc., collectively described as horizontal inequalities); gaps between those at the top and those at the bottom of the achievement scale in each dimension (e.g. the income of the richest 20% of individuals compared to that of the poorest 20%, referred to as vertical inequalities); and deprivations (i.e. the share of the population falling below a given threshold of achievement, such as a minimum level of skills or health).
The systemic resources that underpin future well-being over time are expressed in terms of four types of capital, i.e. stocks that last over time but are also affected by decisions taken (or not taken) today. Economic Capital includes both man-made and financial assets; Natural Capital encompasses natural assets (e.g. stocks of natural resources, land cover, species biodiversity) as well as ecosystems and their services (e.g. oceans, forests, soil and the atmosphere); Human Capital refers to the skills and future health of individuals; and Social Capital refers to the social norms, shared values and institutional arrangements that foster co-operation. Many of these capital stocks and flows stretch well beyond those “owned” by private agents and are, effectively, public goods: for example, an individual’s beliefs in how much others can be trusted contributes to the overall atmosphere of interpersonal trust in a country or community, while greenhouse gas emissions in one country influence the world’s overall climate. In addition to considering capital stocks and flows, How’s Life? also highlights some key risk and resilience factors that might affect the well-being value of those stocks and flows in future. For example, household debt poses risks to future economic prospects, while the inclusiveness of decision-making in politics can be a protective factor for well-being.
How’s Life? over time
How’s Life? 2020 is the 5th edition in the series, which started with the launch of the OECD’s Better Life Initiative in 2011. Since then the OECD’s work on well-being has evolved significantly, with several improvements following a thorough review of the Well-being framework and indicators in 2019 (Exton and Fleischer, 2020[5]). These are reflected in How’s Life 2020 and include a cleaner distinction between well-being today and the resources needed to sustain it in the future (i.e. eliminating the indicator overlap that existed previously between these two categories2); the rebranding of some dimensions of current well-being; and the extension of the Well-being Dashboard to over 80 indicators, including new data on the environment, mental health, time use, unpaid work and satisfaction with personal relationships and with how time is spent.
Box 1.2. How to read this book
How’s Life? 2020 consists of three parts:
“How’s Life in OECD countries?” – an overview of well-being (Chapter 1)
Detailed information on each well-being dimension, showing averages, inequalities and changes over time, indicator-by-indicator (Reference Chapters 2 to16)
Key statistics on well-being performance for each OECD and partner country (country profiles available online-only at http://oecd.org/howslife).
The present chapter presents an overall analysis of well-being trends since 2010, based on a small set of headline indicators. It provides a high-level perspective on the more in-depth evidence provided in the Reference Chapters 2 to 16, which include the full range of results for the more than 80 indicators in the OECD Well-being Dashboard. Readers interested in more information about a specific dimension of well-being, such as Health, can turn to the respective Reference Chapter and find country-by-country data on different health outcomes, how these have changed over time, and how health differs between various groups in society. These chapters also contain information on measurement methods and on the critical data gaps that still need to be filled to provide a more comprehensive picture of people’s well-being.
The headline indicators used in Chapter 1 have been chosen for more concise communication and to highlight key findings: 12 headline indicators of current well-being averages, 12 indicators of current well-being inequalities and 12 indicators of resources for future well-being (see Annex 1.A). Unless otherwise indicated, Chapter 1 refers only to these headline sets.
How’s Life in the OECD?
Income and Wealth, Housing, Work and Job Quality
Material aspects shape people’s economic conditions and can have wide-ranging consequences for other aspects of life, such as education and health. Key dimensions are Income and Wealth, which together determine people’s consumption possibilities; Housing, which provides shelter, safety, privacy and personal space; and Work and Job Quality, which are about both the availability of job opportunities and people’s working conditions in paid employment.
According to 2017 or the latest available data, average annual household income in the OECD is approximately USD 28 000, and median household wealth is around USD 162 000. On average, the 20% of people at the top of the distribution have an annual income which is 5.4 times higher than that of people in the bottom 20%. Households in OECD countries spend just over 21% of their disposable income on housing, and 12% of households live in overcrowded conditions. Almost eight in ten adults aged 25-64 in the OECD are in paid employment. Overall, 7% of paid employees routinely work very long hours (i.e. 50 hours or more each week), and women earn almost 13% less than men annually (Table 1.1).
Compared to 2010, people in OECD countries have, on average, experienced improvement in some aspects of their material conditions, as several economies recovered from crisis. Specifically, household disposable income and employment rates both picked up between 2013 and 2017, increasing by approximately 6 and 5 percentage points, respectively. The overcrowding rate fell by nearly 3 percentage points, mainly due to a steep drop between 2010 and 2011. Close to one-third of OECD countries made consistent progress on reducing the gap between male and female earnings between 2010 and 2017. However, the average gender wage gap only shrank by only just over 1 percentage point over this time, and at nearly 13% remains far from parity (Figure 1.2).
Little progress has been achieved since 2010 with respect to reducing average income inequality or improving housing affordability (despite increasing household incomes) (Figure 1.3). Moreover, for the 15 countries with available data, median household wealth decreased by 4%, on average, since around 2010. In some OECD countries, part of this decrease in household wealth can be attributed to rising house prices (OECD, 2017[6]).
There are key statistics worth highlighting beyond the headline indicators on material conditions shown here (see Reference Chapters 2 to 4). For example, the wealthiest 10% of households own more than half of all household wealth. While 12% of the population in OECD countries live in relative income poverty (based on a threshold of half the national median), the share of those reporting difficulties making ends meet in European OECD countries is almost twice as high (21%). Since 2010, people’s ability to make ends meet has improved on average, while relative income poverty remained stable. Meanwhile, more than 1 in 3 people in those OECD countries with available data can be considered as financially insecure, meaning they do not have enough liquid financial wealth to support their household at the income-poverty level for more than three months in the event of an income shock. Among low-income households, around one in five spend over 40% of their disposable income on rent and mortgage costs. Furthermore, 1 in 10 youth (aged 15-24) are not in employment, education or training (compared to the overall employment rate of 76%), a rate that has fallen only slightly (by 2 percentage points) since 2010.
Health, Knowledge and Skills, Environmental Quality, Subjective Well-being, Safety
Quality of life is about personal experiences and environmental conditions: how well people are and how well they feel, and how healthy and safe their surroundings are. This includes the well-being dimensions of Health (a long life unencumbered by physical or mental illness, and the ability to participate in activities that people value), Knowledge and Skills (what people know and can do), Environmental Quality (free from pollution and including access to amenities), Subjective Well-being (good mental states and how people experience their lives) and Safety (freedom from harm).
A newborn in 2017 can expect to live 80.5 years, on average, across all OECD countries. As life goes on, strong education and income-related inequalities come into play: on average, a man aged 25 who has completed tertiary education can expect to live 7.6 years longer than a peer with low education, i.e. no schooling or up to lower secondary educational attainment. In the case of women, the same gap is 4.8 years. On average, approximately one of every eight 15 year-old students has skills below “baseline” levels, meaning they score low in all three subjects of maths, reading and science, as assessed by the OECD’s PISA survey. In European OECD countries, 93% of the urban population can walk to a park or other green spaces within 10 minutes of their home. As of 2017, over 60% of the population across all OECD countries are exposed to a level of fine particulate matter (PM2.5) air pollution above 10 micrograms/m3, the threshold considered as harmful to human health by the World Health Organisation (WHO). Across the OECD, the number of deaths due to assault is 2 per 100 000 people, with most of these deaths being young men in the Americas and men aged 30-44 in European and Asian countries (UNODC, 2019[7]). On average in the OECD, men report feeling safer than women: eight in ten men compared with six in ten women say they feel safe when walking alone at night in the neighbourhoods where they live. When people are asked how satisfied they are with their lives on a scale from 0 (not at all satisfied) to 10 (completely satisfied), the average evaluation in OECD countries is 7.4. Approximately 1 in 8 people experience more negative (anger, sadness, worry) than positive (enjoyment, laughing or smiling a lot, well-rested) feelings in a typical day (Table 1.2).
Compared to 2010, homicide rates fell on average by 0.8 deaths for 100 000 people, and the gender gap in feeling safe when walking alone at night narrowed by 3.5 percentage points. Moreover, newborns in OECD countries are expected to live about 1 year and 2 months longer, people aged 15 and over are slightly more satisfied with their lives (compared to 2013), and fewer people are exposed to harmful air pollution (Figure 1.4). However, there are important qualifications: in some countries with already high levels of longevity (such as Iceland, Germany, Greece and the United Kingdom), life expectancy is starting to plateau, and there have been no net gains since 2010 in the United States. Levels of air pollution have decreased by almost 12 percentage points since 2005, but improvements have not always occurred where the situation was most critical: in 10 OECD countries (the Czech Republic, Greece, Hungary, Israel, Korea, Mexico, the Netherlands, Poland, the Slovak Republic and Slovenia) almost the entire population continues to be exposed to dangerous levels of PM2.5.
Little progress has been achieved for negative affect balance (the share of the population reporting more negative than positive feelings and states in a typical day), which has remained relatively stable since 2010-12. Student’s cognitive skills in science have meanwhile declined overall (Table 1.2).
Social Connections, Civic Engagement, Work-Life Balance
Quality of life is also about the quality of relationships: how connected and engaged people are, and how and with whom they spend their time. Key dimensions include Social Connections (both the quantity and quality of time spent with others, and how supported people feel), Civic Engagement (whether or not citizens can and do take part in important civic activities that enable them to shape the society in which they live) and Work-Life Balance (being able to balance family commitments, leisure time and work – whether paid or unpaid3).
On average across OECD countries, people spend approximately 6 hours per week in social interactions (such as talking with family members or going out with friends4). Overall, almost 1 in 10 people express a lack of social support, i.e. say they do not have relatives or friends they can count on for help in times of need. Nearly 70% of the population registered to vote cast a ballot in the last election, but almost half (46%) of people report feeling they have no say in what their government does. Full-time employees have on average 15 hours per day of “time off” – i.e. time spent on leisure and personal care (including sleep). If both paid and unpaid work are taken into account, women work longer hours than men in almost every OECD country, on average by almost 25 minutes per day, or 12.5 hours per month (Table 1.3).
The overall trend across these relational dimensions is stable or slightly negative, in contrast with the tendency towards improvement for well-being indicators related to material conditions and the individual-level aspects of quality of life. Trends in time use for many relational facets of well-being are not available for most countries, however, with only six OECD countries (Belgium, Canada, Italy, Korea, Japan and the United States) having conducted at least two time-use surveys over the past two decades. The data that are available show that, among these countries, people’s time off for leisure and personal care has not increased since the mid-2000s. Meanwhile, average weekly time spent in social interactions has fallen by 20 minutes or more in four of these countries: by around half an hour in Canada, Italy and the United States, and by a little more than 40 minutes in Belgium (Table 1.3). The average share of people lacking social support and voter turnout in OECD countries have remained stable since 2010-13 (Figure 1.5).
In which countries is life getting better or worse?
Across the headline indicators considered here, OECD countries with higher average current well-being also tend to be more equal, i.e. they have a lower share of people who are deprived, and there are smaller gaps in the distribution of well-being outcomes and fewer differences between population groups (Figure 1.6). Generally speaking, people in the Nordic countries, the Netherlands, New Zealand and Switzerland enjoy both comparatively higher levels of current well-being and lower inequalities. On the other hand, people in eastern European and Latin American countries as well as Turkey and Greece experience relatively lower levels of current well-being and are exposed to comparatively deeper inequalities. There are exceptions: Denmark performs better on inequalities compared to its well-being levels, while Austria, Korea and Germany are relatively unequal, given their average well-being scores.
Average trends for the OECD area as a whole often mask what happens at the country level. When considering member states’ development since 2010, it becomes clear that no country has consistently improved, or consistently deteriorated, in every aspect of current well-being captured by the headline indicators (Box 1.3). Rather, there are visible differences in well-being stories.
Box 1.3. Assessing trends in well-being: A note on methodology
To identify the areas of well-being which call for closer monitoring and policy attention, it is essential to know with some degree of confidence whether an outcome is genuinely improving or worsening over time. How’s Life? 2020 uses two types of analysis to classify trends:
For indicators with sufficient time series (a minimum of 3 observations per country), movement over the entire period since 2010 is taken into account to detect whether the overall trend is positive or negative. This is because restricting the analysis to change between the start and end points of an indicator (i.e. 2010 and 2018) carries the risk of catching an unusual year and over- or under-estimating actual change. Whenever there are sufficient time series for at least 75% of all countries for which data exists, How’s Life therefore uses the Spearman (rank) correlation coefficient between the observed values of each indicator and time (expressed in years). Countries are classified as “consistently improving” or “consistently deteriorating” if the Spearman correlation is significant at least at the 10% level, and as “no clear trend” otherwise. Figure 1.7 illustrates this: Even though household disposable income in Italy was lower in 2017 than in 2010, it has actually declined for 3 years over this period and increased for 4. The results of the Spearman method thus render this as “no clear trend”.
For indicators with insufficient time series (i.e. fewer than 75% of all countries for which data exists have at least 3 observations), change over time has been assessed as the simple point change between 2010 (or the closest available year) and 2018 (or the latest available year). A country is classified as “improving”, “deteriorating” or “no clear trend” with reference to indicator-specific thresholds (Table 1.4). These thresholds take a number of factors into consideration, including the total magnitude of change observed among OECD countries (both in absolute unit values and in percentage terms), the univariate distribution of values among OECD countries, and the likely margin of error in the estimated values.
Limitations
Missing data limit the ability to fully assess changes over time in many countries and underscores the need for more frequent collection of official well-being statistics. For example, more than half of OECD countries (23) have insufficient information to determine trends for at least one-third of the 12 headline indicators for averages in current well-being. Half of these metrics are missing for Australia, Iceland, Turkey and New Zealand, and almost 60% for Colombia and Israel. There are even more gaps in terms of inequalities in current well-being, where all OECD countries are missing information for at least one-third of the 12 headline indicators. For some headline measures, no OECD country has more than one data point: access to green space, gaps in life expectancy by education, the share of students with low skills, the gender gap in hours worked, and the share of people who feel they have no say in what the government does. Across the wider OECD well-being dataset (Reference Chapters 2 to 16), there are many more gaps that hinder meaningful analysis.
Table 1.4. Thresholds for assessing change in well-being headline indicators with insufficient time series
Indicator |
Unit of measurement |
Threshold |
---|---|---|
Income and Wealth |
||
Household wealth |
Median net wealth, USD at 2016 PPPs |
+/-9 000 USD |
Knowledge and Skills |
||
Student skills in science |
PISA mean scores |
Based on confidence intervals provided by the OECD Education Directorate |
Subjective Well-being |
||
Life satisfaction |
Mean value on a 0-10 scale |
+/-0.2 scale points |
Safety |
||
Gender gap in feeling safe |
Percentage difference that women feel less safe than men when walking alone at night |
+/-5.0 percentage points |
Work-Life Balance |
||
Time off |
Hours per day |
+/-20 min |
Social Connections |
||
Social interactions |
Hours per week |
+/-20 min |
Civic Engagement |
||
Voter turnout |
Share of registered voters who cast votes |
+/-3 percentage points |
Trends in average well-being headline indicators since 2010, by country
Across most of the headline indicators of current well-being, average scores have either improved or shown no clear change since 2010 (Figure 1.8). Life expectancy, employment rates and disposable household income have consistently improved for more than half of OECD countries. Norway is the only country for which employment rates have significantly declined, and Austria and Greece are the only two countries with consistent falls in household net adjusted disposable income. Homicide rates have consistently declined in 18 out of 37 OECD countries, and life satisfaction has risen for 15 out of 27 OECD countries. In other aspects, trends diverge: relative to 2010-12, most OECD members experienced no clear change for voter turnout while, among the remaining countries, there were increases in eight but falls in seven (with Latvia and Slovenia experiencing drops exceeding 10 percentage points). Housing affordability has improved in 11 OECD countries, but consistently worsened in 10. In Finland, Ireland and Portugal, households now spend over 2 percentage points more of their income on housing than they did in 2010.
Several outcomes worsened between 2010 and 2018 for a majority of OECD countries with available data. For example, students’ scores on the PISA science tests have significantly deteriorated for a slight majority of OECD countries. Among the subset of countries with available information, household median wealth fell in twice as many countries as where it improved. In Greece, median household wealth decreased by 40% since 2010. No OECD country has improved in terms of time use, i.e. the time spent on leisure and personal care, or on social interactions compared with 2010 or the latest available year. Indeed, the amount of people’s time spent in social interactions has fallen by around half an hour in Canada, Italy and the United States, and by a little over 40 minutes in Belgium.
Canada, the Czech Republic, Estonia, Hungary, Korea, Germany, Poland and the United Kingdom experienced the highest number of gains in current well-being averages (i.e. the largest number of headline indicators improving since 2010) (Figure 1.9). Some of these top performers, e.g. Germany, started from a position of comparatively high well-being in 2010. But often progress has been concentrated among those countries that started from a lower baseline level, and therefore have more room to rise (Figure 1.10). For example, Hungary is the only OECD country where more than half of well-being averages improved: household disposable income, the employment rate, housing affordability, life expectancy, life satisfaction and voter turnout have all risen, while homicide rates have fallen. Nevertheless, Hungary remains in the bottom third of the OECD on these indicators, as does the other top improver, Poland (Figure 1.6).
On the other hand, the countries with the lowest number of gains in well-being since 2010 include Belgium, Finland, Iceland, Luxembourg, New Zealand and the United States (Figure 1.9). While generally strong performers on average well-being, in Iceland only the employment rate steadily rose, while in New Zealand only household incomes and life expectancy consistently improved.5
Positive developments in some aspects of life do not automatically translate into improvements in others. For example, while Canada is among the top OECD countries that have improved across half of their headline indicators of average well-being, the share of income that households devote to housing costs, students’ cognitive skills in science, and time spent interacting with friends and family have all deteriorated there since 2010. Greece experienced the largest number of falls in average well-being (Figure 1.9), with a consistent worsening since 2010 in student skills, voter turnout, disposable income and median household wealth.
Trends in inequalities in well-being headline indicators since 2010, by country
In contrast to the overall rise in current well-being, OECD countries have been somewhat less successful at reducing inequalities, with progress across the board less evident (Figure 1.11). The share of employees regularly working long hours and exposure to harmful air pollution are the only headline measures in which most (i.e. half or more) OECD countries have consistently reduced the level of deprivation since 2010. Yet while 32 countries consistently reduced exposure to fine particulate matter (PM2.5) in 10 OECD countries (the Czech Republic, Greece, Hungary, Israel, Korea, Mexico, the Netherlands, Poland, the Slovak Republic and Slovenia) almost the entire population continues to be exposed to dangerous levels.
For all other inequalities in the headline set, the typical pattern is one of “no clear change”. Often, the patterns for the subset of countries that do show a consistent trend since 2010 point in different directions. For example, the share of people lacking social support has risen in roughly as many countries (9) as where it has declined (10). One of these countries is Greece, where almost 1 in 5 people say they have no one to count on for help in times of need. At the same time, while 5 OECD countries have consistently reduced the income gap between the richest and poorest 20% of the population since 2010, this measure of income inequality has increased in over twice as many countries as it has declined (11). Compared to other OECD countries, it increased most – by over 30% – in Lithuania, where the richest 20% of the population now earn almost 8 times more than the bottom 20%.
Relative to other OECD countries, the Czech Republic and the Slovak Republic made good progress in reducing inequalities, with 40% of indicators consistently improving between 2010 and 2018 (Figure 1.12). In both countries, the share of employees working long hours, the number of households living in overcrowded conditions, and those reporting more negative than positive feelings and states (or those with a negative affect balance) have fallen. In addition, income inequality and air pollution fell in the Czech Republic, while the gender gap in feeling safe when walking alone at night narrowed, and there are fewer people expressing lack of social support in the Slovak Republic.
By contrast, Korea, Norway and the United States each consistently improved in only one type of inequality since 2010: gender gaps in feeling safe in Korea and exposure to harmful air pollution in Norway and the United States. Inequalities have widened on the largest number of headline measures (3 in total) in Denmark, Sweden and the United States. In all three countries, a consistently larger share of households now live in overcrowded conditions, and more people feel they have no one to ask for help in times of need. In addition, the two Nordic countries have also seen consistently higher income inequality, while in the United States the share of the population reporting more negative than positive feelings in a typical day steadily increased.
The countries with the largest number of improvements in inequalities since 2010 are sometimes those where the gaps were widest in the first instance (Figure 1.13). For example, while income inequality has steadily narrowed in Mexico, the richest 20% still earn ten times more than those at the bottom of the income distribution – the highest level of income inequality among OECD countries, alongside Chile. Likewise, Japan’s gender wage gap has contracted since 2010, but remains within the bottom third of OECD countries.
At the other end of the spectrum, some of the Nordic and Anglophone countries that have traditionally fared very well on international comparisons of inequality experienced a fall in their rankings. For example, when taking into account both improvements and areas of no clear change, Denmark, Norway and Sweden (although top performers in terms of both inequalities and average well-being) have overall become less equal since 2010, together with the United States. Similarly, New Zealand and the Netherlands have overall stagnated in terms of inequality reduction when all headline inequalities are considered together.
Who has a good life?
Inequalities are about going beyond averages and zooming in on “who gets what?” Horizontal inequalities highlight the well-being achievements and disadvantages faced by different groups (e.g. women and men, and people of different ages and education).
Well-being inequalities between women and men
Average differences between women and men for life satisfaction, voter turnout, time off, and adults’ skills in reading and numeracy are generally very small (Figure 1.14). In 2018, 15 year-old girls and boys achieved similar test scores in maths and science – a first since the launch of OECD’s PISA studies in 2000 – while girls continue to slightly outperform boys in reading (see Reference Chapter 6).6
There are large gender differences in experiences of work. Men are more likely to be employed – the OECD average employment rate is 83% for men versus 70% for women – and earn 13% more. However, men are also more than twice as likely to work long hours regularly (50 or more hours per week). Yet, when both paid and unpaid work (i.e. time spent doing routine housework, care work for children and adults, shopping for goods and services for the household, and travel related to household activities) are taken into account, women work longer hours than men in almost every OECD country, on average by almost 25 minutes per day, or 12.5 hours per month (see Reference Chapter 10). Indeed, in every OECD country, men with a paid job spend longer hours at work than women do (90 minutes more per day on average), but even in the most equal countries with available data, women systematically spend longer hours than men in unpaid work (around 2 hours more per day for the OECD average). Even in countries where gender differences in time spent on paid work are small (e.g. Estonia), women still do the lion’s share of unpaid work. On the other hand, population-wide measures of satisfaction with time use (among people aged 16 or over) show few clear gender differences, and their direction differs across countries.
In terms of social connections, men spend on average 40 minutes less per week in social interactions relative to women, and are 10% more likely to say they lack social support. Experiences of safety also contrast strongly between women and men: on the one hand, men in OECD countries are 4.5 times more likely to die due to assault, mainly reflecting the high values observed in Colombia (where men are more than ten times more likely than women to be homicide victims) and Mexico (where the same ratio is above eight). On the other hand, on average eight in ten men but only six in ten women report feeling safe when walking alone at night, possibly reflecting women’s greater risk of contact crimes and sexual assault.
Regarding health, newborn girls can expect to live on average five years longer than boys. Men are also around four times more likely to die from “deaths of despair” (i.e. fatalities from suicide and acute substance abuse). Nevertheless, compared to 2010, deaths of despair among women are on the rise, having increased in one-third of OECD countries. Overall, the OECD toll of deaths of despair for both genders – while still a small share of overall deaths – is three times higher than road deaths, and six times higher than deaths from homicide (see Reference Chapter 5).
Well-being inequalities by age
In all OECD countries, there are notable well-being differences between younger people (aged 15-24/29), the middle-aged (aged 25/30 to 45/50) and older people (aged 50 and over) (Figure 1.15). On average, younger people are more satisfied with their lives and are just over half as likely to lack social support compared to their middle-aged peers. Gaps in well-being outcomes related to work and time-use partly reflect life cycle factors and labour market experiences of different age groups: middle-aged people are twice as likely to be employed (employment rates are 81% for middle-aged people compared to 41% for young adults) and earn on average USD 8 (at 2018 PPPs) more per hour. Meanwhile, they are also almost 50% more likely to work very long hours in paid employment, and time off is lowest during middle age. For the 13 OECD countries with available and harmonised data, younger and older full-time employed people enjoy, on average, around 50 and 25 additional minutes of time off per day, respectively, compared to those aged 30-49. Across age groups, those aged 30-49 are also the least satisfied with how they spend their time (see Reference Chapter 10).
Voter turnout among older people (people aged 50 and over) is 17 percentage points higher than among younger people, with elderly people also faring better in the labour-market related aspects of well-being (i.e. being employed and earning more). However, younger people score better on skills tests and are more satisfied with their lives, and a larger share report that they feel safe when walking alone and night and that they have a say in what the government does (though patterns for the latter vary, depending on the country – see Reference Chapter 12). Older people are almost three times more likely than young people to say they have no friends or family members to turn to for help in case of an emergency, underscoring the importance of addressing old-age loneliness.
Well-being inequalities by education
Positive returns to education and the individual characteristics and socio-economic circumstances of those who pursue higher degrees can translate into better well-being outcomes. People who completed tertiary education fare better in most areas of well-being compared to those with only an upper-secondary education, with the exception of regularly working long hours in paid employment (Figure 1.16). For example, voter turnout among more educated people is more than 6 percentage points higher, and 43% of people with a tertiary degree feel they have a say in what the government does compared to only 32% among their less educated peers.
How sustainable is well-being going forward?
Good lives for all can only last over time if the resources that sustain well-being are maintained, and if risks to the economic, natural and societal systems are recognised and appropriately managed (Box 1.4). Overall, trends since 2010 indicate progress for Human Capital, several causes for concern in Natural Capital, and room for improvement in Economic and Social Capital. Economic Capital includes both man-made and financial assets; Natural Capital encompasses natural assets (e.g. stocks of natural resources, land cover, species biodiversity) as well as ecosystems and their services (e.g. oceans, forests, soil and the atmosphere); Human Capital refers to the skills and future health of individuals; and Social Capital refers to the social norms, shared values and institutional arrangements that foster co-operation.
Developments in Economic Capital headline indicators since 2010 have generally been positive, yet slow. The OECD average of stock of produced fixed assets (such as buildings, machinery and infrastructure) per person is close to USD 119 000 (Table 1.5), having increased by nearly 11% cumulatively between 2010 and 2018 – though at an annual pace that is significantly lower than the one recorded in previous years (2005-10). While government financial liabilities exceed financial assets to the tune of 27 percentage points of GDP in 2018, households had debt equivalent to 126% of their disposable income in 2017. The average financial net worth of OECD governments fell by 4 percentage points of GDP overall since 2010, having declined sharply up to 2014 (when liabilities exceeded assets by over 30% of GDP) and only partially recovering since then. Over the same period, household debt has fallen by around 3 percentage points of household income for OECD countries on average (Figure 1.17), though 13 countries have seen indebtedness rise.
There are multiple warning signs related to climate change and biodiversity loss in Natural Capital. Total OECD GHG emissions from domestic production fell by 4.3% between 2010 and 2017 – though they have stabilised in recent years, and may rise again in future due to recent increases in energy use and CO2-related emissions (OECD, 2019[8]). On a per capita basis, OECD average GHG emissions have fallen by around one tonne from 2010, to 11.9 tonnes annually in 2017 (Table 1.5). However, these efforts are unlikely to put most countries on track to reach the emission reduction targets of the 2015 Paris Agreement, with population growth partially offsetting reductions in emissions per capita. Beyond emissions from their own production, OECD countries are also partly responsible for growing emissions in non-OECD countries through emissions embedded in their imports. On a global scale, total atmospheric carbon concentrations are still rising rapidly: global emissions have increased 1.5-fold since 1990, and CO2 emissions from energy use reached a historic high in 2018 (see Reference Chapter 14). OECD countries are also consuming more of the Earth’s materials than in 2010: the total OECD material footprint increased by 1.2 tonnes/capita to 25 (Table 1.5). Biodiversity in OECD countries is also at higher risk. An increasing number of species are classified as threatened compared to 2010, resulting in an average worsening of 0.01 on the Red List Index for threatened species (Figure 1.18).
Developments are more encouraging for aspects of Human Capital (Table 1.5, Figure 1.19). 85% of today’s young adults aged 25 to 34 (the OECD’s future labour force) have completed at least their upper secondary education, an increase of 2 percentage points since 2010. Nevertheless, questions remain about the quality of cognitive skills gained, given declining PISA test scores in most OECD countries (see Reference Chapter 6). On average, 12% of the labour force is unemployed, discouraged or underemployed (which taken together are referred to as the labour underutilisation rate) – a potential source of lower Human Capital in the future, since labour market slack can reduce people’s skills, confidence and learning opportunities. In line with rising employment rates, the labour underutilisation rate has dropped by almost 5 percentage points on average. Premature mortality due to a range of medical conditions or fatal accidents in OECD countries is at around 4 600 years of potential life lost per 100 000 inhabitants; this has also improved since 2010, with potential years of life lost falling by 620 on average. Despite these improvements, the wider set of Human Capital indicators covered in Reference Chapter 15 suggests that rising obesity in almost all OECD countries poses risks to future health status: One in every five people are obese in OECD countries, on average (where obesity is defined as a Body Mass Index of 30 or higher). Of the 27 countries with time series data, none showed a fall in obesity rates, and only 2 maintained the same rate over the past 15 years.
There is wide room for improvement in Social Capital. When people are asked whether they trust other people (0 meaning no trust and 10 meaning complete trust), the average score in OECD countries is 6.1 (Table 1.5). After a general deterioration in the aftermath of the 2007-08 financial crisis, trust in public institutions has improved by 3 percentage points for the OECD on average since 2010, although still less than half of the population (43%) trusts their national government. This could weigh on countries’ capacity to put in place collective responses to the challenges that loom ahead. Gender parity in politics is far from being achieved: women hold one-third of parliamentary seats in OECD countries on average, with no country reaching parity. Progress in this measure of the inclusiveness of decision-making has been slow, rising by only 2.6 percentage points on average since 2010 (Figure 1.20).
Box 1.4. The relationship between current well-being and resources for the future
While more work is needed to disentangle how the stocks and flows of economic, natural, human and social capital combine to produce current well-being outcomes, and to understand which other factors might be at play, the basic correlations suggest some co-dependency (Figure 1.21).
OECD countries with strong performance in Economic Capital also achieve good comparative outcomes in aspects of current well-being related to material conditions (i.e. Income and Wealth, Housing, Work and Job Quality) and the individual and environmental aspects of quality of life (i.e. Health, Knowledge and Skills, Environmental Quality, Subjective Well-being and Safety).Similarly, achievements in both Human Capital and Social Capital significantly correlate with high well-being related to material conditions, as well as all aspects of quality of life including relational ones (i.e. Work-Life Balance, Social Connections, Civic Engagement).
Country-specific relationships between current well-being and Natural Capital are more complex to unpack, since much of the natural capital that is critical to well-being refers to global common goods. In the short run, high current well-being within a country can co-exist with threats to natural capital stocks, both nationally and globally, that may affect well-being tomorrow. However, the use of natural resources to enhance well-being today depletes the stocks available to future generations – and indeed, the association between good outcomes in current well-being and Natural Capital is negative, albeit non-significant.
Trends in resources for future well-being headline indicators since 2010, by country
Trends in resources for future well-being since 2010 have diverged, depending on the resource considered (Figure 1.22). On the one hand, more than half of all OECD countries have consistently improved in terms of premature mortality, educational attainment of young adults, labour underutilisation, greenhouse gas emissions per capita and produced fixed assets. Bucking the general trend, Greece, the Netherlands and Portugal are the only countries where produced fixed assets have consistently declined since 2010, and the United States is the only country experiencing higher premature mortality, mirroring trends in life expectancy at birth. Greenhouse gas emissions per capita have consistently increased in Chile and Turkey, countries where per capita emissions still remain among the lowest in the OECD. On the other hand, the majority of countries have seen “no clear change” when it comes to Social Capital, in particular gender parity in politics and trust in government. Among the countries where trend have a clear direction, trust has increased in more (9) countries than where it has deteriorated (6). In some cases, drops in the share of the population trusting public institutions have been substantial, exceeding 10 percentage points in Chile and Sweden, and 20 percentage points in Colombia. Aspects of Economic Capital – household debt and financial net worth of government – have consistently deteriorated in a third of OECD countries, with the largest falls in government net worth occurring in countries already well below the OECD average (e.g. Greece, Portugal and Spain).
Biodiversity has consistently been lost in many OECD countries (23) since 2010. The largest declines in the Red List Index for threatened species have generally occurred in those countries with already high at-risk rates – including New Zealand, Mexico, Korea, Colombia, Chile, the United Kingdom, Japan and Australia, as well as France. Similarly, despite lower greenhouse gas emissions per capita, 16 out of 37 OECD countries have consistently increased their material footprint per capita. The largest increases (by 3 tonnes or more) were recorded in Lithuania, Latvia, Estonia, the Slovak Republic and Australia – countries with footprints above the OECD average. This raises questions around the trade-off between sustainability and improving living standards, since many of these countries are among the ones that have recorded stronger gains in current well-being since 2010. By contrast, three OECD countries with below-average footprints bucked the overall trend and consistently improved their consumption of the Earth’s materials: material footprints fell by more than 3 tonnes per capita in Greece, Ireland and Portugal.
Despite mixed progress at the indicator level, overall, most OECD countries achieved progress in at least 50% of their headline indicators of resources for future well-being (Figure 1.23). Relative to other countries, Canada recorded the largest number of improvements, with consistent gains in 8 out of its 11 headline indicators since 2010 (fixed produced assets, net worth of government, greenhouse gas emissions per capita, and all three indicators of Human Capital, i.e. premature mortality, educational attainment of young adults, labour underutilisation, as well as trust in government and gender parity in politics). By contrast, Turkey improved in fewest systemic resources and only consistently increased the share of young adults with upper secondary education. Chile, Colombia and Finland also improved on only 2 out of 11 aspects of future well-being, with Chile as the country with the largest number of reductions in resources for future well-being.
Some OECD countries recorded deteriorations in their resources for the future only for one headline indicator or not at all. This is the case of Austria, Belgium, Iceland, Luxembourg, Israel and several eastern European countries that experienced improvements in a large number of current well-being indicators (the Czech Republic, Estonia, Hungary and Lithuania) (Figure 1.23).
Though related, the speed of progress in current well-being has not always matched that in resources for the future well-being. Indeed, the countries that experienced many improvements in well-being outcomes today have not always matched them with a similar improvement in their resources for the future (Figure 1.24). Some OECD members, such as Ireland, Switzerland and the United States, gained comparatively much more in the resources for their future well-being than they improved in well-being outcomes “here and now”. Others, like Colombia, Turkey and the Slovak Republic increased people’s well-being today much more than they invested in future resources. This implies that, in order to balance well-being between generations, countries need to consider both current and future aspects of well-being separately to minimise the risk of neglecting one at the cost of the other – a risk that appears to be particularly acute in the case of Natural Capital (Box 1.4). Further, while some well-being gains have gone hand in hand with higher GDP growth, this is not always the case, underscoring the need to look beyond GDP growth as the sole indicator of progress (Box 1.5).
Box 1.5. The relationship between GDP growth and well-being
A well-being approach is useful to identify, at a glance, countries’ relative strengths and weaknesses across a wide range of outcomes that matter to people. These can help to identify priorities for action and make trade-offs in policy explicit. Data on well-being can also be useful to see which areas are particularly at risk of being neglected when GDP growth is taken as the main indicator of progress. GDP growth fares reasonably well as a leading indicator for changes in some aspects of both current and future well-being since 2012 (the year from which comparable data on GDP growth in the latest OECD calculations is available). Yet not all well-being indicators have shared a positive relationship with GDP growth, and many others would be overlooked entirely if GDP were the only yardstick used to judge success (Figure 1.25).
Since 2012, GDP growth at the country level has been significantly related to growth in several aspects of material conditions, such as higher household incomes, employment rates and lower labour underutilisation (i.e. unemployed, discouraged or underemployed). In countries where economies grew, people’s evaluations of their lives have also improved, more people turned out to vote, fewer people live in overcrowded housing conditions, a smaller share of the population felt they have no friends or family members to count on for help, and the financial net worth of government rose. However, greenhouse gas emissions per capita improved and gender gaps in feeling safe when walking alone at night have narrowed as economies contracted (mainly because countries that did not experience strong GDP growth were more successful in reducing the gender gap in feeling safe).
At the same time, progress on other well-being outcomes appears unrelated to GDP growth. Changes in current well-being indicators on income inequality, the prevalence of long hours in paid employment, the gender wage gap, housing affordability, air pollution, the homicide rate and life expectancy are not significantly associated with changes in GDP. The same applies to changes in several resources for future well-being (household debt, produced fixed assets, premature mortality, the educational attainment of young adults, the protection of threatened species, countries’ material footprint, trust in government and gender parity in politics). Thus, while a growing economy can be associated with rising well-being in some aspects of life, it is insufficient to capture everything that matters to people today and in the future.
References
[1] Durand, M. and C. Exton (2019), “Adopting a Well-Being Approach in Central Government: Policy Mechanisms and Practical Tools”, in Global Happiness Policy Report 2019, Sustainable Development Solutions Network, New York, http://happinesscouncil.org/.
[5] Exton, C. and L. Fleischer (2020), “The Future of the OECD Well-being Dashboard”, OECD Statistics Working Papers, OECD Publishing, Paris (forthcoming).
[3] Fleischer, L., M. Frieling and C. Exton (2020), “Measuring New Zealand’s Well-being”, OECD Statistics Working Papers, OECD Publishing, Paris (forthcoming).
[8] OECD (2019), Environment at a Glance Indicators, OECD Publishing, Paris, https://dx.doi.org/10.1787/ac4b8b89-en.
[4] OECD (2019), OECD Economic Outlook, Volume 2019 Issue 1, OECD Publishing, Paris, https://dx.doi.org/10.1787/b2e897b0-en.
[2] OECD (2019), OECD Economic Surveys: New Zealand 2019, OECD Publishing, Paris, https://dx.doi.org/10.1787/b0b94dbd-en.
[9] OECD (2019), PISA 2018 Results (Volume II): Where All Students Can Succeed, PISA, OECD Publishing, Paris, https://dx.doi.org/10.1787/b5fd1b8f-en.
[6] OECD (2017), OECD Economic Outlook, Volume 2017 Issue 1, OECD Publishing, Paris, https://dx.doi.org/10.1787/eco_outlook-v2017-1-en.
[7] UNODC (2019), Global Study on Homicide, http://unodc.org/documents/data-and-analysis/gsh/Booklet2.pdf (accessed on 17 January 2020).
Annex 1.A. Headline well-being indicators
Annex Table 1.A.1. Headline indicators: Current well-being averages
Dimension |
Label |
Indicator |
Unit |
Latest available year |
Source |
---|---|---|---|---|---|
Income and Wealth |
Household income |
Household net adjusted disposable income |
USD at 2017 PPPs, per capita |
2017 |
OECD National Accounts Statistics (database), http://dx.doi.org/10.1787/na-data-en |
Household wealth |
Household median net wealth |
USD at 2016 PPPs |
2016 |
OECD Wealth Distribution (database), http://stats.oecd.org/Index.aspx?DataSetCode=WEALTH |
|
Housing |
Housing affordability |
Disposable income after housing costs |
Share of household gross adjusted disposable income remaining, after deductions for housing rents and maintenance |
2018 |
OECD National Accounts Statistics (database), http://stats.oecd.org/Index.aspx?DataSetCode=SNA_TABLE5 and http://stats.oecd.org/Index.aspx?DataSetCode=SNA_TABLE14A |
Work and Job Quality |
Employment rate |
Employment rate |
Employed people aged 25-64, as a share of the population of the same age |
2018 |
OECD Labour Force Statistics by Sex and Age – Indicators (database), https://stats.oecd.org/Index.aspx?DataSetCode=LFS_SEXAGE_I_R |
Health |
Life expectancy |
Life expectancy at birth |
Number of years a newborn can expect to live |
2017 |
OECD Health Status (database), http://stats.oecd.org/Index.aspx?DataSetCode=HEALTH_STAT |
Knowledge and Skills |
Student skills in science |
Cognitive skills of 15-year-old students in science |
OECD Programme on International Students Assessment (PISA) – mean score for science |
2018 |
OECD (2019), PISA 2018 Results (Volume I): What Students Know and Can Do, PISA, OECD Publishing, Paris, https://doi.org/10.1787/5f07c754-en |
Environmental Quality |
Access to green space |
Access to green space |
Share of urban population with access within a 10 minutes’ walk |
2012 |
Poelman (2018), “A walk to the park? Assessing access to green areas in Europe’s cities, update using completed Copernicus urban atlas data”, European Commission, Regional and urban policy, https://ec.europa.eu/regional_policy/sources/docgener/work/2018_01_green_urban_area.pdf |
Subjective Well-being |
Life satisfaction |
Life satisfaction |
Mean values on an 11-point scale, with responses ranging from 0 (not at all satisfied) to 10 (completely satisfied) |
2018 |
European Union Statistics on Income and Living Conditions (EU-SILC) (database), https://ec.europa.eu/eurostat/data/database; Australian General Social Survey; Canadian Community Health Survey; Colombia's National Quality of Life Survey; Korean Social Integration Survey; Mexican National Survey of Household Income and Expenditure (Socioeconomic Conditions Module) and New Zealand General Social Survey |
Safety |
Homicides |
Deaths due to assault |
Age-standardised rate, per 100 000 population |
2016 |
OECD Health Status (database), http://stats.oecd.org/Index.aspx?DataSetCode=HEALTH_STAT |
Work-Life Balance |
Time off |
Time allocated to leisure and personal care |
Hours per day, people in full-time employment |
Around 2018 |
OECD calculations based on public-use time-use survey microdata when available; Eurostat’s Harmonised European Time Use Surveys (database), https://ec.europa.eu/eurostat/web/time-use-surveys and tabulations from National Statistical Offices |
Social Connections |
Social interactions |
Time spent interacting with friends and family as primary activity |
Hours per week |
Around 2018 |
OECD calculations based on public-use time-use survey microdata when available; Eurostat’s Harmonised European Time Use Survey database, https://ec.europa.eu/eurostat/web/time-use-surveys and tabulations from National Statistical Offices |
Civic Engagement |
Voter turnout |
Voter turnout |
Share of votes cast among the population registered to vote |
2016-19 |
Institute for Democracy and Electoral Assistance (IDEA) (database), https://www.idea.int/ |
Annex Table 1.A.2. Headline indicators: Current well-being inequalities
Dimension |
Label |
Indicator |
Unit |
Latest available year |
Sources |
Type of inequality |
---|---|---|---|---|---|---|
Income and Wealth |
S80/S20 income share ratio |
Ratio of average (equivalised) household disposable income of the top 20% of the income distribution to the average income of the bottom 20% |
S80/S20 ratio of household disposable income |
2017 |
OECD Income Distribution Database, https://stats.oecd.org/Index.aspx?DataSetCode=IDD |
Vertical |
Housing |
Overcrowding rate |
Overcrowding rate |
Share of households living in overcrowded conditions (EU- definition) |
2017 |
OECD Affordable Housing Database, |
Deprivation |
Work and Job Quality |
Gender wage gap |
Gender wage gap |
Difference between male and female median wages expressed as a share of male wages |
2018 |
OECD Indicators of gender equality in employment (database), https://stats.oecd.org/Index.aspx?DataSetCode=GENDER_EMP |
Horizontal |
Long hours in paid work |
Employees working very long (paid) hours |
Share of employees usually working 50+ hours per week |
2018 |
OECD Labour Force Statistics by Sex and Age – Indicators (database), https://stats.oecd.org/Index.aspx?DataSetCode=LFS_SEXAGE_I_R |
Deprivation |
|
Health |
Gap in life expectancy by education |
Gap in life expectancy among men with low (no schooling, primary and lower secondary educational attainment) and high (tertiary) education at age 25 |
Years |
2011 |
Murtin et al. (2017), “Inequalities in longevity by education in OECD countries: Insights from new OECD estimates”, OECD Statistics Working Papers, No. 2017/2, OECD Publishing, Paris, https://dx.doi.org/10.1787/6b64d9cf-en |
Horizontal |
Knowledge and Skills |
Students with low skills |
Share of 15-year-old students with low scores in maths, reading and science |
Share of 15- year-old students below OECD Programme on International Students Assessment (PISA) level 2 in reading, maths, and science |
2018 |
OECD (2019), PISA 2018 Results (Volume I): What Students Know and Can Do, PISA, OECD Publishing, Paris, https://doi.org/10.1787/5f07c754-en |
Deprivation |
Environmental Quality |
Exposure to outdoor air pollution |
Population exposure to outdoor air pollution by fine particulate matter above World Health Organisation (WHO) Guidelines |
Share of population exposed to more than 10g/m3 of PM2.5 |
2017 |
OECD Exposure to PM2.5 in countries and regions (database), http://dotstat.oecd.org/Index.aspx?DataSetCode=EXP_PM2_5 |
Deprivation |
Subjective Well-being |
Negative affect balance |
Negative affect balance |
Share of population reporting more negative than positive feelings and states in a typical day |
2016-18 |
Gallup World Poll (database), |
Deprivation |
Safety |
Gender gap in feeling safe |
Gender gap in feeling safe at night |
Percentage difference that women feel less safe than men when walking alone at night in the city or area where they live |
2013-18 |
Gallup World Poll (database), |
Horizontal |
Work-Life Balance |
Gender gap in hours worked |
Extra minutes of total time spent working (paid and unpaid) that women work, relative to men (aged 15-64) |
Minutes per day |
Between 2005-18 |
OECD Time Use (database), https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE |
Horizontal |
Social Connections |
Lack of social support |
Perceived lack of social support |
Share of people who report having no friends or relatives whom they can count on in times of trouble |
2016-18 |
Gallup World Poll (database), |
Deprivation |
Civic Engagement |
Having no say in government |
Having no say in government |
Share of people aged 16-65 who feel they have no say in what the government does |
Around 2012 |
OECD Survey of Adult Skills (PIAAC) (database), https://oecd.org/skills/piaac |
Deprivation |
Annex Table 1.A.3. Headline indicators: Resources for future well-being
Dimension |
Label |
Indicator |
Unit |
Latest available year |
Source |
Type of capital |
---|---|---|---|---|---|---|
Economic Capital |
Produced fixed assets |
Produced fixed assets |
USD at 2010 PPPs, per capita |
2018 |
OECD National Accounts Statistics (database), http://stats.oecd.org/Index.aspx?DataSetCode=SNA_TABLE9B |
Stock |
Financial net worth of general government |
Adjusted financial net worth of general government |
Percentage of GDP |
2018 |
OECD Financial Indicators – Stocks (database), http://stats.oecd.org/Index.aspx?DataSetCode=FIN_IND_FBS |
Risk factor |
|
Household debt |
Household debt |
Share of household net disposable income |
2018 |
OECD Financial Indicators – Stocks (database), http://stats.oecd.org/Index.aspx?DataSetCode=FIN_IND_FBS |
Risk factor |
|
Natural Capital |
Greenhouse gas emissions |
Total greenhouse gas emissions from domestic production, excluding those from land use, land-use change and forestry (LULUCF) |
Tonnes per capita, CO2 equivalent |
2017 |
OECD Greenhouse gas emissions (database), https://stats.oecd.org/Index.aspx?DataSetCode=AIR_GHG |
Risk factor |
Material footprint |
Used raw material extracted to meet the economy's final demand |
Tonnes per capita |
2017 |
OECD Material resources (database), https://stats.oecd.org/Index.aspx?DataSetCode=MATERIAL_RESOURCES |
Flow |
|
Red List Index of threatened species |
Red List Index of threatened species |
Combined indicator of extinction risk for birds, mammals, amphibians, cycads and corals. A value of 1.0 equates to all species qualifying as Least Concern (i.e. not expected to become extinct in the near future). A value of 0 equates to all species having gone extinct |
2019 |
UN DESA Global SDG Indicator Database, indicator 15.5.1 http://unstats-undesa.opendata.arcgis.com/datasets/indicator-15-5-1-red-list-index-2/data?orderBy=seriesCode – sourced from International Union for the Conservation of Nature (IUCN) |
Risk factor |
|
Human Capital |
Educational attainment among young adults |
Upper secondary educational attainment among young adults |
Share of people aged 25-34 who have attained at least an upper secondary education |
2018 |
OECD Educational attainment and labour-force status (database), http://stats.oecd.org/Index.aspx?DataSetCode=EAG_NEAC |
Stock |
Labour underutilisation |
Broad labour underutilisation rate |
Share of unemployed, discouraged (persons not in the labour force who did not actively look for work during the past four weeks but who wish and are available to work) and underemployed (full-time workers working less than usual during the survey reference week for economic reasons and part-time workers who wanted but could not find full-time work) workers in the total labour force |
2018 |
OECD Household Dashboard (database), http://stats.oecd.org/Index.aspx?DataSetCode=HH_DASH |
Risk factor |
|
Premature mortality |
Potential years of life lost due to a range of medical conditions and fatal accidents |
Years of potential life lost per 100 000 population (age standardised) |
2017 |
OECD (2020), "Potential years of life lost" (indicator), https://doi.org/10.1787/193a2829-en (accessed on 04 February 2020) |
Flow |
|
Social Capital |
Trust in others |
Interpersonal trust |
Mean score on a scale from 0 (you do not trust any other person) to 10 (most people can be trusted) |
2013 |
European Union Statistics on Income and Living Conditions (EU-SILC) (database), https://ec.europa.eu/eurostat/web/income-and-living-conditions, Stats NZ |
Stock |
Trust in government |
Trust in national government |
Share of the population responding “yes” to a question about confidence in the national government |
2016-18 |
Gallup World Poll (database), https://gallup.com/analytics/232838/world-poll.aspx |
Stock |
|
Gender parity in politics |
Women in national parliament |
Share of women in the national lower or single houses of parliament |
2017 |
OECD Women in politics (database), https://data.oecd.org/inequality/women-in-politics.htm, Statistics Lithuania |
Resilience factor |
Notes
← 1. The labour underutilisation rate includes unemployed people, discouraged workers (i.e. persons not in the labour force who did not actively look for work during the past four weeks but who wish and are available to work) and underemployed workers (i.e. full-time workers working less than usual during the survey reference week for economic reasons, and part-time workers who wanted but could not find full-time work).
← 2. The 2017 edition of the How’s Life? dashboard listed several indicators under both current well-being and resources for future well-being. This double listing was a conscious decision when the indicators for resources for future well-being were operationalised in 2015, since knowledge, health and wealth are clearly both intrinsically valuable to individuals, but also determine well-being outcomes later in life and for society as a whole. However, the multiple listing of indicators has proven to be challenging when communicating the logic of the Framework to stakeholders. In order to improve its overall clarity and interpretability, How’s Life? 2020 reduces the overlap of indicators as much as possible while maintaining the spirit and integrity of the well-being dimensions and capitals. For example, the cognitive skills of adults and (15 year old) youth were previously included under both the Knowledge and Skills dimension in current well-being and Human Capital in future well-being. While they are important for well-being today and drive outcomes tomorrow, they are competencies that are intrinsically valuable to people (i.e. what they know and can do), and hence only retained under Knowledge and Skills. Human Capital continues to feature a (future-oriented) measure of education through an indicator on the educational attainment of young adults.
← 3. Unpaid work includes routine housework, shopping for goods and services (mainly food, clothing and items related to accommodation), caring for household members (children and adults) and non-household members, volunteering, travel related to household activities and other unpaid work.
← 4. The measure excludes interactions that occur while doing other primary activities (e.g. when eating or caring for household members).
← 5. Data on trends for half of the headline indicators for current well-being averages are missing for these two countries, which might negatively bias their comparative assessment.
← 6. However, gender stereotyping continues to act as a powerful barrier to career choices, and is a powerful driver of future occupational segregation for women: only 1% of 15-years girls assessed by PISA across OECD countries report that they envisage working in Information and Communication Technology (ICT)-related occupations in the future, compared with 8% of boys (OECD, 2019[9]).