Graph and download economic data for Gross Domestic Product: Implicit Price Deflator (GDPDEF) from Q1 1947 to Q1 2025 about implicit price deflator, headline figure, inflation, GDP, and USA.

Consumer Price Index CPI in the United States increased to 321.47 points in May from 320.80 points in April of 2025. This dataset provides the latest reported value for - United States Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus 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.

At **** U.S. dollars, Switzerland has the most expensive Big Macs in the world, according to the January 2025 Big Mac index. Concurrently, the cost of a Big Mac was **** dollars in the U.S., and **** U.S. dollars in the Euro area. What is the Big Mac index? The Big Mac index, published by The Economist, is a novel way of measuring whether the market exchange rates for different countries’ currencies are overvalued or undervalued. It does this by measuring each currency against a common standard – the Big Mac hamburger sold by McDonald’s restaurants all over the world. Twice a year the Economist converts the average national price of a Big Mac into U.S. dollars using the exchange rate at that point in time. As a Big Mac is a completely standardized product across the world, the argument goes that it should have the same relative cost in every country. Differences in the cost of a Big Mac expressed as U.S. dollars therefore reflect differences in the purchasing power of each currency. Is the Big Mac index a good measure of purchasing power parity? Purchasing power parity (PPP) is the idea that items should cost the same in different countries, based on the exchange rate at that time. This relationship does not hold in practice. Factors like tax rates, wage regulations, whether components need to be imported, and the level of market competition all contribute to price variations between countries. The Big Mac index does measure this basic point – that one U.S. dollar can buy more in some countries than others. There are more accurate ways to measure differences in PPP though, which convert a larger range of products into their dollar price. Adjusting for PPP can have a massive effect on how we understand a country’s economy. The country with the largest GDP adjusted for PPP is China, but when looking at the unadjusted GDP of different countries, the U.S. has the largest economy.

In 2024, the U.S. GDP increased from the previous year to about 29.18 trillion U.S. dollars. Gross domestic product (GDP) refers to the market value of all goods and services produced within a country. In 2024, the United States has the largest economy in the world. What is GDP? Gross domestic product is one of the most important indicators used to analyze the health of an economy. GDP is defined by the BEA as the market value of goods and services produced by labor and property in the United States, regardless of nationality. It is the primary measure of U.S. production. The OECD defines GDP as an aggregate measure of production equal to the sum of the gross values added of all resident, institutional units engaged in production (plus any taxes, and minus any subsidies, on products not included in the value of their outputs). GDP and national debt Although the United States had the highest Gross Domestic Product (GDP) in the world in 2022, this does not tell us much about the quality of life in any given country. GDP per capita at purchasing power parity (PPP) is an economic measurement that is thought to be a better method for comparing living standards across countries because it accounts for domestic inflation and variations in the cost of living. While the United States might have the largest economy, the country that ranked highest in terms of GDP at PPP was Luxembourg, amounting to around 141,333 international dollars per capita. Singapore, Ireland, and Qatar also ranked highly on the GDP PPP list, and the United States ranked 9th in 2022.

Quarterly estimates of productivity in the total economy and in the industries are derived from a Fisher chained index of gross domestic product (GDP). The approach to measure the GDP in the total economy differs from the one that used in the estimates by industry. For the total economy, GDP is measured using the expenditure approach at market prices published by the Quarterly Income and Expenditure Accounts. For the estimates by industry, GDP is measured using the value added approach at basic prices published by the Industry Accounts Division. This was the Fisher chained index in the case of years for which final input-output tables are available. For the most current years or annual post-benchmarks, the real GDP is based on a fixed-weight Laspeyres chained index formula. GDP estimates in the productivity measures for the businesses producing services and for real estate, and rental and leasing exclude the rental value of owner occupied dwellings. The estimate of the total number of jobs covers four main categories: employee jobs, work owner of an unincorporated business, own account self-employment, and unpaid family jobs. The last category is found mainly in sectors where family firms are important (agriculture and retail trade, in particular). Jobs data are consistent with the System of National Accounts. This is the quarterly average of hours worked for jobs in all categories. The number of hours worked in all jobs is the quarterly average for all jobs times the annual average hours worked in all jobs. Hours worked data are consistent with the System of National Accounts. According to the retained definition, hours worked means the total number of hours that a person spends working, whether paid or not. In general, this includes regular and overtime hours, breaks, travel time, training in the workplace and time lost in brief work stoppages where workers remain at their posts. On the other hand, time lost due to strikes, lockouts, annual vacation, public holidays, sick leave, maternity leave or leave for personal needs are not included in total hours worked. Labour productivity is the ratio between real GDP and hours worked. For the estimates of productivity in the total economy, a Fisher chain index of GDP at market prices is used as measure of the output. On the other hand, in the quarterly productivity estimates for the industries, a Fisher chain index of GDP at basic prices for each industry is used as measure of the output up to the last year benchmark for which final input-output tables are available, after that by a fixed-weight volume Laspeyres chained index formula for the most recent years. The ratio between total compensation for all jobs, and the number of hours worked. The term hourly compensation" is often used to refer to the total compensation per hour worked." This measures the cost of labour input required to produce one unit of output, and equals labour compensation in current dollars divided by the real output. It is often calculated as the ratio of labour compensation per hour worked and labour productivity. Unit labour cost increases when labour compensation per hour worked increases more rapidly than labour productivity. It is widely used to measure inflation pressures arising from wage growth. The measure of real value added used in the labour unit cost estimation is based on a Fisher chain index excluding the rental value of owner occupied dwellings. The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply side or production oriented principles, to ensure that industrial data, classified to NAICS, is suitable for the analysis of production related issues such as industrial performance. Since 1997, the System of National Accounts' (SNA) input-output industry classification system is based on NAICS. In the National Accounts industries, the levels of the different classification systems were chosen so as to provide the most detail possible in order to maximise continuity with the previous classification systems used in Statistics Canada since 1961. Therefore, the greatest level of detail that is available over time occurs at the L level of aggregation, which corresponds, to 105 industries. This L level can also be aggregated to the M level (medium - 56 industries) and to the S level (small - 21 industries). This combines the business establishments of the North American Industry Classification System (NAICS) codes 11, 21, 22, 23, 31-33. This combines the business establishments of the North American Industry Classification System (NAICS) codes 41, 44-45, 48-49, 51, 52, 53, 54, 55, 56, 61, 62, 71, 72, 81. The Gross Domestic Product (GDP) used to measure productivity excludes rent value for owner occupied dwellings from the business service producing industries. This combines the business establishments of the North American Industry Classification System (NAICS) code 53. The gross domestic product (GDP) used to measure productivity excludes rent value for owner occupied dwellings from this industry code. This combines the business establishments of the North American Industry Classification System (NAICS) codes 61, 62, 81. This combines the part of non-business establishments of the North American Industry Classification System (NAICS) codes 11-91, but also including the owner occupied dwellings industry and the private households. Total economic activities that have been realized within the country. That covers both business and non-business sectors. Unit labour cost in United States dollars is the equivalent of the ratio of Canadian unit labour cost to the exchange rate. This latter corresponds to the United States dollar value expressed in Canadian dollars. This combines the business establishments of the North American Industry Classification System (NAICS) codes 52 and 55.

Consumer Price Index CPI in India increased to 194.20 points in June from 193 points in May of 2025. This dataset provides - India Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The CCI is intended for use in the survey of living conditions of households, calculation of the consumer price index, calculation of final consumption expenditures of the institutional household sector in accordance with the methodology of the system of national accounts (SNA), in particular international comparisons of gross domestic product (GDP) by categories of costs. The CCI provides a comparison of national statistics, in particular data on the final consumption expenditures of the household sector, with relevant data from the European Union countries and statistical services of other countries. Order of the State Statistics Committee dated December 29, 2007 Ü 480.

United States GDP: VA: 2009p: Not Allocated by Industry data was reported at 164.900 USD bn in 2017. This records an increase from the previous number of 157.000 USD bn for 2016. United States GDP: VA: 2009p: Not Allocated by Industry data is updated yearly, averaging -85.400 USD bn from Dec 1997 (Median) to 2017, with 21 observations. The data reached an all-time high of 164.900 USD bn in 2017 and a record low of -616.500 USD bn in 1997. United States GDP: VA: 2009p: Not Allocated by Industry data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s United States – Table US.A143: NIPA 2013: GDP by Industry: Value Added: Chain Linked 2009 Price: Annual. Chained (2009) dollar series are calculated as the product of the chain-type quantity index and the 2009 current-dollar value of the corresponding series, divided by 100. Because the formula for the chain-type quantity indexes uses weights of more than one period, the corresponding chained-dollar estimates are usually not additive. The value of the 'Not allocated by industry' line reflects the difference between the first line and the sum of the most detailed lines, as well as the differences in source data used to estimate GDP by industry and the expenditures measure of real GDP.

Indicator: 8.1.1The annual growth rate of real GDP per capita.The equation used to calculate the results is:The annual growth rate of real Gross Domestic Product (GDP) per capita is calculated as follows:a. Convert annual real GDP in domestic currency at 2010 prices for a country or area to US dollars at 2010 prices using the 2010 exchange rates.b. Divide the result by the population of the country or area to obtain annual real GDP per capita in constant US dollars at 2010 prices.c. Calculate the annual growth rate of real GDP per capita in year t+1 using the following formula: [(G(t+1) – G(t))/G(t)] x 100, where G(t+1) is real GDP per capita in 2010 US dollars in year t+1 and G(t) is real GDP per capita in 2010 US dollars in year t.Note : GDP Constant (2010 = 100)*Data Source:Planning & Statistics Authority, National Accounts Bulletin

United States GDP: VA: 2009p: saar: Not Allocated by Industry data was reported at 244.500 USD bn in Mar 2018. This records an increase from the previous number of 238.500 USD bn for Dec 2017. United States GDP: VA: 2009p: saar: Not Allocated by Industry data is updated quarterly, averaging 70.900 USD bn from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 244.500 USD bn in Mar 2018 and a record low of -120.500 USD bn in Jun 2005. United States GDP: VA: 2009p: saar: Not Allocated by Industry data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A186: NIPA 2013: GDP by Industry: Value Added: Chain Linked 2009 Price: saar. Chained (2009) dollar series are calculated as the product of the chain-type quantity index and the 2009 current-dollar value of the corresponding series, divided by 100. Because the formula for the chain-type quantity indexes uses weights of more than one period, the corresponding chained-dollar estimates are usually not additive. The value of the 'Not allocated by industry' line reflects the difference between the first line and the sum of the most detailed lines, as well as the differences in source data used to estimate GDP by industry and the expenditures measure of real GDP.

Consumer Price Index CPI in Pakistan increased to 264.22 points in June from 263.60 points in May of 2025. This dataset provides - Pakistan Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

Susenas (National Socio-economic Survey) was held for the first time in year 1963. In the last two decades, up to year 2010, Susenas was conducted every year. Susenas was designed to have 3 modules (Module of Household Consumption/Expenditure, Module of Education and Socio-culture, and also Module of Health and Housing) and each module should be conducted every 3 years. Household Consumption/ Expenditure Module of Susenas shall be conducted in year 2011 .

To improve the accuracy of data result and in line with the increased frequency of household consumption/expenditure data request for quarterly GDP/GRDP and poverty calculation, data collection of household consumption/expenditure, it is planned that starting in 2011 it should be held quarterly. Each year, collecting data shall be conducted in March, June, September, and December.

In accordance with the 5-year cycle, in year 2012, BPS (Central Statistical Agency) shall have planned Survei Biaya Hidup-SBH (Cost of Living Survey) with the aim to generate a commodity package and a weigh diagram in the calculation of Consumer Price Index (CPI). Data of food and non-food consumption expenditures as well as household characteristics collected in SBH and Susenas has the same concept/definition, but different implementation time. In order to be more efficient in the utilization of resources of the two surveys and to have a better quality of results achieved, in year 2011 a trial of Susenas and SBH integration shall be conducted in 7 cities (Medan, Sampit, Denpasar, Kudus, Bulukumba, Tual, and South Jakarta).

Poverty data, CPI/Inflation data, GDP/GRDP are BPS strategic data that have to be released on time. Therefore, planning, field preparation, processing, and presentation of data Susenas 2011 activities and trial of integrating Susenas and SBH must be in accordance with the set schedule.

Activities of Susenas 2011 preparation shall be conducted in year 2010, covering activities of workshop/training of chief instructor with the aim to synchronize the perception toward the concept/definition as well as procedure and protocol of survey implementation. National instructor training will also be conducted in year 2010.

Geographic coverage

National coverage, representative to the district level

Analysis unit

Household Members (Individual) and Household

Universe

Susenas 2011 cover 300,000 household sample spread all over Indonesia where each quarter distribute about 75,000 household sample (including 500 households additional sample for Survey in Maluku Province). The result from each quarter can produce national and provincial level estimates. Meanwhile from the cummulative four quarter, the data can be presented until the district/municipality level.

Kind of data

Sample survey data [ssd]

Sampling procedure

From the master sampling frame (Nh enumeration areas) were retractable sample enumeration areas in a probability proportional to size (pps) method, nh acquired 30,000 enumeration areas. Then divided into 4 quarters so that each quarter 7,500 enumeration areas. The next stage selected one census block (BS) in a probability proportional to size (pps) method, whereas size is the number of households from SP 2010 RBL1. The last stage, of each BS Susenas been selected for a number of common household (m = 10) based on the results of systematic updating of listing of households using SP 2010 C1 VSEN2011 List - P. Then do the enumeration of 75,000 households.

Mode of data collection

Face-to-face

Key information about Singapore GDP Per Capita

• Singapore Gross Domestic Product (GDP) per Capita reached 90,689.000 USD in Dec 2024, compared with 85,392.000 USD in Dec 2023.
• Singapore GDP Per Capita data is updated yearly, available from Dec 1960 to Dec 2024, with an average number of 16,136.000 USD.
• The data reached an all-time high of 90,689.000 USD in Dec 2024 and a record low of 428.000 in Dec 1960.
• Mid-Year Population is used in the calculation of GDP per Capita.

• In the latest reports, Singapore GDP expanded 0.400 % YoY in Mar 2023.
• Singapore Nominal GDP reached 120.607 USD bn in Mar 2023.
• Its GDP deflator (implicit price deflator) fell 0.011 % in Mar 2023.
• Gross Savings Rate of Singapore was measured at 47.456 % in Dec 2024.

The model estimated in this document uses a set of variables that are available for a wide range of countries with different levels of development, resulting in a sample of 91 countries for the period 1970-2010. The file titled “Database PLS-PM” contains the data with which is possible to estimate the human capital index (ich) calculated in the paper. The variables used and their notation is as follows: FR= Fertility Rates VAAS = value-added contributed by the agricultural sector to GDP GNI = Gross National Incomes per capita LE = Life Expectancy MR = Mortality rate for children under five years AYE = Average Years of Education SPR = Student-Professor Ratio EC = Energy Consumption per capita PP = patent applications by residents per capita Given the database is not complete for all countries or for all years, this missing data was complete through interpolation method. All variables were transformed by mean of logarithms, except GNI. In the case of EC and PP, block of returns on human capital, the manifest variables are transformed such that they may be retrieved in levels at a later stage. 2. Data to estimate the economic growth regressions Cross-section: The file titled “Database – Cross-Section” contains the data with which it is possible to estimate the results shown in tables 1-5 of the manuscript. The variables used and their notation is the following: grow = GDP per capita, rate of change log(gdp75) = lag of GDP in 1975, logarithm demo = a binary variable measuring the level of democracy in the countries contes = indicators by principal component analysis to approximate the degree of contestation inclu = indicators by principal component analysis to approximate the degree of inclusiveness lnihc = human capital index estimated through PLS-PM, logarithm lnaye = average years of education developed by Barro and Lee (2013), logarithm lninves = investment in physical capital, measured as the average share of investment real to GDP, logarithm lngov = average government consumption as a percentage of GDP, logarithm lninfla = inflation measured by consumer prices, logarithm lnpop = population growth rate, logarithm lnich70, lnich75, lnape70, lnape75 lninves70 lninves75 lnpop70 lnpop75 = lags of lnich, lnaye, lninves and lnpop dafri = dummy for African countries Panel data: The file titled “Database – Panel data” contains the data with which it is possible to estimate the results shown in tables 6-9 of the manuscript. All variables are averages for the underlying period. The variables used and their notation is the following: grow = GDP per capita, rate of change lngdp75 = initial GDP in 1975, logarithm demo = a binary variable measuring the level of democracy in the countries contes = indicators by principal component analysis to approximate the degree of contestation inclu = indicators by principal component analysis to approximate the degree of inclusiveness lnihc = human capital index estimated through PLS-PM, logarithm lnaye = average years of education developed by Barro and Lee (2013), logarithm lninves = investment in physical capital, measured as the average share of investment real to GDP, logarithm lngov = average government consumption as a percentage of GDP, logarithm lninfla = inflation measured by consumer prices, logarithm lnpop = population growth rate, logarithm dafri = dummy for African countries

puerto rico - Price Level of GDP, G-K method for Puerto Rico was -3.50000 U.S.=100 in February of 2025, according to the United States Federal Reserve. Historically, puerto rico - Price Level of GDP, G-K method for Puerto Rico reached a record high of 53.10000 in December of 1992 and a record low of -55.60000 in January of 1994. Trading Economics provides the current actual value, an historical data chart and related indicators for puerto rico - Price Level of GDP, G-K method for Puerto Rico - last updated from the United States Federal Reserve on June of 2025.

The graph shows per capita gross domestic product (GDP) in China until 2024, with forecasts until 2030. In 2024, per capita GDP reached around 13,300 U.S. dollars in China. That year, the overall GDP of China had amounted to 18.7 trillion U.S. dollars. Per capita GDP in China Gross domestic product is a commonly-used economic indicator for measuring the state of a country's economy. GDP is the total market value of goods and services produced in a country within a given period of time, usually a year. Per capita GDP is defined as the GDP divided by the total number of people in the country. This indicator is generally used to compare the economic prosperity of countries with varying population sizes.In 2010, China overtook Japan and became the world’s second-largest economy. As of 2024, it was the largest exporter and the second largest importer in the world. However, one reason behind its economic strength lies within its population size. China has to distribute its wealth among 1.4 billion people. By 2023, China's per capita GDP was only about one fourth as large as that of main industrialized countries. When compared to other emerging markets, China ranked second among BRIC countries in terms of GDP per capita. Future development According to projections by the IMF, per capita GDP in China will escalate from around 13,300 U.S. dollars in 2024 to 18,600 U.S. dollars in 2030. Major reasons for this are comparatively high economic growth rates combined with negative population growth. China's economic structure is also undergoing changes. A major trend lies in the shift from an industry-based to a service-based economy.

India’s share of global gross domestic product (GDP) rose to 8.25 percent in 2024 when adjusted for purchasing power parity (PPP) and was projected to increase to 10 percent by 2030. This reflects the growth of India’s economy, which is helped in this ranking by the low purchasing power of the rupee. The Indian economy A significant portion of India’s economic growth comes from a shift in the workforce from the agricultural sector to the more-productive service sector. This labor force shift is particularly significant in India because of the country’s staggering population figures. As such, changes in the Indian economy have an impact on a significant portion of the world population. What does PPP mean? The Economist magazine uses the Big Mac Index to illustrate purchasing power. Since the product should be the same in every country that has a McDonalds, the Big Mac’s price should reflect the purchasing power of each local currency. For the calculation in this statistic, economists took the prices of several standard goods (though not the Big Mac) and put them at the same level based on their prices in the local currency. Thus, the power of these currencies to purchase was put on par across countries, giving purchasing power parity. As such, this statistic can be interpreted as the relative size of the Indian economy if the whole world used the Indian rupee price levels.