System of National Accounts

The System of National Accounts or SNA (until 1993 known as the United Nations System of National Accounts or UNSNA^[1]) is an international standard system of concepts and methods for creating national accounts.^[2] It is nowadays used by most countries in the world. The first international standard was published in 1953.^[3] Manuals have subsequently been released for the 1968 revision, the 1993 revision, and the 2008 revision.^[4] The pre-edit version for the SNA 2025 revision was adopted by the United Nations Statistical Commission at its 56th Session in March 2025.^[5] 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, media, academics and interest groups from all nations.^[6]

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

Adherence to SNA standards by national statistics offices (NSO's) and by governments is strongly encouraged by the United Nations, but using SNA is in principle voluntary and not mandatory. What countries are able to do, will depend on available capacity, local priorities, and the existing state of statistical development. Government agencies determine their own policies for economic statistics. However, cooperation with SNA has a lot of benefits in terms of data comparability and quality, 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.^[7]

The SNA-based European System of Accounts (ESA)^[8] 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.^[9] Another exception is North Korea (the DPRK).^[10] North Korea is a member of the United Nations since 1991,^[11] but does not use SNA as a framework for its economic data production. Although North Korea’s Central Bureau of Statistics does traditionally produce economic statistics,^[12] using a modified version of the Material Product System, its macro-economic data area are not (or very rarely^[13]) published for general release.^[14] UNDP and the Bank of Korea produce a few estimates; the accuracy of the Bank of Korea estimates is in dispute.^[15]

SNA has now been adopted or applied in more than 200 separate countries and areas,^[16] although in many cases with some adaptations for unusual local circumstances.^[17] 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, data and classifications.^[18]

The global 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,^[19] and Eurostat. The European Commission is also involved, via membership of the Intersecretariat Working Group on National Accounts (ISWGNA) set up by the United Nations Statistical Commission (UNSC) to promote cooperation between statistical agencies worldwide. All these organizations (and associated/related organizations) have a vital interest in internationally comparable economic and financial data, based on data sets obtained regularly from national statistics offices, and they play an active role in the regular publication of international statistics for data users worldwide. The SNA accounts are also "building blocks" for many more macro-economic data sets which are created using SNA data.

History and actuality

The first attempts at national accounting by individual researchers, from the 17th century through most of the 19th century, aimed mainly to estimate national income and national wealth. The first known attempt in England was by William Petty, in 1665. Petty tried to work out how best to spread the tax burden caused by state spending on the second Anglo-Dutch War (1665-1667). For this purpose, he estimated the income and capital of England.^[20] The new science was often called “political arithmetick” (a term invented by Petty) – it aimed to calculate what the best policies would be for the state and the country, with recognition of different economic, social and political interests at stake. The first estimate of “value-added” in England was created by Arthur Young around 1770, in a production account for agriculture; he also created a national income estimate for England.^[21]

At first individual researchers in different countries followed their own approach, although they borrowed ideas from each other. Subsequently interventionist governments began to organize much more statistical research, and used national income & wealth estimates on a regular basis to inform their fiscal, social and economic policies.^[22] The production of “official statistics” was increasingly delegated to separate statistical authorities, bureaus or institutes with considerable scientific autonomy, to safeguard the objectivity and integrity of data reports.

The first official estimates of national income were made in Australia (1886), Canada (1925), Soviet Russia (1925), Germany (1929), Netherlands (1931), New Zealand (1931), United States (1934), Turkey (1935), Yugoslavia (1937) and Switzerland (1939).^[23] In Britain, the Central Statistics Office established in 1941 created the first official white papers with annual estimates of national income and expenditure, which subsequently became a standard feature of the Blue Book.^[24]

The first global national accounts standard, SNA 1953, was an initiative of the United Nations Statistical Commission. The UN believed that the creation of internationally comparable economic data was essential for its own work, and that such data would also serve many other policymaking needs of government and intergovernmental agencies. UNSD provides a useful overview and summary of the historical evolution of SNA across the last 70 years, with supporting documentation.^[25]

Nowadays, the role of the state in the economy has become much larger (see Wagner's Law).^[26] As a corollary, the standard national accounts have become much more sophisticated and comprehensive. The aim is now to account systematically for almost everything that happens in the national economy, plus its external transactions. This has to be done in a way that both follows standard recording principles and measurement criteria, and satisfies the data needs of a much wider group of data users.

These data users are not just governments or international and intergovernmental organizations, but also corporations, business people, academics, NGO's, thinktanks, research institutes, interest groups and political parties, media organizations and individual researchers. The global rollout of SNA is no longer the task of the United Nations only. It is shared with other intergovernmental organizations, each of which has its own area of expertise (principally the IMF, OECD, World Bank and Eurostat). Regional SNA advisory organizations and individual experts are also involved.

In the modern world, national accounts data has become essential for macro-economic forecasting; decision making on monetary policy, state subsidies and debt management; fiscal policy and fiscal surveillance; government policy analysis in many other areas; macro-economic research and sector studies; and academic, business and investor research about all kinds of economic trends. Globalization has greatly increased demand for detailed economic data on international transactions, international investment, and international comparisons of economies.

All of this means that detailed 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)”.^[27] To create comparable data for all countries, requires a conceptually rigorous, logically consistent accounting system, and standardized measurement practices. SNA provides that unitary framework, for the whole world. It also makes an important contribution to democratic participation and democratic representation.^[28]

The Penn World Tables project provides long-run historical time series for SNA-based gross product, national income and capital formation statistics, covering most countries in the world. This data is used by economists, econometrists and economic historians for statistical comparisons and trend analysis across longer intervals of time.^[29]

The flagship academic journal for research on national accounts is the online Review of Income and Wealth, published since 1951 by the International Association for Research in Income and Wealth. Other journals include the Journal of Income and Wealth, the National Accounting Review, Journal of Economic Perspectives, Survey of Current Business,and the Review of Economics and Statistics.

Series of technical papers and documentation covering national accounts topics include the United Nations Statistics Division publications, the OECD Statistics Working Papers, IMF Staff Papers, IMF Working Papers, World Bank documents and reports and Eurostat statistical working papers. Often national statistics offices publish their own methodology papers, and may send a copy to UNSD, which archives it in UNdata.^[30]

The SNA framework

Broadly, the SNA framework integrates a series of standards which guide the production of national accounts, including:

1. Social accounting concepts and methods.
2. Macro-economic concepts and theories.
3. Statistical measurement and aggregation methods.
4. Terminology standards.
5. Classification and categorization systems.
6. Information design principles.
7. Relevant laws, regulations, agreements, obligations and official rules/procedures governing SNA data production.^[31]

The framework guides SNA data 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. It is not possible to set out the whole SNA framework here; this article gives only some of the main points. The official SNA manuals (and associated handbooks and guidelines) provide in-depth and detailed coverage.^[32]

Components

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

In reality, however, the sequence of the data production process may not be so linear and straightforward. Considerable methodological discussion may occur before the decision is made to use an estimate for the official accounts. There may be lot of information to assemble and collate, at different stages of the work. One accounting entry may be derived from other accounting entries, or it has to fit exactly with other accounting entries. There are often many different rules and guidelines to follow, at different levels of abstraction. There may be 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. Organizationally, different departments or separate institutes may each create different parts of the national accounts, which are then integrated by a core group of statisticians, accountants and economists.^[33]

In practice, the SNA framework used by national accounts statisticians has the following main components:^[34]

1. Calendars, scripts, planning agenda's and deadlines for the annual and quarterly production/publication cycles of SNA data and for statistical development projects.
2. Required economic observations and observational data, collected from a variety of sources.
3. Survey instruments (including questionnaires, sampling frames, data collection and data coding systems, data compilation methods and econometric models).
4. Coding, categorization and classification systems for observations and data sets.
5. Purpose-built secure data storage and information storage systems^[35] which include a library collection, an archive, networked databases and data warehouses.
6. A legal framework and NSO protocols for the process of SNA data production, publication, and dissemination.
7. Registers of institutional units, sectors and sub-sectors defined by institutional type and economic activity.
8. A set of logically related economic processes, concepts, equations and categories, for which empirical measures are produced.
9. Price and volume indexation methods and rules, and a portfolio of indexes which are continuously updated (for the purpose of uniform valuation and estimation).
10. Definitions of accounting terms, accounting concepts, account equations, account derivation principles and standard accounting procedures.
11. Accounting and recording rules for timing, valuation, grossing, netting and consolidation.
12. Statistical aggregation rules and inclusion/exclusion rules.
13. Measuring techniques, data calculation methods and estimation methodologies.
14. Specifications of standards for the structure and content of core accounts and supplementary accounts.
15. Information design specifications for account formats, layouts and publishing.
16. A compilation system for allocating data entries/lines to the accounts.
17. Systems for storing finalized economic statistics, and the publication of data series (the finished products, which can also be used to derive/create other statistics).
18. Methods and models for testing and checking data quality, data reliability, and revision effects.
19. Systems for providing access to data collections online and offline, and for sending/receiving statistical information internationally.
20. Systems for outreach, advocacy, training and knowledge-sharing about SNA theory and practice.

All these aspects have to be identified, decided on, approved and documented by the national accounts team and the NSO management, as the official methodology. The NSO has to be able to "account for the accounts", i.e. what was done, how it was done, why it was done, where it was done and who did it. It must be possible to track down the whole data production process for every part of the accounts, from beginning to end.

• The SNA concepts form a logically consistent system. Its categorization is conceptually coherent, mathematically rigorous and testable. However, in practice it is not exactly 100% consistent. Statistical discrepancies may occur between different approaches to estimating a stock value or a flow value. Conceptual boundary problems can occur, because the relevant items that have to be counted do not fit exactly with an accounting concept, or because the conceptual boundaries of a category are difficult to apply empirically. There can also be interpretation disputes about how the accounting definitions should be applied in specific cases. In principle, a variable or category should be measured in the same way (using the same method) year after year, but if this is not possible in practice for some reason, data distortions can occur that have to be resolved in some way. It can happen sometimes that data go missing, creating data gaps.
• In a double-entry accounting system, for every item of expenditure/payment there exists in principle an item of revenue/income or receipt (and vice versa), for every debit there is a credit (and vice versa), and for every withdrawal there exists an addition/deposit. This enables checks and controls for the accuracy and reliability of the estimates. In the case of Balance of Payments data, the international transactions are usually measured both by the sending country and the receiving country, enabling reliability checks of the data sets.
• In principle, each line-item in the core accounts, whether a large or small aggregate, can be derived by adding/subtracting other items in the accounts and via standard equations, and the tallies can be verified exactly.
• 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).^[36] In Europe, the ESA 2010 implementation and the introduction of other statistical improvements had the effect of raising the level of EU-28 gross domestic product (GDP) by 3.7 % in 2010.^[37]

From observables to estimates for SNA stock values and flow values

The observables about the national economy which are the basis for SNA accounts concern the recorded activities of buying and selling; owning, paying and renting; lending and borrowing; disbursing, receiving, depositing and saving; leasing and hiring; financial gains and losses; insuring, charging, taxing and levying; and various other types of financial claims and counter-claims. These economic observables can be identified, allocated and grouped for accounting purposes using six criteria:

1. Economic actions involving flows of money, goods and services which create, transform, exchange, transfer or destroy (extinguish) economic value, or which change the value, volume or composition of assets and liabilities. The question here is: what sort of economic action is this?
2. Human purposes for the actions, behaviors and functions of transactors involved in transactions. A transaction is defined as an interaction between separate institutional units which occurs by mutual agreement or through the operation of law, and involves an exchange of value or a transfer of value. The question is: what is the aim or function of the transaction or group of transactions?
3. Context, location or setting of the transactions or assets/liabilities. Where or under whose authority does a transaction occur, or how does an ownership title/claim arise and change?
4. Transaction records expressed as money prices or physical volumes (sales, purchases, transfers, incomes & expenditures, and other payments, whether in cash, on credit or in kind). What and where is the registered price data required to estimate an accounting category?
5. Ownership records for, and changes of, all kinds of asset holdings, liabilities, debts, deposits and financial claims owned by persons and by organizations. What and where is the registered ownership data required to estimate an accounting category?
6. Effects (measurable impacts or consequences) of economic activity. What can observable and quantifiable economic effects tell us about the magnitudes of economic variables and accounting categories? For example, the data about a natural disaster can help to estimate the value of capital losses for the country.

Using information about these six criteria and SNA accounting rules, statisticians categorize, group, aggregate and reaggregate all the observables into a large set of 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, so that the trend can be measured. There are three noteworthy exceptions:

• Some non-observed items also exist in the accounts, which are derived from observables by imputation, inference, interpolation, or extrapolation.
• Some financial account entries are not called "stocks" or "flows" of value, but positions; a position refers to the situation of assets and liabilities held at a specific point in time. This occurs for example in balance sheet accounts and external transactions accounts (Balance of Payments accounts, foreign investment).
• Some supplementary accounts (called supplementary/supplemental tables, satellite accounts, thematic accounts or extended accounts) may show the relationship between financial stocks/flows and relevant social or physical quantities (such as demographic, geographic, environmental or employment variables). In this case, a sum of money is not related to another sum of money, but to a physical, environmental or social aggregate.

Part of the work involved in allocating observables to categories can be automated with the aid of computer programmes, but part of the work requires the human judgement of SNA statisticians. Some transactions are easily identifiable and countable, because they always occur in the same way, and for the same purpose. The way these transactions are recorded is plain, straightforward and uncontroversial. But there are other transactions which are much more complex and changeable - they may not be consistently recorded, and therefore they are more challenging to categorize and allocate correctly for accounting purposes.

Institutional units

To compile the whole inventory of SNA stock values and flow values, a complex grid of concepts, definitions and rules is applied. In this way, all the base data collected to build the accounts is ordered and structured. It begins with grouping the types of “institutional units” of a country, guided by the Classification of Institutional Sectors. An institutional unit is a separate economic entity which can in its own right engage in production and/or trade with other entities, receive income, own assets and incur liabilities (debts, or obligations to pay). Normally an institutional unit maintains its own accounts. Institutional units are usually legally defined organizations, social groups, or households consisting of one or more economically active persons. The main types of institutional units are:

• Financial corporations.

• Non-financial corporations.

• Non-incorporated enterprises.

• Government organizations.

• Households.

• Non-profit institutional units.

• Foreign institutional units (a source of balance of payments data about external transactions such as foreign trade, investment, transfers, taxes and remittances).

Institutional units can be grouped in sectors, and institutional sectors also contain sub-sectors, which identify and distinguish e.g. public and private, market and non-market enterprises, and domestically owned and foreign-owned enterprises, as well as different types of households. Usually the characteristics of all units are registered in large databases with metadata, and are regularly updated. These databases are the largest, most detailed collection of information about all the organizations active in the national economy.

Industrial classification

All economic activities of institutional units in a country are identified and grouped with the aid of the 2023 International Standard Industrial Classification of All Economic Activities (ISIC version 5) or one of its predecessors.^[38] 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. Some classifications are universal, others are tailored to local conditions which could be relatively unique. At more detailed levels, the classification systems may be guided by existing SNA standards, but they may also be adapted to local circumstances or specific purposes (depending on the economic structures and processes involved). For example, the IMF Balance of Payments statistics modify and expand the SNA standards for external transactions.

The standard classification systems are designed to enable international comparisons. But they are also designed to provide data that give insight into local economic conditions. Statisticians normally try to design categories which combine standardization requirements plus 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 if they are not consistent with what the government requires, then the statistical information is not useful. So this matter has to be thought through carefully.

Categories and classifications in SNA are not so easily changed, because that can create new problems of statistical comparability, and because it can change the estimates of related statistical aggregates. Any classification change must be consistent with SNA concepts. Usually the majority of changes occur when a new SNA revision is released. Examples of some other global standard classifications that are, or will be applied in SNA are:

• OECD Benchmark Definition of Foreign Direct Investment 2025 (Fifth Edition) which sets the international standard for the compilation of FDI statistics, consistent with the Integrated Balance of Payments and International Investment Position Manual, Seventh Edition (BPM7) and SNA 2025.^[39]

• Harmonized Commodity Description and Coding System (HS, 2022). For classifying internationally traded goods in external trade statistics feeding into goods accounts.

• System of Environmental-Economic Accounting (SEEA-EA, 2021). For accounting for ecosystem services, conditions, and natural capital within the national accounts.

• Individual Consumption According to Purpose (COICOP, 2018). For household final consumption expenditure in national accounts, CPI compilation, and household budget surveys.

• Status in Employment (ICSE, 2018). For classifying jobs by employment relationship in labour force surveys, social statistics, and labour accounts.

• Classification of Financial Assets and Liabilities 2017 for the categorization of financial instruments (e.g., equity, debt securities, loans, currency and deposits, insurance and pension schemes, financial derivatives, other accounts receivable/payable).

• Activities for Time-Use Statistics (ICATUS, 2016). For classifying paid and unpaid work in time-use surveys and satellite household accounts.

• Classification by Broad Economic Categories (BEC, 2016). For converting trade data into end-use categories (capital goods, intermediate goods, consumption goods), integrating national accounts data and industrial statistics.

• Central Product Classification (CPC, 2015). For classifying products and services in supply and use tables, deflators, trade statistics, and price-volume measures in the SNA.

• Standard Classification of Education (ISCED, 2011). For classifying education levels in human capital accounts and public education expenditure.

• Extended Balance of Payments Services Classification 2010 (EBOPS, 2010) for standard breakdowns of the international trade in services (debit and credit) by types of services.

• Balance of Payments and International Investment Position Manual (BPM, 2009). For compiling external sector statistics including current, capital, and financial accounts (BPM7 is released in 2025).

• Standard Classification of Occupations (ISCO, 2008). For classifying occupations in labour statistics, productivity analysis, and workforce accounts.

• Standard International Trade Classification (SITC, 2006). For organizing international trade statistics in time series and analytical frameworks.

• Functions of Government (COFOG, 2000, next revision expected to be finalized in 2027). For classifying general government expenditure by function in public finance and fiscal analysis.

• Balance of Payments Codes for Standard Components and Additional Items 1999 (BOPCODE, 1999) which defines the standard components for balance of payments data and international investment position data.

• Purposes of Non-Profit Institutions Serving Households (COPNI, 1993). For classifying NPISH final consumption expenditure in the SNA institutional sector framework.

• Outlays of Producers by Purpose (COPP, 1993). For classifying producer expenditures by function in satellite accounts such as R&D, health, or environment.

Ten core SNA accounts

Traditionally, the SNA framework provides a set of ten core accounts. The detailed design and terminology has changed somewhat through successive revisions, but conceptually the design remains more or less the same. The accounting principles for each of these core accounts are explained in the SNA manual. Broadly speaking, the ten traditional accounts deal with four main topics: (1) national income & product, (2) capital formation and investment, (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. The ten core accounts can be described as follows:

1. The production account of economic activity that generates new incomes (the components of gross output and gross value-added).
2. The primary distribution of income account (the distribution of gross national income generated).
3. The redistribution of income account (including transfers and social spending by governments).
4. The use of income account (consumption expenditure and saving, sometimes also complemented with household assets/liabilities).
5. The capital account (investment, capital formation and accumulation).
6. The (domestic) financial transactions account ("flow of funds", tracking changes in assets/liabilities and debt financing).
7. The revaluation account (price changes in assets/liabilities, including capital gains and losses).
8. The other changes in assets account (changes in assets, liabilities and net worth which are not caused by transactions).
9. The balance sheet account of assets, liabilities and net worth.
10. The external transactions ("rest of the world") account (integration of current accounts, capital accounts and financial accounts).

Most member countries of the United Nations compile these ten "core" accounts. However, national statistics offices do not provide a complete national set of all “possible” SNA accounts. They might not even 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 applicable/relevant/useful, (2) that it is currently 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.

The SNA 2025 framework changes the formats of the core accounts to some extent. An important new step in SNA 2025 is the acceptance of more comprehensive household accounts, which according to many experts ought to be a standard feature of the SNA framework (household income, expenditure, assets, liabilities/debts and net wealth). The experience of the 2008 financial crisis revealed that changes in the financial position of households can have very large macro-economic effects. Traditionally, statistics offices have collected data on household income and spending, but not for the whole financial position of households. The main reason usually was that some respondents find the financial survey questions too intrusive, and do not want to cooperate. However, in the digital era (and because of legal changes), people's attitudes have changed, so that they are more willing to provide information (with proper data custody, and anonymized by the statisticians), because they recognize its national importance.

Satellite accounts and supplementary tables

Each of the SNA core accounts can be complemented with annexes providing extra details, sub-accounts within the core accounts, satellite accounts separate from the core accounts, and supplementary tables (or account variants) providing additional information. Some of these added accounts follow an existing SNA standard, but others could be mainly designed by a national statistics office for its own (limited) uses in local conditions. Ideally all extra national accounts or tables produced by an NSO should be internationally comparable, but that may not always be the case. The non-core accounts are in principle always optional (there are exceptions to this norm in the European Union). Whether extra accounts or extra tables are compiled and published by a national statistics office, depends mainly on their practical usefulness. National statistics offices produce them, if there is a need or demand for such accounts, and if 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.

Starting with the 1968 SNA revision, standards are provided for input-output tables (I/O 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). The supply and use tables (SUT tables)^[40] are a further development of the input-output analysis for which standards were first created in SNA 1993. These SNA tables provide a detailed breakdown of the origin and use of goods and services in the national economy. They show in matrix format the supply of goods and services from production and imports, and their destined uses (intermediate and final consumption, capital formation and exports). In the European System of Accounts (ESA 2010), it is compulsory for EU member states to provide both SNA standard input-output tables and SNA standard supply & use tables to Eurostat, with a deadline of three years.^[41]

The term "satellite accounts" (comptes satellites) originated in France.^[42] French statisticians created the first satellite accounts in the late 1960s, initially with experimental housing accounts in 1968. By the 1970s, they had developed systematic satellite accounts for health, education, research, social protection, and transportation.^[43] The goal was to provide detailed analyses of specific sectors to support government planning – maintaining consistency with the central national accounts framework, without altering it.^[44]

The U.S. Bureau of Economic Analysis (BEA) developed auxiliary accounts for its NIPA framework already in the 1950s, but they were not called "satellite" accounts.^[45] In the late 1980s, the demand for environmental accounts was met by the creation of satellite accounts.^[46] The US Bureau for Economic Analysis officially adopted a satellite account framework for research & development in 1994 and later for tourism and the space economy, referring to SNA guidelines.^[47]

Satellite accounts were officially recognized and defined for the first time in SNA 1993, and elaborated in SNA 2008.^[48][49] Several standards for satellite accounts are outlined in SNA 2008 and SNA 2025. Often more comprehensive explanations of standards and their application have been given in special handbooks, brochures or working papers. The OECD provides a guide to designing satellite accounts.^[50] In 2019, a review suggested that satellite accounts had been implemented for 21 different topics, with another 11 account topics being planned.^[51] Another source claimed that over 80 countries had implemented satellite accounts by 2019, with more than 20 different topics.^[52] A 2020 survey about the national use of SNA satellite accounts discovered that 241 satellite accounts had been 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).^[53]

In SNA 2025, the term "satellite account" is formally abandoned in favour of the terms "thematic account" and "extended account". Thematic accounts disaggregate and rearrange already existing items in SNA core accounts, to make particular aspects of economic relations more visible and explicit. In other words, they provide extra details and breakdowns for the totals given in core accounts. Extended accounts go beyond the conceptual boundaries of the SNA integrated framework, often linking SNA accounting data to external data, with the aim of enabling more comprehensive insight about a topic of interest (for example, demographic data, geographic data, employment data, population data, data on natural resources). In this case, SNA data is linked to non-SNA variables, following standard conventions to assist comparability. The SNA 2025 Manual enlarges the scope of macro-economic accounting, and defines how SNA standards can be linked to non-SNA standards. For example, SNA 2025 recognizes four kinds of capital: economic capital, human capital, natural capital and social capital.

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, an econometric 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.^[54] 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.^[55]

In principle, there is a place in SNA for almost every type of transaction in the economy. However, some things that happen in the economy are not measured in SNA accounts.^[56] That is either because they are conceptually excluded from the SNA framework, or because it is practically difficult to estimate them accurately (for example, specific changes occurring within an accounting interval, or across several accounting intervals; the sales of specific types of used goods; illegal transactions).

SNA statisticians get the data and information they need to compile the accounts 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 sampling frame based on a geostatistical database for the survey population, and mathematical models. Some direct surveys are taken exclusively for the purpose of compiling national accounts, but the national accounts statisticians also use relevant data from other surveys which are not specifically carried out only for national accounts purposes.

• 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 government, state government, provincial government, district government and local government authorities. Included are the general government accounts, budget allocation and expenditure reports, and expenditures on specific items (for example, defence and education).

• Central bank, financial institution 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 types of financial intermediation. In some cases, private research institutes can provide relevant information.

• 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, impractical 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 empirical indicators that can reliably predict the quarterly trends.

• 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 information on retail prices and retail volumes, tourism data and transport/mobility data.^[57] Different government agencies also share or exchange information from their digitalized administrative 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.^[58] Much of the detailed source data used to produce statistics is confidential or secret information (for privacy, military, official and business reasons). Normally only the anonymized aggregates derived from the detailed base data are accessible and published in the accounts (typically many more tables and accounts are produced by national accounts staff which are not accessible to the general public, or which are not officially published).

Normally there exists a national or federative legal framework^[59] for the collection and publication of all official statistical data (not just SNA data), which defines (1) the obligations to supply and collect data, (2) legitimate use of data, (3) protection of data, (4) privacy rights and (5) the release of data. 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 (see, for example, the 1980 Paperwork Reduction Act of the United States).

An important reason why some types of information are traditionally not collected, is simply because there is resistance to supplying it, or a lack of trust. Ultimately SNA statistical research cannot be done successfully, if people do not cooperate with information requests. Different countries have different laws, but usually there are norms and rules for data collection. A lot of thought goes into finding the best ways to approach individuals and organizations for information requests, so that the response rate is high, the response burden is low, response errors are low, and response quality is high.

The world's largest national accounts

How the “largest national accounts” should be defined is debatable.^[60] The criterion used here is population size, because as a general rule the larger the population is, the larger will be the volume and complexity of transactions and transfers that have to be accounted for. In 2025, the world’s eight largest countries by population together had about 4.67 billion residents, which is equal to about 56.7% of the total world population. The United States and the European Union are included as "countries", because they produce integrated national accounts based on data from their member states.

Annual SNA-based estimates for the People's Republic of China (excluding Hong Kong,^[61] Macao^[62] and Taiwan^[63]) 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).^[64] In 1992, 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.^[65]

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).^[66] Participation in the ESA system is mandatory for European Union member states.^[67] All EU Member States are legally obliged to use ESA 2010 for their national and regional accounts.^[68] 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.^[69] 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.^[70] 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.^[71] 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.^[72]

Regional organizations for SNA development

The United Nations Economic Commission for Europe (UNECE) set up in 1947 by the UN Economic and Social Council (ECOSOC) promotes the implementation of SNA in UNECE countries, especially in South-East European (SEE) countries and East European, Caucasus and Central-Asian (EECCA) countries.^[73] UNECE maintains its own statistical database.

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)^[74] 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).^[75] The Statistical Institute for Asia and the Pacific (SIAP) of the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) provides trainings in SNA knowledge.^[76]

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 associated countries. The organization promotes harmonized national accounts, following SNA 1993 and moving to SNA 2008 and SNA 2025. 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 Antigua and Barbuda, Bahamas, Barbados, Belize, Dominica, Grenada, Guyana, Jamaica, Haiti, Montserrat, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, Suriname, Trinidad and Tobago. 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 SNA data

No single agency has a monopoly on publishing SNA statistics. There are few universal standards for how they are published. Published SNA statistics can be freely used and cited by the public, provided that the source is acknowledged correctly by the user. Statistics offices typically provide a lot of information free of charge (as a government-funded public service). But they do charge fees for many printed publications, for the supply of specialized data sets, and for specialized data services. How exactly the boundary between paywall data and free data is drawn, and what the costs are, can vary from country to country. It may depend on who the data users are, how the data is used, and what the local laws and policies permit.

For particular sorts of SNA 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. Detailed national SNA statistics are usually available from national statistics offices or national governments. Data users have the option of getting their national data sets either from national statistics offices, or from intergovernmental bodies, or from some third-party source (such as central banks, economic research institutes or academic collections).

International agencies will often include adjusted 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 which are at present still outside the SNA aegis.

Economic and financial data produced by 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 by national statistics offices, 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.

Current and constant US dollar equivalents can be found in the online UN National Accounts Main Aggregates Database. Additional variables can be accessed online in the UNdata Portal. Alternative sources of GDP and components in US dollars at current and constant prices are the World Development Indicators (WDI) of the World Bank, and the World Economic Outlook Database of the IMF. Both the World Bank and the IMF use exchange-rate converted GDP estimates and PPP-adjusted measures. The IMF publishes comprehensive SNA-based Balance of Payments statistics for the world's countries, as well as comparative statistics on government finance. The OECD^[77] and the World Bank publish a lot of SNA-based comparative economic statistics, country reports and regional reports. To make the comparisons, the data series often have to be converted to a common currency (usually US dollars).

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, the World Bank and Eurostat sometimes adjust national SNA data according to their own methodologies.

National accounts data is notoriously prone to revision. A very large number of different data sources, entries and estimation procedures are involved 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 later be revised, sometimes several times. The revisions may be quantitatively slight, but cumulatively across e.g. ten years they can sometimes alter a trend significantly. The researcher has to bear this in mind when seeking to obtain consistent data series. Often it is possible to link old and new data series using some suitable chaining method. Data revisions are another reason for correctly citing the source of the data.

Data quality and coverage

SNA data quality is relatively good, because there are data standards and because the data are regularly checked and monitored by several agencies, 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 five 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 policymaking 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; pervasive illiteracy; the absence of a cash economy; survey access difficulties because of geographic factors, socio-political instability, pervasive corruption, disasters, pandemics,^[78] public hostility to statistical surveys, lack of accurate population and address registers, armed conflict and large-scale wars; or large-scale mobility/migration of people and assets.^[79]
• Degree of autonomy: some statistical agencies have more scientific autonomy, mandates 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, professional 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 lengthy research traditions. However, developing countries have the advantage, that in creating their statistics production systems, they can often 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.
• Legal frameworks: there can be specific legal rules which influence the quality and coverage of national accounts, because they can facilitate, or restrict, or block statistical research in specific areas.

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.^[80] Some of the world's states are part of other international/interstate 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 interstate 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.

SNA Developments

SNA continues to be developed further. International conferences are regularly held to discuss various conceptual and measurement issues, and proposed revisions. This is necessary, because the world changes,^[81] new data needs emerge, new coordination/integration challenges arise, and new production techniques become available.^[82] The proposed SNA 2025 features many new standards for supplementary SNA tables on different topics.^[83] 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,^[84] the measurement of the trade in various services and of productivity, the treatment of insurance payments, the grey and informal 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.^[85]

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^[86] and works with the Advisory Expert Group (AEG).^[87]

Discussions and updates are reported in the news bulletin SNA News and Notes.^[88] Official SNA revisions are always documented at the UN Statistics Division site.^[89] For the 2008 SNA revision, the full final text is available online.^[90] For the 2025 Revision, only the pre-edit document is available so far; the final official text still has to be approved and published.^[91]

Achievements of SNA

• After more than 70 years of development across the world, the System of National Accounts is the only comprehensive, internationally agreed standard for national accounting practice. It is now used by almost all governments, universities, and international financial institutions, as well as by enterprises, economic research institutes, thinktanks, NGO's, interest groups, media and private researchers. It provides detailed guidance to national statistical offices in more than 200 countries and territories. 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 most of the important 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, supply and use 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 and territories 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. SNA data sets enable opinions and hypotheses about the economy to be tested in a comprehensive way, and can contribute to greater objectivity about economic affairs. 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. While SNA accounts are not designed to provide all the data relevant to solving all of society's problems, they can complement other information sources to improve understanding, reasoning and effective action.

• 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 intergovernmental organizations such as the United Nations, IMF, World Bank, OECD, and Eurostat. This cooperation is mostly based on voluntary agreements and mutual understanding among countries. It enables the use of shared methodologies, terminology, a common language 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 emerging, transitional, and 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 research and discussion ensure that the SNA can meet new challenges, such as measuring the digital economy, accounting for cryptocurrencies, and incorporating environmental sustainability measures. With continual efforts for improvement and refinement, SNA remains an indispensable tool for achieving consistency, comparability, and clarity in the statistical representation of national economies and the world economy.

Debates about SNA

SNA data is used by tens of millions of public servants, private sector data professionals, businesspeople, media 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.^[92] 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.^[93] There do already exist international happiness measures, such as the World Happiness Report, which can be compared with SNA economic variables.^[94] The United Nations introduced the Human Development Index in 1990 specifically because it was felt that economic indicators alone are insufficient to assess human development; economic indicators do not necessarily express the average quality of life of a country’s residents.

Representation issues

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.^[95] The effect of that is (allegedly) a distorted picture of the world. For example, there are the following sorts of criticisms:

1. The SNA system allegedly does not provide explicit detail for particular economic phenomena, suggesting thereby that they do not really exist or are of no significance (for example, Islamic banking, large multinational corporations and small business, the value of natural resources, the value of housework). The largest global capital asset is residential housing (and more generally, real estate),^[96] but there are few internationally comparable economic statistics for it.^[97] In many countries, the national statistics office does already survey and provide household financial statistics, but the statistics are not (or not fully) standardized, often incomplete and therefore not internationally comparable (or difficult to compare).
2. There is allegedly something wrong with the valuation scheme that is being assumed (for example, the productive contribution of capital assets, the income of banks and other financial institutions, and the services of owner-occupied housing).
3. In the valiant attempt to include transactions of all "micro" business activities under general "macro" headings, the true situation is allegedly misrepresented because a large portion of micro-transactions does not easily fit under the general conceptual headings (for example, the informal economy).
4. It is claimed that the traditional structure of SNA, based on the concepts of value-added and capital formation, plus a particular view of assets and liabilities, is in reality no longer adequate to describe the modern economy.^[98] This is (allegedly) caused by (1) successive piecemeal or "patchwork" revisions, which aim to preserve continuity and comparability, but which are now out of step with economic science and economic reality, (2) the increase of non-traditional transactions and economic activities as well as totally new financial phenomena, and (3) changes in the weighting and composition of many different kinds of economic activities which are not adequately reflected in SNA categorization and classification systems — within countries, between countries and between regions.
5. National accounts data on their own are, it is claimed, 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.
6. National accounts data are often revised to some extent after the first release. The effect can be, that financial markets overreact in the wrong way, when the first estimates are published. Sometimes politicians try to interfere with or downplay the figures that are released, to calm the markets (normally this is rare, because the risk is that people will no longer trust the figures, which increases business, political and consumer uncertainty).
7. The international streams of past and present publications about SNA and SNA data can appear to data users as a complex jungle, which lacks oversight, transparency, coherence and consistency. It may take a lot of time and effort to track down the comparative statistics that researchers want to use. Cognitively helpful information design, clear fonts and layouts, and comprehensible language are allegedly often lacking in official publications. Online databases may not be user-friendly. Little comparative research of good quality is done about SNA data users — what data users are looking for, how they use the data, what problems they encounter, what improvements could be made etc. There is no standard user survey with good questions that provides essential and useful information about data users (both organizations and individuals), so that communicating about data can be improved on the basis of reliable evidence.

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 changes in economic activity, national income and economic growth in a standard way, which enables international comparisons. SNA was not designed to include “everything we need to know about a country or about the world”, and it is impossible for SNA to do that. SNA design is a compromise involving many different concerns and interests, but it aims to be the best possible compromise that is currently feasible.

• Many concerns about unmet data needs are being addressed via the design of supplementary standard tables or satellite accounts (thematic and extension accounts), which provide modified SNA aggregates for special uses, or which integrate SNA accounts data with social, demographic, 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. SNA requires standard, comparable accounting formats, and its design has a specific, limited statistical purpose. Some types of data production simply do not fit with that structure and purpose (but SNA data could be combined with data from other sources). The SNA 2025 Manual provides standard conceptual frameworks to address most of the contemporary concerns and data needs, clearly distinguishing between what SNA can contribute and the integration or matching of the SNA framework with non-SNA standards.

• 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 survey populations (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.^[99] There are now more and more different ways to make data available to users, and much more attention is being given to information design to make data understandable.^[100] In the digital era, people have to process much more information in much less time. In order to do this, they have to be able to find/navigate through records, data sets and documents faster. Good information design saves time, effort and money. Data means nothing, if it is not communicated in an effective way so that people can understand it.^[101]

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.^[102] Such measures have already been designed, but so far they have not been widely included in SNA accounts. However, SNA 2025 does broaden the national accounts framework, to account better for elements affecting wellbeing and sustainability, and inform 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 the value of a country's total net output and measures of national income, showing their 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.^[103]

GDP measures are frequently misused by writers who do not understand what they mean, how the measures were produced, or what the measures can be validly used for. Many of the critics of SNA have no real knowledge about the main purpose of SNA, never mind the possibilities and limits of the accounting design. GDP is used for an enormous diversity of comparisons, but many of those comparisons may conceptually not be valid or 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 plainly false — GDP does not measure all economic activity, it is only a measure of the new gross value added generated by production during an interval of time (the net value of a country's output) which, in the production account, equates to certain measures of national income/expenditure.^[104]

For another example, a popular statistic is "public debt as a percentage of GDP". This debt/GDP ratio could be understood (wrongly) to mean that the public debt, or its annual repayment, is a component of expenditure on GDP, or that it represents the size of national income currently required to pay off the national debt. What this debt/GDP ratio ignores, is that the coverage of the public debt variable and the coverage of the GDP variable are quite different. GDP includes only flows of incomes/expenditures and taxes considered to be inside the production boundary, i.e. flows directly generated by production. GDP does not include all the revenues and expenditures of the government, it does not include all the revenues and expenditures in the economy, and it is not a measure of assets or liabilities. The debt/GDP ratio says nothing about the amount of principal and interest that must repaid per year or per quarter. To assess a financial position, debt liabilities incurred must in principle always be related to the total assets held and the total revenues from which the debt can be repaid. It must be made clear how much must be paid each year or quarter to repay the debt (which is not the whole sum). If (say) a couple applies for a home mortgage loan from a bank, the bank usually wants to know much more financial information than just their annual net salary from work. To assess the total "mortgage" of the whole national economy, both public debt and private debt has to be considered - quite often, private debt exceeds public debt.

The main response by statistical authorities to the criticism and misuse of GDP data has not been to abandon or abolish the GDP measure.^[105] Instead, statisticians have provided additional, complementary data sets about phenomena which GDP does not measure, and cannot measure.^[106] 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 official 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^[107] and Maria Mies^[108] 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"^[109] and an imputation for "financial intermediation services indirectly measured" (FISIM). This SNA omission of unpaid housework (because it falls outside the SNA "production boundary"^[110]) is said to obscure the reality that market production depends to a large extent on non-market labor being performed.^[111] In turn, that lacuna in the data allegedly promotes a distorted picture of economic life (which in reality includes both paid and unpaid work).^[112]

However, such criticism does raise technical issues^[113] for the statisticians who would have to produce the standard data, such as:

• whether an international standard method of comparing the value of household services is technically feasible, given e.g. that the precise financial arrangements between household members are difficult to verify and measure, and that the conditions under which the market equivalents for unpaid household services are supplied vary greatly between countries.^[114]

• whether making imputations for the value of women's voluntary work would result in truly meaningful and uniformly valued measures.^[115]

• 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.^[116]

The intention of those who would like to produce standard data for the imputed market value or imputed cost of women's voluntary labor can be perfectly honorable. Many scientific studies already exist on the subject. However, the production and cost of creating this data every year, as a standard procedure, has to be justifiable in terms of scientific feasibility and practical utility. It could be argued that attaching an imaginary price to housework as a standard international procedure, might not be the best data to have about housework. It míght not make people who do housework more valued in the eyes of others, and it might not result in a general improvement of social attitudes and behaviour. There is certainly a permanent need for data on housework and voluntary work, because (as surveys prove) so many people are involved in it. But SNA 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 definitive standard solution (there are proposals for a standard SNA satellite account for household labour).

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 on average, 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.^[117] Robert Eisner estimated that the market value of unpaid housework in money terms was equivalent to about 33% of the value of US GDP in 1981.^[118] Nancy Folbre provides more recent comparative data.^[119]

When she was the head of the International Monetary Fund, Christine Lagarde reportedly 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.^[120]

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 childcare and eldercare supplied by paid caregivers from the public sector, or from the private sector. Many mothers don't care about a GDP number from a statistics office, they care about their children, and do not want to outsource their parenting. With a greying population, the economy will need more children that can replace retired workers in the future; that makes raising children properly a priority (particularly in the first five years of life). The majority of young people with young children cannot afford to hire caregivers themselves.^[121] According to later IMF data, the female labor-force participation rate for paid work in Japan rose from 63 percent in 2012 to 74 percent in 2023,^[122] but estimates of the added contribution to GDP were not very large^[123] (the amount of paid hours worked that are involved in women's "labour force participation" can vary considerably, and in Japan there is still a large gender pay gap^[124]).

According to the International Labour Organization (ILO), about 75.6 million domestic workers are employed in the world, mostly women and migrants, representing 4.5% of all workers (among every 22 workers, one worker is a domestic worker). In terms of their social status, domestic workers remain largely "undervalued, underprotected, and underrepresented". In 2021, the ILO estimated that 81% of all domestic workers were "informally" employed.^[125] They are mainly servants of wealthy people and the professional middle classes.

Left-wing criticism

The Marxist/socialist criticism is basically that SNA categories (1) hide the exploitation of the workers and farmers who produce the wealth, and (2) hide the sources and growth of economic inequality^[126] among the social classes of a country, in terms of disparities in income, wealth and consumption.^[127] The neoclassical concepts and some Keynesian concepts used in SNA are often regarded as unreal, incoherent or non-observable (and therefore scientifically not verifiable or provable). More specifically, Marxian economists have criticized SNA concepts from a different theoretical perspective on the new value added or value product and on capital accumulation.^[128]

From a Marxist perspective, 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 (profit, interest, rent, tax, fees, royalties, honorariums, certain net capital gains, subsidies); the categories are said to be based on an inconsistent view of newly created value, conserved value, and transferred value. One result is that the true profit volume is underestimated in the accounts – since true profit income in a country is larger than operating surplus^[129] – and workers' earnings are overestimated since the account shows the total labor costs to the employer rather than the "factor income" which workers actually receive. If one is interested in what incomes workers 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 make explicit pre-tax and post-tax wage income, the income of higher corporate officers, deferred income (employee and employer contributions to social insurance and retirement schemes) and other labour costs. "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 labour income generated and distributed in the economy.

Marxists are also critical of the lack of integrated statistical information about the financial sector (banking, investment finance, funds management, insurance and real estate) and the lack of interest in stock-flow consistent accounting. In this they are not entirely alone; US government statisticians admit frankly that "Unfortunately, the finance sector is one of the more poorly measured sectors in national accounts".^[130] The financial sector is nowadays the biggest player in international transactions, and strongly influences the developmental path of the world economy, through international financing/directing investment and through assets/funds management. Yet oddly it is precisely this leading sector in the world economy for which systematic, comprehensive, and comparable data sets are not available.^[131]

SNA statisticians acknowledge that alternative measures of gross product, income/expenditure, capital accounts and external transactions accounts are possible. However, they would emphasize that considerable opportunities exist for researchers to reaggregate/rework existing official statistics, to create their own alternative measures. Examples are Alan Freeman's Marxist national accounts group^[132] and the socialist Distributional National Accounts (DINA) framework pioneered by Thomas Piketty, Emmanuel Saez, and Gabriel Zucman.^[133] 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.^[134] In the DINA design, the sum of individual incomes aligns with standard SNA macroeconomic aggregates, providing a consistent and comprehensive picture of income distribution. Future SNA accounts will address some of the concerns raised, via satellite accounts, on topics such as labor inputs, income distribution and financial activities.

Environmentalist criticism

Originally, SNA was designed to provide standard, comparable measures for magnitudes and changes in national income, output, investment, capital wealth and external trade. All of these are essential to understand the causes and patterns of economic growth, and to provide indicators of the trends. However, that approach is now often deemed to be inadequate (and for some, totally wrongheaded - see for example degrowth), because it leaves out crucial variables, such as environmental variables which impact on the whole economy.

The debates about including environmental variables in SNA accounts have carried on for half a century. Nowadays a very large scientific literature exists about the subject. However, for many years it proved difficult to reach a workable international consensus about a feasible SNA methodology for creating meaningful environmental accounts – standard SNA accounts which would be both useful and internationally comparable (keeping in mind the great diversity of environmental conditions in 200+ different countries and territories).

There have been ten main sorts of environmentalist criticisms of alleged deficiencies in SNA accounts.^[135] Most of the criticisms are about things that are not accounted for by SNA, but which (it is argued) ought to be accounted for as a standard procedure.

1. In general, SNA traditionally does not account for most of natural environment (the land, the seas and oceans, the polar ice caps, the biosphere, and the atmosphere) which contains and supports the whole economy, and from which resources are extracted (national accounts do not account for many resources which exist outside national borders, although the production of e.g. oil rigs,^[136] fisheries and other marine industries of national enterprises in the open seas is included in the corresponding national accounts, sometimes in separate blue economy satellite accounts).^[137]
2. SNA’s approach to the valuation of goods, services and assets does not recognize that many environmental variables require a different valuation approach, or a different cost/benefit approach with a different logic.
3. SNA does not account systematically for existing stocks of renewable and non-renewable resources, the use of those resources, and the value of their depletion.
4. SNA does not account for the value of many environmental functions and ecosystems which provide essential supports for human production, consumption and habitats.
5. SNA does not include environmental "externalities" (such as the social costs of pollution) as part of the economy, so that national accounts overstate the net benefits of economic activity for enterprises as against true costs for communities.
6. SNA does not explicitly account for the costs that result from environmental degradation, and the costs of recovery from environmental damage.
7. SNA does not provide adequate data to understand, monitor and evaluate what is required for sustainable economic growth.
8. SNA lacks standard satellite accounts which link economic activity to physical resource flows, pollution impacts, and ecosystem changes.
9. SNA’s concept of value excludes cultural values or any other valuations than what can be expressed in money-units. Spiritual and social dimensions of nature are absent in SNA reports, which are not designed to report on such things.
10. In general, SNA sends out the wrong message about the macroeconomic future for humanity, if it does not account properly for the natural environment (the latter which contains the economy, and is a primary source of its wealth).

Each of these ten concerns has been elaborated and debated in much more detail by many different researchers.

Statisticians' critical views

Statisticians have commented on the limitations of international comparisons using national accounts data, on the ground that in the real world, the SNA estimates are rarely compiled in a truly uniform way – despite appearances to the contrary. People often assume that the data are "precisely accurate", although the data may only be a "best estimate" under the given conditions, or "approximately true" and "indicative". There is often little official transparency about data errors in national accounts.^[138]

Jochen Hartwig once provided 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".^[139] It can happen that the reported percentage change in a macro-economic variable is equal to the possible margin of error in the statistical estimates for that variable.

The "magic" of national accounts is, that they provide an instant source of detailed international comparisons.^[140] 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 not credible. Had there been better education in the use of economic data, a lot of controversies would have been quickly resolved, or they would not occur. The counterargument is, that because countries are applying the same statistical standards and concepts, this already makes an enormous positive difference to data comparability. This positive difference far outweighs the effects of remaining methodological discrepancies in the data of different countries.

SNA producers do not have control over how SNA data will be used. National statistics offices only control what information is released, and when it is released. They act in accordance with a legal framework, and follow directives from the government officials in charge. The data can be used for purposes which are not valid, or used for purposes which the data were never meant to serve.^[141] That is not the fault of SNA producers, but a matter of data awareness, statistical literacy and data user education.^[142]

Both the strengths 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 for the bigger picture. In each account, things do have to "add up" correctly, and the different accounts have to be mutually consistent. The weakness is, that the sheer number of inferences made in compiling data sets increases the possibility of data errors, and can make it more difficult to trace the causes of errors.

SNA data quality has been criticized, on the ground that what pretends to be "economic data" may involve extrapolated estimates using mathematical models, and not direct observations. These econometric models are designed (sometimes with great ingenuity) 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 available 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; at a later stage, the estimates from the model can be checked against relevant new data when it becomes available.

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. They make use of inferences from data that they already have, or from selected data which they can get more easily. Sometimes this procedure can be proved to supply accurate data successfully. But the purist objection to this approach is often that there is a loss in data accuracy and data quality.

• The extrapolated estimates may lack a 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, very large and sudden fluctuation in a variable may be 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", although it is real. The statisticians may not be able to track down and prove why an unusual fluctuation occurred, and adjust the figures according to the "most likely hypothesis".
• Without sufficient observational data from direct surveys and real records, many of the statistical inferences made are not truly verifiable. All one can then say about the estimates is, that they are "probably fairly accurate, given previous and other concurrent data."

Statisticians do admit that data errors and inaccuracies are possible, it is an occupational risk. It would be preferable to have comprehensive survey data available as a basis for estimation. But it is usually possible to find estimation techniques that keep margins of error within acceptable bounds. The real problem may be, that errors can be corrected only quite some time after the publication deadline, in the light of fresh data or additional data. If governments refuse to pay for the production of quality data with qualified staff, statisticians can only do what they are able to do, with the techniques they have. Imperfect statistics may be better to have, than no statistics at all. In the future, digital technology and artificial intelligence will most likely make the production of economic statistics easier, cheaper, faster and better.^[143] In particular, artificial intelligence can potentially provide much faster data error detection. However, artificial intelligence is not a panacea and it may introduce new errors in information systems: “Hundreds of Wikipedia articles may contain AI-generated errors. Editors are working around the clock to stamp them out.”^[144]

Technical and conceptual criticism can always be made of national accounts statistics. SNA statisticians make criticisms themselves, although they may not do so publicly (because they lack authorization to do so - the bottom line for the quality of official national accounts data is adequate funding and staffing, cooperation and trust.^[145]). However, in the end people do want to have comparable macro-economic data, to understand the proportions and magnitudes of an economic situation. This macro-economic data has to be supplied according to deadlines. When it is published, it can have a strong effect on investment decisions and business activity. If data users are not satisfied with the data they get, they may be able to create their own data sets, starting out from publicly available information supplied by statistical agencies. Behind the published statistical totals, there also exist databases, archives and registers with more detailed information used to compile the totals. With appropriate authorization, it may sometimes be possible to obtain extra data and more detailed information. Usually the NSO staff is willing to help,^[146] within the constraints of the relevant laws and rules, and professional protocols. A great advantage of modern digital technology is that data users are in principle no longer restricted to one set of published official SNA accounts - it is possible for specialists to generate a great variety of account variants or alternative accounts, by reaggregating, rearranging and recalculating SNA data in a spreadsheet.

See also

• Accounting identity
• Aggregation problem
• Artificial Intelligence for Environment & Sustainability
• Balance of Payments
• Bureau of Economic Analysis
• Capital account
• Capital formation
• Capital gain
• Chained volume series
• Circular economy
• Classification
• Classification of Individual Consumption by Purpose
• Colin Clark (economist)
• Compensation of employees
• Consumption of fixed capital
• Disposable income
• Domar aggregation
• Double counting (accounting)
• Double deficit (economics)
• Double-entry bookkeeping
• Economic development
• Economic growth
• Economic sector
• Environmentally extended input–output analysis
• Environmental accounting
• European System of Accounts
• Export performance
• Factor cost
• Factor income
• Final consumption expenditure
• Fiscal gap
• FISIM
• Fixed capital
• Fixed investment
• Ragnar Frisch
• Generational accounting
• Raymond W. Goldsmith
• Robert J. Gordon
• Government final consumption expenditure
• Green accounting
• Green gross domestic product
• Green national product
• Gross Domestic Product
• Gross domestic income
• Gross fixed capital formation
• Gross loan
• Gross National Happiness
• Gross National Income
• Gross national income in the European Union
• Gross National Product
• Gross operating surplus
• Gross Output
• Gross private domestic investment
• Gross value added
• China GDP
• History of accounting
• Household
• Household final consumption expenditure
• Household net worth
• Human Development Index
• IMF Balance of Payments Manual
• Income distribution
• Input–output model
• Intermediate consumption
• Inventory
• John Whitefield Kendrick
• Labor share
• Leprechaun economics
• List of countries by GNI per capita growth
• List of countries by real GDP per capita growth
• List of global issues
• List of Latin American and Caribbean countries by GDP (nominal)
• List of national and international statistical services
• List of sovereign states by current account balance
• Macroeconomics
• Maddison Project
• Market production
• Material Product System
• Measures of national income and output
• Wesley Clair Mitchell
• Modified gross national income
• Monetary Financial Institutions
• Robert R. Nathan
• National Accounts
• National agencies responsible for GDP measurement
• National income
• National income and product accounts
• National Intangible Capital
• Natural capital accounting
• Net (economics)
• Net international investment position
• Net material product
• Net national product
• Net output
• Official statistics
• Operating surplus
• Penn World Table
• Personal income
• Philosophy of accounting
• Primary sector of the economy
• Production (economics)
• Productive and unproductive labour
• Property income
• Quaternary sector of the economy
• Questionnaire
• Real gross domestic product
• Real prices and ideal prices
• Redistribution of income and wealth
• Richard Stone
• Saving identity
• Savings identity
• Secondary sector of the economy
• Sectoral balances
• Sectoral output
• Simon Kuznets
• Social accounting
• Social accounting matrix
• Social reserves
• Statistical survey
• Stock and flow
• Sudden stop (economics)
• Survey (human research)
• Survey data collection
• Survey methodology
• Survey of production
• Sustainability accounting
• System of Environmental and Economic Accounting for Water
• System of Integrated Environmental and Economic Accounting
• Tertiary sector of the economy
• Jan Tinbergen
• United Kingdom National Accounts – The Blue Book
• Value added
• Wages and salaries
• Wagner's law
• War finance
• Wassily Leontief