The Romanian city with the most permanent residents in 2023 was Bucharest, with over 2.14 million inhabitants. Iași was the second largest city, populated by around 392.6 thousand people, followed by Cluj-Napoca and Timișoara.

This statistic shows the biggest cities in Romania in 2021. In 2021, approximately **** million people lived in București, also known as Bucharest, making it the biggest city in Romania.

The city with the highest pollution index in Romania in 2025 was Bucharest, with an index of 75.4, followed by Iasi. Brasov ranked fifth, with a pollution index of 35.7.

This horizontal bar chart displays population (people) by city using the aggregation sum in Romania. The data is about cities.

Romania RO: Population in Largest City data was reported at 1,830,515.000 Person in 2017. This records a decrease from the previous number of 1,839,695.000 Person for 2016. Romania RO: Population in Largest City data is updated yearly, averaging 1,886,986.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2,060,655.000 Person in 1992 and a record low of 1,002,300.000 Person in 1960. Romania RO: Population in Largest City 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.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Population in largest city in Romania was reported at 1767520 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Romania - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Population in the largest city (% of urban population) in Romania was reported at 16.89 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Romania - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The city Buzau in Romania had an unemployment rate of 7.84, making Buzau the town with the highest unemployment rate as of December 2020. It was followed by Vaslui and Dolj, both with an unemployment rate of over seven percent.

This horizontal bar chart displays population (people) by continent using the aggregation sum in Romania. The data is about cities.

The Cultural Vitality of Cities in Romania is a study conducted by the National Institute for Cultural Research and Training with data collected for five categories of indicators, for the period 2010-2016 at the level of 46 cities, which we consider the main poles of cultural development/potential for cultural development, except for Bucharest which was not included in the analysis due to the special nature of the level of cultural facilities and services that dominate the rest of the cities in terms of cultural vitality. The cultural vitality of cities speaks about the cultural potential of local communities and highlights the development of cities on a cultural level. Vitality indices reflect cultural infrastructure, cultural participation, budget expenditure allocated to the cultural sector, specialised human resources and creative industries in the most important cities in the country. In the top of cultural vitality there are also appearances of cities with a spectacular evolution, being cases where propulsion in the top was achieved due to a certain category of indicators rather than a general picture of strong elements of vitality. This is the case for cities such as Craiova, Satu Mare, Târgu Jiu, Bistrita, Sfântu Gheorghe. Studies can be found on the INCFC website: https://www.culturadata.ro/publicatii/

Romania RO: Population in Largest City: as % of Urban Population data was reported at 17.328 % in 2017. This records an increase from the previous number of 17.324 % for 2016. Romania RO: Population in Largest City: as % of Urban Population data is updated yearly, averaging 16.910 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 18.986 % in 1977 and a record low of 15.918 % in 1960. Romania RO: Population in Largest City: as % of Urban Population 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.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

The most listened radio station in urban areas in Romania, from 7:00 am until 10:00 am, by people above 18 years old, was the music radio station ZU, with a daily reach of over 80 thousand people. It was followed by other music radio channels such as Kiss FM, Rock FM and Magic FM each with a daily listenership of over 50 thousand people.

In 2024, according to data provided by StartupBlink, the top city for startups in Romania was Bucharest, with a total score of ****. Cluj-Napoca and Timișoara followed.

Abstract

The survey is the follow-up of the Diagnostic Review on Consumer Protection and Financial Literacy conducted by the World Bank in 2008-2009. The Diagnostic Review in Romania was the fourth in a World Bank-sponsored pilot program to assess consumer protection and financial literacy in developing and middle-income countries.1 The objectives of this Review were three-fold to: (1) refine a set of good practices for assessing consumer protection and financial literacy, including financial literacy; (2) conduct a review of the existing rules and practices in Romania compared to the good practices; and (3) provide recommendations on ways to improve consumer protection and financial literacy in Romania. The Diagnostic Review was prepared at the request of the National Authority for Consumers' Protection (ANPC), whose request was endorsed by the Ministry of Economy and Finance. Support was provided by the National Bank of Romania (BNR), which supervises banks and non-bank credit institutions. Further assistance was given by the supervisory commissions for securities (CNVM), insurance (CSA) and private pensions (CSSPP).

The Diagnostic Review found that the basic foundations needed for consumer protection and financial literacy are in place in Romania but they benefit from further strengthening support. The Review proposes improvements in six areas: consumer awareness, information and disclosure for consumers, professional competence, dispute resolution, financial education and financial literacy surveys.

Consequently, in 2010 the World Bank commissioned a nation-wide survey of the levels of financial literacy. A consultant (sociologist Manuela Sofia Stanculescu) developed the survey methodology (sampling methodology and questionnaire) in line with the Financial Literacy Survey in Russia (the World Bank, 2008) and the baseline survey Financial Capability in the UK (Financial Services Authority, 2005).2 The final form of the questionnaire was agreed with representatives of the National Bank of Romania (BNR), the Romanian Banking Institute (IBR), the National Authority for Consumers' Protection (ANPC), and the Financial Companies Association in Romania (ALB). The Institute for World Economy (Romanian Academy) collected the data in May 2010.

The main objective of this work is the establishment (and later the evaluation) of a well targeted national program of financial education.

Geographic coverage

National

Analysis unit

Household, individual

Universe

Non-institutionalized persons aged 18 or older

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the survey is probabilistic, two-stage, stratified, representative at national level with an error of +/- 3% at a 95% confidence level.

The sample is based on two stratification criteria: (i) historical region (8 regions) and (ii) type of locality (7 types depending on the city size, in urban areas, and on the synthetic index of community development,4 in the rural ones).

The sample volume is 2048,5 out of which 148 cases represent a boost of persons aged 16, 17 or those had their 18th birthday after November 2009.6 Respondents were randomly selected from electoral registers corresponding to 185 voting sections (randomly selected), located in 141 localities (77 communes, 63 towns/cities and the capital Bucharest).

The sample includes a slight over-representation of men, rural respondents, and elderly particularly due to the boost of young but also to the fact that people left abroad concentrate among the 25-44 age category. Nevertheless, the sample fairly reproduces the structure (by gender, age categories and area of residence) of the country population 16+ years according to the data for 2009 provided by the National Institute for Statistics. Socio-demographic structure of the sample is presented in table 3 of the survey report.

Demographic data and data regarding the use of financial services were collected for all members of respondents? households. In the respondents? households live 5406 persons overall. This extended sample has also a slight over-representation of rural respondents and an under-representation of children (0-14 years) and persons 25-24 years (most probably young people who left abroad with children).

MORE INFORMATION ON THE SAMPLING METHODOLOGY

Sample volume: 2,200 non-institutionalized persons aged 18 or older. In addition, the sample will be boosted with 180 persons aged 16-18 years old. Overall, at least 2,000 valid questionnaires should be completed during fieldwork.

Type of the sample: Probabilistic, two-stage, stratified, representative at national level, with an error of +/- 2.8% at a 95% confidence level.

Stratification criteria: The sampling scheme is based on two stratification criteria

(a) Historical region (8 regions) (b) Type of locality, with 7 theoretical strata

i. Urban areas - 4 strata 1. very small towns under 30 thou inhabitants 2. small towns 30,001-100 thou inhabitants 3. medium cities 100,001-199 thou inhabitants 4. large cities 200 thou inhabitants or more

ii. Rural areas - 3 strata determined based on the synthetic index of community development 37 1. poor communes (the 30% communes with the lowest level of development within the country) 2. medium developed communes 3. developed communes (the 30% communes with the highest level of development within the country).

Sampling stages: The sampling scheme includes two stages.

Sampling units: There are two sampling units corresponding to the two sampling stages. In the first sampling stage, voting sections are selected and in the second stage, non-institutionalized persons aged 18 years or more.

Selection: Random selection in all sampling stages.

Sampling scheme: In the first stage the sample is distributed proportionally with the volume of population for each of the 56(= 8 x 7) theoretical strata different from zero.

The corresponding number of voting sections for each strata is determined taking into account on the one hand, the volume of each strata sub-sample (= sample size x share of total population in that strata) and, on the other hand, a minimum level of 10 questionnaires for each sampling point. The voting sections which will represent sampling points are then randomly selected based on the exhaustive national list of voting sections (the latest available from the Permanent Electoral Authority).

The sample has 188 sampling points (voting sections) of which 104 are in urban areas, and 84 are in rural localities, including the capital city.

For each sampling point is computed the number of corresponding questionnaires by dividing the strata sub-sample by the number of sampling points of that strata. In the second sampling stage, the electoral registers corresponding to the voting sections (selected as sampling points) are used as sampling frame. Non-institutionalized persons aged 18 or more are randomly selected from the electoral registers based on the mechanical step method.

In those localities where the electoral registers are not available (or the municipality do not grant access), the random route method will be used. All these cases will be specified and explained in the fieldwork report, except for Bucharest, where the random route method will be used for all voting sections, as the rate of replacement from electoral registers is high in all national representative surveys.

The electoral registers include only persons 18 years or more. Accordingly, the sample will include a boost of persons aged 16, 17 or persons that had their 18th birthday after November 2009.39 For each voting section, one person aged 16-18 years will be added. They will be selected based on the random route method.

Mode of data collection

Face-to-face [f2f]

Response rate

The overall response rate of the survey is 95.2%. More detailed information is provided in "Table 2 Response rates and quality of the sampling frame by sampling method (%) " of the survey report.

Download high-quality, up-to-date Romania shapefile boundaries (SHP, projection system SRID 4326). Our Romania Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

In 2019, Brasov was the city with the highest purchasing power index in Romania, reaching *****. Romania's capital, Bucharest, ranked fourth, with a purchasing power index of *****.

Graph and download economic data for Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Credit Unions and Financial Cooperatives for Romania (ROUFCBODULNUM) from 2008 to 2015 about branches, credit unions, Romania, financial, and depository institutions.

The number of individual dwelling transactions has fluctuated in the past few years, reaching the lowest number in 2019 at 113,800, and the highest peak recorded in 2021–183,000. Bucharest was by far the most busy real estate market, accounting for 35.5 percent of total transactions. Out of all the large cities, only Pitesti and Ploiesti had a positive number of transactions growth compared to 2022—up by 16 percent each.

The city in Romania with the highest crime index was Constanta with ****, it was followed by Craiova, with an index value of ****. These values are high, given that the higher the index value, the higher the level of crime. Nevertheless, theses values are way above the overall crime index in Romania, which by 2024 increased to *****.

The purpose of this research is to identify the best time of year for open-air tourism in ten of Romania's most populated cities. The climate conditions were assessed using the enhanced tourism climate index (ETCI) on a temporal scale of 10 days over 61 years (1961-2021) to determine the best times of year for outdoor tourism. For observing any change, we compared the last 10 years (2012-2021) to the entire period of the current study. Daily mean temperature, relative humidity, wind speed, precipitation and sunshine, maximum temperature, and minimum relative humidity were employed. The trend detection methods were the Mann-Kendall test combined with Sen’s slope and the parameters considered for change detection were the frequency of days ranked as good, very good, excellent and ideal for outdoor tourism; the duration of the occurrence period, the first and the last day of occurrence of each class. We found that the most appropriate weather for open-air tourism usually begins in the third 10-day period of April and ends during the second 10-day period of October. This study could become an extremely useful tool for better planning events for tourism and recreation in the short and mid-term.