Estonian Social Survey
Statistical activity code: 40003
Dwelling and living conditions, health, employment and job search, income, economic well-being, social exclusion, poverty risk, childcare, etc. The results are analysed by household composition. The output is based on the education, social status, sex, age and other important characteristics of household members.
Classification of Estonian administrative units and settlements (EHAK)
Estonian Classification of Economic Activities (EMTAK 2008) based on NACE Rev. 2
International Standard Classification of Occupations (ISCO 08)
National Standard Classification of Education (ISCED 2011)
Classification of fields of education and training 2013
International Standard Codes for the Representation of the Names of Countries (ISO 3166)
Codes for the Representation of Names of Languages (ISO 639-2)
Classification of Ethnicities
Absolute poverty gap – the distance of mean income of people in absolute poverty from the absolute poverty threshold in percentages.
Absolute poverty rate – share of persons with an equivalised annual disposable income lower than the absolute poverty threshold.
Absolute poverty rate before social transfers – the absolute poverty rate when social benefits paid by the state and local governments are not counted in the household's income. It can be calculated in two ways: either by counting pensions as social transfers and excluding them from the household's income or by including them in the household's income like wages and salaries.
Absolute poverty threshold – since 2004 the estimated subsistence minimum. In 1997–2003, the absolute poverty threshold was established by the working group of the University of Tartu based on household consumption data and considering people’s minimum needs.
Adult – a household member aged 18 or older (as at 1 January of the reference year) who is not a dependent child.
Adult and child(ren) – household consisting of one adult and at least one dependent child.
At-risk-of-poverty rate – share of persons with an equivalised annual disposable income lower than the at-risk-of-poverty threshold.
At-risk-of-poverty rate anchored in time – share of persons with an equivalised annual disposable income lower than the at-risk-of-poverty threshold from three years ago adjusted for inflation.
At-risk-of-poverty rate before social transfers – the at-risk-of-poverty rate when social benefits paid by the state and local governments are not counted in the household's income. It can be calculated in two ways: either by counting pensions as social transfers and excluding them from the household's income or by including them in the household's income like wages and salaries.
At-risk-of-poverty threshold – 60% of the median equivalised annual disposable income of household members.
Below upper secondary education – less than primary education, primary education, basic education, vocational education for young people without basic education.
Child deprivation rate – the proportion of children up to the age of 16 whose household at least half of the persons (at least 16 years old) cannot afford five of the 13 components (of which at least three of these five components must be between components 1 to 7): 1) payment of rent and utilities, 2) keeping the home warm enough, 3) unforeseen expenses, 4) eating food containing meat, fish or equivalent proteins throughout the day, 5) a week's holiday away from home, 6) a car, 7) worn out, or replacement of damaged furniture, 8) replacement of worn-out clothes with new ones, 9) at least two pairs of outdoor shoes in good condition and suitable for our climate, 10) spending even a small amount on each week, 11) regularly participating in some paid leisure activities, 12) at least once a month meeting with friends or relatives to eat and drink together or 13) using the Internet at home for personal purposes, if necessary. For components 8–13, persons who are at least 16 years old will be asked. Therefore, when calculating the deprivation of these components for children, it has been taken into account that at least half of the household members (at least 16 years old) would have deprivation in these components.
City and town settlement regions – cover settlements where most inhabitants live in regions where population density is greater than 200 inhabitants per km² and the population figure in a cluster of this density is greater than 5,000.
Couple aged 64 and less without children – household consisting of two members, both aged 64 or less.
Couple without children, at least one partner is aged over 64 – household consisting of two adults, at least one of them aged 65 or over.
Couple with one child – household consisting of two adults and one dependent child.
Couple with three or more children – household consisting of two adults and at least three dependent children.
Couple with two children – household consisting of two adults and two dependent children.
Dependent child – a household member aged 0–17 (as at 1 January of the reference year) or a household member aged 18–24 whose main social status is inactive and who lives with at least one parent.
Deprivation rate – the share of persons who cannot afford at least 5 of the 13 items: 1) to pay rent or utility bills, 2) to keep home adequately warm, 3) to face unexpected expenses, 4) to eat meat, fish or a protein equivalent every second day, 5) a one-week holiday away from home, 6) a car, 7) to replace furniture when worn out or damaged, 8) to replace worn-out clothes with new ones, 9) to have at least two pairs of outdoor shoes in good condition that are necessary in our climate, 10) to spend a small amount of money each week on oneself, 11) to participate regularly in a leisure activity that costs money, 12) to get together with friends or family for a drink or meal at least once a month or 13) to have internet connection at home for personal use when needed. In the Estonian Social Survey, items 8–13 are asked from persons aged 16 and over. Therefore, when calculating material deprivation for these items for children, at least half of the household members (16 and over) should be deprived with regard to these items.
Disposable (net) income – a sum of income from wage labour and self-employment, property income, social transfers, regular inter-household cash transfers received and receipts for tax adjustment of which inter-household cash transfers paid, taxes on wealth and repayments for tax adjustment have been subtracted.
Equalised income — total household income, which is divided by a sum of equivalence scales of all household members.
Equivalised income – total household income, which is divided by a sum of equivalence scales of all household members.
Equivalence scale – a weight designated to a household member depending on his/her age to reflect the joint consumption of a household.
Estimated subsistence minimum – the minimum amount of living resources, which covers the daily needs of a person. The subsistence minimum consists of minimum estimated food basket (excl. expenditure on alcoholic beverages and tobacco products) and individual non-food expenditures (incl. expenditure on dwelling).
Gini coefficient – the relationship of cumulative shares of the population arranged according to the level of equivalised disposable income to the cumulative share of the equivalised total disposable income received by them. The value of Gini coefficient varies from 0 to 1. The closer the value to 0 is, the more equally income is distributed in a country; the closer the value gets to 1, the more unequally income is distributed.
High but not maximal work intensity in a household – designates a situation where the work intensity of a household is greater than 0.5 but lower than 1.
Highest quintile – fifth of the population receiving the highest equivalised disposable income.
Household – a group of persons living in the common main dwelling (at the same address), who share joint financial and/or food resources and whose members consider themselves to belong to the same household. Household can also consist of one member only.
Household with children – household where there is at least one dependent child.
Household without children – household where there are no dependent children.
Income decile – one tenth of the population ordered by monthly disposable income. The first or the lowest decile contains one tenth of the population receiving the lowest income, the second decile contains the next tenth and so on.
Income from self-employment – income from registered or unregistered self-employment and production for own use.
Income from wage labour – earnings received from employment and holiday compensations without income tax.
Income quintile – one fifth of the population ordered by equalised yearly disposable income. The first or the lowest quintile contains one fifth of the population receiving the lowest income, the second quintile contains the next fifth and so on.
Labour status – labour status which characterised a person for more than 6 months in a year.
Long-term unemployment rate – the share of people who have been unemployed for a year or longer of total labour force.
Lowest quintile – fifth of the population receiving the lowest equivalised disposable income.
Maximal work intensity in a household – designates a situation where the work intensity of a household is 1.
Material deprivation rate – the share of persons, who cannot afford at least 4 of the 9 items: 1) to pay rent or utility bills, 2) keep home adequately warm, 3) face unexpected expenses, 4) eat meat, fish or a protein equivalent every second day, 5) a week holiday away from home, 6) a car, 7) a washing machine, 8) a colour TV or 9) a telephone.
Minimal work intensity in a household – designates a situation where the work intensity of a household is 0.
Minimum estimated food basket – food products which cover a person’s daily need of nutrients, vitamins and minerals without causing health problems. The energy value of the minimum estimated food basket is 2,400 kcal per day.
Non-monetary income – non-monetary incomes from wage labour (goods and services received as an income in kind or cut price).
Other income – income tax returned.
Partial work intensity in a household – designates a situation where the work intensity of a household is greater than 0 but lower than 1.
Property income – income from rental of a property or land; interest, dividends, profit from capital investments.
Quintile share ratio – the sum of equivalised annual disposable income of the highest quintile divided by the sum of equivalised annual disposable income of the lowest quintile.
Relative median at-risk-of-poverty gap – the distance of mean income of people at-risk-of-poverty from the at-risk-of-poverty threshold in percentages.
Rural settlements – small towns and villages.
Rural settlement region – covers settlements where population density is lower than 200 inhabitants per km² or regions with higher population density where the population figure is under 5,000.
Severe material deprivation rate – the share of persons, who cannot afford at least 4 of the 9 items: 1) to pay rent or utility bills, 2) keep home adequately warm, 3) face unexpected expenses, 4) eat meat, fish or a protein equivalent every second day, 5) a week holiday away from home, 6) a car, 7) a washing machine, 8) a colour TV or 9) a telephone.
Single person aged over 65 – household consisting of one person aged 65 or more.
Single person aged under 65 – household consisting of one person aged 64 or less.
Tertiary education – professional secondary education based on secondary education, higher education, Master`s and Doctor`s degree.
Transfers – payments made by collectively organised schemes, government or local authorities with the intension to relieve the households or persons from the financial burden of a number of risks.
Upper secondary education – vocational training based on basic education, general secondary education, vocational secondary education based on basic education, professional secondary education based on basic education, vocational secondary education based on secondary education.
Urban settlements – cities, cities without municipal status and towns.
Very long-term unemployment rate – the share of people who have been unemployed for two years or longer of total labour force.
Work intensity in a household – the total number of months spent by working age household members (aged 59 and under) in employment or self-employment during income reference period relative to the maximum number of months the household members could have spent in employment or self-employment. The indicator ranges from zero (no working age member worked) to one (all working age members worked throughout the income reference period). Dependent children are not counted as working age household members.
Young people with education below upper secondary education – a person aged 18–24 who has basic education or less than basic education and who is not acquiring formal education or participating in training.
Households whose usual place of residence is in Estonia, and the members of these households, excluding persons living in institutions (children’s homes, care homes, monasteries, convents, etc.)
The list of permanent residents of Estonia based on the 2011 Population and Housing Census and the Population Register
Estonia as a whole
DIRECTLY APPLICABLE LEGAL ACTS
Commission Delegated Regulation (EU) 2020/256 of 16 December 2019 supplementing Regulation (EU) 2019/1700 of the European Parliament and of the Council by establishing a multiannual rolling planning (Text with EEA relevance)
Commission Delegated Regulation (EU) 2020/258 of 16 December 2019 supplementing Regulation (EU) 2019/1700 of the European Parliament and of the Council by specifying the number and the titles of the variables for the income and living conditions domain (Text with EEA relevance)
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, amending Regulations (EC) No 808/2004, (EC) No 452/2008 and (EC) No 1338/2008 of the European Parliament and of the Council, and repealing Regulation (EC) No 1177/2003 of the European Parliament and of the Council and Council Regulation (EC) No 577/98 (Text with EEA relevance)
Commission Implementing Regulation (EU) 2019/2242 of 16 December 2019 specifying the technical items of data sets, establishing the technical formats and specifying the detailed arrangements and content of the quality reports on the organisation of a sample survey in the income and living conditions domain pursuant to Regulation (EU) 2019/1700 of the European Parliament and of the Council (Text with EEA relevance)
OTHER LEGAL ACTS
Statistical Office of the European Union (Eurostat)
The dissemination of data collected for the purpose of producing official statistics is guided by the requirements provided for in § 32, § 34, § 35, § 38 of the Official Statistics Act.
The treatment of confidential data is regulated by the Procedure for Protection of Data Collected and Processed by Statistics Estonia (in Estonian). See more details on the website of Statistics Estonia in the section Õigusaktid.
Notifications about the dissemination of statistics are published in the release calendar, which is available on the website. Every year on 1 October, the release times of the statistical database, news releases, main indicators by IMF SDDS and publications for the following year are announced in the release calendar (in the case of publications – the release month).
All users have been granted equal access to official statistics: dissemination dates of official statistics are announced in advance and no user category (incl. Eurostat, state authorities and mass media) is provided access to official statistics before other users. Official statistics are first published in the statistical database. If there is also a news release, it is published simultaneously with data in the statistical database. Official statistics are available on the website at 8:00 a.m. on the date announced in the release calendar.
The news release “Relative poverty” once a year.
The news release “Life expectancy and healthy life years” once a year.
The news release can be viewed on the website of Statistics Estonia in the section Uudiskiri (in Estonian).
Data are published under the subject area “Social life / Income” in the statistical database at http://pub.stat.ee.
The dissemination of data collected for the purpose of producing official statistics is guided by the requirements provided for in § 33, § 34, § 35, § 36, § 38 of the Access to microdata and anonymisation of microdata are regulated by Statistics Estonia’s procedure for dissemination of confidential data for scientific purposes.
Data serve as input for statistical activities 40009 “Income, poverty and material deprivation”, 40205 “Living conditions”, 40611 “Integration of disabled persons”, 40612 “Health” and 41001 “Social exclusion – Laeken indicators”.
The quality report sent to Eurostat is available at https://circabc.europa.eu/faces/jsp/extension/wai/navigation/container.jsp.
To assure the quality of processes and products, Statistics Estonia applies the EFQM Excellence Model, the European Statistics Code of Practice and the Quality Assurance Framework of the European Statistical System (ESS QAF). Statistics Estonia is also guided by the requirements in § 7. “Principles and quality criteria of producing official statistics” of the Official Statistics Act.
Statistics Estonia performs all statistical activities according to an international model (Generic Statistical Business Process Model – GSBPM). According to the GSBPM, the final phase of statistical activities is overall evaluation using information gathered in each phase or sub-process; this information can take many forms, including feedback from users, process metadata, system metrics and suggestions from employees. This information is used to prepare the evaluation report which outlines all the quality problems related to the specific statistical activity and serves as input for improvement actions.
Standardised output has been achieved through the definition of specific formats (list and description of output variables; data formats) and the determination of fixed deadlines for data transmission.
Ministry of Social Affairs
The main users of ESS (EU-SILC) are:
- European Union institutions, government authorities (in Estonia, mostly the Ministry of Social Affairs – social protection and social inclusion issues), international organisations (e.g. OECD, UNICEF);
- annual yearbooks and other publications (incl. analytical compilations) of Statistics Estonia and Eurostat;
- researchers who have access to microdata;
- end users (consumers), incl. the media, who are interested in the statistics on living conditions, incomes and social inclusion in Estonia and the European Union.
Users’ suggestions and information about taking these into account are available on the website of Statistics Estonia at http://www.stat.ee/statistikatood.
Since 1996, Statistics Estonia has conducted reputation and user satisfaction surveys. All results are available on the website of Statistics Estonia in the section User surveys.
The data are complete and in compliance with the data composition requirements of EU-SILC regulation of the European Commission.
The accuracy of source data is monitored by assessing the methodological soundness of data sources and the adherence to the methodological recommendations.
The type of survey and the data collection methods ensure sufficient coverage and timeliness.
Sampling error estimates are calculated for all indicators found, but these are published only for more important indicators.
For more complicated survey designs, such as the Estonian Social Survey (ESS), ordinary statistical assumptions about independent and identical distribution of variables cannot be taken as basis. In the case of Laeken indicators, their nonlinearity also makes calculation of standard error more complicated. Additionally, it must be kept in mind that ordinary rules for calculating standard errors have been developed for samples without replacement. Concerning the ESS design, a sample with replacement is used at the level of households, because every household occurs in the sample frame with all its members.
Therefore, a two-step procedure is used for calculating standard errors for Laeken indicators. At first, the indicators are linearized by using linearization procedures developed by Eurostat. Then, the standard error is computed for the total sum of obtained new variable as a standard error of the respective indicator. The program Bascula is used for computing standard errors.
The standard errors are computed by resampling method; a number of sub-samples are taken from the initial sample and the standard errors are computed based on the variability of sub-sample estimates.
Although a person has the obligation to ensure correctness of residential address in the population register, there is some under-coverage of persons and households there. Assuming that all permanent residents of Estonia are registered in the Population Register and considering the share of inaccurate addresses in the Population Register, the rate of under-coverage among households is no more than 1–1.5%. The overall response rate is 61% for households interviewed for the first time and 88% for households interviewed for at least the second time. The detailed response rates are published in the Statistical Database.
Measurement errors may be caused by the questionnaire (wording of questions, questionnaire structure), respondents, interviewers and the data collection method. It is not possible to prevent all this type of measurement errors in social surveys, but Statistics Estonia has tried to limit their amount as much as possible.
The data are checked in three stages: initial check upon data entry during the interview (on the laptop), secondary check of newly received data at the office, and finally data cleaning.
The initial logic checks in the entry program are continually improved, which has reduced the number of errors during data entry.
The extreme values of all income components and total income are checked and handled separately.
The Estonian social survey is part of the European Union Statistics on Income and Living Conditions (EU-SILC), which is coordinated by Eurostat. An EU-SILC survey is conducted in all EU member states and in Ireland, Norway, Switzerland and Turkey based on a harmonized methodology that allows publication of internationally comparable statistics on poverty, inequality and income.
In 2004, Statistics Estonia launched the Estonian social survey general survey, which was preceded by pilot surveys in 2001, 2002 and 2003. The first longitudinal data were compiled in 2008 when the first panel of households exited the survey after having participated for four years.
Until 2007, income did not include money saved on goods produced solely for own consumption and on imputed rent, i.e. money that a household saves on rent by living in its own dwelling. After 2007, these types of income are included in the total household income.
Starting from 2007, mortgage interest payments are deducted from total household income, which in previous years were not taken into account in the calculation of income.
Differences in the methodology, especially in the data collection instrument, need to be taken into account when comparing the statistics with data from other sources.
The internal consistency of the data is ensured by the use of a common methodology for data collection and data aggregation.
Before the beginning of the Estonian social survey, incomes, and based on that poverty and inequality indicators were calculated on the basis of Household budget survey data.
The population consists of all private households whose usual place of residence is in Estonia and the members of these households who do not live in institutions (children’s homes, care homes, monasteries, convents, prisons, etc.). About 1% of the population of Estonia is excluded from the survey.
The sample includes 8,200 households. Systematic stratified random sampling is used. The stratification is based on place of residence. The 15 counties and Tallinn city are divided into four strata by population size: I – Tallinn; II – four bigger counties (Harju (excl. Tallinn), Ida-Viru, Pärnu and Tartu counties); III – ten smaller counties (Jõgeva, Järva, Lääne, Lääne-Viru, Põlva, Rapla, Saare, Valga, Viljandi and Võru counties); IV – Hiiu county.
The following data are received from the Estonian Tax and Customs Board: data on income tax returns for resident natural persons (form A), business income of resident natural person (form E), declaration of income and social tax, unemployment insurance premiums and contributions to mandatory funded pension (form TSD); and unemployment insurance benefits and taxes paid on income.
The following data are received from the Social Insurance Board: amount and time of payment of benefits, pensions and allowances (by type) paid on the basis of the State Pension Insurance Act, State Family Benefits Act, Parental Benefit Act and Social Benefits for Disabled Persons Act; data on percentage of loss of capacity for work (20, 30, etc. until 100) and on degree of disability (moderate, severe, profound); data on old-age pension, pension for incapacity for work, parental benefits, child allowances and maintenance allowance.
The following data are received from the Estonian Health Insurance Fund: amount of benefits for temporary incapacity for work, income tax withheld, number of calendar days and type of benefit; and delivery records.
The data received from the Estonian Tax and Customs Board, the register of registered unemployed persons and jobseekers and labour market services, State Pension Insurance Register and health insurance database are used to check the quality of the collected data regarding income.
Starting from 2013, the following data are used: from the Social Insurance Board old-age pension, pension for incapacity for work, survivor’s benefits, parental benefits, child allowances, maintenance allowance; from the Estonian Unemployment Insurance Fund unemployment insurance benefits, layoff benefits, employer insolvency benefits, enterprise creation support, unemployment benefits; since 2016, the data are obtained concerning partial and no work ability.
DATA FROM OTHER STATISTICAL ACTIVITIES
Data are collected from individuals. The methods used for collecting the data include a personal interview (CAPI), in the case of recurring one-member households a telephone interview (CATI) or a web interview (CAWI), which the respondents complete independently. The interviews are conducted by Statistics Estonia's telephone interviewers with relevant training. The Survey Fieldwork Information System is used to manage and monitor data collection. The questionnaires have been designed to be filled in electronically by the respondent. The information related to data submission is available on the website of Statistics Estonia in the section Questionnaires.
Each household is to be interviewed four times, the rotation period is 12 months, whereas every year part of the sample is replaced. Thus, during the year the survey is cross-sectional which guarantees higher accuracy of estimates while using the given sample size. The interviews carried out with households in four consecutive years will allow getting more precise estimates of changes occurred over the years.
All households living permanently in Estonia are considered the survey population. Persons living in institutional households (children’s homes, care homes, convents, etc.) are excluded. All published estimates have been calculated for the total population of a respective region. The size of respective populations has been determined on the basis of the estimated total population provided by Statistics Estonia. Sampling is carried through among the records of the Population Register, whereas the sampling frame consists of people 14 years old and older. The sampling of persons is carried out by geographically stratified systematic sampling procedure, i.e. independent sub-samples are drawn separately from the non-overlapping subpopulations called strata. Each person is included with his or her household and all members of this household aged 15 or more are interviewed.
The data are collected with the official statistics questionnaires “Estonian Social Survey. Household questionnaire” and “Estonian Social Survey. Personal questionnaire”.
Data from Tax and Customs Board are received via an FTP-server and X-Road. Data from the Social Insurance Board and Estonian Health Insurance Fund are received via an FTP-server.
Arithmetic and qualitative controls are used in the validation process, including comparison with other data. Before data dissemination, the internal coherence of the data is checked.
In the case of missing or unreliable data, estimate imputation based on established regulations will be used. According to the regulation of the European Commission, all missing values of income variables should be imputed. As a rule, statistical imputation is the method used for that.
In case of within-household non-response, the persons who have not responded are imputed by using a person, characterized by similar variables, who is selected from among the responded persons by using the nearest neighbour method.
Variables and statistical units which were not collected but which are necessary for producing the output are calculated. New variables are calculated by applying arithmetic conversion to already existing variables. This may be done repeatedly, the derived variable may, in turn, be based on previously derived new variables.
For statistical units weights are calculated, which are used to expand the data of the sample survey to the total population.
The weights are calculated on the basis of design weights derived from inclusion probabilities. The weights, which are first adjusted to compensate for the bias caused by non-response and then calibrated to the population data, are used in calculating the final data. The basis of the calibration is the distribution of the population of Estonia by sex and age group and county on the 1st of January according to demographic data.
Microdata are aggregated to the level necessary for analysis. This includes summation of data according to the classification and calculating various statistical measures, e.g. average, median, dispersion, etc. The collected data are converted into statistical output. This includes calculating additional variables.