System of National Accounts

The System of National Accounts or SNA (until 1993 known as the United Nations System of National Accounts or UNSNA) is an international standard system of concepts and methods for national accounts, nowadays used by most countries in the world. The first international standard was published in 1953. Manuals have subsequently been released for the 1968 revision, the 1993 revision, and the 2008 revision. The draft version for the SNA 2025 revision was adopted by the United Nations Statistical Commission at its 56th Session in March 2025. Behind the accounts system, there is also a system of people: the people who are cooperating around the world to produce the statistics, for use by government agencies, businesspeople, academics and interest groups from all nations.

The aim of SNA is to provide an integrated, complete system of standard national accounts, for the purpose of economic analysis, policy-making and decision-making. When individual countries use SNA standards to guide the construction of their own national accounting systems, it results in much better data quality and comparability. In turn, that helps to form more accurate judgements about situations, and to put economic issues in correct proportion - nationally and internationally.

Adherence to SNA standards by national statistics offices and by governments is strongly encouraged, but it is voluntary and not mandatory. What countries are able to do, will depend on available capacity, local priorities, and the existing state of statistical development. However, cooperation with SNA has a lot of benefits in terms of gaining access to data, exchange of data, data dissemination, cost-saving, technical support, and scientific advice for data production. Most countries see the advantages, and are willing to participate.

The SNA-based European System of Accounts (ESA) is an exceptional case, because using ESA standards is compulsory for all member states of the European Union. This legal requirement for uniform accounting standards exists primarily because of mutual financial claims and obligations by member governments and EU organizations. Another exception is North Korea. North Korea is a member of the United Nations since 1991, but does not use SNA as a framework for its economic data production. Although Korea’s Central Bureau of Statistics does traditionally produce economic statistics, using a modified version of the Material Product System, its macro-economic data area are not (or very rarely) published for general release (various UN agencies do produce some estimates).

In various versions, the SNA system has now been adopted or applied in more than 200 countries and areas, although in many cases with some adaptations for unusual local circumstances. Nowadays, whenever people in the world are using macro-economic data, for their own nation or internationally, they are most often using information sourced (partly or completely) from SNA-type accounts, or from social accounts "strongly influenced" by SNA concepts, designs and classifications.

The grid of the SNA social accounting system continues to develop and expand, and is coordinated by five international organizations: United Nations Statistics Division, the International Monetary Fund, the World Bank, the Organisation for Economic Co-operation and Development, and Eurostat. All these organizations (and related organizations) have a vital interest in internationally comparable economic and financial data, collected every year from national statistics offices, and they play an active role in publishing international statistics regularly for data users worldwide. SNA accounts are also "building blocks" for a lot more economic data which are created using SNA information.

The SNA framework

Originally social accounting aimed mainly to estimate national income and national wealth. Governments used that data to inform taxation policy and to understand patterns of economic growth and development. Nowadays, the role of the state in the economy is much larger, and national accounts do much more: they aim to account systematically for almost everything that happens in the national economy – in a way that both follows standard recording principles and measurement criteria, and satisfies the data needs of a much wider group of users (not just governments but also international organizations, business people, academics, interest groups and individual researchers).

Globalization has created a lot of demand for detailed economic data on international transactions, international investment, and international comparisons of economies. Quite detailed accounting data is nowadays produced for “which types of economic actors do what, with whom, in exchange for what, by what means and rights, for what economic purpose, and how this changes the financial position of the national economy (or parts of it)”. To create that data, requires a conceptually and logically consistent accounting system, and a consistent measurement methodology. SNA provides that unitary framework for the whole world. It is not possible to systematically set out the whole SNA framework here; this article gives only some of the main points. For the whole story, it is best to consult the SNA manuals where everything is set out and explained with full details.

Components

The SNA framework links together (i) accounting methods, (ii) economic theories and concepts, (iii) statistical measurement methods, (iv) terminology standards, (v) classification and categorization methods, and (vi) information design principles. The framework informs SNA producers about what to do, how to do it and why it should be done in a specific way. There is often room for some flexibility of interpretation, but if the standard is accepted, then data have to be produced in line with the standard.

To compile an entry in an SNA account, the basic logical steps are: accounting goal → economic concept → accounting rules → appropriate measure → measurement technique → data collection → data storage, collation and registration → data calculation/estimation → data result (a statistic) → data vetting/testing → data approval → inclusion in the new accounts table(s) → data publication.

In reality, the sequence of the data production process may not be so linear and straightforward. There is lot of information to assemble and collate. One accounting entry may be derived from other accounting entries, or it has to fit exactly with other accounting entries. There are many different rules and guidelines to follow, at different levels of abstraction. There is often a long way to go from "a general economic measuring idea" to "a precisely defined measurement technique" that yields the correct empirical estimate for an economic concept. In practice, the main components of the SNA framework for national accounts statisticians are:

• Required economic observations and observational data, collected from various sources.

• Purpose-built data storage and information storage systems.

• A set of economic processes, defined using theoretical conventions.

• Defined economic concepts and categories, for which empirical measures are produced.

• Specifications for the structure and content of core and auxiliary accounts.

• Definitions of accounting terms, measures and procedures.

• Classification and categorization systems.

• Registers of institutional units and their economic activity.

• Survey instruments (including questionnaires, survey systems, and models)

• Accounting rules (including valuation rules).

• Recording rules (including timing rules).

• Statistical aggregation rules.

• Statistical inclusion/exclusion rules.

• Price and volume indexation rules.

• Design specifications for account formats and layouts.

• Measuring, calculation and estimation methodologies.

• Entries (lines) of stock values and flow values in each account.

• Economic statistics and other data results (the finished products).

• Methods for testing and checking data quality, data reliability, and revision effects.

All these aspects have to be identified, decided on, approved and documented by the national accounts team, as the official methodology. The SNA concepts form a logically consistent system (although in practice it is not exactly 100% consistent). Thus, if a change is introduced in one part of the system, it can have consequences for other parts of the system and lead to revisions of the estimates. For example, in December 2024 the National Bureau of Statistics of China (NBS) stated that it had revised the 2023 estimate for the value of GDP by +2.7%, after taking into account results of the 5th national economic census and a change in the method for calculating housing services of urban residents (the impact on the reported economic growth rate for China in 2024 was rather small).

From observables to SNA stock values and flow values

The observables about the national economy which are the basis for SNA accounts include five main categories:

• Economic actions involving flows of money, goods and services which create, transform, exchange, or transfer value, or which change the value of assets and liabilities.

• The human purposes, actions, behaviors and functions of transactors involved in transactions.

• The context, location or setting of the transactions.

• Records of transactions expressed as money-prices or physical volumes (sales, purchases, transfers, incomes & expenditures, and other payments).

• Records for, and changes of, all kinds of asset holdings, liabilities, debts and financial claims owned by persons and by organizations.

SNA categorizes, groups, simplifies and computes all these observables into a large set of categorized stock values and flow values. These stocks and flows are the basic units of all the accounts in the SNA system. Each line item in the SNA core accounts is either a stock value, or a flow value. Each item can increase in value, stay constant or decrease across time. Some non-observed items also exist in the accounts which are derived from observables (by imputation, inference, interpolation, or extrapolation).

Institutional units

To compile the whole inventory of SNA stock values and flow values, a complex grid of concepts, classifications, definitions and accounting rules is consistently applied to order and structure all the base data which is collected to build the accounts. It begins with defining the different types of relevant “institutional units” of a country, such as:

• Financial corporations.

• Non-financial corporations.

• Non-incorporated enterprises.

• Government agencies.

• Households.

• Non-profit institutional units.

• Foreign institutional units (a source of balance of payments data about external transactions).

Institutional sectors also contain sub-sectors, which identify e.g. public, private, non-market and foreign-owned enterprises as well as types of households.

Industrial classification

All economic activities of institutional units are identified and grouped with the aid of the 2023 International Standard Industrial Classification of All Economic Activities (ISIC version 5) or its predecessors. When all economic activities are registered in databases with metadata, according to their characteristics, it is possible to sort the data in a huge variety of different ways, at higher or lower levels of generality/specificity. This makes detailed and comprehensive comparisons possible for different economic activities, both within countries and between countries.

Other classifications

There are dozens of other classification systems which are applied to categorize stocks and flows in SNA accounts and sub-accounts. At more detailed levels, the classification systems may be guided by existing SNA standards, but they may also be modified and adapted in some degree to local circumstances (depending on the distinctive economic structure and economic processes of a country). The classification systems are partly designed to enable international comparisons. But they are also designed to provide data that give insight into local economic characteristics. Statisticians normally try to design categories which combine standardization requirements and technical essentials with the known needs of data users. If the data categories are not suited to the analyses that researchers want or need to do, or not consistent with what the government requires, then the classification systems are not useful.

Core accounts

Traditionally, the SNA framework provides a set of ten core accounts (the detailed design and terminology has changed somewhat through successive revisions). The accounting principles for each of these core accounts are explained in the SNA manual. The ten core accounts are:

• The production account (components of gross output).

• The primary distribution of income account (incomes generated by production).

• The transfers (redistribution of income) account (including social spending by governments).

• The use of income account (consumption expenditure and saving, sometimes also household assets/liabilities).

• The capital account (investment, capital formation and accumulation).

• The (domestic) financial transactions account ("flow of funds").

• The revaluation account (including capital gains and losses).

• The other changes in assets account (changes in assets, liabilities and net worth not caused by transactions).

• The balance sheet account of assets, liabilities and net worth.

• The external transactions ("rest of the world") account (integration of current account, capital account and financial account)

Most member countries of the United Nations compile these ten "core" accounts. Broadly speaking, the ten accounts deal with four main topics: (1) national income, (2) capital formation, (3) the national financial position, and (4) foreign transactions of the nation. This provides economic insight into what is happening with production, the generation, distribution and use of income, and the accumulation of wealth of the nation.

However, national statistics offices do not provide a complete national set of all “possible” SNA accounts. They might not provide a 100% complete set of national SNA data for the accounts they do publish. The reasons could be (1) that some sorts of data are not relevant/useful, (2) that it is too difficult or costly to produce the data, (3) that the data is already published elsewhere, or (4) that there is some kind of official restriction on data production. For example, if there is a lot of tourism in a country, a standard tourism account makes sense. But if there is very little tourism, then producing a standard tourism account may lack a good justification.

Supplementary accounts

Each of the SNA core accounts can be complemented with annexes providing extra details, sub-accounts within the core accounts, satellite accounts and supplementary tables. SNA standards are also provided for input-output tables showing interactions between production sectors within the national economy (the enterprises of each sector make payments when they purchase inputs from other sectors, and receive revenue when they sell outputs to other sectors). Quite a few extra accounts alongside core accounts are outlined in the SNA manual.

The non-core accounts are optional. Whether they are compiled or not depends mainly on their practical usefulness. National statistics offices produce them, if there is a need or demand for them and there is a budget to produce the accounts. In some countries, it is not yet feasible to produce particular ancillary or satellite accounts, or it is too costly for them to do that. Sometimes the initiative to produce an extra satellite account was first taken by a national statistics office, which then prompted the adoption of an SNA standard. Sometimes a national statistics office will produce supplementary tables or auxiliary accounts for which there is as yet no SNA standard.

SNA satellite accounts that have been used so far include:

• Agricultural accounts of farm and plantation operations.

• Disaster risk reduction expenditure accounts to track disaster-related spending (implementation remains limited).

• Environment and energy accounts to track environmental protection expenditures, resource stocks and resource use, often aligned with the System of Environmental-Economic Accounting (SEEA).

• Health accounts of health expenditures and funding.

• Information and communication technology accounts of ict product transactions.

• Household production accounts.

• Labour use accounts.

• Non-profit institutions accounts of net output and employment.

• Productivity and growth accounts.

• Research & development accounts.

• Social protection accounts.

• Tourism satellite accounts.

• Transport accounts measuring transport-related economic activity.

A 2020 survey on the national use of SNA satellite accounts discovered that 241 satellite accounts were created by 80 countries for 20 different account topics. The number of satellite accounts per country varied from 1 to 15 accounts, with a median number of 2 accounts, and an average of 4 accounts. The countries with the most satellite accounts were Canada (15), Portugal (13), Israel (9), Australia (8), Finland (8), Lithuania (8), China (7), and Mexico (7).

Proposed new satellite accounts

New satellite accounts proposed for SNA 2025 include:

• Education and human capital accounts tracking monetary and non-monetary investments/expenditures in education.

• Distributional income and wealth accounts, with supplementary tables to analyze income/wealth inequality across households, linked to core national accounts.

• Health satellite accounts to measure health-related expenditures and outcomes.

• Unpaid household work and volunteer work accounts measuring non-market labor, particularly caregiving and domestic services.

• Digital economy accounts: supplementary breakdowns for digital transactions, crypto assets, and fintech activities.

SNA data sources

National accounts are integrated, composite statistical systems. They bring together raw data, computed data and ready-made statistics from a great variety of sources. Typically, hundreds (or even more than a thousand) separate data sources are used for a complete set of annual national accounts, depending on the size and complexity of the country’s economy. For example, the British Office of National Statistics (ONS) uses around a thousand different data sources. The same applies to many European countries. The US Bureau of Economic Analysis (BEA) obtains data from more than 300 major surveys and administrative sources, and exchanges data with the IRS, the Census Bureau, the Federal Reserve, the Department of Labor, and other government agencies.

The source of the data could be a survey, a publication, a government agency, a business agency or institution, a model, or an unofficial source etc. Some of the data sets are fully produced by the national statistics agency itself, some data is imported readymade from other agencies, and some data is obtained from elsewhere but reworked for use in SNA accounts. National accountants often act as "statistical engineers", who reconcile thousands of inconsistencies between different sources, to obtain valid estimates which conform to national accounting standards. An economic "map" is created for all measured transactions in the national economy. In this map, all stocks and flows are allocated and categorized according to SNA rules. For every entry in the SNA accounts, the appropriate measurement methodology is defined by statisticians, consistent with the SNA manual. In principle, there is a place in SNA for almost every type of transaction in the economy.

SNA statisticians get the data and information they need from ten types of sources:

• Direct surveys of business units, institutional units, household units, and consumer units, or special sector-specific sample surveys. These are often sample surveys for specific areas and sectors in the economy (for example, labour force surveys) which are generalized to the whole economy, using a survey frame and mathematical models.

• Census data obtained from population censuses, economic censuses, agricultural censuses and housing & dwelling censuses. Normally a census involves surveying the complete population of an area or sector, not just a sample of it. A national population census is normally taken every five or ten years (sometimes this is temporarily not possible, because of crises, wars or disasters).

• Administrative data. This includes corporate records, company records, institutional records, personal income records and value-added tax records; inventory data; social security contributions and pension records; bookkeeping records and company registers; land and property registers; financial reports of companies and institutions; customs records of imports and exports; licensing databases; and employment registers.

• Public finance statistics and related data sets obtained from central, provincial and local government agencies. Included are the general government accounts, budget execution reports, and expenditures on specific items such as defence and education.

• Central bank and corporate bank statistics, including balance sheet data; data on bank loans, deposits and interest paid/earned; insurance and pension fund reports; data on stocks, bonds, derivatives and other asset transactions; and data on various other financial markets and forms of financial intermediation.

• Satellite data imported from other statistical agencies for use in standardized SNA satellite accounts (for example tourism, health, labour utilization etc.). This material can be supplied to SNA ready-made, or it can be adjusted somewhat for alignment with SNA standards.

• Mathematical models which estimate the value for particular accounting items using observed trends in related contemporaneous data which are already available. Models are not only used for sample surveys. They are also used to extrapolate data sets which are too costly or impossible to obtain from an alternative source. Models are also useful to test the reliability of the data series that are produced. Quarterly economic data is often obtained with the aid of mathematical models and leading indicators that can reliably predict the trend.

• Price indexes, including price and volume indexes for traded goods and services; consumer price indexes; producer price indexes for inputs and outputs; capital expenditure indexes; asset price indexes; export and import price indexes; real estate and construction cost indexes. A national statistics office in the larger countries typically uses 500 to 2000 price indexes. Most price indexes are usually produced by the national statistics office itself, but in some cases, they are produced by other government agencies, by research institutions, or by foreign agencies. They are crucial for the accurate estimation and uniform valuation of entries in the national accounts.

• Online data sources. Increasingly, national statistics offices make use of publicly accessible online data and databases maintained by private sector organizations, as a source of data. Examples are web-sourced price information, retail prices and retail volumes, and tourism & transport data. Different government agencies also share or exchange information from their digital databases.

• International sources: information is obtained from government agencies in other countries, for export and import statistics, balance of payments statistics, international trade in services statistics, tax and pension treaty statistics, foreign income & remittances, and foreign direct investment statistics.

SNA statisticians can refer to all kinds of national and international documentation, including scientific or other academic literature and news stories. But they cannot collect data from any source at will. Much of the detailed source data used to produce statistics is confidential or secret (for privacy, military, official and business reasons). Normally only the aggregates derived from the detailed base data are accessible and published in the accounts. There exists a legal framework for data collection and data publication, which defines the obligation to supply data, legitimate use of data, protection of data, and privacy rights. The national statistics office must specify "under whose authority" the information is collected, and "for what purpose". National accounts data can only be collected if it is really necessary to produce the national accounts. In this way, the response burden is kept within acceptable bounds for data suppliers, unnecessary costs are avoided, and there is less chance of response error, data sabotage or non-compliance with information requests.

The world's largest national accounts

Annual SNA-based estimates for the People's Republic of China (excluding Hong Kong, Macao and Taiwan) were first produced for 1985. For 1985-1992, separate national accounts were compiled according to the Material Product System (MPS) and SNA 1993, although at that time the SNA data were mainly derived from MPS accounts (using a conversion method created by the United Nations Statistics Division). In 1992, the SNA was adopted by the National Bureau of Statistics of China as the official accounting system. From that time, the MPS system was abandoned, and Chinese national accounts were directly compiled in accordance with SNA principles.

India first introduced national income estimates in 1952, and has progressively integrated SNA updates in its National Accounting System (NAS), including the 1968, 1993, and 2008 revisions. NAS adheres broadly to SNA concepts (such as GDP, Gross Value Added, and sectoral accounts), but also uses country-specific methods to deal with data limitations, a large informal sector, and local administrative practices. India's Central Statistics Office continues to revise the NAS to improve harmonization with SNA standards, but retains methods specially designed for Indian economic conditions.

Eurostat uses a version of the SNA for the European Union, called the European System of Accounts (ESA). Participation in the ESA system is mandatory for European Union member states. All EU Member States are legally obliged to use ESA 2010 for their national and regional accounts. This includes providing standardized macroeconomic data to Eurostat, consistent with the ESA framework. The ESA concepts are uniformly applied in budget reports by EU member governments and in their official financial statistics, as well as in EU financial surveillance systems for member governments. For example, according to the EU Stability and Growth Pact (SGP), EU government budget deficits must ordinarily not exceed 3% of GDP, and the norm for EU government debts (the public debt) is that they must not exceed 60% of GDP.

The American-designed National Income and Product Accounts (NIPA), used uniquely in the United States, feature broadly the same concepts as SNA, but they differ from the SNA in details of methodology, classifications and presentation. The traditional similarity between the SNA and the NIPA exists, because the original design of the SNA in 1953 was to a certain extent modeled on the NIPA accounting system already adopted by the US federal government in 1947. The subsequent SNA revisions were also informed or influenced by developments in the NIPA accounts. Since 1993, the American Bureau of Economic Analysis has made an effort to achieve greater conceptual consistency with SNA standards. The differences in data and presentation between the two systems are not an insurmountable problem, because the NIPA and the SNA both provide sufficient information to rework statistics to match each other's concepts, categories and classifications.

The national accounts of Brazil, Indonesia, Pakistan and Nigeria are all based on SNA concepts and methods, but with differences in the SNA versions used, implementation quality, and institutional capacity. The Brazilian Institute of Geography and Statistics (IBGE) uses the SNA 2008, and is highly advanced in social accounting, with full implementation of institutional sector accounts, supply and use tables, quarterly national accounts and integration of satellite accounts (e.g., environmental accounts, health, and education). Statistics Indonesia uses SNA 2008, and its accounts are quite comprehensive. The Pakistan Bureau of Statistics uses SNA 1993 and SNA 2008, but complete data is not yet available for all standard SNA accounts. The National Bureau of Statistics, Nigeria (NBS Nigeria) uses SNA 2008, aiming to rebase the data sets to 2019.

Regional organizations for SNA development

In Latin America and the Caribbean, there is the regional program Sistema de Cuentas Nacionales (SCN), coordinated by the Economic Commission for Latin America and the Caribbean (ECLAC) together with the UNSD, IMF, and World Bank. Its aim is to organize, standardize and harmonize the implementation of SNA 2008 across the region. There are 33 participating countries.

The ASEAN Guidelines on National Accounts aim to improve SNA 2008 alignment, harmonize national accounts, strengthen capacity, and improve data quality and dissemination in the ASEAN region. The program involves 10 countries and is sponsored by ASEANstats, IMF, UN ESCAP, and Asian Development Bank (ADB).

In West Africa and Central Africa, there is the Observatoire économique et statistique d'Afrique subsaharienne (AFRISTAT) created in 1993 by WAEMU countries and other countries. The organization promotes harmonized national accounts, following SNA 1993 and moving to SNA 2008. In East Africa and Southern Africa, there are regional organizations like Common Market for Eastern and Southern Africa (COMESA), Southern African Development Community (SADC), and East African Community (EAC) which have statistical committees supporting SNA implementation. These are backed by AfDB, the IMF's AFRITAC organizations, and UNECA.

The GCC Statistical Center (GCCStat, Gulf Cooperation Council) coordinates statistical work, including national accounts, for Saudi Arabia, UAE, Qatar, Kuwait, Bahrain, and Oman. It is moving toward SNA 2008-compliant national accounts. The focus is now on non-oil sectors, satellite accounts, and price indices.

The Caribbean Community framework (CARICOM) provides SNA technical cooperation for Jamaica, Trinidad and Tobago, Barbados, Guyana, Belize, etc. It coordinates with UNSD and ECLAC on SNA 2008 implementation, with a special focus on tourism satellite accounts (TSA) and remittances.

To support and harmonize the implementation of SNA across the Pacific region, several organizations provide technical assistance and capacity-building initiatives. Pacific Community's Statistics for Development Division offers guidance and training to enhance statistical systems. The Pacific Financial Technical Assistance Centre (PFTAC) aims to strengthen institutional capacities in macroeconomic and financial management, including national accounts statistics. The United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP) conducts regional programs to improve economic statistics in Asia and the Pacific. In addition, the National Transfer Accounts (NTA) network is also active in the region.

Publication of data

No single agency has a monopoly on publishing SNA statistics, but for particular data sets, one national or international agency is usually the "primary" publisher. For example, international agencies are more likely to publish comprehensive international comparisons of SNA data on a regular basis, while detailed national SNA statistics are available from national statistics offices or national governments. International agencies will often include United States data sets in their comparative SNA statistics, even though the US has its own NIPA accounting system. Sometimes estimates for core variables are included for countries/areas outside the SNA framework.

Economic and financial data from UN member countries are used to compile comparable annual (and sometimes quarterly) data on the gross product, national income, investment, capital transactions, government expenditure, and foreign trade. The results are published nationally but also in two UN Yearbooks: (1) National Accounts Statistics: Main Aggregates and Detailed Tables and (2) National Accounts Statistics: Analysis of Main Aggregates. From 2025 onward, the yearbooks are published in line with the SNA 2025 standards. The values provided for the accounts of individual countries in the UN yearbooks are cited in the national currency. The same data in US dollar equivalents may however be available from other agencies such as the IMF, OECD, World Bank, Eurostat or other UN agencies etc. The IMF publishes the most comprehensive SNA-based Balance of Payments statistics for the world's countries, as well as comparative statistics on government finance. The OECD and the World Bank publish a lot of SNA-based comparative economic statistics and country reports. To make the comparisons, the data series have to be converted to a common currency (usually US dollars or euro's).

National statistical offices typically publish SNA-type national data series using their own formats and styles. More detailed accounts data at a lower level of aggregation is often available on request. International organizations like the IMF, OECD and Eurostat sometimes adjust national SNA data according to their own methodologies. Because national accounts data is notoriously prone to revision (since it involves a very large number of different data sources, entries and estimation procedures that have impact on the totals), discrepancies can occur between the totals cited for the same accounting period in different publications issued in different years. The "first final figures" may in fact be retrospectively revised several times, because of necessary corrections, new data sources and methods, or conceptual changes. The revisions may be quantitatively slight, but cumulatively across e.g. ten years they could sometimes alter a trend significantly. This is something the researcher has to bear in mind in seeking to obtain a consistent data set - usually, it's best to check out first what the most recent data releases and the latest revisions are. Often it is possible to link old and new data series using some suitable method.

Quality and coverage

SNA data quality is relatively good, because the data are regularly checked and monitored by several agencies, and not just by the data producers. Nevertheless, the data sets of some countries are much more complete than others. Both the quality and the comprehensiveness of national accounts data that are available can differ between countries. There are four main reasons:

• Available resources: some governments (such as in OECD countries and countries with large populations) invest far more money and employees in statistical research than other governments. What matters in this sense is, above all, whether a society sees the value of statistics, makes extensive use of statistical expertise for analytical and policy purposes, and therefore is sympathetic to investing in the statistical enterprise.
• Local conditions: economic activity in some countries is much more difficult to measure accurately than in others - for example, there may exist a large grey or informal economy; widespread illiteracy; the absence of a cash economy; survey access difficulties because of geographic factors, socio-political instability, disasters, pandemics, wars, or large-scale mobility/migration of people and assets.
• Degree of autonomy: some statistical agencies have more scientific autonomy and budgetary discretion than others, allowing them to do surveys or statistical reports which other statistical agencies are prevented from doing, for legal, financial or political reasons.
• Expertise: some countries (for example, Australia, Brazil, Britain, Canada, China, France, Germany, Hungary, The Netherlands, Poland, Russia and the United States) have a strong intellectual (scholarly or cultural) tradition in the area of national accounts and social statistics, sometimes going back a hundred years or more. Other countries (such as African countries), where a population census began to be organized by the government much later, and where most universities started later, do not have such research traditions. However, developing countries have the advantage, that in creating their statistics production systems, they can adopt straightaway the very latest and most advanced methods and technologies in the world, without having to go through endless revisions and changes from old methods to new methods.

The United Nations has rather little power to enforce the actual production of statistics to a given standard, even if international agreements are signed by member states. But it can help with technical advice, training and capacity building. The UNSD collects national accounts statistics from most of the world's countries and territories. Some of the world's states are part of other international unions (for example the European Union, the OECD, or the United States), which oblige member states to supply standardized data sets, for the purpose of inter-state or international comparisons and coordination. In exchange for supplying data, countries also receive foreign data and expert scientific advice. So there are incentives and benefits for countries to cooperate, for the sake of obtaining more useful, comprehensive, and internationally comparable statistical information. If they cooperate, countries can obtain vastly more foreign statistical information and expertise at a lower cost, which matters if the information is essential to have for local, national and international decision-making.

Developments

SNA continues to be developed further. International conferences are regularly held to discuss various conceptual and measurement issues, and proposed revisions. The proposed SNA 2025 features many new standards for supplementary SNA tables on different topics. Many of the new supplementary tables aim to link SNA financial data with social or physical statistics from other international or national agencies, with the aim of providing standardized, comparable national data sets on specific topics (such as labor use, natural resources, productivity, health etc.).

There are many ongoing projects, such as developing standard accounts for environmental resources, the measurement of the trade in various services and of productivity, the treatment of insurance payments, the grey economy, employee compensation in the form of non-wage income, intangible capital, cryptocurrencies, labor economics etc. Projects related to the SNA 2025 revision are mentioned on the UNSD webpage.

Revisions of the SNA national accounts system are normally coordinated by the Intersecretariat Working Group on National Accounts (ISWGNA), comprising the United Nations Statistics Division (UNSD), International Monetary Fund (IMF), World Bank (WB), Organisation for Economic Co-operation and Development (OECD), Statistical Office of the European Communities (Eurostat) and the United Nations regional commissions. The ISWGNA working group has its own website under the UN Statistics Division and works with the Advisory Expert Group (AEG).

Discussions and updates are reported in the news bulletin SNA News and Notes. Official SNA Revisions are always documented at the UN Statistics Division site.

For the 2008 SNA Revision, the full final text is available online. For the 2025 Revision, only the proposed document is available so far; the final text still has to be approved.

Achievements of SNA

After more than 70 years of development, the System of National Accounts is the only comprehensive, internationally agreed standard for national accounting practice. It is now used by almost all governments, by universities, and by international financial institutions. It provides detailed guidance to national statistical offices in more than 200 countries. Its globally standardized approach ensures that economic activity is measured on a conceptually consistent and quantitatively comparable basis across the whole world.

The SNA offers a coherent, integrated set of macroeconomic accounts built on shared concepts, definitions, classifications, and accounting rules. It provides a comprehensive framework for recording all stocks and flows in the economy of every nation, including production, income, saving, investment, and both financial and nonfinancial wealth. It also encompasses input-output tables, financial accounts, balance sheets, and international transactions. These accounts are an indispensable source for a wide range of macroeconomic statistics used by policymakers, researchers, investors, entrepreneurs and institutions in all countries.

For the first time in history, the SNA has made it possible for almost all countries to produce internationally comparable economic indicators on a regular basis. It offers empirical insight into the size, structure, and evolution of economies, and facilitates the quantitative analysis of national and global economic trends, problems, and developments. It plays a central role in the growth of knowledge and international understanding of economic life in all countries. The quality of the data is checked regularly by different agencies, at the national and international level. The SNA also supports the development of satellite accounts — modular extensions allowing for specialized analysis (in areas such as environmental accounting, the economic contributions of tourism and cultural industries, health expenditures and financing, expenditures and investments in education etc.) — while maintaining consistency/compatibility with the core accounts.

The SNA architecture is one of the biggest collaborative achievements in the global statistical system. Its maintenance and development depend on broad international cooperation from national statistical offices, individual experts and related agencies, coordinated through organizations such as the United Nations, IMF, World Bank, OECD, and Eurostat. This cooperation is based on voluntary agreements and mutual understanding among countries. It enables the use of shared methodologies, terminology, and classifications, and supports the dissemination of economic information worldwide through many different channels. The system also contributes to capacity building on the ground, providing technical assistance and staff training to national statistics offices, especially in developing countries.

Designed for universal use, the SNA system accommodates the needs of countries at all levels of economic development, and in all national contexts. It facilitates integration with other statistical systems, and promotes coherence across different domains of economic and social statistics. Ongoing updates ensure that the SNA remains responsive to new policy challenges, such as measuring the digital economy, accounting for cryptocurrencies, and incorporating environmental sustainability. With continual efforts for improvement and refinement, the SNA remains an indispensable tool for achieving consistency, comparability, and clarity in the statistical representation of national economies and the world economy.

Debates

SNA data is used by tens of millions of public servants, private sector data professionals, businesspeople and academics worldwide. Without SNA data (whether published by the UN, or published by other agencies), they would have no internationally comparable data on the economy of different countries. So the data users appreciate that the information is available. However, SNA has also been criticized for its shortcomings. That is to be expected - with so many users of SNA data worldwide, and given the limits of what the SNA accounts can provide for different countries, it is simply impossible to satisfy everybody's economic data needs all of the time. For example, it has been argued that SNA should include measures of happiness, but this idea has never been implemented.

The criticism most often made of SNA is that its design, concepts and classifications do not adequately reflect the interactions, relationships, and activities of the real world. The effect of that is (allegedly) a distorted picture of the world. For example, there are the following sorts of criticisms:

• The SNA system does not provide explicit detail for particular economic phenomena, suggesting thereby that they do not really exist or are of o significance (for example, Islamic banking, large multinational corporations, the value of natural resources, the value of housework).
• There is something wrong with the valuation scheme that is being assumed (for example, the productive contribution of capital assets).
• In the valiant attempt to include transactions of all "micro" business activities under general "macro" headings, the true situation is misrepresented because a large portion of micro-transactions does not easily fit under the general conceptual headings (for example, the informal economy).
• National accounts data on their own are not useful to solve many of society's problems, because those problems really require quite different kinds of data to solve them (for example, population data, behavioral data, attitudinal data, legal data, or physical data. So SNA data really need to be integrated with other data in a standard way, to provide useful international comparisons.
• National accounts data are constructed from thousands of different data series, and the results are typically revised several times after the first official estimates are published. Therefore, the first estimates may not be completely accurate, in terms of the measurement concepts used. The earlier data series released are sometimes revised many years later, so that the data may never be quite "final" and completely accurate. The effect can be, that financial markets react in the wrong way when the data is published, and that politicians try to interfere with the figures that are released.

The SNA authorities have responded to such criticisms in many different ways, large and small.

• In the last decades, there are constantly many efforts across the world to standardize statistical data to make them internationally comparable, with equal or similar data quality. SNA was created specifically as a tool for measuring economic activity, national income and economic growth in a standard way, which enables international comparisons. SNA was not created to include “everything we need to know about a country or about the world”, and it is impossible for SNA to do that. Many concerns about unmet data needs are being addressed via the design of supplementary standard tables or satellite accounts, which provide modified SNA aggregates for special uses, or which integrate SNA accounts data with social, financial or environmental data from other sources. The advantage of this approach is that the comparability with traditional SNA accounts and previous SNA data is not jeopardized by constant revisions to accommodate new data demands.

• Particularly in OECD countries, a great effort has been made by national statistics offices to supply timely SNA data which is accurate and complete, and which does not have to be revised very much afterwards. Modern technology increasingly makes possible much faster data collection, processing and publication, because it can be done with digital and online questionnaires (sometimes using mobile phones); digital coding; data warehouses; automated searching, editing, error-tracking and dataset construction; automating procedures with artificial intelligence, etc. Aided by modern computers, data production can often be realized faster, more efficiently, with fewer errors and better quality. This is especially important in countries with very large populations that have to be surveyed (for example, Brazil, China, Germany, India, Indonesia, Nigeria, Russia, and the United States).

• Statisticians do their best to safeguard the autonomy, objectivity and integrity of data production and data releases, including specific professional protocols and the provision of explanations to the public about significant statistical trends. There are now more and more different ways to make data available to users, and much more attention is given to information design to make data understandable. Data means nothing, if it is not communicated in an effective way, so that people can understand it.

Criticism of GDP

The most popular criticism of national accounts concerns the concept of gross domestic product (GDP). GDP is criticized for what it does not measure, or because it allegedly mismeasures the national economy. Economists like Joseph Stiglitz have argued that a measure of "well-being" is needed to balance a measure of output growth. Such measures have already been designed, but so far they have not been widely included in SNA accounts. However, SNA 2025 broadens the national accounts framework, to account better for elements affecting wellbeing and sustainability, for the purpose of informing various policy goals of governments and international organizations.

In part, the criticism of GDP is misplaced, because the fault is not so much with the concept itself. It is useful to have a measure of a country's total net output and national income, and its changes over time – that's better than having no measure at all. The fault is more with the actual use that is made of the concept by governments, intellectuals, and businessmen in public discourse. GDP is used for an enormous diversity of comparisons, but many of those comparisons are conceptually not appropriate. In the US, for example, it is very common for politicians and the media to equate GDP with "the economy", but this is false - GDP does not measure all economic activity, it is only a measure of the new gross value added by production during an interval of time (the net value of a country's output) which equates to a measure of national income. GDP measures are frequently abused by writers who do not understand what they mean, how they were produced, or what they can be validly used for. Many of the critics of national accounts have no real knowledge about the possibilities and limits of the accounting design.

The main response by statistical authorities to criticism and abuse of GDP data has therefore not been to abandon or abolish the GDP measure, but instead to provide additional, complementary data about phenomena which GDP does not measure, and cannot measure. With this approach, most data users can get the data that they want, most of the time, without denying the data needs of other users. There are human limits to the varieties of data that can be made available, but with the aid of modern technology, a vastly greater variety of data can be made accessible to the public, at the touch of a button.

Feminist concerns

SNA has been criticized as biased by feminist economists such as Marilyn Waring and Maria Mies because no imputation for the monetary value of unpaid housework or for unpaid voluntary labor (mainly done by women) is made in the accounts, even although GDP does include things like the "imputed rental value of owner-occupied dwellings" and an imputation for "financial intermediation services indirectly measured" (FISIM). This SNA omission is said to obscure the reality that market production depends to a large extent on non-market labor being performed. In turn, that lacuna in the data allegedly promotes a distorted picture of economic life (which in reality includes both paid and unpaid work).

However, such criticism does raise technical questions for the statisticians who would have to produce the standard data:

• whether an international standard method of comparing the value of household services is technically feasible, given e.g. that the conditions under which the market equivalents for unpaid household services are supplied vary greatly between countries.

• whether making imputations for women's voluntary work would result in truly meaningful and uniform measures.

• whether attaching a price to voluntary labor, done primarily by women, itself actually performs an emancipatory or morally propitious function, or has a general useful purpose beyond academia.

The intention of those who would like to produce standard data for the market value of women's voluntary labor might be perfectly honorable. However, the production and cost of the data has to be practically justifiable in terms of technical feasibility and real utility. Attaching an imaginary price to housework, might not be the best data to have about housework. There is a permanent need for data on housework and voluntary work, because so many people are involved in it. But the SNA system might perhaps not be the best place to supply that data. This controversy is not yet finished, and there is not yet a completely satisfactory and definite solution.

In most OECD countries, statisticians have estimated the value of housework using data from time use surveys. The valuation principle applied is usually that of how much a service would cost, if it was purchased at market rates, instead of being voluntarily supplied. Sometimes an "opportunity cost" method is also used: in this case, statisticians estimate how much women could earn in a paid job, if they were not doing unpaid housework. The results often suggest that the value of unpaid housework in money terms would be about a third or half the value of GDP.

When she was the head of the International Monetary Fund, Christine Lagarde claimed at an IMF/World Bank annual meeting in Tokyo (October 2012) that women could rescue Japan's stagnating economy, if more of them took paid jobs instead of doing unpaid care work. A 2010 Goldman Sachs report had calculated that Japan's GDP would rise by 15 percent, if the participation of Japanese women in the paid labor force was increased from 60 percent to 80 percent, matching that of men.

The difficulty with this type of argument is, that domestic and care work would still need to be done by someone, meaning that either women and men would need to share household responsibilities more equally, or that parents would have to rely on child and eldercare supplied by paid caregivers from the public sector or the private sector. Many mothers don't care about a GDP number, they care about their children, and do not want to outsource parenting. With a greying population, the economy needs more children that can replace retired workers in the future. The majority of young people with young children cannot afford to hire caregivers themselves. According to the International Labour Organization (ILO), about 75.6 million domestic workers were employed in the world, mostly women and migrants, representing 4.5% of all workers. Domestic workers remain largely undervalued, underprotected, and underrepresented. In 2021, the ILO estimated that 81% of all domestic workers were "informally" employed. They are mainly servants of the wealthy and the professional middle classes.

Marxist critique

Marxian economists have criticized SNA concepts also from a different theoretical perspective on the new value added or value product. On this view, the distinctions drawn in SNA to define income from production and property income are rather capricious or eclectic, obscuring thereby the different components and sources of realized surplus value; the categories are said to be based on an inconsistent view of newly created value, conserved value, and transferred value (see also double counting). The result is that the true profit volume is underestimated in the accounts – since true profit income is larger than operating surplus – and workers' earnings are overestimated since the account shows the total labor costs to the employer rather than the "factor income" which workers actually get. If one is interested in what incomes people actually get, how much they own, or how much they borrow, national accounts often do not provide the required information.

Additionally, it is argued by Marxists that the SNA aggregate "compensation of employees" does not distinguish adequately between pre-tax and post-tax wage income, the income of higher corporate officers, and deferred income (employee and employer contributions to social insurance schemes of various kinds). "Compensation of employees" may also include the value of stock options received as income by corporate officers. Thus, it is argued, the accounts have to be substantially re-aggregated, to obtain a true picture of income generated and distributed in the economy. The problem there can be, that the detailed information to do it is often not made available, or is available only at a prohibitive cost.

US government statisticians admit frankly that "Unfortunately, the finance sector is one of the more poorly measured sectors in national accounts". The oddity of this is, that the finance sector nowadays dominates international transactions, and strongly influences the developmental path of the world economy. So, it is precisely the leading sector in the world economy for which systematic, comprehensive, and comparable data sets are not available.

SNA statisticians acknowledge that alternative interpretations of the gross product account are possible, but they emphasize that considerable opportunities exist for researchers to reaggregate/rework standard statistical measures, to create their own alternative measures. Examples are Alan Freeman's Marxist national accounts group and the socialist Distributional National Accounts (DINA) framework pioneered by Thomas Piketty, Emmanuel Saez, and Gabriel Zucman. The DINA approach combines tax records, household survey data and national accounts data, to show the real distribution of national income among different income groups. In the DINA design, the sum of individual incomes aligns with standard macroeconomic aggregates, providing a consistent and comprehensive picture of income distribution. In addition, future SNA accounts will address some of the concerns raised, via satellite accounts, on topics such as labor inputs, income distribution and financial activities.

Statisticians' critical views

Statisticians have also criticized the validity of international statistical comparisons using national accounts data, on the ground that in the real world, the estimates are rarely compiled in a uniform way – despite appearances to the contrary.

For example, Jochen Hartwig provides evidence to show that "the divergence in growth rates [of real GDP] between the U.S. and the EU since 1997 can be explained almost entirely in terms of changes to deflation methods that have been introduced in the U.S. after 1997, but not – or only to a very limited extent – in Europe".

The "magic" of national accounts is that they provide an instant source of detailed international comparisons. However, critics argue that, on closer inspection, the numbers are often not really so comparable as they are made out to be. The practical result is, that all sorts of easy comparisons are tossed around by policy scientists, which, if the technical story behind the numbers was told, would never be attempted, because the comparisons are scientifically dubious or untenable.

The counterargument is, that because countries are applying the same statistical standards and concepts, this already makes an enormous positive difference to data comparability, which far outweighs the effects of remaining methodological discrepancies in the data of different countries. Moreover, SNA producers do not have control over how SNA data will be used; national statistics offices control only what information is released and when it is released, in accordance with a legal framework, and with directives from the government officials in charge. The data can be used for purposes which are not valid, or purposes that the data were never intended for. That is not the fault of SNA producers, but a matter of data awareness, statistical knowledge and user education.

Both the strength and the weaknesses of national accounts are, that they are based on an enormous variety of data sources. The strength consists in the fact that a lot of cross-checking between data sources and data sets can occur, to assess the credibility of the estimates. The weakness is, that the sheer number of inferences made from data sets increases the possibility of data errors, and can make it more difficult to assess error margins.

SNA data quality has been criticized on the ground that what pretends to be "economic data" in reality often consists only of estimates extrapolated from mathematical models, not direct observations. These models are designed to predict what particular data values ought to be, based on sample data for "indicative trends". One can, for example, observe that if variables X, Y, and Z go up, then variable P will go up as well, in a specific proportion. In that case, one may not need to survey P or its components directly, it is sufficient to get trend data for X, Y, and Z and feed them into a mathematical model which then predicts what the values for P will be at each interval of time.

Because statistical surveys can be costly or difficult to organize, or because the data has to be produced quickly to meet a deadline, statisticians often try to find cheaper, faster, and more efficient methods to produce the data, by means of inferences from data that they already have, or from selected data which they can get more easily. But the objection to this approach - although it may be proved at times to provide accurate data successfully - is that there is a loss in data accuracy and data quality.

• The extrapolated estimates may lack any solid empirical basis, and the tendency is for fluctuations in the magnitudes of variables to be "smoothed out" by the estimation or interpolation procedure.
• An unusual, large fluctuation in a variable is difficult to predict by a mathematical model, because the model's descriptions assume the future trend will conform to the law of averages and the patterns of the past. An unusual pattern could be regarded as a "data error", not as real.
• Without adequate, comprehensive observational data from direct surveys and real records, many of the statistical inferences made are in reality not truly verifiable. All one can then say about the estimates is, that they are "probably fairly accurate, given previous and other concurrent data."

A typical reply of statisticians to this kind of objection is, that although it is preferable to have comprehensive survey data available as a basis for estimation, and although data errors and inaccuracies do occur, it is usually possible to find techniques that keep margins of error within acceptable bounds. Moreover, if governments refuse to pay for the production of quality data, statisticians can only do what they are able to do, with the techniques they have available (although better methods could be used). Imperfect data may be better to have, than no data at all. In the future, digital technology and artificial intelligence will most likely make the production of economic statistics easier, cheaper, faster and better. But if the demand for quality data grows, investment by countries in data production will have to grow as well.

See also

• Aggregation problem
• Artificial Intelligence for Environment & Sustainability
• Balance of Payments
• Bureau of economic analysis
• Capital account
• Capital formation
• Capital gain
• Circular economy
• Classification of Individual Consumption by Purpose
• Colin Clark (economist)
• Compensation of employees
• Consumption of fixed capital
• Distribution of wealth
• Double counting (accounting)
• Double-entry bookkeeping
• Economic development
• Economic growth
• European System of Accounts
• Fixed capital
• Fixed investment
• Green accounting
• Green gross domestic product
• Environmental accounting
• Gross fixed capital formation
• Gross Domestic Product
• Gross National Income
• Gross National Product
• Gross Output
• Gross value added
• China GDP
• History of accounting
• Human Development Index
• Income distribution
• Input–output model
• Intermediate consumption
• List of global issues
• Macroeconomics
• Material Product System
• Measures of national income and output
• National Accounts
• National agencies responsible for GDP measurement
• National income
• National income and product accounts
• Natural capital accounting
• Net output
• Operating surplus
• Philosophy of accounting
• Production (economics)
• Productive and unproductive labour
• Property income
• Questionnaire
• Real prices and ideal prices
• Richard Stone
• Sectoral output
• Simon Kuznets
• Social accounting
• Social accounting matrix
• Statistical survey
• Stock and flow
• Survey data collection
• Survey (human research)
• Survey methodology
• Sustainability accounting
• System of Environmental and Economic Accounting for Water
• System of Integrated Environmental and Economic Accounting
• Value added
• Wassily Leontief

References

• Frits Bos, “Value and income in the national accounts and economic theory.” Review of Income and Wealth, Series 43, Number 2, June 1997.[32]
• Frits Bos, "Meaning and measurement of national accounts statistics". Paper discussed online, at the World Economics Association’s Conference on the Political Economy of Economic Metrics, 28 January-25 February 2013.
• Utz-Peter Reich, National Accounts and Economic Value: A Study in Concepts. New York: Palgrave, 2001
• Paul Studenski, The Income of Nations; Theory, Measurement, and Analysis: Past and Present. New York: New York University Press, 1958.
• Andre Vanoli, A History of National Accounting, IOS Press, Amsterdam, 2005
• Carol S. Carson, Jeanette Honsa, "The United Nations System of National Accounts: an introduction", in: Survey of Current Business, June 1990 [33]
• CEC, IMF, OECD, UN & World Bank “System of National Accounts 1993”. Commission of the European Communities-Eurostat, International Monetary Fund, Organisation for Economic Co-operation and Development, United Nations and World Bank, Brussels/Luxembourg, New York, Paris, Washington, 1993, xlix + 711 pp.
• EC, IMF, OECD, UN & World Bank “System of National Accounts 2008”. European Commission, International Monetary Fund, Organisation for Economic Co-operation and Development, United Nations and World Bank, New York, Dec. 2009, 1993, lvi + 662 pp.
• The Review of Income and Wealth [34]
• United Nations Statistics Division (UNSD) “National Accounts".
• Zoltan Kenessey (Ed.), The Accounts of Nations, Amsterdam IOS, 1994.

External links

• Glossary for SNA 1993
• SNA 2008 Manual
• SNA 2025 Manual
• IMF, Manuals for National Accounts and Prices Statistics
• OECD Glossary of Statistical Terms 2008
• OECD, Understanding National Accounts Second Edition 20 October 2014
• Eurostat, ESA 2010 Manual European System of National Accounts
• Eurostat, Building the System of National Accounts 2014
• UK Office of National Statistics, Glossary of economic terms 2016
• UK Office of National Statistics, An introduction to the UK National Accounts
• UK Office for National Statistics, A guide to the UK National Accounts: March 2020
• UNSD, National Accounts Handbooks portal
• UNStats Glossary of macroeconomic terms and definitions 2025
• U.S. National Product and Income Accounts glossary of terms
• U.S NIPA Handbook: Concepts and Methods of the U.S. National Income and Product Accounts