The gross domestic product (GDP) in current prices in Romania amounted to about 384.15 billion U.S. dollars in 2024. Between 1980 and 2024, the GDP rose by approximately 338.10 billion U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The GDP will steadily rise by around 140.72 billion U.S. dollars over the period from 2024 to 2030, reflecting a clear upward trend.This indicator describes the gross domestic product at current prices. The values are based upon the GDP in national currency converted to U.S. dollars using market exchange rates (yearly average). The GDP represents the total value of final goods and services produced during a year.

The Gross Domestic Product (GDP) in Romania was worth 382.77 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Romania represents 0.36 percent of the world economy. This dataset provides the latest reported value for - Romania GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The leading company in Romania's machinery and equipment market in 2023 was Schaeffler România, with a revenue of over 3.9 billion Romanian lei, followed by Bosch Automotive, with an income of three billion Romanian lei. The most significant net profit was also recorded by Bosch Automotive - 60.9 million Romanian lei, while Frigoglass România suffered a net loss of 78.2 million Romanian lei.

The latest data from show economic growth of 0.6 percent, which is an increase from the rate of growth of 0.4 percent in the previous quarter and
a decrease compared to the growth rate of 1.9 percent in the same quarter last year. The economic growth time series for Romania cover the period from...

The leading bank in Romania in 2022 was Banca Transilvania, with financial assets worth over 161.7 billion Romanian lei. It was followed by Banca Comercială Română (BCR), CEC Bank and BRD-SocGen each with financial assets above 80 billion Romanian lei.

Key information about Romania Real GDP Growth

• The Gross Domestic Product (GDP) in Romania expanded 2.9 % YoY in Mar 2023, following a growth of 4.3 % in the previous quarter.
• Real GDP Growth YoY data in Romania is updated quarterly, available from Mar 1996 to Mar 2023, with an average rate of 3.5 %.
• The data reached an all-time high of 11.9 % in Dec 2004 and a record low of -7.9 % in Jun 2020.

CEIC calculates Real GDP Growth from quarterly Real GDP. The National Institute of Statistics provides Real GDP in local currency, at chain linked 2000 prices.


Related information about Romania Real GDP Growth

• In the latest reports, Nominal GDP of Romania reached 86.0 USD bn in Mar 2023.
• Its GDP deflator (implicit price deflator) increased 14.4 % in Mar 2023.
• GDP Per Capita in Romania reached 14,987.8 USD in Dec 2021.
• Its Gross Savings Rate was measured at 14.5 % in Mar 2023.
• For Nominal GDP contributions, Investment accounted for 18.7 % in Mar 2023.
• Public Consumption accounted for 18.4 % in Mar 2023.
• Private Consumption accounted for 67.1 % in Mar 2023.

Romania: Economic growth forecast: The latest value from 2030 is 3.5 percent, an increase from 3.4 percent in 2029. In comparison, the world average is 3.25 percent, based on data from 182 countries. Historically, the average for Romania from 1980 to 2030 is 1.99 percent. The minimum value, -12.93 percent, was reached in 1991 while the maximum of 10.43 percent was recorded in 2004.

The Gross Domestic Product (GDP) in Romania expanded 0.30 percent in the first quarter of 2025 over the same quarter of the previous year. This dataset provides the latest reported value for - Romania GDP Annual Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Hidroelectrica, Electrica Furnizare and E.ON Energie Romania had the highest revenue in 2022, each totaling over 10 billion Romanian lei. Meanwhile, PPC Energie and PPC Energie Muntenia registered net losses in 2023.

Full Year GDP Growth in Romania decreased to 0.90 percent in 2024 from 2.40 percent in 2023. This dataset includes a chart with historical data for Romania Full Year GDP Growth.

The Gross Domestic Product (GDP) in Romania stagnated 0 percent in the first quarter of 2025 over the previous quarter. This dataset provides - Romania GDP Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Key information about Romania Market Capitalization: % of GDP

• Romania Market Capitalization accounted for 19.8 % of its Nominal GDP in Dec 2024, compared with a percentage of 18.3 % in the previous year
• Romania Market Capitalization: % Nominal GDP is updated yearly, available from Dec 1995 to Dec 2024
• The data reached an all-time high of 21.4 % in Dec 2006 and a record low of 0.2 % in Dec 1996

CEIC calculates Market Capitalization as % of Nominal GDP from annual Market Capitalization and annual Nominal GDP. Bucharest Stock Exchange provides Market Capitalization in local currency. The National Institute of Statistics provides Nominal GDP in local currency.


Further information about Romania Market Capitalization: % of GDP

• In the latest reports, Bucharest Stock Exchange (BVB) recorded a monthly P/E ratio of 8.6 in Jan 2025
• RON closed at 17,520.8 points in Feb 2025

OMV Petrom had by far the highest revenue in 2023, totaling over 33.8 billion Romanian lei. OMV Petrom was also the most profitable company with over 3.9 billion Romanian lei, while OMV Petrom Marketing had a net profit worth only 620 million Romanian lei.

Graph and download economic data for Gross Domestic Product (Euro/ECU Series) for Romania (CPMEURNSAB1GQRO) from Q1 1995 to Q1 2025 about Romania and GDP.

Abstract This data repository contains data at municipality data in Romania about population and population change, wages, agregate turnover, sectorial employment, and e,ployees by types of capital (FDI-capital, domestic and public). The data explores the spatial dynamics of the labor market at the subnational level, providing insights into wage moderation and repression in export-led growth regimes in Central and Eastern Europe. The data are used to investigate the spatial concentration of specialized economies within cities and their periurban areas, where the regional labor force is leveraged to moderate wage increases and attract populations in economies heavily reliant on FDI, in Romania. The data and models are used to show that this leads to the formation of ‘enclave economies’, characterized by localized labor regimes shaped by territorial zoning strategies that regulate labor migration and economic zoning of capital. Employing spatial regression with SARAR-SUR, we model population change and concentration to identify different labor regimes in regional enclaves, examining the impact of wages, sectorial employment, and types of capital. Our findings demonstrate that the sub-national distribution of FDI-led growth in Romania primarily revolves around labor-intensive activities and low capitalization costs, rather than urbanization. Additionally, we observe that changes in employment within public services are not significantly associated with population changes, suggesting that the state does not play a major role as a competitor in the labor markets. Furthermore, our analysis captures the specific labor requirements of multinational firms operating in business services and manufacturing, highlighting the negative impact of foreign companies in the business service sector on the population of core cities.

Data Dependent Variable - The dependent variable in our analysis is population change, which we measure using the population ratio of 2012 to 2011 on a natural logarithmic scale due to its mathematical similarity to percent growth. Dual citizens of Romanian descent from Moldova and Ukraine are drawn to the eastern region, particularly border towns in Suceava, Botoșani, Iași, and Vaslui counties. These immigrants often use their Romanian citizenship to migrate within the EU. To account for this regional trend, we substracted from the population the number of emigrants from each locality over the past decade (both in 2011 and 2021)

Independent variables - We model population change at locality level using wages as a pull factor, capital type and economic sector. To assess the impact of personal income on employment, we have utilized personal income tax data to estimate aggregated wages at the local level as provided on the data portal of the Romanian's Ministry of Regional Development and Public Administration. - The Romanian National Institute of Statistics categorizes individuals as employed or working to account for those not receiving wages, including self-employed and contributing family workers. Agricultural workers make up most of the un-waged working population. To measure waged relations within the labor pool, we used the ratio of waged employees to the active age population (16-65 years), which serves as a measure of the size of the labor market at the local level. - We obtained employment data from the National Institute of Statistics, which provided aggregated balance sheets of all companies at the subsidiary level for 2011 and 2021. - We used a dummy variable to distinguish between foreign and domestic companies, and we separately aggregated the number of employees working in local and foreign companies. For the purposes of this study, a company was deemed foreign if it was incorporated in Romania and had 50% or more of its equity shares or share capital owned by a natural or legal person residing outside of Romania. - NACE codes related to manufacturing were used to isolate the companies of interest. To differentiate business services from other service activities, NACE codes related to activities such as information and communication, financial and insurance activities, real estate activities, professional, scientific, and technical activities, and administrative and support service activities were used to filter companies. The aim is to capture the growth of outsourcing in this sector while excluding other service activities such as social services and commerce and logistics. - The first layer of municipalities surrounding the 260 cities in Romania are referred to as periurban area, as they represent the transitional zone between urban and rural environments (Dadashpoor and Ahani, 2019; Stahl, 1969). Out of the 319 cities in Romania, 59 towns are located within the periurban areas adjacent to larger cities in terms of population. This classification creates three typologies of administrative territorial units (3180): core cities (260), periurban localities (1330), and villages (1590). These locality types (core city, periurban localities, and villages) were transformed into dummy variables and utilized as interaction variables. - In Romania, periurban areas are defined by Law no. 246/2022, which focuses on metropolitan areas and involves modifications and additions to certain normative acts. For municipalities, the periurban area includes the first two layers of municipalities surrounding the core city, while for cities, it encompasses only the first layer. However, it's important to note that the majority of population growth occurred in the first layer of municipalities. Due to this, we considered the periurban area for all 260 cities to be equivalent to the first layer of municipalities. - An alternative approach for analysis would have been to use the functional urban area, as defined by Eurostat, which covers the localities within the commuting range of the central city. Nevertheless, this scale is unsuitable for examining population change, as it shows only a negligible percentage change (0.1%) between 2003 and 2020. In contrast, periurban areas exhibited a much more significant population change of 5% during the same period. Consequently, we opted to present our analysis using the concept of periurban areas.

Model specification - We employed two specifications for the independent variables: a cross-sectional specification for 2021 and a first-differencing strategy that measures the difference between municipality-level values in 2011 and 2021. We used both specifications to assess the effect of employment composition across municipalities on population dynamics. The cross-sectional specification assumes that larger employment markets with more employees out of the active age population act as population magnets. However, it is influenced by idiosyncratic factors specific to each municipality. The first-differencing strategy controls for individual-level effects and plays a similar role to a fixed effect for two discontinuous time points, accounting for time-variant factors . It assumes that an increase in employment opportunities at the municipality level generates an overall population increase, irrespective of the size of the labor market out of the active age population. - Despite utilizing all three categories of the locality type simultaneously as a dummy system, multicollinearity did not pose a problem. The interaction term divided the independent variable into spatial components, forming spatial regimes, as described by Anselin and Rey (2014). Furthermore, when the locality type was used as an interaction effect in all models, the continuous variable only covered a portion of the population, specifically those within an economic sector. It did not account for the entire population of employees.

Model selection - We employed a three-stage least squares approach using Seemingly Unrelated Regression (SUR) models. We incorporated Spatial Autoregressive terms and Spatial Autoregressive Disturbances (SARAR). R package spsur (Angulo et al., 2021) to estimate the model, and a row-standardized queen contiguity spatial weights matrix was computed from the geometries of Romanian localities to perform the regressions.

Files - data cross.csv: The data for the cross-sectional specification for 2021 - data diff.csv: The data for the first-differencing strategy that measures the difference between municipality-level values in 2011 and 2021 - model.csv: The data which contain the analysis for preparatory analysis and model selection - model A.R: The code in R with the preparatory analysis and model selection - model B.R: The code in R with the analysis with the two specifications for the independent variables - Vizualization.twbx: The Vizualization in Tableau of the data and the predicted values of the different models - codebook data cross.csv - codebook data diff.csv - codebook model.csv

Key information about Romania Public Consumption: % of GDP

• Romania Public Consumption accounted for 16.1 % of its Nominal GDP in Dec 2024, compared with a share of 17.0 % in the previous quarter.
• Romania Public Consumption share of Nominal GDP ratio is updated quarterly, available from Mar 1995 to Dec 2024, with an average number of 15.9 %.
• The data reached an all-time high of 25.1 % in Jun 1995 and a record low of 2.0 % in Sep 1995.

CEIC calculates Government Consumption as % of Nominal GDP from quarterly Government Consumption Expenditure and quarterly Nominal GDP. Government Consumption Expenditure is calculated as the sum of Government Individual Consumption and Collective Consumption. The National Institute of Statistics provides Government Consumption Expenditure in local currency and Nominal GDP in local currency.


Related information about Romania Public Consumption: % of GDP

• In the latest reports, Romania GDP expanded 2.9 % YoY in Mar 2023.
• Romania Nominal GDP reached 86.0 USD bn in Mar 2023.
• Its GDP deflator (implicit price deflator) increased 14.4 % in Mar 2023.
• Romania GDP Per Capita reached 14,987.8 USD in Dec 2021.
• Its Gross Savings Rate was measured at 18.3 % in Dec 2024.
• For Nominal GDP contributions, Investment accounted for 25.0 % in Dec 2024.
• Private Consumption accounted for 65.6 % in Dec 2024.

Key information about Romania External Debt: Short Term: % of GDP

• Romania External Debt: Short Term accounted for 13.8 % of the country's Nominal GDP in 2024, compared with the ratio of 14.3 % in the previous year.
• Romania External Debt: Short Term: % of Nominal GDP data is updated yearly, available from 2004 to 2024.
• The data reached an all-time high of 16.5 % in 2011 and a record low of 5.3 % in 2004.

CEIC calculates Short Term External Debt as % of Nominal GDP from monthly Short Term External Debt and annual Nominal GDP. The National Bank of Romania provides Short Term External Debt in EUR based on BPM6. The National Institute of Statistics provides Nominal GDP in local currency. The National Bank of Romania average market exchange rate is used for currency conversions. Short Term External Debt prior to 2008 is based on BPM5.


Related information about Romania External Debt: Short Term: % of GDP

• In the latest reports of Romania, Current Account recorded a deficit of 3.1 USD bn in Dec 2024.
• Foreign Direct Investment (FDI) increased by 493.2 USD mn in Dec 2024.
• Romania Direct Investment Abroad expanded by 141.4 USD mn in Dec 2024.
• Its Foreign Portfolio Investment fell by 1.6 USD bn in Dec 2024.
• Romania External Debt: Short Term value stood at 50.9 USD bn in Dec 2024.
• The country's Nominal GDP was reported at 86.0 USD bn in Mar 2023.

Contains data from the World Bank's data portal covering the following topics which also exist as individual datasets on HDX: Agriculture and Rural Development, Aid Effectiveness, Economy and Growth, Education, Energy and Mining, Environment, Financial Sector, Health, Infrastructure, Social Protection and Labor, Poverty, Private Sector, Public Sector, Science and Technology, Social Development, Urban Development, Gender, Millenium development goals, Climate Change, External Debt, Trade.

Romania: Informal economy, MIMIC method: The latest value from 2020 is 30.8 percent, an increase from 30.1 percent in 2019. In comparison, the world average is 32.74 percent, based on data from 158 countries. Historically, the average for Romania from 1993 to 2020 is 32.62 percent. The minimum value, 30.1 percent, was reached in 2019 while the maximum of 34.4 percent was recorded in 2000.

Romania - Economic sentiment indicator was 97.00% in June of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Romania - Economic sentiment indicator - last updated from the EUROSTAT on July of 2025. Historically, Romania - Economic sentiment indicator reached a record high of 105.20% in November of 2024 and a record low of 97.00% in June of 2025.