Jan 11, 2013 - Eurostat-OECD Methodological Manual on Purchasing Power. Breakdown of its expenditure estimate of GDP for the reference year.
What is Gross Domestic Product (GDP)? Gross Domestic Product (GDP) is the monetary value, in local currency, of all final economic goods and services produced within a country during a specific period of time. It is the broadest financial measurement of a nation’s total economic activity. The total goods and services bought by consumers encompasses all private Expenditure An expenditure represents a payment (either cash or credit) to purchase goods or services. An expenditure is recorded in a single point in time (the time of purchase), compared to an expense which is allocated or accrued over a period of time. This guide will review the different types of expenditures in accounting, government spending, investments, and exports but excludes imports that take place within a designated country.
Below are three different approaches to the GDP formula. What is the GDP formula? There are three methods or formulas by which GDP can be determined: #1 Expenditure Approach The most commonly used GDP formula, which is based on the money spent by various groups that participate in the economy. GDP = C + G + I + NX C = consumption or all private consumer spending within a country’s economy, including, durable goods (items expected to last more than three years), non-durable goods (food & clothing), and services. G = total government expenditures, including, salaries of government employees, road construction/repair, public schools, and military machines.
I = sum of a country’s investments spent on capital equipment, inventories, and housing. NX = net exports or a country’s total exports less total imports. #2 Income Approach This GDP formula takes the total income generated by the goods and services produced. GDP = Total National Income + Sales Taxes + Depreciation + Net Foreign Factor Income Total National Income – the sum of all wages, rent, interest, and Net Profit Margin Net profit margin is a formula used to calculate the percentage of profit a company produces from its total revenue. The profit margin ratio of each company differs by industry. Profit margin = Net income ⁄ Total revenue x 100. Net income is calculated by deducting all company expenses from its total revenue which is.
Sales Taxes – consumer tax imposed by the government on the sales of goods and services. Depreciation – cost allocated to a tangible asset over its useful life. Net Foreign Factor Income – the difference between the total amount that a country’s citizens and companies earn abroad, as well as the total amount foreign citizens and companies earn in that country. #3 Production or Value-Added Approach The sum of the value added to a product during the production process. To determine the value added between businesses, the price at which the product is sold by the seller is deducted from the price it was bought for from the supplier. What are the Types of GDP?
GPD can be measured in several different ways. The most common methods include:. Nominal GDP – the total value of all goods and services produced at current market prices.
This includes all the changes in market prices during the current year due to inflation or deflation. Real GDP – the sum of all goods and services produced at constant prices. The prices used in determining the Gross Domestic Product are based on a certain base year or the previous year. This provides a more accurate account of economic growth, as it is already an inflation-adjusted measurement, meaning the effects of inflation are taken out. Actual GDP – real-time measurement of all outputs at any interval or any given time.
It demonstrates the existing state of business of the economy. Potential GDP – ideal economic condition with 100% employment across all sectors, steady currency, and stable product prices. Why is GDP Important to Economists and Investors?
Gross Domestic Product represents the economic production and growth of a nation and is one of the primary indicators used to determine the overall well-being of a country’s Economics The GDP Formula consists of consumption, government spending, investments, and net exports. We break down the GDP formula into steps in this guide. Gross Domestic Product is the monetary value, in local currency, of all final economic goods and services produced within a country during a specific period of time and standard of living. One way to determine how well a country’s economy is flourishing is by its GDP growth rate.
This rate reflects the increase or decrease in the percentage of economic output in monthly, quarterly, or yearly periods. Gross Domestic Product enables economic policymakers to assess whether the economy is weakening or progressing if it needs improvements or restrictions, and if threats of recession or inflation are imminent. From these assessments, government implementing agencies can determine if expansionary, monetary policies are needed to address economic issues. Investors place important on GDP growth rates to decide how the economy is changing so that they can make adjustments to their asset allocation. However, when there is an economic slump, businesses experience low profits, which means lower stock prices and consumers tend to cut spending. Investors are also on the lookout for potential investments, locally and abroad, basing their judgment on countries’ growth rate comparisons.
What are Some Drawbacks of GDP? Gross Domestic Product does not reflect the underground economy, which may be significant in certain countries. The black market or underground economy includes illegal economic activities, such as the sale of drugs, prostitution, and some lawful transactions that don’t comply with tax obligations. In these cases, GDP is not an accurate measure of some components that play a large roll in the economic state of a country. Income earned in a country by an overseas company that is remitted back to foreign investors is not taken into account.
This overstates a country’s economic output. Sources of GDP Information For US GDP information, the Bureau of Economic Analysis in the U.S. Department of Commerce is the best direct source. You can view the bureau’s latest releases here: Additional resources We hope this has been a helpful guide to the GDP formula. CFI is the official provider of the global FMVA™ Certification The Financial Modeling & Valueation Analyst (FMVA)™ accreditation is a global standard for financial analysts that covers finance, accounting, financial modeling, valuation, budgeting, forecasting, presentations, and strategy. Certification program, designed to help anyone become a world-class financial analyst.
To keep learning about important economic concepts, see the additional free resources below:. Consumer Surplus Formula Consumer surplus is an economic calculation to measure the benefit (i.e. Surplus) of what consumers are willing to pay for a good or service versus its market price.
The consumer surplus formula is based on an economic theory of marginal utility. The theory explains that spending behavior varies with the preferences.
Inelastic Demand Inelastic demand exists when the consumer’s demand does not change as much as the price. Inelastic demand often affects commodities and staple goods. Economics Interview Questions The most common economics interview questions. For anyone with an interview for an analyst position in at a bank or other institution, this is a guide.
Free Financial Modeling Guide This financial modeling guide covers Excel tips and best practices on assumptions, drivers, forecasting, linking the three statements, DCF analysis, Excel modeling and much more. Designed to be the best free modeling guide for analysts by using examples and step by step instructions. Investment banking, FP&A, research.
22 December 2017 Latest information on using Value Added Tax (VAT) turnover data in the GDP (O) estimates for the first time – 22 December 2017 The published on 22 December 2017 uses Value Added Tax (VAT) turnover data to estimate parts of the output approach to gross domestic product (GDP(O)) for the first time. The use of the VAT turnover dataset is one of the first steps towards transforming the way that we use large externally-collected administrative data to supplement data collected via Office for National Statistics (ONS) surveys.
Following an internal review of our methodology and consultation with stakeholders, academic associates and international experts, we have agreed to combine output estimates from both the Monthly Business Survey (MBS) and the newly-developed VAT turnover dataset. The December 2017 release uses VAT turnover for small- and medium-sized businesses for selected industries covered by the monthly business surveys.
Details of the industries being used can be found in. VAT turnover has only been used to estimate growth rates, with the overall level of output still derived from the Annual Business Survey and other annual benchmark sources.
This change will increase the quality of GDP estimates, the revision to GDP growth as a result of this change is small and further information on the use of VAT turnover, and its impact, can be found in the article. We will update this Quality and Methodology Information (QMI) report fully to reflect the use of VAT turnover in GDP estimates in early 2018. Overview of the output Gross Domestic Product measures total national economic activity and can be measured in 3 different ways: the output approach, the expenditure approach and the income approach. GDP estimates are produced quarterly and annually. There are 3 publication stages for the quarterly estimates: the Preliminary Estimate, the Second Estimate of GDP, and the UK Quarterly National Accounts.
The UK national accounts provide the basis for analysing the economic performance of the country and are used throughout business and research communities, education, media and the general public. The accounts are major inputs to and decisions on fiscal and monetary policy and the forecasts produced by the. Further information on GDP and the 3 approaches can be found in the and. Output quality This document provides a range of information that describes the quality of the data and details any points that should be noted when using the output. We have developed; these are based upon the 5 European Statistical System (ESS) quality dimensions. This document addresses these quality dimensions and other important quality characteristics, which are:.
relevance. timeliness and punctuality. coherence and comparability. accuracy. output quality trade-offs. assessment of user needs and perceptions. accessibility and clarity More information is provided about these quality dimensions in the following sections.
About the output Relevance (The degree to which statistical outputs meet users’ needs.) The UK National Accounts are compiled in accordance with the European System of Accounts 2010 , under EU law. ESA 2010 is itself consistent with the standards set out in the United Nations System of National Accounts 2008. Significantly, (GNI), partially derived from the GDP estimates, determines the UK’s contribution to the EU budget. The national accounts cover the UK as a whole, with 3 estimates of GDP published each quarter. In the first month after the end of the reference quarter, the, based on output, is published. In the second month, these estimates are updated within the release as more detail is available.
In the third month, the are published, which includes a full national accounts dataset. These estimates are again updated in the, where a fully balanced dataset is published. Further detail on the balancing process is provided in the section ‘How the output is created’. Regional components of the national estimates are available. These are model-based, or derived from surveys that do not give sufficient sample sizes at smaller areas for reliable estimates to be derived.
We publish an annual statistical bulletin presenting (GVA) estimates for English regions, Scotland, Wales and Northern Ireland which include component totals and industry group totals. Data for GDP estimates are sourced from survey and administrative sources, which are used in the compilation of individual components of GDP. For information on how we have engaged with users of GDP data, please refer to the ‘Assessment of user needs and perceptions’ section, which is located under the ‘Other information’ heading. Timeliness and punctuality (Timeliness refers to the lapse of time between publication and the period to which the data refer.
Punctuality refers to the gap between planned and actual publication dates.) GDP estimates are produced on both quarterly and annual bases. Quarterly of GDP are published around 25 days after the end of the reference period. The consistent dataset is published either in June or September, 6 or 9 months after the reference period. The page on the (IMF) website provides more information on periodicity and timeliness of estimates.
To date, the have always met the pre-announced publication dates. For more details on related releases, the is available online and provides 12 months’ advance notice of release dates. In the unlikely event of a change to the pre-announced release schedule, public attention will be drawn to the change and the reasons for the change will be explained fully at the same time, as set out in the. Production stages The main stages of the GDP production process are outlined below.
M1 This is based on information on output (production) only and is published around 25 days after the end of the quarter. This preliminary estimate is based on 44% “actual” data. The rest is based on projections using a variety of modelling techniques. Data are defined as “actual” when they are based on sufficient survey response to produce robust estimates. The percentage of “actual” data is calculated by weighting the data content of each component according to its gross value added (GVA) weight.
The data content of the preliminary estimate varies by industry. M2 The second estimate is published around 7 and a half weeks after the end of the quarter. In this release, we improve on the preliminary estimate by including more complete output data, as well as providing early information on GDP measured by the expenditure and income approaches. At this point the output approach to GDP is based upon 80% of “actual” data and for the income and expenditure approaches around 50 to 60% of data content is available.
The output approach is thought to be the best indicator of growth in the short term. However, at this point, any conflicting information from the expenditure or income sides would be used to inform the average estimate of GDP. M3 The third estimate is published 90 days after the end of the quarter. In this release we produce a full set of quarterly economic accounts, updating and expanding the information made available in the earlier estimate as well as updating estimates for earlier quarters in the current year and normally the previous year. Fuller survey data for components of each of the expenditure, output and income approaches are available. At this point the output approach to GDP is based upon 91% of “actual” data. There is also around 90% data content available to produce estimates of GDP from the expenditure approach and around 70% data content from the income approach.
The output approach is still taken to be the best estimate of short-term growth, although again, the other approaches are used to inform the average measure of GDP, as well as to construct the sector and financial accounts. Annual Annual estimates are published in the, usually in July or October. Blue Book is an annual estimate; however, we must emphasise that it is not the first annual estimate, and more so a process that is used for annual reconciliation. The quarterly data are updated again during the production of the first and second estimates of annual GDP, as data from new and more comprehensive annual data sources become available. The second time an annual estimate is published in the, supply and use balancing is applied to the estimate for the first time.
The supply and use balancing is re-run in subsequent Blue Books using further benchmark data. UK Quarterly National Accounts will contain data consistent with the coinciding Blue Book in either June or September. Methodological improvements may also be made during the publication of the; describes the changes introduced at Blue Book 2016. Balancing process The 3 measures become coherent in the long term through the use of a. This enables differences between the estimates of supply and use of specific products to be investigated, and the accounts adjusted to ensure a balance. We publish information on the methods for.
In the short run, there are not enough data available to produce a full supply and use balancing table. The first step in increasing the coherence of the raw data received is adjustment for quality by national accounts experts following comprehensive analysis and investigation of possible incoherencies. Estimates of quarterly growth from the expenditure and income sides are brought into line with the estimate measured from the output side using an alignment adjustment. The output approach is taken to be the best estimate of growth in the short term. The alignment adjustment is applied to the component of the accounts that is conceptually the most difficult to measure and which has the suspected lowest accuracy on a quarterly basis. It is applied to the series “changes in inventories” (on the expenditure side) and ”gross operating surplus of private non-financial corporations” (on the income side). The size of these alignment adjustments is one measure of coherence of the accounts, and is published in the and the.
These alignment adjustments sum to zero annually as output is not thought to be the best estimate of annual growth because unlike expenditure and income, output does not feed into the supply and use framework which is used to balance GDP. Further to the alignment adjustments, a statistical discrepancy remains between the 3 approaches until supply and use balancing is run and this is also published.
This is the difference between the sum of the expenditure components and average GDP and is published likewise for income components. These are detailed in Table M of the and. The residual error is the amount by which the expenditure-based approach to measuring GDP exceeds the income-based estimate. It is also the sum of the statistical discrepancy (expenditure) with sign reversed and the statistical discrepancy (income) with natural sign (Table L of the statistical bulletin). Although a limited audience have access to GDP data ahead of publication, those involved in the process are selected to ensure each GDP balance achieves a rigorous statistical and economic challenge.
A “balancing meeting” is held during each production round, where presentations assess GDP and its components against a range of external indicators and a focus on GDP headline components. The data is challenged to ensure consistency and plausibility of the GDP balance. We recognise the importance of transparency and have recently introduced an additional section in our where the balancing adjustments applied – size and the components targeted – are now published.
Deflation Nominal GDP (GDP in current prices) gives the value of GDP at a specific point in time. Growth in nominal GDP reflects the effects of inflation, as well as real GDP growth; it reflects changes in value terms. Real GDP (GDP chained volume measures) excludes any inflationary issues and reflects the changes in volume terms. Using chained volume measures makes use of more up-to-date weights and is therefore more relevant. We have published an article which shows.
Seasonal adjustment The headline estimates of quarterly GDP are seasonally adjusted (non-seasonally adjusted versions are available in the ). Seasonal adjustment is the process of removing the variations associated with the time of year, or the arrangement of the calendar, from a time series. GDP estimates, as for many time series, are difficult to analyse using raw data because seasonal effects dominate short-term movements. Identifying and removing the seasonal component leaves the trend and irregular components. Further information We have produced, which gives further information on the content of the national accounts covering uses, principles and compilation. Validation and quality assurance Accuracy (The degree of closeness between an estimate and the true value.) Some common pitfalls in interpreting series are:.
expectations of accuracy and reliability in early estimates are often too high. early estimates are based on incomplete data. revisions are an inevitable consequence of the trade-off between timeliness and accuracy Very few statistical revisions arise as a result of “errors” in the popular sense of the word. All estimates, by definition, are subject to statistical “error”.
Gdp Reference Manual Pdf
In this context the word refers to the uncertainty inherent in any process or calculation that uses sampling, estimation or modelling. Most revisions reflect either the adoption of new statistical techniques or the incorporation of new information which allows the statistical error of previous estimates to be reduced. Only rarely are there avoidable “errors” such as human or system failures and such mistakes are made quite clear when they do occur.
Unlike many short-term indicators that we publish, there is no simple way of measuring the accuracy of GDP. All estimates, by definition, are subject to statistical uncertainty and for many well-established statistics we measure and publish the sampling error and non-sampling error associated with the estimate, using this as an indicator of accuracy. Since sampling is typically done to determine the characteristics of a whole population, the difference between the sample and population values is considered a sampling error. Non-sampling errors are a result of deviations from the true value that are not a function of the sample chosen, including various systematic errors and any other errors that are not due to sampling.
The estimate of GDP, however, is currently constructed from a wide variety of data sources, some of which are not based on random samples or do not have published sampling and non-sampling errors available. As such it is very difficult to measure both error aspects and their impact on GDP. While development work continues in this area, like all other G7 national statistical institutes, we don't publish a measure of the sampling error or non-sampling error associated with GDP. One dimension of measuring accuracy is reliability, which is measured using evidence from analyses of revisions to assess the closeness of early estimates to subsequently estimated values.
Many users try to minimise the impact of uncertainty by using the historical experience of revisions as a basis for estimating how confident they are in early releases and predicting how far and in what direction the early release might be revised. The estimate is subject to revisions as more data become available, but between the preliminary and third estimates of GDP, revisions are typically small (around 0.1 to 0.2 percentage points), with the frequency of upward and downward revisions broadly equal. Many different approaches can be used to summarise revisions; this paper analyses the mean average revision and the mean absolute revision for GDP estimates over data publication iterations. In addition to this analysis, Section 11 of the updates the metrics used to test revisions performance in order to answer the question “Is GDP biased?”.
Revisions are an inevitable consequence of the trade-off between timeliness and accuracy. It is our role to produce the best possible estimate of GDP using all of the available information at that time. Therefore the only way to avoid subsequent revisions to GDP as more information becomes available would be to either delay publication until all the relevant information has been received, which could be up to 3 years after the reference period, or to publish a first estimate and then ignore any subsequent new data and any methodological improvements. So revisions should be treated as generally a good thing, as long as we document the reasons for them and communicate this to users. The balance between necessary revisions and revisions for minor issues is achieved through a published. The results of revisions analysis are regularly presented in the within the revision triangles and real time databases. Many different approaches can be used to summarise revisions.
The first way to analyse revisions is to look at the simple mean (arithmetic) average revision for estimate of GDP for the period T, between the maturity T+I and the maturity T+j. Figure 1 presents the mean revision by stage of the GDP compilation process, using 10 years’ worth of data. Download this chart It can be observed that there are more upward revisions than downward; this is partly due to the move in 2011 from Retail Price Index (RPI) to Consumer Price Index (CPI), as the main source of deflation index for the expenditure approach. The total mean absolute revision is relatively sizeable; another factor that will impact this would be that of the changes in measurement during the downturn). More information on the revisions to GDP can be found in. It is important to note that there are other aspects to accuracy, which revisions analysis cannot attempt to measure. A value can be reliable (as in not revised) without being accurate.
Broader ways of examining accuracy are presented in. The article describes how basic “raw” data are transformed by a series of adjustments to give the statistical estimates that are used to compile the national accounts. Accuracy of the short-term estimates of GDP growth can be affected by response rates to important surveys. If a lower response rate than normal is received then there is a decrease in the information base of the estimate in the short term, and this may possibly lead to an increased chance of revisions in subsequent estimates of GDP. Looks at ways of assessing accuracy, amid a wider discussion of quality in the current climate.
We are continually working on the methodological changes to improve the accuracy of the national accounts. The first improvement was the harmonisation of the deflators used across the accounts. The second was the replacement of Retail Price Index (RPI) series with Consumer Price Index (CPI) series in forming the deflators. For more information see. Blue Book 2014 saw an introduction of the European System of Accounts 2010 (ESA 2010) and a series of articles were published explaining the. Accompanying each quarterly and annual production cycle, external quality assurers with particular areas of expertise are invited to challenge and report on the statistical and economic coherence of the headline national account and component dataset.
Current assessors include HM Treasury, Bank of England, National Institute of Economic and Social Research, HM Revenue and Customs and Tax Administration Research Centre. The external quality assurers work to challenge the synergy of the dataset from a full range of views – those of producers, data compilers and users of the statistics – before final sign-off. Coherence and comparability (Coherence is the degree to which data that are derived from different sources or methods, but refer to the same topic, are similar. Comparability is the degree to which data can be compared over time and domain for example, geographic level.) Since international standards such as and are used in the production of the national accounts, the figures should be directly comparable with the accounts of other countries. However, the revisions policies of these countries should be examined before comparing data for back periods. Data in the are consistent with our following outputs:.
The only inconsistencies occur when more timely monthly releases introduce revisions in advance of their incorporation into the later quarterly publications. For example, data are not always consistent with trade in goods as the contains more up-to-date quarterly data. Inconsistencies with the Public Sector Accounts releases are also possible due to the different revisions policies being applied to these releases. When annual data first become available (in the February M2 release) they contain revisions to previous quarter data.
This introduces inconsistencies between the latest data and data published in the earlier M3 release. Another important aspect is the coherence between the 3 different approaches to the measurement of GDP, which are theoretically equal. However, since they are measured independently, statistical and measurement errors will mean that this is not the case. Further explanation is provided within the ‘Balancing process’ section of this document.
These issues also formed a major part of the article. Every effort is made to ensure that the series is comparable over time, and a comparable time series is available back to 1948 for annual estimates (1955 for quarterly estimates).
Where possible, changes to methodology are applied to the whole series to ensure this comparability is maintained. However, the may mean that this is not possible. For more information see.
Concepts and definitions (Concepts and definitions describe the legislation governing the output and a description of the classifications used in the output.) GDP estimates are produced in line with international standards, most notably which is enforced for all EU Member States through. ESA 2010 is in turn consistent with the United Nations System of National Accounts 2008. The SNA 2008 is the recent update of and led in turn to the revision of forming, which has subsequently been implemented in the UK National Accounts, as well as those of all other EU member states.
We also provide further information on the introduction of ESA 2010. GDP estimates are compiled using, used for the first time at Blue Book 2011, replacing the previously used.
The introduction of for GDP estimates was in keeping with EU regulations and adapted the classifications to changes in the structure of the economy. Important changes in SIC 2007 include a number of new sections giving more service sector detail while the detail in manufacturing is significantly reduced, reflecting the move towards more services-based economies over the past 20 years. For further information on the introduction of SIC 2007 see. Other information Output quality trade-offs (Trade-offs are the extent to which different dimensions of quality are balanced against each other.) There is a trade-off between accuracy and timeliness. Provisional outputs are timely, but less firmly based. Estimates may be revised during intermediate stages.
These are explained under the section ‘How the output is created’. Assessment of user needs and perceptions (The processes for finding out about users and uses, and their views on the statistical products.) User engagement surveys for the second estimate of GDP and the Quarterly National Accounts were conducted from May to July 2015. In accordance with the Code of Practice for Official Statistics requirements, the objectives of the user engagement surveys were to investigate:. who the users of the statistical product were. what the statistics were used for (including the decisions they informed). users’ perceptions of the quality of the statistics, statistical presentation and statistical commentary. users’ perceptions of the statistical service in relation to this particular statistical product The results of the and Second estimate of GDP user engagement survey are available.
We plan to run the user engagement surveys every 1 to 2 years. Sources for further information or advice Accessibility and clarity (Accessibility is the ease with which users are able to access the data, also reflecting the format in which the data are available and the availability of supporting information. Clarity refers to the quality and sufficiency of the release details, illustrations and accompanying advice.) Our recommended format for accessible content is a combination of HTML web pages for narrative, charts and graphs, with data being provided in usable formats such as CSV and Excel. Our website also offers users the option to download the narrative in PDF format. In some instances other software may be used, or may be available on request. Available formats for content published on our website but not produced by us, or referenced on our website but stored elsewhere, may vary.
For further information please refer to the contact details at the beginning of this document. For information regarding conditions of access to data, please refer to the links below:. In addition to this Quality and Methodology Information document, basic quality information relevant to each release is available in each.
Advance notice of any forthcoming major changes in methodology for the GDP estimates can be found under. Useful links Guide to Gross Domestic Product: Measuring the UK's economic activity.