On July 1, 2005, the Romanian leu lost the last 4 zeros by denomination at the rate of 1 new leu for 10,000 "old" lei. The average gross monthly salary in Romania peaked in March 2025 at 9,495 Romanian lei. As a consequence, the average net monthly salary slightly increased as well, totaling 5,691 Romanian lei as of March 2025.

Wages in Romania decreased to 9187 RON/Month in May from 9415 RON/Month in April of 2025. This dataset provides the latest reported value for - Romania Average Gross Monthly Wages - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The average net monthly salary in Romania amounted to over five thousand Romanian lei in 2023, having increased by nearly 15.5 percent compared to the previous year. Furthermore, the net minimum wage increased as well, set at 1,863 Romanian lei in 2023.

Key information about Romania Household Income per Capita

• Romania Annual Household Income per Capita reached 7,531.947 USD in Dec 2023, compared with the previous value of 6,591.522 USD in Dec 2022.
• Romania Annual Household Income per Capita data is updated yearly, available from Dec 2001 to Dec 2023, with an averaged value of 3,229.809 USD.
• The data reached an all-time high of 7,531.947 USD in Dec 2023 and a record low of 746.832 USD in Dec 2001.
• In the latest reports, Retail Sales of Romania grew 9.991 % YoY in Jun 2024.

CEIC calculates Annual Household Income per Capita from annual Monthly Average Household Income multiplied by 12 and annual Average Household Size and converts it into USD. The National Institute of Statistics provides Household Income in local currency and Average Household Size. The National Bank of Romania average market exchange rate is used for currency conversions.

Key information about Romania Monthly Earnings

• Romania Monthly Earnings stood at 1,949 USD in Dec 2024, compared with the previous figure of 1,884 USD in Nov 2024
• Romania Monthly Earnings data is updated monthly, available from Jan 1991 to Dec 2024, with an average number of 578 USD
• The data reached the an all-time high of 1,949 USD in Dec 2024 and a record low of 50 USD in Nov 1991

CEIC converts Monthly Earnings into USD. The National Institute of Statistics provides Monthly Earnings in local currency. The National Bank of Romania average market exchange rate is used for currency conversions. According to the national legislation provisions in force (GEO No. 79/2017), the social security contribution and the social health insurance contribution paid by the employer were transferred to the employee. Starting with March 2017, Average Monthly Gross Earnings are not comparable to data prior March 2017.


Further information about Romania Monthly Earnings

• In the latest reports, Romania Population reached 19 million people in Dec 2023
• Unemployment Rate of Romania dropped to 6 % in May 2023
• The country's Labour Force Participation Rate dropped to 52 % in Sep 2024

Wages in Romania increased 10.30 percent in April of 2025 over the same month in the previous year. This dataset provides - Romania Wage Growth- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Wages in Manufacturing in Romania decreased to 8226 RON/Month in May from 8594 RON/Month in April of 2025. This dataset provides the latest reported value for - Romania Average Monthly Gross Wages in Manufacturing - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Romania RO: Wage And Salary Workers: Modeled ILO Estimate: Male: % of Male Employment data was reported at 71.969 % in 2017. This records a decrease from the previous number of 72.154 % for 2016. Romania RO: Wage And Salary Workers: Modeled ILO Estimate: Male: % of Male Employment data is updated yearly, averaging 66.861 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 74.778 % in 1991 and a record low of 56.016 % in 2000. Romania RO: Wage And Salary Workers: Modeled ILO Estimate: Male: % of Male Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Romania – Table RO.World Bank: Employment and Unemployment. Wage and salaried workers (employees) are those workers who hold the type of jobs defined as 'paid employment jobs,' where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections.

Romania RO: Wages Index data was reported at 169.459 2010=100 in 2017. This records an increase from the previous number of 148.427 2010=100 for 2016. Romania RO: Wages Index data is updated yearly, averaging 0.021 2010=100 from Dec 1955 (Median) to 2017, with 60 observations. The data reached an all-time high of 169.459 2010=100 in 2017 and a record low of 0.004 2010=100 in 1955. Romania RO: Wages Index data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Romania – Table RO.IMF.IFS: Wages, Labour Cost and Employment Index: Annual.

Romania - Monthly minimum wages - bi-annual data was EUR814.00 in June of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Romania - Monthly minimum wages - bi-annual data - last updated from the EUROSTAT on July of 2025. Historically, Romania - Monthly minimum wages - bi-annual data reached a record high of EUR814.00 in June of 2025 and a record low of EUR25.00 in June of 2000.

Romania RO: Law Mandates Equal Remuneration for Females & Males for Work of Equal Value: 1=Yes; 0=No data was reported at 1.000 NA in 2017. This stayed constant from the previous number of 1.000 NA for 2015. Romania RO: Law Mandates Equal Remuneration for Females & Males for Work of Equal Value: 1=Yes; 0=No data is updated yearly, averaging 1.000 NA from Dec 2013 (Median) to 2017, with 3 observations. The data reached an all-time high of 1.000 NA in 2017 and a record low of 1.000 NA in 2017. Romania RO: Law Mandates Equal Remuneration for Females & Males for Work of Equal Value: 1=Yes; 0=No data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Romania – Table RO.World Bank: Policy and Institutions. Law mandates equal remuneration for females and males for work of equal value is whether there is a law that obligates employers to pay equal remuneration to male and female employees who do work of equal value.“Remuneration” refers to the ordinary, basic or minimum wage or salary and any additional emoluments payable directly or indirectly, whether in cash or in kind, by the employer to the worker and arising out of the worker’s employment. “Work of equal value” refers not only to the same or similar jobs but also to different jobs of the same value.; ; World Bank: Women, Business and the Law.; ;

Romania RO: Time to Prepare and Pay Taxes data was reported at 163.000 Hour in 2017. This records an increase from the previous number of 161.000 Hour for 2016. Romania RO: Time to Prepare and Pay Taxes data is updated yearly, averaging 202.000 Hour from Dec 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 230.000 Hour in 2010 and a record low of 161.000 Hour in 2016. Romania RO: Time to Prepare and Pay Taxes data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Romania – Table RO.World Bank: Company Statistics. Time to prepare and pay taxes is the time, in hours per year, it takes to prepare, file, and pay (or withhold) three major types of taxes: the corporate income tax, the value added or sales tax, and labor taxes, including payroll taxes and social security contributions.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for romania in the U.S.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for east european studies romanian in the U.S.

Abstract

In 2012, the EU-SILC instrument covered all EU Member States plus Iceland, Turkey, Norway, Switzerland and Croatia. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labor, education and health observations only apply to persons aged 16 and over. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

This is the 3rd version of the 2012 Cross-Sectional User Database as released in July 2015.

Geographic coverage

The survey covers following countries: Austria; Belgium; Bulgaria; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Spain; Ireland; Italy; Latvia; Lithuania; Luxembourg; Hungary; Malta; Netherlands; Poland; Portugal; Romania; Slovenia; Slovakia; Sweden; United Kingdom; Iceland; Norway; Turkey; Switzerland

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United Kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

Abstract

EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Longitudinal data is limited to income information and a limited set of critical qualitative, non-monetary variables of deprivation, aimed at identifying the incidence and dynamic processes of persistence of poverty and social exclusion among subgroups in the population. The longitudinal component is also more limited in sample size compared to the primary, cross-sectional component. Furthermore, for any given set of individuals, microlevel changes are followed up only for a limited duration, such as a period of four years.

For both the cross-sectional and longitudinal components, all household and personal data are linkable. Furthermore, modules providing updated information in the field of social exclusion is included starting from 2005.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

This is the 5th release of 2010 Longitudinal user database as published by EUROSTAT in September 2014.

Geographic coverage

National

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Mode of data collection

Mixed

Abstract

EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 7th version of the 2008 Cross-Sectional User Database (UDB) as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Greece, Spain, France, Ireland, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, Netherlands, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, United Kingdom, Iceland, Norway.

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

Average net earnings in the European Union was ****** Euros for a single person with no children in 2022, while for a couple with children who both worked it was ****** Euros. Among countries in Europe, *********** was the country with the highest net earnings in 2022, followed by *******************************. The lowest net earnings were found in Bulgaria and Romania, where a single person without children earned on average less than ***** Euros in 2022.

Romania was forecast to have the highest real salary increase in the last quarter of 2024 of the 34 countries included. The salary increase in the European country was forecast to reach ** percent. Croatia and Serbia followed behind. On the other hand, Iceland and Japan were forecast to have a real wage growth of only *** percent.

The minimum gross wage per hour in Poland as of July 2024 amounted to **** zloty. As of January 2025, the minimum hourly wage will increase to **** zloty gross, an increase of **** percent. Purchasing power standards (PPS) in the CEE region From 2009 to 2023, almost every country in Central and Eastern Europe experienced increased GDP per capita in purchasing power standards. For example, Czechia's GDP per capita amounted to ** PPS last year, reaching the highest level among Central and Eastern European countries but lower than the EU average. A similar situation occurred in Poland, one of the countries experiencing an increase in GDP per capita, amounting to ** PPS. On the other hand, the highest actual individual consumption per capita expressed in purchasing power standards in the CEE region was recorder in Lithuania, Slovenia, and Romania. However, all Central and Eastern European countries reached actual individual consumption per capita below the EU average. Inflation’s effect on Poles Since the beginning of the COVID-19 pandemic, inflation has increased drastically. That caused people to look at their expenditure of salaries more responsibly but also made them want to earn more. From 2021 to 2023, a fair share of Poles felt that food prices and fuel increased the most over the year. In 2022, due to the rising of some products and services in recent months in Poland, ** percent of people bought less and looked for cheaper products during daily shopping. Moreover, around ** percent of Poles gave up higher expenses to put them off for later. Inflation causes people to look for cheaper products. However, only about ** percent of Poles had higher trust in the promotions due to inflation.