Statistics Explained

Enlargement countries - statistics on living conditions


Data from March 2022.

Planned article update: May 2023.

Highlights

Income distribution was less unequal in 2020 in Serbia, Montenegro and North Macedonia (2019 data) than it had been in 2010, as measured by the income quintile share ratio.

On the basis of the most recent data available, the share of the population at risk of poverty after social transfers in the candidate countries and potential candidates ranged from 21.6 % in North Macedonia to 27.9 % in Kosovo. In the EU in 2020 it was 17.1 %.

In 2020, the proportion of people aged 18-59 years that lived in households with very low work intensity in the candidate countries and potential candidates ranged from 11.0 % in Turkey to 38.6 % in Kosovo (2018 data). This ratio was 8.7 % in the EU.

[[File:CPC22_Proportion of the population at risk of poverty after transfers 2020.xlsx]]

Proportion of the population at risk of poverty after transfers, 2020

This article is part of an online publication and provides information on a range of statistics related to living conditions in the European Union (EU) enlargement countries, in other words the candidate countries and potential candidates. Montenegro, North Macedonia, Albania, Serbia and Turkey currently have candidate country status, while Bosnia and Herzegovina as well as Kosovo* are potential candidates.

The article includes information relating to income distribution, the risk of poverty (before and after social transfers), the contribution of social transfers to median equivalised disposable income, the proportion of persons who are living in households with very low work intensity, as well as health and social protection expenditure.

Full article

Income distribution

The income quintile share ratio, also known as the S80/S20 ratio, is a measure of the inequality of income distribution. It is calculated as the ratio of total income received by the 20 % of the population with the highest income (the top quintile) to that received by the 20 % of the population with the lowest income (the bottom quintile). Incomes are equivalised to take account of the varying composition of households.

Figure 1 shows that the income of the top population quintile in all candidate countries and potential candidates lay between close to 6 and 24 times the size of the income of the bottom population quintile in the year for which the latest data is available. In North Macedonia (2019 data) the ratio of income inequality was 5.6; in Albania 5.9; in Montenegro 6.0; in Serbia 6.1; and in Turkey 9.2. Kosovo recorded the highest ratio, at 24.1 (2019 data). Between 2015 and 2020, the income quintile share ratio fell in North Macedonia (between 2015 and 2019) by 1.1 percentage points (pp); in Montenegro by 1.5 pp; and in Serbia by 4.6 pp. The ratio increased somewhat by 0.6 pp in Turkey. Albania and Kosovo did not report data for 2015. In the EU, the income of the top population quintile was 5.2 times the size of the income of the bottom population quintile in 2020, having remained almost unchanged from 2015.

Figure 1: Inequality of income distribution (income quintile share ratio), 2015 and 2020
(ratio)
Source: Eurostat (ilc_di11) and Eurostat data collection

The Gini coefficient is an alternative measure of income inequality. It shows the extent to which all incomes within the population differ from the average income: the closer the coefficient is to 100 the less equal are the incomes, while the closer it is to 0 the more equal are the incomes. As was already observed for the income quintile share ratio, Gini coefficients for the candidate countries and potential candidates were generally higher than in the EU, except for Albania in 2008 and North Macedonia in 2020, suggesting that income disparities usually were greater in the candidate countries and potential candidates. In 2020 in the candidate countries and potential candidates, the coefficient ranged from 30.7 in North Macedonia to 45.7 in Kosovo (2019 data). The Gini coefficient in Montenegro was 32.9; Albania, 33.2; Serbia, 33.3; and in Turkey, 43.4. There was no data available for Bosnia and Herzegovina. In Figure 2, only two candidate countries have data for both a recent year and another year approximately 10 years earlier. Albania reported an increase in the Gini coefficient over 2008-2020 from 28.2 to 33.2, while Turkey was essentially unchanged, reporting a marginal decrease from 43.5 in 2010 to 43.4 in 2020. In the EU, the Gini coefficient in 2020 was 30.8. The value recorded in 2010 had been 30.2 but the methodology has meanwhile changed and data are estimated.

Figure 2: Gini coefficient, 2010 and 2020
(ratio)
Source: Eurostat (ilc_di12) and Eurostat data collection

Monetary poverty

The poverty threshold shown in Table 1 is set at 60 % of the national median equivalised disposable income after social transfers. The total net income of each household is calculated by adding together the income received by all the members of the household from all sources. For each person, the equivalised total net income is calculated as the household’s total net income divided by the equivalised household size. This is generally based on the modified OECD scale: a weight of 1.0 for the first adult, 0.5 for other persons aged 14 years or over who are living in the household and 0.3 for each child aged less than 14 years.

The poverty threshold is shown as a monthly income, ranging in 2020 among the candidate countries and potential candidates for which data are available from the equivalent of EUR 103 in Kosovo (2018 data) to EUR 196 in Montenegro. No data was available for Bosnia and Herzegovina.

Table 1: Poverty main indicators, 2020
Source: Eurostat (ilc_li02), (ilc_li09) and (ilc_li01) and Eurostat data collection

The at-risk-of-poverty rate is the proportion of the population with an equivalised disposable income below the poverty threshold. This indicator can be calculated either before social transfers or after social transfers. The difference between the two reflects the proportion of the population moved above the threshold as a result of receiving social transfers. Social transfers cover the social help given through benefits such as: old-age and survivors’ (widows’ and widowers’) pensions; unemployment, family-related, sickness and invalidity, education-related and other benefits; housing allowances; and social assistance.

As the poverty threshold is set independently for each candidate country or potential candidate, the indicator reflects low income in comparison with other residents in the same economy. This does not necessarily imply an absolutely low standard of living. In 2020 in the candidate countries and potential candidates for which data is available, the at-risk-of-poverty rates before transfers disaggregated by gender were in every case higher for women than for men. The highest difference was recorded in Turkey: 54.9 % for men and 58.3 % for women. Serbia was close behind: 48.2 % for men and 51.5 % for women. The difference was somewhat smaller in Montenegro: 46.5 % for men and 49.1 % for women; and in Kosovo (2018 data): 47.5 % for men and 49.6 % for women. The gender proportions were closer to being equal in Albania: 43.3 % for men and 44.8 % for women; and in North Macedonia (2019 data): 44.5 % for men and 45.8 % for women). The disaggregation for the EU was 45.7 % for men and 49.9 % for women, a greater difference than in any of the candidate countries or potential candidates. No data is available for Bosnia and Herzegovina. The most recent data from the candidate countries and potential candidates on the proportions of the population at risk of poverty after social transfers ranged from 21.6 % in North Macedonia (2019 data) to 27.9 % in Kosovo (2018 data). All were higher than in the EU, where the proportion in 2020 was estimated at 17.1 %. Montenegro was the only candidate country or potential candidate with a higher proportion of men than of women, the difference being -0.8 pp. Elsewhere, the proportion of women was higher than of men by between +0.8 pp in Serbia and +1.4 pp in Kosovo (2018 data). No data is available for Bosnia and Herzegovina. In the EU in 2020, the proportion of men at risk of poverty after social transfers was 16.3 %, while for women the figure was 17.8 %.

The analysis of the contribution of social transfers to median equivalised disposable income can illustrate the impact and redistributive effects of welfare policies. These transfers cover assistance that is given by central, state or local institutional units and include, among others, pensions, unemployment benefits, sickness and invalidity benefits, housing allowances, social assistance and tax rebates.

Figure 3 shows the overall impact of social transfers. The data distinguish transfers for pensions from other transfers such as social security benefits and social assistance, which have the aim of alleviating or reducing the risk of poverty. The statistics are reported in terms of purchasing power standards (PPS) per inhabitant. This measure normalises the level of transfers against median equivalised disposable income, permitting comparisons between countries with different standards of living.

In the candidate countries and potential candidates for which data is available, the value of social transfers varied considerably. The largest total transfers were observed in Serbia, Montenegro and Turkey, where social transfers including pensions increased the median equivalised disposable income by PPS 2 043, 1 949 and 1 764 per inhabitant, respectively. At the other end of the scale, Kosovo (2018 data) recorded the lowest transfers, at PPS 778 per inhabitant, followed by Albania with PPS 846 and North Macedonia (2019 data) with PPS 1 524 per inhabitant. There is no data for Bosnia and Herzegovina. The highest social transfers other than pensions were recorded in Montenegro at PPS 596 per inhabitant, followed by Serbia at PPS 405 per inhabitant. Kosovo (2018 data) recorded the lowest level of transfers with PPS 113 per inhabitant, followed by North Macedonia (2019 data), Albania and Turkey with PPS 153, 154 and 164 per inhabitant, respectively.

Figure 3: Contribution of social transfers to median equivalised disposable income, 2020
(PPS per inhabitant)
Source: Eurostat (ilc_di03), (ilc_di13) and (ilc_di14)

Households with very low work intensity

Persons living in households with low work intensity are those aged 0-59 living in households where the adults aged 18-59, excluding students, have worked 20 % or less of their total work potential during the past year. The work intensity of a household is the ratio of the total number of months that all working-age household members have worked during the income reference year to the total number of months the same household members could theoretically have worked in the same period. The indicator is based on the EU statistics on income and living conditions (EU-SILC). The two indicators presented in Figure 4 concern different subpopulations: people aged 0-17 years, who are considered as dependent children; and those of working age, defined as 18-59 years.

Figure 4: Proportion of persons who are living in households with very low work intensity, 2010 and 2020
(%)
Source: Eurostat (ilc_lvhl11) and (demo_pjan) and Eurostat data collection

The proportion of persons who were living in households with very low work intensity in the candidate countries and potential candidates in 2020 was lowest in Turkey, where 8.1 % of persons aged 0-17 and 11.0 % of persons aged 18-59 years were in this category. In Albania, the shares were 11.6 % for both age categories. In North Macedonia (2019 data), there were 13.7 % of younger people living in households with very low work intensity and 13.5 % of working age people. In Serbia, 13.6 % of people aged 0-17 years were living in households with very low work intensity, as were 16.9 % of people of working age. In Montenegro, 14.8 % of people aged 0-17 and 19.2 % of those 18-59 years were living in households with very low work intensity. In Kosovo (2018 data), the proportions were much higher: there were 35.8 % of younger people living in households with very low work intensity and 38.6 % of working age people. There is no data available for Bosnia and Herzegovina.

For both age groups, the proportions of people living in households with very low work intensity in North Macedonia (2010-2019) and Turkey were lower in 2020 than in 2010. In North Macedonia, the proportion declined by 11.4 pp for the younger age group and by 10.7 pp for the working age population. In Turkey, the decline was by 1.6 pp for the population aged 0-17 and by 2.4 pp for people of working age. In the EU, there was an estimated decrease of 0.8 pp in the proportion of young people living in households with very low work intensity over 2010-2020 and a decrease of 1.6 pp for persons aged 18-59 years.

Health and social protection expenditure

Total expenditure on health concerns total current expenditure on health and investment, regardless of the source of funds. It covers: curative and rehabilitative care (in-patient care, day cases, out-patient and home care); services of long-term nursing care (in-patient, day cases and home care); ancillary services to health care; medical goods dispensed to out-patients; services of prevention and public health; health administration and health insurance. The level of expenditure on health relative to gross domestic product (GDP) is shown in Figure 5 and Table 2. The values recorded vary greatly, from 4.0 % of GDP in Kosovo, through 4.7 % in Turkey to 8.6 % in Serbia and 9.1 % in Bosnia and Herzegovina (2018 data).

Figure 5: Expenditure on health, social protection benefits and pensions, 2019
(% of GDP)
Source: Eurostat (hlth_sha11_hp), (spr_exp_sum) and (spr_exp_pens) and Eurostat data collection

Social protection expenditure comprises social protection benefits, administration costs and other expenditure. The data shown in Figure 5 and Table 2 only concern the benefits. Social benefits consist of transfers, in cash or in kind, by social protection schemes to households and individuals to relieve them of the burden of a defined set of risks or needs, provided that there is neither a simultaneous reciprocal nor an individual arrangement involved. The list of risks or needs is fixed as: sickness/health care; disability; old-age; survivors; family/children; unemployment; housing; and other social exclusion. Note that not all health expenditure falls within social protection expenditure.

In 2019, expenditure on social protection benefits in the five candidate countries and potential candidates for which data are available was equivalent to less than one fifth of GDP. In Serbia the ratio was 19.0 %; in Bosnia and Herzegovina (2018 data) 18.5 %; in Montenegro (2018 data) 16.1 %; and in North Macedonia (2018 data) 14.3 %. In Turkey, the ratio was 12.3 % in 2019. The expenditure on social protection benefits in the EU in 2019 was estimated to be equivalent to more than one quarter of GDP at 26.9 %.

Table 2: Expenditure on health, social protection benefits and pensions, 2009 and 2019
(% of GDP)
Source: Eurostat (hlth_sha11_hp), (spr_exp_sum) and (spr_exp_pens) and Eurostat data collection

The ratio of expenditure on social protection benefits to GDP, shown in Table 2, for the two candidate countries for which data are available for both 2009 and 2019 fell by 3.4 percentage points in Serbia over the period and by 0.9 percentage points in Turkey. In the EU, this ratio was 0.6 percentage points lower in 2019 than it was in 2009.

A large part of expenditure on social protection benefits consists of payments for pensions. The relative importance of this depends, among other factors, on the age structure of the population. Between 2009 and 2019, the ratio of social protection expenditure on pensions relative to GDP in Serbia decreased from 12.7 % in 2009 to 10.1 % in 2019, down 2.6 percentage points. Turkey reported a marginal increase of 0.1 percentage points between 2009 and 2019, from 7.4 % to 7.5 %. The ratio social protection expenditure on pensions to GDP fell in the EU, from 12.8 % to 12.7 %. Data for other candidate countries and potential candidates is not available for both years. Expenditure on pensions accounted for more than half of the total expenditure on social protection benefits in all the five candidate and potential candidate countries for which recent (2018 or 2019) data is available, ranging from 50.3  % (2018 data) in Bosnia and Herzegovina to 61.0 % (2019 data) in Turkey. This share was less than half in the EU in 2019 (47.2 %).

Data sources

The data used in this article are derived from EU statistics on income and living conditions (EU-SILC), data which are compiled annually and are the main source of statistics that measure income and living conditions in Europe.

Data for some of the enlargement countries (Albania and Turkey) are collected for a wide range of indicators each year through a questionnaire that is sent by Eurostat to candidate countries or potential candidates. A network of contacts has been established for updating these questionnaires, generally within the national statistical offices, but potentially including representatives of other data-producing organisations (for example, central banks or government ministries).

EU-SILC is an instrument that aims to collect timely and comparable data on income, poverty, social inclusion and living conditions, in both monetary and non-monetary terms. The data are generally collected for private households and household members. EU-SILC provides both cross-sectional data and longitudinal data (typically over a four-year period).

The legal basis for this data collection exercise is Regulation (EU) 2019/1700 of the European Parliament and of the Council of 10 October 2019 establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples (Integrated European Social Statistics – IESS).

Information concerning the current statistical legislation on income and living conditions can be found here.

Currently, EU-SILC data are also available for the following candidate countries and potential candidate: Montenegro, North Macedonia, Serbia, Turkey and Kosovo.

The European system of integrated social protection statistics (ESSPROS) is a common framework developed within the European Statistical System (ESS) that has been designed to provide a coherent comparison across European countries (27 EU Member States plus the United Kingdom, Iceland, Norway, Switzerland, Montenegro, North Macedonia, Serbia, Turkey as well as Bosnia and Herzegovina) of social benefits to households and their financing, in terms of precisely defined risks or needs that refer to the ESSPROS functions: disability, sickness/health care, old-age, survivors, family/children, unemployment, housing and social exclusion. The legal basis for the data collection exercise is provided by Regulation (EC) No 458/2007 of the European Parliament and of the Council on the European system of integrated social protection statistics (ESSPROS). ESSPROS is composed of a core system that contains annual data from 1990 onwards on (gross) expenditures and receipts. In addition to the core system, one module on pension beneficiaries and one on net social benefits data are available.

More detailed information concerning the current statistical legislation on social protection can be found here.

Tables in this article use the following notation:

Value in italics     data value is forecasted, provisional or estimated and is therefore likely to change;
: not available.

Context

Social protection systems are generally well-developed in the EU: they are designed to protect people (to some degree) against the risks and needs associated with unemployment, parental responsibilities, sickness/health care and invalidity/disability, the loss of a spouse or parent, old-age, housing and other forms of social exclusion.

The main policy framework in this field is the EU’s strategic agenda 2019-2024. The open method of coordination (Social OMC) for social protection and social inclusion aims to promote social cohesion and equality through adequate, accessible and financially sustainable social protection systems and social inclusion policies.

Through the Social OMC – and in collaboration with the Social Protection Committee – the EU provides a framework for national strategy development for social protection and social investment, as well as for coordinating policies between EU countries on issues relating to:

While basic principles and institutional frameworks for producing statistics are already in place, the enlargement countries are expected to increase progressively the volume and quality of their data and to transmit these data to Eurostat in the context of the EU enlargement process. EU standards in the field of statistics require the existence of a statistical infrastructure based on principles such as professional independence, impartiality, relevance, confidentiality of individual data and easy access to official statistics; they cover methodology, classifications and standards for production.

Eurostat has the responsibility to ensure that statistical production of the enlargement countries complies with the EU acquis in the field of statistics. To do so, Eurostat supports the national statistical offices and other producers of official statistics through a range of initiatives, such as pilot surveys, training courses, traineeships, study visits, workshops and seminars, and participation in meetings within the European Statistical System. The ultimate goal is the provision of harmonised, high-quality data that conforms to European and international standards.

Additional information on statistical cooperation with the enlargement countries is provided here.

Notes

* This designation is without prejudice to positions on status, and is in line with UNSCR 1244/1999 and the ICJ Opinion on the Kosovo Declaration of Independence.

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