OECD Regional Well-Being:
A user’s guidewww.oecdregionalwellbeing.org

Using data to build better communities

Version: October 2018

How does your region perform when it comes to
education, environment, safety and other topics
important to your well-being?
The interactive website allows you to measure wellbeing in your region and compare it with 446 otherOECD regions based on eleven topics central to thequality of our lives.
It uses several indicators to rank regions, see trends
over time and understand how large disparities are
across regions.

Explore the visualisationwww.oecdregionalwellbeing.org
Give your feedback
cferegionstat@oecd.org
2

Table of Contents
Introduction ............................................................................................................................................ 4
I. Framework to measure regional and local well-being........................................................................................... 5
II. The Interactive web tool at a glance www.oecdregionalwellbeing.org ........................................... 7
III. Defining Scores and Trends................................................................................................................ 9
1. Regional well-being scores.............................................................................................................. 9
2. Trends ............................................................................................................................................. 9
3. Regions with similar well-being profiles in other countries ......................................................... 10
4. Regional disparities in a topic within a country ............................................................................ 10
IV. Defining Regions .............................................................................................................................. 11
V. Well-being Topics and Indicators...................................................................................................... 13
VI. Topics and indicators in the OECD Better Life Index and in the Regional well-being tool .............. 14VII. Sources and References .................................................................................................................. 14
a. Data source and period ................................................................................................................. 14
b. Statistics for Israel ......................................................................................................................... 16
c. Country code ................................................................................................................................. 16
d. References .................................................................................................................................... 16

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Introduction
Where people live matters for their well-being. Quality of life is shaped by a multitude offactors - from income and jobs to health and environment, among others. Our results showthat quality of life varies greatly, not only between countries, but also within countries.
The mix between different well-being dimensions is unique to each community where
people live, study, work and connect. Improving people’s lives requires making where they
live a better place.
Understanding personal well-being is crucial to gear public policies towards better
societies. As many of the policies that bear most directly on people’s lives are local orregional, more fine-grained measures of well-being will help policy-makers to enhance thedesign and targeting of policies. They can also empower citizens to demand placed-based
policy actions that respond to their specific expectations and, in turn, to restore people’s
trust.
The OECD publication How’s life in your region? builds on the Better Life Initiative, thatmeasures well-being at national level, as well as on the work carried out on regional
inequalities through the Regions and Cities at a Glance series. How’s Life in your region?
provides:•a conceptual framework for measuring well-being in regions and cities;•

a common set of internationally comparable indicators of well-being and a criticalassessment of the statistical agenda ahead;•guidance to policy-makers at all levels on the use of well-being metrics for improving
policy results.

This Guide describes the general framework of How’s life in your region? and themethodology used to visualise the set of regional well-being indicators found in theinteractive web tool.

For further information on regional analysis, read the latest publication OECD Regions
and Cities at a Glance, available on November 15, 2022 at:
http://www.oecd.org/fr/regional/oecd-regions-and-cities-at-a-glance.htm

4I. Framework to measure regional and local well-being
The framework for regional and local well-being starts with the consideration thatmaking better policies for better lives means understanding what matters to people. Whatdo people perceive and value about their local conditions? How do they behave when they
are not satisfied with one aspect or more of their life? Do local inequalities in theaccessibility of services matter in shaping citizens’ choices and do they have an impact onnational well-being? How much does the place where we live predict our future well-being?
These are some of the questions that are addressed in the OECD work on measuring
regional well-being.
The OECD conceptual framework for measuring well-being in regions and cities has sevendistinctive features (Figure 1):• It measures well-being where people experience it. It focuses both on individuals
and on place-based characteristics, as the interaction between the two shapes
people’s overall well-being.
• It concentrates on well-being outcomes that provide direct information on
people’s lives rather than on inputs or outputs.
• It is multi-dimensional and includes both material and non-material dimensions.
• It assesses well-being outcomes not only through averages but also by how they
are distributed across regions and groups of people.
• It is influenced by citizenship, governance and institutions.
• It takes account of complementarities and trade-offs among the different
well-being dimensions.
• It looks at the dynamics of well-being over time, at its sustainability and at theresilience of different regions.
Eleven well-being dimensions are identified and a set of indicators developed for the
447 OECD regions.1 This set of indicators can also serve as a common reference for regionsthat aim to develop their own metrics of well-being. The availability of indicators
comparable across regions and countries can be useful not only for benchmarking therelative position of a place, but also as a catalyst for policy-makers, to spur public support
for action and to create a mechanism for prioritising resources.
The conceptual framework to measure regional well-being builds on over ten years ofOECD work focusing on measures of people's well-being and societal progress which led tothe creation of the Better Life Initiative. The OECD Framework for Measuring Well-Being andProgress, developed as part of the Better Life Initiative, proposes to measure well-being
through a multi-dimensional approach expanding on the work done by the Commission on
the measurement of economic performance and social progress (Stiglitz et al., 2009). The
publications How’s Life? (OECD 2015) and the Better Life Index web tool identify eleven

1

The OECD defines regions as the first tier of sub-national government (for example states in the UnitedStates, provinces in Canada, or “régions” in France). See “IV. Defining Regions” to learn more.

5dimensions that play a key role in individuals’ well-being and provide a set of indicators tomeasure them, allowing cross-countries comparison.

Figure 1: Regional well-being conceptual framework

Place characteristics

People’s well-being

Individuals’
characteristics

Including citizenship,
governance and institutions

People’s well-being is composed of many dimensions

Average outcomes and distribution across regions andgroups of people

A second important inspiration behind the conceptual framework for regional wellbeing is the OECD Regions and Cities at a Glance series. This work has shown that disparities
within and among regions in jobs, income, quality of life and sustainability still characterise
most OECD countries.
Sub-national data offer a clearer picture of how life is lived than national averages do,allowing people to recognise their own experience more easily. A closer look at regional
data shows that well-being in a region may differ widely according to the dimension
considered. No country appears to have regions that enjoy simultaneously high or low levels
of well-being in every dimension. For instance, a region may enjoy a satisfactory level of
employment but suffer from poor environmental conditions; in another region, an increasein public transport may improve job outcomes, making it easier to commute to work, as wellas improve air quality.
Data on disparities among and within regions might also capture the well-being ofgroups of people more accurately than national data do, especially when these groups are
not distributed evenly across space. For example, health outcomes are likely to be
influenced by the demographic characteristics of rural and urban populations.
Spatial analysis may also help to shed light on the impact of perceived distribution
inequalities on subjective well-being. Evidence shows that individuals assign great
importance to the inequalities they experience in their local living context when assessing
their own well-being and forming expectations about returns of education and skills, andfairness and efficiency of service delivery.
6II. The Interactive web tool at a glancewww.oecdregionalwellbeing.org* Website design and production by Moritz Stefaner and Dominikus Baur with support from Raureif GmbHThe interactive website is a means to initiate a conversation on well-being on what
people know best – their home region. The web tool localises the region where the user isand shows how the region fares on eleven well-being topics (for example Ile-de-France inthe figure).
For each topic, a score on a scale from 0 to 10 is attributed to the region, based on one
or more indicators. A higher score indicates better performance in a topic relative to all theother regions.
The regional well-being is assessed by looking at the different topics represented by theeleven branches of the illustration. The length of each branch reflects the performance (thescore) of the region relatively to the other OECD regions.
The web tool does not include a regional composite well-being index. The trade-off
between a composite index (which conveys a single unified view, but may diluteinformation) and a range of indicators (which offers detailed information, but is moredifficult to communicate) is widely debated. As OECD (2014) underlines, translating acomposite index into concrete policy messages and actions has proven to be a complex task
in practice for regional policy makers. Therefore in the web tool we do not make a single
statement about the overall well-being in a region. Instead, we present the information insuch a way that users can consider the relative importance of each topic and bring their own
personal evaluations to these questions.

“The user experience of the website is centred around the measurement of single regions in theircontext. Reflecting your own region in context provides a natural starting point for further
explorations. For example, the option “regions with similar well-being” visualise other regions withthe same level of well-being all over the world. Who knew that Massachusetts and Hamburg are
actually not that far apart, when it comes to well-being? Or that Bavaria has a similar profile to
Northern Norway?” (M. Stefaner – Information designer for oecdregionalwellbeing.org)

7

Below the findings for each region, users
can also visualise regions from othercountries with a similar combination ofwell-being outcomes.
4

Each region’s well-being can becompared with that of the other regions.
When selecting a specific topic ofinterest – for example health – the score
for the region is presented , as well as
the relative position of the region
compared to the other regions in the same
country , its relative position comparedto all of the OECD regions , and thetrend, whether the region has increased or
decreased its relative ranking in the past
decade . Values of well-being indicators
expressedin
theiroriginal
units(percentage, dollars, etc.) are at the bottomof the card , and you can share the card
to your social network .

1

2

3

5

7
6

You can also compare countries on the basis of their average score ineach topic2  and on the disparities ofwell-being outcomes across regions of
the same country . Regional
disparities in a topic are measured bylooking at the difference between the
top and bottom 20% regional values inthat specific topic compared to theother OECD countries.

8

9

2

The country average scores may differ from those obtained through the BLI since the underlying set ofindicators may be different. National comparisons ought to be done with the BLI rather than with the regional
well-being indicators as the BLI selection of indicators better reflects the national perspective

8

III. Defining Scores and Trends
1. Regional well-being scores
Well-being indicators are expressed in different units, for example the household
disposable income per capita is expressed in USD whereas voter turnout is the percentageof registered voters who voted at the most recent national election. In order to compare
indicators on a same scale, they have been normalised using the min-max method (OECD,2008), a statistical formula that range values from 0 to 10. Three steps are followed totransform the regional value of an indicator into a well-being score:
1. Identify the regions with the minimum and the maximum values of theindicator across OECD regions;
2. Normalise each indicator with the min-max formula; and3. Aggregate scores, when a topic contains more than one indicator.
First, for each indicator, the 447 regions have been sorted from the region with thelowest value to the region with the highest value. In order to reduce the skewness of the
distribution, a threshold has been applied to eliminate the values that are below the 4th
percentile and above the 96th percentile. Imposing a threshold on extreme values allows to
obtain well-being scores that are more evenly distributed and avoids cases where (as e.g. in
the homicides rate) almost all regions would be comprised between 9 and 10. Secondly, themin-max formula is applied, the extreme values identified in the first step are assigned tothe scores of 0 and 10, and other regions are assigned to a score x̂i . Indicators that
correspond to lower well-being outcomes (unemployment rate, mortality rate, air pollution
and homicide rate) are inversely coded x̌i :𝑥̂𝑖 = (

𝑥𝑖 − min(𝑥)⁡) × 10max(𝑥) − min(𝑥)𝑥̌𝑖 = (

max(𝑥)⁡ − 𝑥𝑖 ⁡) × 10max(𝑥) − min(𝑥)Finally, when a topic of well-being is measured by two indicators, like job which iscomposed by employment and unemployment rates, the score is defined by the arithmetic
mean of the normalised value of the respective indicators.

2. Trends
Well-being trends compare the score of the region from the most recent year to its
score in 2010 or the closest year available before 2010. It shows if the region has progressedin the topic, relatively to the other regions. The main constraint to assess trends is related tothe missing data in the earliest period, where some missing regions can jeopardise thecomparability of the score across time. In order to overcome this issue, the indicators werenormalised in the two periods using only the sample of regions for which values areavailable in the earliest period. Evolution of the score above +5% or below -5% over theperiod is considered respectively as an improvement (increasing arrow) or a decline(decreasing arrow), otherwise as a stable situation (horizontal arrow).
9

3. Regions with similar well-being profiles in othercountries
The interactive web tool presents regions from other countries that have a similar levelof well-being outcomes as the selected region. The calculation to identify similar regions isbased on the sum of the absolute differences in the topics scores, the so-called Manhattan
distance. If one value in a topic is not available, the difference is set at 5 by default. The top
four regions from different countries with the lowest distance to the selected region aredisplayed.

4. Regional disparities in a topic within a country
Low regional disparities (or regional similarities) within a country indicates the degree
to which well-being outcomes are similar between regions belonging to the same country.
International comparability of regional disparities is limited by the fact that indexes arevery sensitive to the size and number of regions. In fact, as the size of regions increases (orthe number of regions decreases), territorial differences tend to be averaged out anddisparities decrease. This effect can be reduced – but not totally be eliminated – bycomparing the performance of top 20% regional values with the bottom 20% regional
values.
An index to measure regional disparities in a country for each topic has been computed
comparing the ratio between top and bottom 20% regional values of a country to the ratioof top and bottom 20% regional values in the OECD area. The index is then expressed interms of similarity rather than disparities so that higher values of the index correspond tobetter territorial cohesion in the country: it ranges between 0 and 10, where 0 means thecountry has large regional disparities relatively to the other countries and 10 means that thecountry has small disparities relatively to the other countries.
𝑡𝑜𝑝⁡(𝑋)) − bottom(𝑂𝐸𝐶𝐷)⁡
𝑏𝑜𝑡𝑡𝑜𝑚⁡(𝑋)̿
𝑋 = (1 −) × 10top(𝑂𝐸𝐶𝐷) − bottom(𝑂𝐸𝐶𝐷)(

where top and bottom refer to the regional share in each indicator and corresponding to
20% of the national population.

10

IV. Defining Regions
There are many ways to identify a region within a country: according to its
administrative boundaries, whether it represents an electoral district, according to thespace where people travel to work, according to the geographical features or instead
economic functions, etc.
For analytical purposes, the OECD classifies regions as the first administrative tier of
sub-national government (for example States in the United States, Provinces in Canada, or
Régions in France). This classification is used by National Statistical Offices to collectinformation and it represents in many countries the framework for implementing regional
policies.
While the number of regions (so called Territorial Level 2 or TL2 in the OECD Territorial
Grid) varies from country to country, the international comparability is ensured by the factthat these administrative regions are officially established in countries. No regions aredefined in Luxembourg, while for Estonia, Latvia and Lithuania smaller regions (Territorial
Level 3) are included in the interactive web tool. The well-being topics and indicators areshown for the 447 regions (Table 1).
The OECD series Regions and Cities at a Glance also documents, when possible, wellbeing in smaller administrative regions (more than 2 400 regions) and in the 281
metropolitan areas (functional urban areas with more than 250 000 population).
While the regional classification is being extended to non-OECD countries, the regional
well-being indicators are currently available only for the 38 OECD countries.
Table 1: Number of regions in OECD countries defined for the well-being tool
Country

Territorial level 2 (number of regions)

Australia

States/territories (8)Austria

Bundesländer (9)Belgium

Régions (3)CanadaProvinces and territories (13)

Chile

Regions (15)Colombia

Departamentos + Capital District (33)

Costa Rica

Planning regions (6)Czech Republic

Oblasti (8)Denmark

Regioner (5)EstoniaGroups of maakond (5, TL3)

Finland

Suuralueet (5)FranceRégions (13)Germany

Länder (16)GreeceRegions - Perifereies (13)Hungary

Planning statistical regions (8)IcelandRegions (2)IrelandGroups regional authority regions (3)IsraelDistricts (6)Italy

Regioni (21)Japan

Groups of prefectures (10)11

KoreaRegions (7)LatviaStatistical regions (6, TL3)

Lithuania

Counties (10, TL3)

Luxembourg

State (1)MexicoEstados (32)Netherlands

Provinces (12)New Zealand

Regional councils (14)NorwayLandsdeler (7)PolandVojewodztwa (17)Portugal

Comissaoes de coordenaçao e des. regional + regioes autonomas (7)Slovak Republic

Zoskupenia krajov (4)Slovenia

Kohezijske regije (2)SpainComunidades autonomas (19)SwedenRiksomraden (8)Switzerland

Grandes regions (7)TurkeyRegions (26)

United Kingdom

Regions and countries (12)United States

States and the District of Columbia (51)12

V. Well-being Topics and Indicators
Overview
A set of indicators to measure the different topics of well-being has been developed forthe 447 OECD regions. These indicators, comparable across OECD countries, come fromofficial sources in most of the cases and are available over different years. They are publicly
available in the OECD Regional Well-Being Database. At present, regional measures areavailable for OECD countries in eleven well-being topics: income, jobs, housing, education,
health, environment, safety, civic engagement and governance, access to services,
community, and life satisfaction (Table 2).
Regional measures, comparable across countries, are not currently available on worklife balance, which is instead included in the OECD Better Life Initiative at the national level.
The OECD plans to include this indicator in future releases.
For each topic, one or two indicators have been selected (Table 2). Improvements inthe way we measure the well-being topics in regions are underway: for example, additional
measures of access to services or indicators that measure other environmental performanceare being developed. A larger set of indicators is available in the OECD publication Regions
and Cities at a Glance, including measures of income inequalities within regions.
Table 2: Well-Being topics selected for visualisation

Material
conditions

TopicsIncomeJobs
Housing

Subjective
wellbeing

Quality of life

HealthIndicators
 Household disposable income per capita (in real USD PPP) Employment rate (%)
 Unemployment rate (%)
 Number of rooms per person (ratio) Life expectancy at birth (years)
 Age adjusted mortality rate (per 1 000 people)

Education

 Share of labour force with at least secondary education (%)

Environment

 Estimated average exposure to air pollution in PM2.5 (µg/m³), based onsatellite imagery data

Safety Homicide rate (per 100 000 people)

Civic engagement

 Voter turnout (%)

Accessibility ofservices Share of households with broadband access (%)
 Internet download speed: deviation from OECD average (%)
 Percentage of people who have friends or relatives to rely on in case ofneedCommunity
Life satisfaction

 Average self-evaluation of life satisfaction on a scale from 0 to 10

Reference years: see details in section VII.
Source: OECD Regional Well-Being Database.

13

VI. Topics and indicators in the OECD Better Life Indexand in the Regional well-being tool
The OECD regional well-being work makes uses of the same topics and similar
indicators as in the Better Life Initiative at the national level, whenever data are available ina suitable format. Applying the framework used for the Better Life Initiative at the regional
level has required some adjustments to bring in aspects that have special importance forregional policy-makers, for example the topic Access to services. For some topics of the
Better Life Initiative, regional indicators are not currently available. More regional wellbeing indicators are available in the publication OECD Regions at a Glance. (OECD, 2016).
Regional well-being indicators in
the interactive web tool

Dimensions
Income•Household disposable income•••

Employment rate
Unemployment rate

•
•
•

•

Number of rooms per person•••

Life expectancy at birth
Age adjusted mortality rate
Educational attainment•

Air quality•

Homicide rate•

Voter turnout••

Broadband connection
Internet download speed
N/A

Jobs

Housing
Health status
Education andskillsEnvironmental
quality
Personal security
Civic engagement
and governance
Accessibility ofservices

•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

•

Social network support

•
•
•

•

Life satisfaction•

Work-life balanceSocialconnections
Subjective wellbeing•

National indicators in the
Better Life Initiative
Household net adjusted disposable
incomeHousehold net financial wealth
Employment rateLong-term unemployment rate
Average annual earnings per
employees
Job tenure
Number of rooms per person
Housing expenditure
Dwellings without basic facilities
Life expectancy at birthSelf-reported health status
Educational attainment
Students cognitive skills (PISA)
Years in education
Air quality
Satisfaction with water quality
Homicide rate
Self-reported victimization
Voter turnout
Consultation on rule making
N/A
Employees working very long hours
Time devoted to leisureSocial network support
Life satisfaction

VII. Sources and References
a. Data source and period
Data source: OECD Regional Statistics (database), http://dx.doi.org/10.1787/region-data-en
Data and detailed data sources are available in the excel file downloadable on the site.

14

Table 3: Reference years for data: Last year (first year)
Unemployment
rate

Number ofrooms percapitaPopulation
with atleast
secondaryeducationLife
expectancy

Mortalityrate

Air quality(PM2.5)

Homicide
rate

Voter
turnout

Households
broadband
accessInternet
speed

Perceivedsocialnetwork
supportLifesatisfaction

2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2016 (06)2020 (10)2021 (01)2016 (06)2021 (..)
2021 (10)2021 (10)2020 (..)

2019 (10)2020 (10)2020 (10)2019 (10)2020 (10)2021 (10)2021 (10)2019 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2021 (10)2019 (10)2019 (08)2019 (10)2019 (08)2017 (10)2021 (10)2021 (10)2019 (10)

2021
2021
2021
2021

2018
2018
2018
2018

2018
2018
2018
2018

AUS
AUT
BEL
CAN

2017 (09)2020 (10)2021 (..)
2020 (10)2021 (10)2020 (10)2021 (10)2021 (10)2021 (10)2020 (10)2021 (10)2021 (10)2020 (02)2020 (..)
2021 (10)2021 (10)2020 (09)2020 (10)2021 (10)2021 (10)2021 (10)2021 (10)..
2020 (10)2019 (10)2020 (10)2020 (10)2021 (10)2020 (10)2020 (10)2020 (10)2020 (10)2021 (10)2021 (10)2021 (..)
2020 (10)2017 (10)2019 (10)2018 (..)
2017 (10)2017 (10)2020 (..)
2021 (10)2021 (10)

2021
2021
2021
2021

2018
2018
2018
2018

2018
2018
2018
2018

CHL
COL
CRI
CZE

2020 (10)2018 (10)2019 (10)2019 (10)2019 (10)2019 (10)2019 (10)2018 (10)2020 (10)2018 (10)2020 (10)2018 (10)2020 (10)2018 (10)2019 (10)2020 (10)2020 (10)2019 (10)2020 (10)2019 (..)
2019 (10)2019 (10)2019 (10)2020 (10)2019 (10)2020 (10)2016 (10)2021 (..)
2019 (10)2019 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (..)
2020 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2020 (10)2021 (10)2020 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2020 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (..)
2020 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2020 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2017 (10)2012 (05)2016 (10)2016 (..)
2021 (01)2021 (10)..
2021 (..)
2019 (10)2021 (10)2018 (08)2020 (10)2020 (10)2020 (10)2012 (..)
2020 (10)2021 (09)2013 (..)
2021 (10)2020 (02)2018 (06)2020 (10)2021 (..)
2021 (10)2021 (10)2020 (10)2014 (05)2011 (05)2016 (05)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)..
2021 (..)
2017 (..)
2021 (10)..
2020 (10)2018 (10)2021 (..)
2021 (10)2020 (10)2021 (10)2020 (..)
2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2020 (10)2021 (10)2019 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)..
2020 (..)
2019 (10)2021 (10)2015 (10)2020 (10)2020 (10)2020 (10)2020 (10)2021 (10)2020 (10)2018 (06)2021 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2021 (10)2020 (10)2019 (10)2018 (10)2019 (10)2021 (10)2020 (10)2021 (10)2020 (10)2017 (10)2021 (10)2021 (10)2021 (10)2020 (10)2019 (10)2021 (10)2019 (10)2020 (10)2021 (..)
2021 (10)2021 (10)2017 (10)2021 (10)2016 (10)2021 (10)2021 (10)2021 (10)2021 (10)2020 (10)2020 (10)2021 (10)2021 (10)2019 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2020 (10)2021 (10)2020 (10)2021 (10)2018 (..)
2019 (10)2021 (10)2015 (10)2020 (10)2019 (10)2020 (10)2021 (10)2020 (10)2021 (10)2021 (10)2017 (10)2020 (10)2010 (10)2014 (10)2021 (10)2019 (10)2020 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2020 (10)2020 (10)2020 (10)2019 (07)2019 (03)2018 (06)2017 (07)2021 (09)2019 (00)2018 (10)2020 (09)2020 (..)
2019 (09)2018 (08)2021 (10)2020 (10)2014 (10)2021 (07)2018 (09)2021 (09)2017 (10)2017 (..)
2021 (09)2019 (07)2019 (09)2020 (10)2018 (07)2019 (08)2018 (10)2019 (07)2015 (07)2019 (10)2020 (10)2021 (10)2017 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2012 (08)2021 (..)
2018 (10)2021 (10)2020 (..)
2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2021 (10)2012 (09)2021 (10)2021 (..)
2021 (10)2021 (10)2021 (..)
2021 (10)2021 (10)2021 (..)
2021 (..)
2019 (09)2019 (10)

2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021
2021

2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018

2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018

DNK
EST
FIN
FRA
DEU
GRC
HUN
ISL
IRL
ISR
ITA
JPN
KOR
LVA
LTU
LUX
MEX
NLD
NZL
NOR
POL
PRT
SVK
SVN
ESP
SWE
CHE
TUR
GBR
USA

Disposable
income percapitaEmployment
rate

AUS
AUT
BEL
CAN

2019 (10)2020 (10)2019 (10)2020 (10)

CHL
COL
CRI
CZE
DNK
EST
FIN
FRA
DEU
GRC
HUN
ISL
IRL
ISR
ITA
JPN
KOR
LVA
LTU
LUX
MEX
NLD
NZL
NOR
POL
PRT
SVK
SVN
ESP
SWE
CHE
TUR
GBR
USA

Note: last year (first year). “.." means that regional data are not available for this indicator.

15

b. Statistics for Israel
The statistical data for Israel are supplied by and under the responsibility of the relevant
Israeli authorities. The use of such data by the OECD is without prejudice to the status of theGolan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms ofinternational law.

c. Country codes
AUS
AUT
BEL
CAN
CHE
CHL
COL
CRI
CZE
DEU
DNK
ESP
EST

Australia
Austria
Belgium
CanadaSwitzerland
Chile
Colombia
Costa Rica
Czech Republic
Germany
Denmark
Spain
Estonia

FIN
FRA
GBR
GRC
HUN
IRL
ISL
ISR
ITA
JPN
KOR
LTU
LUX

FinlandFranceUnited Kingdom
GreeceHungary
Ireland
IcelandIsrael
Italy
Japan
Korea
Lithuania
Luxembourg

LVA
MEX
NLD
NOR
NZL
POL
PRT
SVK
SVN
SWE
TUR
USA

LatviaMexicoNetherlands
NorwayNew Zealand
PolandPortugal
Slovak Republic
Slovenia
SwedenTürkiye
United States

d. References
OECD (2016), OECD Regions at a Glance 2016, OECD Publishing, Paris, http://dx.doi.org/10.1787/reg_glance2016-en.

OECD (2015), How's Life? 2015: Measuring Well-being, OECD Publishing,Paris, http://dx.doi.org/10.1787/how_life-2015-en
OECD (2014), , How's Life in Your Region?: Measuring Regional and Local Well-being for Policy Making,OECD Publishing, Paris. DOI: http://dx.doi.org/10.1787/9789264217416-en
OECD (2011), How's Life?: Measuring Well-being, OECD Publishing. doi: 10.1787/9789264121164-en
OECD/European Union/JRC (2008), Handbook on Constructing Composite Indicators: Methodology andUser Guide, OECD Publishing. doi: 10.1787/9789264043466-enSen, A. (1993). Capability and Well-Being. In Nussbaum, M. & Sen, A. (eds), The Quality of Life (30-45).
Oxford: Oxford University Press.
Stiglitz, J. et al. (2009) Report by the Commission on the Measurement of Economic Performance andSocial Progress16