Graph and download economic data for Gross Domestic Product: Implicit Price Deflator (GDPDEF) from Q1 1947 to Q2 2025 about implicit price deflator, headline figure, inflation, GDP, and USA.

Overview with Chart & Report: Canada Gross Domestic Product (GDP) Implicit Price q/q shows changes in the prices for goods and services included in GDP calculation, in one quarter compared to the previous quarter. In contrast to

Consumer Price Index CPI in the United States increased to 324.80 points in September from 323.98 points in August 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.

Nominal GDP is an assessment of economic production in an economy but includes the current prices of goods and services in its calculation. GDP is typically measured as the monetary value of goods and services produced.

**Real gross domestic product **(real GDP for short) is a macroeconomic measure of the value of economic output adjusted for price changes (i.e. inflation or deflation). This adjustment transforms the money-value measure, nominal GDP, into an index for quantity of total output.estions do you want to see answered?

As of the first quarter of 2025, the GDP of the U.S. fell by 0.5 percent from the fourth 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.

Consumer Price Index CPI in India increased to 197.30 points in October from 197 points in September of 2025. This dataset provides - India Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

It is a statistic that measures the comprehensive price level of export and import products. It is used as a deflator for export profitability fluctuations or import cost burden of import and export companies, measurement of terms of trade through mutual comparison of import and export price indexes, and real GDP calculation.

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 a pps manner 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 pps with household size number 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 [f2f]

Abstract

The fourth expenditure and consumption survey (LECS 4) in Lao PDR is a survey in terms of socio-economy at the household echelon. This survey is conducted in every 5 years. The present round of surveys started from 1992 and the main statistical collection unit is the household. This survey is a sample survey which is carried out in every province and district over the whole country. The survey was undertaken from April 2007 to March 2008 (for a period of 12 months), in order to be able to provide data on expenditure and consumption covering all seasons and relating to aspects of every area and region in the Lao PDR.

The purpose of the expenditure and consumption survey (LECS) is to estimate the expenditure and consumption of household as well as production, investment, accumulation and other socio-economic aspects of the households in the formal and informal sector of the economy.

The results of expenditure and consumption survey in Lao PDR will provide necessary data to be used for calculation of various indicators and are intended for socio-economic planning. It will also provide data for calculation of GDP, definition of poverty line, data on nutrition and other important information. The LECS surveys are the most important surveys in the statistical data collection system of Lao PDR.

The main objectives of this survey are: - Estimation at macro level for national accounts, including private consumption, household investment, production and income from agriculture and household business; - Structure of household consumption (weight system) for consumption price index calculation (CPI); - Estimation on labor force; - Nutrition statistic; - Poverty statistics and statistics of income distribution.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Villages/ Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design and Selection

First Step: Description of Sample Village

The survey design for the LECS 4 uses the same methodology and sampling technique as used in the LECS 3. The sample selection is conducted in two steps. The first step is selection of sample villages using the zoom selection methodology according to the proportion of the population (PPS). Village unit is distributed according to the following echelon: village classified by province, district, rural area with access to road and rural area without access to road. The number of sample villages in each province is in between 17 to 48 villages depending on the number of villages, and the number of households in every survey area.

Comparing the last two surveys, LECS 3 and LECS 4, the number of sample villages is decreased from 540 to 518 villages. This is due to the situation of allocation and unification of small villages into larger villages, which in past years has appeared in every province in the whole country. In order to assure normal rule of distribution of sample, the number of sample households has been from 15 to 16 per village.

Each month the number of sample villages is almost the same, because the sample has been selected as zoom for every month.

Second Step: Selection of Sample Household

In the present expenditure and consumption survey half of the number of households are the same as households that were surveyed in the LECS 3, and the other half are new households that previously were not surveyed. The selection of households in the sample uses the zoom methodology on arbitrary and systematic basis. Selection of the 8 sample households from the survey of LECS 3 uses the zoom methodology on arbitrary basis by taking part in a lottery among LECS 3 households. New 8 sample household are selected among the other households in the village using the same methodology. Together the number of sample households in one village is 16. The selection of sample household is based on the number of existing households in the village at the time of the conduction of the survey. If the village has 16 or less households all households are covered by the survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used to collect the 2007-2008 LECS: - Household Questionnaire - Dairy Sheet - Time USe Questionnaire - Village Questionnaire - Price Questionnaire

Cleaning operations

The survey data has been edited and data editing process include: - Structure checking and completeness - Checking and coding

Sampling error estimates

Sampling errors have been calculated for some important variables based on the confidence of 95% ("margin of errors").

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.