This statistic shows the average annual change in real GDP per capita in the United States from President Hoover to Obama, as of 2011. The biggest economic growth happened during Franklin D. Roosevelt's presidency. The Real Gross Domestic Product per capita increased by 5.25 percent each year.

Additional information on President Barack Obama’s first term economic policy performance

“It’s the economy, stupid” as the now famous saying by former President Bill Clinton goes is often used to demonstrate the importance continuants place on the economy’s performance. Appointed to President of the United States in 2008, President Obama entered the job in the early stages of a global economic crisis. The unemployment rate in the United States since 1990 demonstrates that Obama oversaw a reduction in unemployment rate since an initially sharp increase to over 9 percent in 2009 and 2010. Prior to the reduction, public approval of President Obama and the Republicans in congress in handling the economy shows that the public’s trust in Obama waned from 61 percent in February 2009 to 42 percent in November 2011. The fluctuation of America’s economy meant that Obama’s first term saw him reach an average of 76 thousand private sector jobs created per month as of June 2012, leaving him sixth in private sector job creation on the list of post-war presidents.

As leader of the most economically influential country on the planet, praise and criticism of Obama’s economic performance is also a global issue. In 2012, opinion on Obama’s management of global economic issues by country demonstrates the variety in opinion held in and across countries. While countries such as Britain and Germany whose economies appeared to be recovering held Obama’s economic policy in a positive light, opinion was more negative in Egypt and Greece were the economic situation was less optimistic.

Adding to national debt is an inevitable fact of being President of the United States. The extent to which debt rises under any sitting president depends not only on the policy and spending choices they have made, but also the choices made by presidents and congresses that have come before them. Ronald Reagan and George W. Bush President Ronald Reagan increased the U.S. debt by around **** trillion U.S. dollars, or ****** percent. This is often attributed to "Reaganomics," in which Reagan implemented significant supply-side economic policies in which he reduced government regulation, cut taxes, and tightened the money supply. Spending increased under President George W. Bush in light of the wars in Iraq and Afghanistan. To finance the wars, President Bush chose to borrow the money, rather than use war bonds or increase taxes, unlike previous war-time presidents. Additionally, Bush introduced a number of tax cuts, and oversaw the beginning of the 2008 financial crisis. Barack Obama President Obama inherited both wars in Iraq and Afghanistan, and the financial crisis. The Obama administration also did not increase taxes to pay for the wars, and additionally passed expensive legislation to kickstart the economy following the economic crash, as well as the Affordable Care Act in 2010. The ACA expanded healthcare coverage to cover more than ** million more Americans through programs like Medicare and Medicaid. Though controversial at the time, more than half of Americans have a favorable view of the ACA in 2023. Additionally, he signed legislation making the W. Bush-era tax cuts permanent.

The Gross Domestic Product (GDP) in the United States contracted 0.50 percent in the first quarter of 2025 over the previous quarter. This dataset provides the latest reported value for - United States GDP Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The United States recorded a Government Debt to GDP of 124.30 percent of the country's Gross Domestic Product in 2024. This dataset provides - United States Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

As of the third quarter of 2024, the GDP of the U.S. grew by 2.8 percent from the second quarter of 2024. GDP, or gross domestic product, is effectively a count of the total goods and services produced in a country over a certain period of time. It is calculated by first adding together a country’s total consumer spending, government spending, investments and exports; and then deducting the country’s imports. The values in this statistic are the change in ‘constant price’ or ‘real’ GDP, which means this basic calculation is also adjusted to factor in the regular price changes measured by the U.S. inflation rate. Because of this adjustment, U.S. real annual GDP will differ from the U.S. 'nominal' annual GDP for all years except the baseline from which inflation is calculated. What is annualized GDP? The important thing to note about the growth rates in this statistic is that the values are annualized, meaning the U.S. economy has not actually contracted or grown by the percentage shown. For example, the fall of 29.9 percent in the second quarter of 2020 did not mean GDP is suddenly one third less than a year before. In fact, it means that if the decline seen during that quarter continued at the same rate for a full year, then GDP would decline by this amount. Annualized values can therefore exaggerate the effect of short-term economic shocks, as they only look at economic output during a limited period. This effect can be seen by comparing annualized quarterly growth rates with the annual GDP growth rates for each calendar year.

In 2023 the real gross domestic product (GDP) of the United States increased by 2.5 percent compared to 2022. This rate of annual growth indicates a return to economy normalcy after 2020 saw a dramatic decline in the GDP growth rate due to the the coronavirus (COVID-19) pandemic, and high growth in 2021.

What does GDP growth mean?

Essentially, the annual GDP of the U.S. is the monetary value of all goods and services produced within the country over a given year. On the surface, an increase in GDP therefore means that more goods and services have been produced between one period than another. In the case of annualized GDP, it is compared to the previous year. In 2023, for example, the U.S. GDP grew 2.5 percent compared to 2022.

Countries with highest GDP growth rate

Although the United States has by far the largest GDP of any country, it does not have the highest GDP growth, nor the highest GDP at purchasing power parity. In 2021, Libya had the highest growth in GDP, growing more than 177 percent compared to 2020. Furthermore, Luxembourg had the highest GDP per capita at purchasing power parity, a better measure of living standards than nominal or real GDP.

GDP per Capita: Annualized: Quarterly data was reported at 7,049.000 TJS in Mar 2018. This records an increase from the previous number of 6,883.800 TJS for Dec 2017. GDP per Capita: Annualized: Quarterly data is updated quarterly, averaging 2,417.800 TJS from Mar 2000 (Median) to Mar 2018, with 73 observations. The data reached an all-time high of 7,049.000 TJS in Mar 2018 and a record low of 39.661 TJS in Mar 2000. GDP per Capita: Annualized: Quarterly data remains active status in CEIC and is reported by Аgency on Statistics under the President of the Republic of Tajikistan. The data is categorized under Global Database’s Tajikistan – Table TJ.A003: Gross Domestic Product per Capita. The Аgency on Statistics under the President of the Republic of Tajikistan provides quarterly annualized GDP per Capita, calculated using moving sum of the last four quarters' GDP and total population at the end of the reference period.

Key information about Tajikistan Nominal GDP Growth

• Tajikistan Nominal GDP Growth was reported at 23.985 % in Dec 2024.
• This records an increase from the previous number of 14.709 % for Sep 2024.
• Tajikistan Nominal GDP Growth data is updated quarterly, averaging 24.356 % from Mar 1994 to Dec 2024, with 124 observations.
• The data reached an all-time high of 950.000 % in Mar 1994 and a record low of -17.284 % in Sep 2013.
• Tajikistan Nominal GDP Growth data remains active status in CEIC and is reported by CEIC Data.
• The data is categorized under World Trend Plus’s Global Economic Monitor – Table: Nominal GDP: Y-o-Y Growth: Quarterly.

Graph and download economic data for Federal Surplus or Deficit [-] as Percent of Gross Domestic Product (FYFSGDA188S) from 1929 to 2024 about budget, federal, GDP, and USA.

Key information about Tajikistan Real GDP Growth

• The Gross Domestic Product (GDP) in Tajikistan expanded 8.4 % YoY in Dec 2024, following a growth of 8.4 % in the previous quarter.
• Real GDP Growth YoY data in Tajikistan is updated quarterly, available from Mar 2000 to Dec 2024, with an average rate of 7.3 %.
• The data reached an all-time high of 12.6 % in Sep 2004 and a record low of 2.7 % in Sep 2009.

• In the latest reports, Nominal GDP of Tajikistan reached 2.2 USD bn in Mar 2023.
• Its GDP deflator (implicit price deflator) increased 5.5 % in Mar 2023.
• GDP Per Capita in Tajikistan reached 1,131.2 USD in Dec 2022.
• Its Gross Savings Rate was measured at 37.9 % in Dec 2022.
• For Nominal GDP contributions, Investment accounted for 35.5 % in Dec 2022.
• Public Consumption accounted for 10.1 % in Dec 2022.
• Private Consumption accounted for 87.6 % in Dec 2022.

Dataset covering every recognized political leader in 19 Latin American countries during 1945-2010. It measures yearly outcomes for each president: survival in office, exit via military coup, or exit via legal removal (impeachment or forced resignation). The sample includes 36 presidential interruptions (21 coups and 15 legal removals). Predictors include Per capita GDP, GDP growth, Demonstrations, Radicalism, Military coups in the past 20 years, Military coups in the region in the past 5 years, Size of the president’s party (% in the House), and Support for democracy among elites.

The Gross Domestic Product (GDP) in Philippines expanded 5.40 percent in the first quarter of 2025 over the same quarter of the previous year. This dataset provides - Philippines GDP Annual Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Key information about Tajikistan GDP Per Capita

• Tajikistan Gross Domestic Product (GDP) per Capita reached 1,131.183 USD in Dec 2022, compared with 890.481 USD in Dec 2021.
• Tajikistan GDP Per Capita data is updated yearly, available from Dec 1993 to Dec 2022, with an average number of 572.234 USD.
• The data reached an all-time high of 1,131.183 USD in Dec 2022 and a record low of 99.669 in Dec 1995.
• CEIC converts quarterly annualized GDP per Capita into USD. Agency on Statistics under the President of the Republic of Tajikistan provides GDP per Capita in local currency. The National Bank of Tajikistan average market exchange rate is used for currency conversions. GDP per Capita prior to 2000 is calculated from Nominal GDP and Population.

• In the latest reports, Tajikistan GDP expanded 7.800 % YoY in Sep 2022.
• Tajikistan Nominal GDP reached 3.568 USD bn in Dec 2022.
• Its GDP deflator (implicit price deflator) increased 9.662 % in Sep 2022.
• Gross Savings Rate of Tajikistan was measured at 31.015 % in Dec 2020.

Key information about Tajikistan GDP Deflator Growth

• Tajikistan GDP deflator (implicit price deflator) increased 9.7 % in Sep 2022, compared with an increase of 7.8 % in the previous quarter.
• Tajikistan GDP Deflator Growth data is updated quarterly, available from Mar 2000 to Sep 2022, with an average rate of 11.6 %.
• The data reached an all-time high of 53.4 % in Mar 2001 and a record low of -0.6 % in Mar 2021.

• In the latest reports, Tajikistan GDP expanded 7.8 % YoY in Sep 2022.
• Its Nominal GDP reached 3.6 USD bn in Dec 2022.
• Tajikistan GDP Per Capita reached 1,131.2 USD in Dec 2022.
• Its Gross Savings Rate was measured at 31.0 % in Dec 2020.

Tajikistan Gross Domestic Product (GDP): Year to Date: GVA: Education data was reported at 3,992.950 TJS mn in Dec 2018. This records an increase from the previous number of 2,518.440 TJS mn for Sep 2018. Tajikistan Gross Domestic Product (GDP): Year to Date: GVA: Education data is updated quarterly, averaging 1,076.600 TJS mn from Dec 2010 (Median) to Dec 2018, with 33 observations. The data reached an all-time high of 3,992.950 TJS mn in Dec 2018 and a record low of 198.600 TJS mn in Mar 2011. Tajikistan Gross Domestic Product (GDP): Year to Date: GVA: Education data remains active status in CEIC and is reported by Аgency on Statistics under the President of the Republic of Tajikistan. The data is categorized under Global Database’s Tajikistan – Table TJ.A001: Gross Domestic Product: by Industry.

Key information about Tajikistan Nominal GDP

• Tajikistan Nominal GDP reached 2.2 USD bn in Mar 2023, compared with 3.6 USD bn in the previous quarter.
• Nominal GDP in Tajikistan is updated quarterly, available from Mar 1993 to Mar 2023, with an average number of 887.6 USD mn.
• The data reached an all-time high of 3.6 USD bn in Dec 2022 and a record low of 62.7 USD mn in Mar 1993.

• In the latest reports, Tajikistan GDP expanded 8.2 % YoY in Mar 2023.
• Its GDP deflator (implicit price deflator) increased 5.5 % in Mar 2023.
• Tajikistan GDP Per Capita reached 1,131.2 USD in Dec 2022.
• Its Gross Savings Rate was measured at 31.0 % in Dec 2020.
• For Nominal GDP contributions, Investment accounted for 33.5 % in Dec 2020.
• Public Consumption accounted for 11.6 % in Dec 2020.
• Private Consumption accounted for 77.6 % in Dec 2020.

Iran’s gross domestic product (GDP) inclined by 3.33 percent in 2020 after adjusting for inflation. This figure fell from 13.4 percent growth four years ago, which had been a reaction to sanctions lifting after the Joint Comprehensive Plan of Action (JPCOA) regarding Iran’s nuclear program. United States president Donald Trump ended that country’s participation in the deal, imposing new sanctions.

Political influence on the economy

Political tensions have hampered the economy of Iran, keeping growth low in spite of the country’s considerable oil reserves. The effect of these sanctions becomes obvious when looking at Iran’s oil exports to Europe over the past decade. Some analysts have blamed the new sanctions for the increase in Iran’s inflation rate, as well as the currency depreciation that has accompanied it.

Iran’s options

Although Iran’s main export partners are largely in Asia, many of the transactions are carried out using U.S. dollars. Even though other means of payment are possible, some countries worry about political ramifications of continuing trade relations with Iran. Iran’s greatest strength at the moment may be its low national debt, meaning that it can borrow a substantial amount of money if it can find a willing lender. However, given the instability of the political situation worldwide and regionally, it is difficult to assume that such a borrower exists at the moment.

This dataset looks at the number of Brazilian municipalities where mining is a key economic activity and those where mining is a key job provider. We also listed municipalities that have mining as both a main economic activity and the main employer in a given town. We have also generated maps to visualize the impact of mining in Brazil as a key economic activity and/or job provider. Similarly, we have listed the same information for all the municipalities that received oil royalties in 2019, and the top 100 municipalities whose wealth was mainly generated by agribusiness in 2022. By detailing the economic and employment situation in Brazilian extractive municipalities (mining, oil, and crops), we demonstrate that company towns in Brazil (locations that are highly dependent on one key economic activity for employment generation) are few. Extractive industries may no longer be labour intensive, although economic dependency may follow indirectly, such as because of tax generation. We also offer data on national elections to demonstrate that there is not a clear correlation between economic activity and voting patterns, which may be explained by low employability. The main objective of this dataset is to generate a discussion on the need to redefine company towns in Brazil. Methods The first resource used to collect the data presented here is the Annual List of Social Information – RAIS database – which provides information on employment and companies. RAIS contains social information about each employee of a given firm, such as salary, race, gender, and length of employment. This data must be provided annually by every company based in Brazil. According to the Ministry of Labour and Social Security, every establishment must provide, through the Annual Social Information List (RAIS), information regarding each of its employees, in accordance with Decree No. 10,854, of November 10, 2021. Each line in the RAIS represents a single firm. It contains information such as the number of employees per firm, the address of the firm, and the National Classification of Economic Activities (CNAE 2.0). For the year 2020, the database contains 8,196,730 lines, from all Brazilian companies that delivered information to the annual RAIS. The CNAE is a categorization system that identifies the economic activities carried out by companies in Brazil. Each economic activity is represented by a unique code, which helps with the identification and legal and fiscal framework of companies. Based on the RAIS database, in Table 1 economic activities related to the mineral extraction sector were selected, namely: Section B, codes 05 – Extraction of mineral coal; 07 – Extraction of metallic minerals; 08 – Extraction of non-metallic minerals; and 09 – Activities to support the extraction of minerals. Subsequently, in Table 2 municipalities were selected where one of the aforementioned sectors was the largest employer, measured by the percentage of employees hired in relation to the total number of employees in the municipality. Another database used to compose our dataset was the voting data of the Superior Electoral Court – Tribunal Superior Eleitoral (TSE). It contains information on the total votes per Brazilian municipality in the Brazilian general elections by all candidates who participated in the election: Federal Deputies, Senators of the Republic, State Governors, and President of the Republic. Data from the 2022 general elections, from the second round for President of the Republic, were used. Table 1 presents the municipalities where in 2020 the mining sector had the highest percentage of employment generation in relation to other economic sectors in the municipality. In total, there were 37 such municipalities, distributed across 8 Brazilian states. Then, as mentioned previously, the results were examined alongside TSE voting data. Regarding Table 2, another source of data used was Gross Domestic Product – municipal GDP 2020, published annually by the Brazilian Institute of Geography and Statistics (IBGE). In it, the Institute presents which economic activity contributes most to the municipality’s added value. Therefore, we selected the municipalities where the mining industry produces the highest added value to GDP. Table 2 presents the results: 55 Brazilian municipalities have this characteristic. Municipalities from Tables 1 and 2 have columns presenting TSE voting data. Table 3, in turn, combines Tables 1 and 2. It presents the municipalities in which mineral extraction activity is both the main employer and generates the highest added value to GDP. Maps 1, 2, and 3 plot the locations of the municipalities found in Tables 1, 2, and 3, respectively. Table 4 presents the Brazilian municipalities that received oil royalties in Brazil in 2019. Municipalities entitled to royalties are those that are in some way affected by the oil industry, the information regarding current revenues is consolidated by Secretaria do Tesouro Nacional (National Treasury of Brazil) and oil royalties’ information is provided by the Agencia Nacional do Petroleo (ANP) National Oil Agency. In addition, the voting pattern for the President of the Republic in each municipality that received royalties was also presented. Table 5 presents the 100 top Brazilian municipalities with the highest Agricultural Production Value, according to the IBGE Monthly Agricultural Production survey for the year 2020 as described by the Ministry of Agriculture. TSE voting data was added for each of those municipalities. Usage notes Company towns are usually referred to in the literature as locations highly economically dependent on the production of one company that generates most employment opportunities in a region; this economic activity therefore has major political influence in the area. Our dataset presents municipalities with strong oil, mining, and agribusiness economic presence but that is not always followed by employment generation. From this data, users can see that economic markers such as GDP and employment creation indicate a company town pattern in Brazil where income generation and direct employment are not strongly correlated. Thus, the dominant economic activity in those towns does not determine electoral results.

The module was administered as a post-election interview. The resulting data are provided along with voting, demographic, district and macro variables in a single dataset. CSES Variable List The list of variables is being provided on the CSES Website to help in understanding what content is available from CSES, and to compare the content available in each module. Themes: MICRO-LEVEL DATA: Identification and study administration variables: weighting factors; election type; date of election 1st and 2nd round; study timing (post-election study, pre-election and post-election study, between rounds of majoritarian election); mode of interview; gender of interviewer; date questionnaire administered; primary electoral district of respondent; number of days the interview was conducted after the election; language of questionnaire. Demography: year and month of birth; gender; education; marital status; union membership; union membership of others in household; business association membership, farmers´ association membership; professional association membership; current employment status; main occupation; socio economic status; employment type - public or private; industrial sector; current employment status, occupation, socio economic status, employment type - public or private, and industrial sector of spouse; household income; number of persons in household; number of children in household under the age of 18; number of children in household under the age of 6; attendance at religious services; religiosity; religious denomination; language usually spoken at home; region of residence; race; ethnicity; rural or urban residence; primary electoral district; country of birth; year arrived in current country. Survey variables: perception of public expenditure on health, education, unemployment benefits, defense, old-age pensions, business and industry, police and law enforcement, welfare benefits; perception of improving individual standard of living, state of economy, government's action on income inequality; respondent cast a ballot at the current and the previous election; vote choice (presidential, lower house and upper house elections) at the current and the previous election; respondent cast candidate preference vote at the current and the previous election; difference who is in power and who people vote for; sympathy scale for selected parties and political leaders; assessment of parties on the left-right-scale and/or an alternative scale; self-assessment on a left-right-scale and an optional scale; satisfaction with democracy; party identification; intensity of party identification, institutional and personal contact in the electoral campaigning, in person, by mail, phone, text message, email or social networks, institutional contact by whom; political information questions; expected development of household income in the next twelve month; ownership of residence, business or property or farm or livestock, stocks or bonds, savings; likelihood to find another job within the next twelve month; spouse likelihood to find another job within the next twelve month. DISTRICT-LEVEL DATA: number of seats contested in electoral district; number of candidates; number of party lists; percent vote of different parties; official voter turnout in electoral district. MACRO-LEVEL DATA: election outcomes by parties in current (lower house/upper house) legislative election; percent of seats in lower house received by parties in current lower house/upper house election; percent of seats in upper house received by parties in current lower house/upper house election; percent of votes received by presidential candidate of parties in current elections; electoral turnout; party of the president and the prime minister before and after the election; number of portfolios held by each party in cabinet, prior to and after the most recent election; size of the cabinet after the most recent election; number of parties participating in election; ideological families of parties; left-right position of parties assigned by experts and alternative dimensions; most salient factors in the election; fairness of the election; formal complaints against national level results; election irregularities reported; scheduled and held date of election; irregularities of election date; extent of election violence and post-election violence; geographic concentration of violence; post-election protest; electoral alliances permitted during the election campaign; existing electoral alliances; requirements for joint party lists; possibility of apparentement and types of apparentement agreements; multi-party endorsements on ballot; votes cast; voting procedure; voting rounds; party lists close, open, or flexible; transferable votes; cumulated votes if more than one can be cast; compulsory voting; party threshold; unit for the threshold; freedom house rating; democracy-autocracy polity IV rating; age of the current regime; regime: type of executive; number of months since last lower house and last presidential election; electoral formula for presidential elections; electoral formula in all electoral tiers (majoritarian, proportional or mixed); for lower and upper houses was coded: number of electoral segments; linked electoral segments; dependent formulae in mixed systems; subtypes of mixed electoral systems; district magnitude (number of members elected from each district); number of secondary and tertiary electoral districts; fused vote; size of the lower house; GDP growth (annual percent); GDP per capita; inflation, GDP Deflator (annual percent); Human development index; total population; total unemployment; TI corruption perception index; international migrant stock and net migration rate; general government final consumption expenditure; public spending on education; health expenditure; military expenditure; central government debt; Gini index; internet users per 100 inhabitants; mobile phone subscriptions per 100 inhabitants; fixed telephone lines per 100 inhabitants; daily newspapers; constitutional federal structure; number of legislative chambers; electoral results data available; effective number of electoral and parliamentary parties.

Tajikistan Gross Domestic Product (GDP): Annual: Procurement data was reported at 0.000 TJS mn in 2016. This stayed constant from the previous number of 0.000 TJS mn for 2015. Tajikistan Gross Domestic Product (GDP): Annual: Procurement data is updated yearly, averaging 0.000 TJS mn from Dec 1995 (Median) to 2016, with 21 observations. The data reached an all-time high of 1.400 TJS mn in 1997 and a record low of 0.000 TJS mn in 2016. Tajikistan Gross Domestic Product (GDP): Annual: Procurement data remains active status in CEIC and is reported by Аgency on Statistics under the President of the Republic of Tajikistan. The data is categorized under Global Database’s Tajikistan – Table TJ.A001: Gross Domestic Product: by Industry.