Decent Work and Economic Growth

Living Edition
| Editors: Walter Leal Filho, Anabela Marisa Azul, Luciana Brandli, Pinar Gökcin Özuyar, Tony Wall

Discussing Approaches to Standard of Living

  • Maria Barreiro-GenEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-71058-7_22-1

Definition

The three main, and sometimes conflicting, definitions of Standard of Living are (1) the utility of life (Pigou 1952); (2) economic provision or “opulence,” which measures the amount and quality of commodities that the individual is free to use (Deutsch and Silber 1987); and (3) a type of freedom, i.e., to be free to do something, the capability to live well for a certain socioeconomic class in a certain geographic area (Sen 1984). Among these, the last one is the most complete and complex definition; however, in practice, governments and institutions tend to use the second approach since it is easier to obtain data for this one.

Introduction

Unlimited growth, as a main goal of a country, has been criticized, especially during the last 10 years (Stiglitz et al. 2008; Heinrichs 2013; Barreiro-Gen 2018), since it may not increase people’s well-being (Juknys et al. 2018). Equally, the economic assumption that a person who consumes more is always better off than a person who consumes less has been questioned (Schumacher 1978). These criticisms entail the rethinking of the basic foundations of the traditional economic system, increasing the importance of development, exchange, proximity, and ecological issues (Monteil 2014), as well as co-responsibility, efficiency, and sustainability (Lozano 2008; Heinrichs 2013; Martin 2016). Such reflections are highlighted in the 2030 Agenda for Sustainable Development as adopted by all United Nations Member States in 2015 under the promotion of sustained, inclusive, and sustainable economic growth goal, particularly through the promotion of full and productive employment and decent work for all (United Nations 2015).

Comparative studies between different countries or regions are frequently carried out in order to study their economic or social context, where the use of indicators such as gross domestic product (GDP) or gross national income (GNI) is common (Mochón Morcillo 2010). These indicators were designed to explain economic growth and not to measure development or well-being (Peterson 2017). Many issues, such as inequality and gender, are not included in GDP or in GNI (see Stiglitz et al. 2008). International institutions have developed a number of alternative indicators to better reflect the complexities of Standard of Living or the Quality of Life in a country (United Nations Development Programme 2016; OECD 2017a; Eurostat 2018a).

The structure of this piece is as follows: The second section provides an overview of the main macroeconomic measures used for assessing well-being; the third section presents the main theoretical approaches to standard of living; the fourth section discusses some practical approaches; the fifth section compares the concept of standard of living to quality of life; and the sixth section provides the conclusions.

An Overview of the Main Macroeconomic Measures Used to Assess Well-Being

How can two economies that produce different types of goods be compared? Using physical units to compare their production is not always a good option because countries can produce different goods and services, and thus it becomes difficult to compare them. The concept of “value,” i.e., using production in monetary units, offers a good option for such comparisons (Barreiro Gen and del Campo Villares 2017).

The indicator most widely used to compare different economies is GDP, which measures economic growth (Eurostat 2018b). GDP is one of the main indicators used to control macroeconomic variables, mainly due to availability of data from most countries (Barreiro Gen and del Campo Villares 2017). GDP is an aggregate measure of production and is calculated as the sum of the final uses of goods and services – except intermediate consumption – measured in purchasers’ prices, minus the value of imports of goods and services (Eurostat 2018b). GDP can be also expressed in purchasing power standards (PPS), a common currency that removes the differences in price levels between countries, and can take into account population through GDP per capita.

GNI is a similar concept to GDP. GNI is the sum of incomes of residents of an economy in a given period of time. It is equal to GDP minus primary income payable by resident units to nonresident units plus primary income receivable from the rest of the world (from nonresident units to resident units) (Eurostat 2018c).

GDP and GNI both fail to measure the well-being of societies however, since they focus only on production. A country could have a positive trend of production and, at the same time, the situation of its population could be getting worse. Societies need more than hard numbers of GDP and to take into account Quality of Life (OECD 2017a). New approaches propose alternative indicators and well-being metrics that can be used to compare countries or regions, especially if a more precise vision about the development or the real situation of the people that are part of these territories is required.

The United Nations, for example, has developed several indices, including the Human Development Index (HDI), Inequality-adjusted Human Development Index (IHDI), Gender Inequality Index (GII), the Multidimensional Poverty Index (MPI), and the Happiness Index.

The HDI is a measure of Standard of Living and is an attempt at designing and applying indicators that more accurately reflect the real situation of populations. HDI is a synthetic index. It includes GDP per capita, as well as variables related to health or education (United Nations Development Programme 2016). HDI is composed by:
  • Life expectancy at birth

  • Expected years of schooling

  • Mean years of schooling

  • Gross national income (GNI) per capita

HDI index ranges from 0 to 1. The higher the HDI of a country, the better position it has in the ranking on human development. There are several groups according to this indicator: those with very high human development, such as Norway, Australia, or Denmark; those with high human development, such as Bulgaria, Panama, or Cuba; those with medium human development, such as Egypt or the Philippines; those with low human development, such as Nigeria or Afghanistan; and other countries, e.g., Monaco (United Nations 2018a).

Countries with the lowest positions, such as Mozambique, South Sudan, and Niger, have an HDI between 0.35 and 0.4, which is less than half of the HDI for countries higher in the rank of HDI (see Table 1). Analyzing the variables that compose this index, the low HDIs are due to low values in all of the variables that compose HDI and not due to any given variable. Therefore, all variables need improvement in the countries with lower scores: their production per capita is too low, and they need investment in education and health provision. For instance, the difference between the life expectancy at birth in Norway (82.3 years) and in Chad (53.2) is almost 30 years. In addition, the lack of information for the lowest positioned countries is considerable, in spite of the UN attempting to obtain data for such indicators. In some cases, where data is not available, estimates have been used by the UN.
Table 1

Human Development Index and its components (2017). Countries with highest and lowest positions

HDI rank

Country

Human Development Index (HDI) (value)

Life expectancy at birth (years)

Expected years of schooling (years)

Mean years of schooling (years)

Gross national income (GNI) per capita (2011 PPP $)

Countries with the highest ranks

1

Norway

0.953

82.3

17.9

12.6

68,012

2

Switzerland

0.944

83.5

16.2

13.4

57,625

3

Australia

0.939

83.1

22.9a

12.9

43,560

4

Ireland

0.938

81.6

19.6a

12.5b

53,754

5

Germany

0.936

81.2

17.0

14.1

46,136

6

Iceland

0.935

82.9

19.3a

12.4b

45,810

7

Hong Kong, China (SAR)

0.933

84.1

16.3

12

58,420

7

Sweden

0.933

82.6

17.6

12.4

47,766

9

Singapore

0.932

83.2

16.2c

11.5

82,503d

10

Netherlands

0.931

82.0

18.0

12.2

47,900

Countries with the lowest ranks

180

Mozambique

0.437

58.9

9.7

3.5e

1,093

181

Liberia

0.435

63.0

10.0g

4.7f

667

182

Mali

0.427

58.5

7.7

2.3e

1,953

183

Burkina Faso

0.423

60.8

8.5

1.5g

1,65

184

Sierra Leone

0.419

52.2

9.8g

3.5f

1,24

185

Burundi

0.417

57.9

11.7

3.0g

702

186

Chad

0.404

53.2

8.0

2.3g

1,75

187

South Sudan

0.388

57.3

4.9g

4.8

963h

188

Central African Republic

0.367

52.9

7.2e

4.3f

663

189

Niger

0.354

60.4

5.4

2.0f

906

Source: Based on United Nations (2018a)

aIn calculating the HDI value, expected years of schooling is capped at 18 years

bBased on data from OECD (2017b)

cBased on data from the national statistical office

dIn calculating the HDI value, GNI per capita is capped at $75,000

eUpdated by HDRO based on data from UNESCO Institute for Statistics (2018)

fBased on Barro and Lee (2016)

gUpdated by HDRO based on data from ICF Macro Demographic and Health Surveys for 2006–2017

hHDRO estimate based on data from World Bank (2018) and United Nations Statistics Division (2018)

Countries with very high human development can serve as a model for others. Such countries have high HDI values and have been improving their index over recent years. The variables used to calculate HDI are fairly easy to fulfill for more developed countries; thus, it makes the indicator to have high ranks. As it can be seen, HDI is a simple measure that includes essential factors needed for human development, but it could be improved. For example, Engineer et al. (2010) questioned the inclusion of life expectancy as a proxy for all health issues, since life expectancy is a direct measure of quantity of life, but it is only an indirect measure of healthy years lived. These authors have proposed to introduce into the HDI the morbidity indicator, that is to say, “expected lost healthy years” (LHE).

A related index to HDI is the Inequality-adjusted Human Development Index (IHDI), which quantifies the effects of inequality on human development, measured in terms of the HDI. It is the HDI value adjusted for inequalities in the three basic dimensions of human development: production, education, and health (United Nations Development Programme 2016).

As Table 2 shows (note that there is no information about some categories for countries such as New Zealand or Singapore), if the values of the HDI for the 27 best-placed countries in the ranking are compared with the HDI adjusted for inequality in 2015, it can be seen that all of them get worse when inequalities are taken into account. However, the overall loss is not the same for all of them: Norway (5.4%), Finland (5.8%), Slovenia (5.9%), and Sweden (6.7%) have the lowest overall loss. These countries have been implementing policies in order to reduce inequalities. Sweden, for example, has been experimenting with policies to reduce the gender gap for decades.
Table 2

Inequality-adjusted DHI (IDHI) (2015). Countries better positioned

Country

2015 (DHI)

2015 (Inequality-adjusted DHI)

Overall loss (%)

Norway

0.949

0.898

5.4

Australia

0.939

0.861

8.2

Switzerland

0.939

0.859

8.6

Germany

0.926

0.859

7.2

Denmark

0.925

0.858

7.2

Singapore

0.925

NA

NA

Netherlands

0.924

0.861

6.9

Ireland

0.923

0.85

7.9

Iceland

0.921

0.868

5.8

United States

0.920

0.796

8.9

Canada

0.920

0.839

13.5

Hong Kong

0.917

NA

NA

New Zealand

0.915

NA

NA

Sweden

0.913

0.851

6.7

Liechtenstein

0.912

NA

NA

United Kingdom

0.909

0.836

8.0

Japan

0.903

0.791

12.4

Republic of Korea

0.901

0.753

16.4

Israel

0.899

0.778

13.5

Luxembourg

0.898

0.827

8.0

France

0.897

0.813

9.4

Belgium

0.896

0.821

8.3

Finland

0.895

0.843

5.8

Austria

0.893

0.815

8.7

Slovenia

0.890

0.838

5.9

Italy

0.887

0.784

11.5

Spain

0.884

0.791

10.5

Source: Based on United Nations Development Programme (2016)

NA not available

The Gender Inequality Index (GII) is a composite measure reflecting inequality between women and men in three dimensions: reproductive health, empowerment, and labor market (United Nations 2018a).

United Nations has also developed an Index focused on Poverty: The Multidimensional Poverty Index (MPI). MPI takes into account, for example, the percentage of functionally illiterate people within the working age population, and the percentage of people with incomes below the average income (United Nations 2018a).

The Happiness Index has been elaborated by United Nations from 2012. It is an attempt to measure subjective well-being. This Index report life evaluations in terms of six key variables: GDP per capita, social support, healthy life expectancy, freedom to make life choices, generosity, and freedom from corruption (United Nations 2018b). According to the last World Happiness Report (United Nations 2018b), almost all the top ten positions are held by countries in Northern Europe, such as Finland (7.632), Norway (7.594), Denmark (7.555), Iceland (7.495), Switzerland (7.487), and the Netherlands (7.441). The worst positioned countries are Syria (3.462), Rwanda (3.408), Yemen (3.355), Tanzania (3.303), South Sudan (3.254), the Central African Republic (3.083), and Burundi (2.905).

The OECD proposed the Better Life Index that allows comparison of well-being across countries, based on 11 essential topics in the areas of material living conditions and Quality of Life (OECD 2017a), such as job issues and education. Turkey, for instance, performs well in only a few measures of well-being such as civic engagement, if its data are compared with other countries included in this index. Turkey ranks below average in many variables, such as income and wealth, health status, education and skills, jobs and earnings, subjective well-being, environmental quality, and work-life balance. Sweden and Norway perform very well in many measures of well-being in relative terms and rank above the average in all dimensions. As discussed, the promotion of decent work for all is one of the Sustainable Development Goals (SDG8) (United Nations 2016). Focusing on job issues, the Better Life Index includes the following variables:
  • Labor market insecurity

  • Employment rate

  • Long-term unemployment rate

  • Personal earnings

According to the OECD (2017a), labor market insecurity is defined in terms of the expected earnings loss, measured as the percentage of the previous earnings, associated with unemployment. The risk of becoming unemployed, the expected duration of unemployment, and the degree of mitigation against these losses provided by government transfers to the unemployed have an influence on this insecurity.

Within the OECD, Greece (17.4%), Spain (17.3%), and Turkey (13%) had the highest levels of labor market insecurity in 2017 (Fig. 1), whereas Portugal (6.5%), Sweden (5.7%), and France (5%) were all above the OECD average (4.9%). Countries with the highest levels of labor market insecurity should design and implement public policies in order to improve their labor market situation and contribute to achieve SDG8.
Fig. 1

Labor market insecurity. Better Life Index 2017. Based on OECD (2017a)

Main Theoretical Approaches to Standard of Living

There are a number of definitions of Standard of Living; however, there is no scientific consensus on its precise extent. The three main ones include (1) Standard of Living defined as the utility of life, (2) Standard of Living considered to be the economic provision or “opulence,” and (3) Standard of Living considered to be a type of freedom.

Standard of Living is defined as the utility of life, where the utility view of the Standard of Living is well presented by Pigou himself. Pigou uses “economic welfare,” “the Standard of Living,” “standard of real income,” and “material prosperity” as more or less synonymous (Pigou 1952). According to the modern version of this approach, utility is identified with fulfillment of wishes (Poduzov 2008).

More specific concepts have been defined recently, in order to go beyond just subsistence, or poverty, such as the decent living standard (DLS). This concept includes material conditions that are essential for humans to flourish, that is to say, a “basic minimum” (Rao and Min 2018). DLS includes essential requirements for well-being, such as nutrition, clean air, education expenditure, and mobility. According to Rao and Min (2018), DLS can be defined as “basic material requirements that are instrumental, but not sufficient, to achieve physical, and to an extent social, dimensions of human wellbeing, whether conceived as basic needs or basic capabilities, and independent of peoples’ values or relative stature in society.”

Standard of Living is considered to be an economic provision or “opulence,” which measures the amount and quality of commodities that the individual is free to use. This approach relies on market purchase data when evaluating the Standard of Living of an individual, a household, or even a country (Deutsch and Silber 1987). However, whether the economic-provision conception of Standard of Living represents accurately the level of personal well-being is not clear (Poduzov 2008). This approach is insufficient since it does not provide, according to Naidoo (2019), a “full command over resources.”

Standard of Living considered to be a type of freedom is, according to Sen (1984), when economic provision or utility is a poor substitute for life. For Sen, Standard of Living is to be free to do something, the capability to live well. Sen’s perspective is focused on what people are actually able to do or to be. Sen has proposed two conceptions of Standard of Living: the actual Standard of Living of a person and the choice of lifestyles that are available to a person at a given point in time, because only one lifestyle can be chosen and the decision influences the actual situation (Poduzov 2008). In line with this, Nussbaum (2000) proposes how capabilities can provide a basis for principles that people have a right to demand from their governments.

From these three definitions, the last one is the most complete and complex approach; in practice, however, governments and institutions often use the second approach because of data availability, mainly from developed countries.

Practical Approaches to Standard of Living

Most of practical approaches to measure Standard of Living have been carried out in developed countries since official data on many relevant variables is available.

Atkinson and Marlier (2010) focused on disposable income as a defining indicator of Standard of Living. They argue that for comparative statistics on living conditions, income measures are convenient and independent from subjective evaluation. In this line, Eurostat (2018d) defines the Standard of Living as the median equivalized disposable income, that is to say, the total income of a household (after tax and other deductions) available for spending or saving, divided by the number of household members, converted into equalized adults. Eurostat uses this measure to calculate the dispersion around the at-risk-of-poverty threshold that is defined as the percentage of persons with an equivalized disposable income below, respectively, 40%, 50%, 60%, and 70% of the national median equivalized disposable income.

Llewellyn Consulting (2016) developed a study based on four key indicators related to economic issues: (1) average nominal wages; (2) the purchasing power parity (PPP), that is to say, adjusted average wage; (3) the cost of living in main European cities; and (4) the purchasing power of the average wage in main European cities. In the study Standard of Living is defined as the gap between the take-home pay and price levels.

Some institutions around the world have developed surveys to measure the living standards in a country, such as in Nepal (Central Bureau of Statistics 2011), that has a more holistic approach by including several variables in the analysis related to housing, access to facilities, literacy, and education or health services, and also in Mexico, where information on Living Standards of its population, covering topics such as employment, time spending, health and retrospective health, and crime and victimization is collected (Ibero-American University 2009).

In several European countries, e.g., Spain and Sweden, National Statistics Institutes conduct similar studies, but they use concepts such as living conditions or “life conditions” instead of “living standards” (e.g., INE 2017). They analyze the average net annual income, the risk of poverty, or the material deprivation. Eurostat (2015) also has available data about material deprivation in the European Union Statistics on Income and Living Conditions, which includes many variables, such as “persons who cannot afford to spend a small amount of money each week on themselves.” Table 3 shows the results in 2015 by sex. The data are sorted by percentage of the total population, from lower to higher percentage. Nordic countries (Finland, Norway, and Sweden) make up the top three. Bulgaria, Greece, and Romania are at the bottom. The data show that females have more problems in all countries except Finland in being able to afford to spend a small amount of money on themselves.
Table 3

Persons who cannot afford to spend a small amount of money each week on themselves by sex (2015)

Country

Total

Females

Males

Finland

1.0

0.9

1.0

Norway

3.6

4.7

2.6

Sweden

4.6

6.2

2.9

Luxembourg

5.4

6.3

4.5

Cyprus

5.7

6.3

5.0

Slovenia

5.7

6.3

5.2

Austria

6.1

7.5

4.6

Czech Republic

7.4

8.5

6.3

Netherlands

7.5

9.9

4.8

Estonia

7.6

9.0

6.1

Denmark

8.2

9.2

7.1

Belgium

11.2

12.4

9.9

Germany

11.4

12.9

9.7

Ireland

12.1

13.6

10.2

Poland

12.8

13.3

12.1

Spain

13.1

14.0

12.0

Latvia

14.2

14.2

14.1

France

14.7

18.4

10.6

Portugal

15.0

18.7

10.7

United Kingdom

15.1

16.7

13.4

Slovakia

15.8

17.2

14.2

European Union (28)

16.0

17.5

14.2

Italy

16.2

17.0

15.4

Iceland

16.6

20.0

13.1

Lithuania

18.7

18.8

18.6

Serbia

19.7

21.7

17.5

Croatia

20.2

21.8

18.4

Malta

20.5

21.7

19.2

Hungary

22.8

24.6

20.8

FYROMa

34.8

36.5

33.0

Bulgaria

35.8

38.3

33.2

Greece

45.6

46.5

44.7

Romania

50.3

51.5

49.0

Source: Based on Eurostat (2015)

aRepublic of Macedonia

Table 4 shows the percentages of “Persons who cannot afford to get together with friends or family (relatives) for a drink or meal at least once a month by sex” in 2015. The data are also sorted by percentage of the total population, from lower to higher percentage. The ranking of countries is quite similar to the Table 3. Nordic countries are positioned in the top. Cyprus is in a better position than in the previous variable. As in Table 3, Bulgaria, Greece, and Romania are again at the bottom of the table. Women have more difficulties than men to afford to get together with friends and family in all countries with percentages above the average.
Table 4

Persons who cannot afford to get together with friends or family (relatives) for a drink or meal at least once a month by sex (2015)

Country

Total

Females

Males

Sweden

0.8

1.1

0.5

Finland

1.7

1.4

1.9

Cyprus

2.0

2.1

1.9

Czech Republic

2.2

2.3

1.9

Norway

3.0

3.4

2.6

Netherlands

3.7

4.1

3.4

Denmark

4.0

3.6

4.5

Luxembourg

4.6

5.4

3.9

Austria

4.6

5.4

3.7

Estonia

5.2

5.8

4.4

France

5.3

6.7

3.8

Slovenia

6.3

6.8

5.9

Spain

7.1

7.4

6.6

Croatia

7.5

7.9

7.1

United Kingdom

8.0

8.3

7.6

Slovakia

8.1

9.0

7.2

Latvia

8.3

8.7

7.8

Malta

9.8

10.2

9.3

Poland

10.2

10.5

9.9

Belgium

10.6

11.7

9.5

European Union (28)

10.7

11.5

9.9

Italy

11.1

11.2

11.0

Portugal

11.2

12.5

9.8

Germany

12.7

14.0

11.2

Ireland

14.4

15.3

13.4

Iceland

16.1

17.1

15.0

Lithuania

16.3

17.5

14.7

Greece

18.5

19.5

17.4

Serbia

23.5

24.7

22.3

Bulgaria

24.9

26.8

22.8

FYROMa

30.1

32.8

27.4

Romania

32.0

33.3

30.6

Hungary

33.5

34.9

31.9

Source: Based on Eurostat (2015)

aRepublic of Macedonia

Measures of material deprivation include variables related to the lack of Information and Communication Technology (ICT) access, due to the growing importance of new technologies. Eurostat (2015) includes, for example, the following item: “persons who cannot afford Internet connection for personal use at home.” The top three are Norway (0.6%), Sweden (1%), and Finland (1.1%), whereas Bulgaria (15.7%) and Romania (25.1%) are at the bottom. Infrastructures and access to new technologies should be improved in these countries.

Most “living conditions” approaches have been developed in developed countries (e.g., in European countries), where poverty level is not as high as in other areas of the world. Holistic approaches take into account variables other than economic ones, which are minimum economic conditions but not enough to have a decent Standard of Living.

Standard of Living Versus Quality of Life

Quality of Life is a controversial multidimensional concept, and there is no unanimity in defining or quantifying it (Bucur 2017). According to Eurostat, Quality of Life is broader than economic issues and living standards. It includes key factors that influence what people value in life beyond its material aspects (Eurostat 2018a). These factors are related to, for example, safety or time spend.

An evaluation of Standard of Living may include factors such as income, quality and availability of employment, poverty rate, life expectancy, climate, safety, or cost of goods and services. Standard of Living is often used to compare geographic areas or different moments in time.

Quality of Life is more subjective and intangible than Standard of Living. Many factors can be used to measure this variable. For example, it may contain some of the rights of the United Nations’ Universal Declaration of Human Rights (1948): freedom of thought, freedom of religion, freedom from slavery and torture, freedom from discrimination, equal pay for equal work, right to vote, and right to have a family. In this line, the Report elaborated by the Commission on the Measurement of Economic Performance and Social Progress recommended developing Quality of Life indicators covering multidimensional measures of conditions that contribute to people’s life satisfaction (Stiglitz et al. 2008).

In summary, the main difference between Living Standards and Quality of Life is the objectivity of these measures: Standard of Living is more objective. It is possible to measure and to define with numbers this concept. Factors related to Quality of Life are a more difficult to measure because they are particularly qualitative (Fig. 2).
Fig. 2

Some measures of well-being. (Source: Author’s own)

Eurostat (2018a) offers a set of Quality of Life indicators for the European Union on the basis of the nine dimensions: eight of these dimensions are related to people’s capabilities to pursue their self-defined well-being in accordance with their own values and priorities. They are as follows:
  1. 1.

    Material living conditions (income, consumption, material conditions)

     
  2. 2.

    Productive or other main activity (e.g., quantity and quality of employment)

     
  3. 3.

    Health (health status, determinants of health, access to healthcare)

     
  4. 4.

    Education (educational attainment, self-reported skills, lifelong learning, opportunities of education)

     
  5. 5.

    Leisure and social interactions (leisure and social interactions, social interactions)

     
  6. 6.

    Economic security and physical safety (economic security, physical security)

     
  7. 7.

    Governance and basic rights (trust in institutions and public services, discrimination and equal opportunities, active citizenship)

     
  8. 8.

    Natural and living environment (pollution, landscape and built environment)

     
The last dimension refers to the personal perception of Quality of Life (Eurostat 2018a). Table 5 shows some results of those perceptions in 2013. Answers are rated from 0 to 10. Data are sorted by percentage of the total population, from lower (4.8) to higher percentage (8.0). Nordic countries have the highest averages; meanwhile Bulgaria, Serbia, and Turkey have comparatively the worst rates.
Table 5

Average rating of satisfaction by sex (2013)

Country

Total

Females

Males

Bulgaria

4.8

4.8

4.8

Serbia

4.9

5.0

4.9

Turkey

5.7

5.7

5.6

Hungary

6.1

6.1

6.1

Greece

6.2

6.2

6.1

Cyprus

6.2

6.3

6.1

Portugal

6.2

6.1

6.2

Croatia

6.3

6.3

6.4

Estonia

6.5

6.5

6.4

Latvia

6.5

6.5

6.5

Italy

6.7

6.7

6.7

Lithuania

6.7

6.7

6.8

Czech Republic

6.9

7.0

6.9

Spain

6.9

6.9

6.9

European Union (28)

7.0

7.0

7.1

Slovenia

7.0

7.0

6.9

Slovakia

7.0

6.9

7

France

7.1

7.0

7.1

Malta

7.1

7.1

7.2

Romania

7.1

7.1

7.2

Germany

7.3

7.2

7.3

Poland

7.3

7.3

7.3

United Kingdom

7.3

7.3

7.2

Ireland

7.4

7.4

7.4

Luxembourg

7.5

7.5

7.4

Belgium

7.6

7.5

7.6

Netherlands

7.8

7.8

7.8

Austria

7.8

7.9

7.8

Sweden

7.9

7.9

7.9

Iceland

7.9

7.9

8

Norway

7.9

7.9

7.9

Denmark

8.0

8.1

7.9

Finland

8.0

8.1

8

Switzerland

8.0

8.1

8

Source: Based on Eurostat (2018d)

Table 6 shows population satisfaction in the countries that have the lowest levels according to their different life issues, such as job, finances, and accommodation. This shows the key factors that limit satisfaction in countries. The financial situation of the population is the factor that has the lowest percentage of high satisfaction in all these countries. However, there are more dimensions to take into account: almost 50% of the population in Bulgaria have a low satisfaction with accommodation or with job issues, as well as commuting time. There is only one dimension in which these countries, except Bulgaria, have percentages over 25% of high satisfaction: satisfaction with personal relationships. That is related to the importance of family ties and social relations, for example, in Serbia.
Table 6

Percentage of the population rating their satisfaction as high, medium, or low by domain (2013)

Variable

Satisfaction with financial situation

Satisfaction with accommodation

Country

High

Low

Medium

High

Low

Medium

Bulgaria

2.8

78.5

18.8

18.2

46.2

35.6

Serbia

3.6

73.6

22.8

18.0

40.6

41.4

Turkey

6.4

61.9

31.7

13.2

48.2

38.5

Hungary

6.1

54.2

39.7

20.0

27.8

52.2

Greece

3.8

65.8

30.4

19.0

29.7

51.3

Variable

Job satisfaction

Satisfaction with commuting time

Country

High

Low

Medium

High

Low

Medium

Bulgaria

16.1

47.7

36.1

16.8

47.4

35.7

Serbia

18.8

41.6

39.6

29.9

33.1

37.0

Turkey

18.3

42.2

39.5

23.8

38.2

38.0

Hungary

23.0

21.3

55.7

28.5

22.2

49.3

Greece

19.0

29.7

51.3

21.5

33.6

44.8

Variable

Satisfaction with time use

Satisfaction with recreational and green areas

Country

High

Low

Medium

High

Low

Medium

Bulgaria

14.6

51.5

33.9

9.8

58.0

32.2

Serbia

22.0

40.9

37.1

15.8

52.5

31.7

Turkey

12.2

51.5

36.4

17.7

46.1

36.2

Hungary

15.4

35.2

49.4

15.1

38.6

46.3

Greece

11.6

36.2

52.2

16.9

40.2

42.9

Variable

Satisfaction with living environment

Satisfaction with personal relationships

Country

High

Low

Medium

High

Low

Medium

Bulgaria

8.4

59.0

32.6

14.6

51.1

34.3

Serbia

12.4

58.4

29.2

54.5

12.8

32.7

Turkey

18.3

39.5

42.3

33.3

20.6

46.1

Hungary

15.8

32.3

51.9

33.8

15.5

50.7

Greece

18.3

36.5

45.2

25.2

21.9

53.0

Variable

Meaning of life

   

Country

High

Low

Medium

   

Bulgaria

18.1

43.0

38.9

   

Serbia

30.1

27.4

42.4

   

Turkey

15.1

37.1

47.9

   

Hungary

22.1

22.5

55.4

   

Greece

16.8

26.3

56.9

   

Source: Based on Eurostat (2018d)

Conclusions

Traditional macroeconomic indicators, such as GDP or GNI, fail to measure the well-being of societies, since they focus only on production. A country could have a positive trend of production, and, at the same time, the situation of its population could be getting worse. A number of alternative indicators have been proposed to address this challenge, such as Standard of Living or Quality of Life, which are helpful in comparing two regions or the circumstances of an specific population at different moments in time.

There is still no scientific consensus on the exact extent of Standard of Living. The main approaches define Standard of Living as the utility of life, as economic provision, and as the capability to live well, of a certain socioeconomic class in a certain geographic area. International institutions have opted for the “economic provision” approach, relating Standard of Living to the level of “material deprivation” and “living conditions” instead of a more holistic approach, because these institutions differentiate between “Standard of Living,” a measure that is more objective, and Quality of Life that is more subjective. Quality of Life can be defined as the grade of achievement of self-defined well-being in accordance with the own values and priorities. Standard of Living and Quality of Life are complementary concepts. These concepts can help to understand and to compare the condition of the population living in two different countries. At the moment, many organizations have developed indexes with the objective of measuring well-being in different ways. It is necessary to continue with such studies, in order to improve the existing indexes and to develop new ones, since the design and implementation of public policies based on indicators focused exclusively on production and on purely economic issues which could have serious consequences for societies. Currently, economic parameters play a key role in all the indicators developed, even if other variable may be included. It is necessary to take into account possible impacts of the implemented measures, for example, the distribution of income and inequalities; however, this will only be achieved when governments make the effort to collect statistical data and publish them. The lack of available official data is a problem that occurs especially in least-developed countries, which needs to be solved with urgency in order to develop the right bases to implement better policies.

Cross-References

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of GävleGävleSweden
  2. 2.University of A CorunaA CorunaSpain

Section editors and affiliations

  • Rosa Maria Fernandez
    • 1
  1. 1.Department of Social and Political ScienceUniversity of ChesterChesterUK