copy the linklink copied!Reader’s guide

On 25 May 2018, the OECD Council invited Colombia to become a Member. While Colombia appears in the list of OECD Members and is included in the OECD averages reported in this publication, at the time of its preparation, Colombia was in the process of completing its domestic procedures for ratification and the deposit of Colombia’s instrument of accession to the OECD Convention was pending.

copy the linklink copied!Conventions

  • In each figure, data labelled “OECD” are simple mean averages of the OECD countries displayed, unless otherwise indicated. Whenever data is available for fewer than all 37 OECD countries, the number of countries included in the calculation is specified in the figure (e.g. OECD 33).

  • A weighted OECD average (or OECD total) is shown in instances where the OECD convention is to provide this type of average. Where used, this is specified in the figure notes along with details of the weighting methodology. For example, when data are population-weighted this is done according to the size of the population in different countries, as a proportion of the total OECD population. The OECD total considers all the OECD countries as a single entity, to which each country contributes proportionally to the sum.

  • In analysis of change over time and trendlines, the OECD averages refer to only those countries with data available for every year shown, since the sample of countries needs to be held constant across all years. Since this means that only countries with a complete time series can be included, this can sometimes lead to different OECD averages for trendlines (shown in Chapter 1) versus the those for the latest and earliest available time points (shown in Reference Chapters 2 to 16).

  • Each figure specifies the time period covered, and figure notes provide further details when data refer to different years for different countries. Countries are denoted by their ISO codes (Table 1).

  • Data for key partner countries (Brazil, Costa Rica, the Russian Federation, South Africa), where available, are presented in a separate part of the figure to OECD countries.

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Table 1. ISO codes for countries and word regions

AUS

Australia

FIN

Finland

MEX

Mexico

AUT

Austria

FRA

France

NLD

Netherlands

BEL

Belgium

GBR

United Kingdom

NOR

Norway

BRA

Brazil

GRC

Greece

NZL

New Zealand

CAN

Canada

HUN

Hungary

OECD

OECD average

CHE

Switzerland

IRL

Ireland

POL

Poland

CHL

Chile

ISL

Iceland

PRT

Portugal

COL

Colombia

ISR

Israel

RUS

Russian Federation

CRI

Costa Rica

ITA

Italy

SVK

Slovak Republic

CZE

Czech Republic

JPN

Japan

SVN

Slovenia

DEU

Germany

KOR

Korea

SWE

Sweden

DNK

Denmark

LTU

Lithuania

TUR

Turkey

ESP

Spain

LUX

Luxembourg

USA

United States

EST

Estonia

LVA

Latvia

ZAF

South Africa

copy the linklink copied!How’s Life? indicator dashboard

Following a thorough review of the OECD Well-being Framework (Exton and Fleischer, 2020[1]) How’s Life? 2020 features an extended dashboard of over 80 well-being indicators. These reflect the 11 dimensions of current well-being and the four capitals for future well-being of the OECD Well-being Framework. Relative to How’s Life? 2017, this edition includes new data on the environment, mental health, time use, unpaid work and satisfaction with personal relationships and how time is spent.

Headline indicator selection

For more concise communication and to highlight key findings, Chapter 1 uses three sets of headline indicators: 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 Chapter 1 Annex).

The headline indicators have been chosen from the extended dashboard to jointly satisfy conceptual and practical criteria to the best possible extent:

  • They reflect a balance across all components of the Well-being Framework and include at least one average and one inequality indicator for each dimension of current well-being, and three indicators for each type of capital. The headline inequalities also follow the framework for measuring well-being inequalities introduced in How’s Life? 2017 – i.e. they include examples of gaps between the top and bottom of the distribution (“vertical inequalities”), differences between population groups (“horizontal inequalities”) and deprivations (the share of the population falling below a given minimum threshold).

  • They frequently appear in various national well-being initiatives led by OECD countries and mirror the strategic priorities emerging from other OECD policy work, indicating some consensus about their importance. For example, the gender wage gap features in many national initiatives and in the OECD Framework for Policy Action on Inclusive Growth (OECD, 2018[2]).

  • They perform particularly strongly on a range of statistical quality criteria: many act as broad summary indicators of their respective dimensions, cover the large majority of OECD countries, and are more frequently collected and produced in a timelier manner than other indicators of the extended dashboard. However, much better data exists for some dimensions than for others. For example, some headline indicators for Work-Life Balance and Social Connections come from Time Use surveys that are only conducted every 5-10 years, and only for a subset of OECD countries. By contrast, several indicators for Work and Job Quality come from annually conducted labour force surveys.

The introduction of headline indicator sets for communication purposes should not be interpreted as implying they are more important than other indicators in the extended dashboard, or that this smaller set is sufficient to analyse well-being fully.

copy the linklink copied!Change over time

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 (since 2010, unless otherwise indicated):

  • 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

  • For indicators with fewer than 3 observations per country for at least 75% of all countries for which data exists, 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 2). 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 relative percentage change terms; the univariate distribution of values among OECD countries; and the likely margin of error in the estimated values.

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Table 2. Thresholds used to assess changes in well-being for selected indicators

Indicator

Unit of measurement

Threshold

Income and Wealth

Household wealth

Median net wealth, USD at 2016 PPPs

+/-9 000 USD

Work and Job Quality

Job strain

Proportion of employees who experience a number of job demands that exceeds the number of job resources

+/-3.0 percentage points

Health

Deaths from suicide, alcohol, drugs

Combined deaths from suicide, acute alcohol abuse and drug overdose, per 100 000 population

+/-1.9 deaths

Knowledge and Skills

Student skills

OECD Programme on International Students Assessment (PISA) – mean score for mathematics, reading, and science

Based on confidence intervals provided by the OECD Education Directorate

Subjective Well-being

Life satisfaction

Mean values on an 11-point scale, with responses ranging from 0 (not at all satisfied) to 10 (completely satisfied)

+/-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

Time allocated to leisure and personal care, hours per day

+/- 20 min

Social Connections

Social interactions

Time spent interacting with friends and family as primary activity, hours per week

+/- 20 min

Civic Engagement

Voter turnout

Share of registered voters who cast votes

+/- 3 percentage points

Natural Capital

Natural and semi-natural land cover

Natural and semi-natural vegetated land cover (tree-covered area, grassland, wetland, shrubland and sparse vegetation) as a percentage of total land area

Any change different from zero

Intact forest landscapes

Square kilometres

Any change different from zero

Human Capital

Smoking prevalence

Share of people aged 15 and over who report smoking every day

+/-1 percentage point

Obesity prevalence

Share of people aged 15 and older who are obese, either self-reported or measured through health interviews

+/-1 percentage point

Social Capital

Government stakeholder engagement

0-4 scale, based on the OECD Regulatory Indicators Survey

Any change different from zero

Corruption

Corruption Perception Index score on a scale of 0 (highly corrupt) to 100 (very clean)

Based on

confidence

intervals provided by Transparency International

copy the linklink copied!Breakdowns considered in inequalities analyses

The education and age ranges considered in the inequalities sections throughout this report have been selected to maximise international comparability with what is readily available in aggregate statistics.

  • Education ranges refer to the highest level of education completed.

    • In most cases, they correspond to ISCED levels 0-2 for “below upper secondary” level (i.e. less than primary, primary and lower secondary); 3-4 for “upper secondary” level (i.e. secondary and post-secondary non-tertiary education); and 5-8 for “tertiary” level. For individual country-level mappings to the ISCED 2011 classifications, please see http://uis.unesco.org/en/isced-mappings.

    • Indicators sourced from the Gallup World Poll correspond to: completed elementary education or less (up to eight years of basic education) for “primary” level; completed some secondary education up to three years tertiary education (9 to 15 years of education) for “secondary” level; and completed four years of education beyond “high school” and/or received a four-year college degree for “tertiary” level.

  • The age ranges considered can differ between indicators and are reported in the respective figure notes.

References

[1] Exton, C. and L. Fleischer (2020), “The Future of the OECD Well-being Dashboard”, OECD Statistics Working Papers, No. forthcoming, OECD Publishing, Paris.

[2] OECD (2018), Opportunities for All: A Framework for Policy Action on Inclusive Growth, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264301665-en.

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