System of National Accounts

The System of National Accounts (often abbreviated as SNA; formerly the United Nations System of National Accounts or UNSNA) is an international standard system of national accounts, the first international standard being published in 1953.^[1] Handbooks have been released for the 1968 revision, the 1993 revision, and the 2008 revision.^[2] The System of National Accounts 2025 (SNA 2025) was adopted by the United Nations Statistical Commission at its 56th Session in March 2025, as the new international statistical standard for national accounts statistics. The SNA 2025 manual is available in draft form, but the final text has not yet been published.^[3]

The System of National Accounts, in its various released versions, has now been adopted by more than 200 countries and areas, often with some adaptations for unusual local circumstances. The SNA social accounting system continues to evolve, and is maintained with the cooperation of the United Nations Statistics Division, the International Monetary Fund, the World Bank, the Organisation for Economic Co-operation and Development, and Eurostat. All these organizations have a vital interest in internationally comparable economic and financial data.

The aim of SNA is to provide an integrated, complete system of standard accounts for the purpose of economic analysis, policy-making and decision-making. When individual countries use SNA standards to guide the construction of their own national accounting systems, it results in much better international comparability. Adherence to the international standards is in principle voluntary, and cannot be rigidly enforced. But cooperation has a lot of benefits in terms of gaining access to data, exchange of data, data dissemination, cost-saving, technical support, and scientific advice for data production.

Eurostat uses a version of the SNA for the European Union, called the European System of Accounts (ESA). Participation in the ESA system is obligatory for European Union member states. The National Income and Product Accounts (NIPA) used uniquely in the United States features broadly the same concepts as SNA, but differ significantly from the SNA in details of methodology, classifications and presentation. The similarity between the SNA and the NIPA exists, because the original design of the SNA in 1953 was modeled on the NIPA system that was already created earlier. Since 1993 the American Bureau of Economic Analysis has made an effort to achieve greater conceptual consistency with SNA standards. The differences in data and presentation between the 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.

Publication of data

Economic and financial data from UN member countries are used mainly to compile comparable annual (and sometimes quarterly) data on the gross product, national income, investment, capital transactions, government expenditure, and foreign trade. The results are published nationally but also in two UN Yearbooks: (1) National Accounts Statistics: Main Aggregates and Detailed Tables and (2) National Accounts Statistics: Analysis of Main Aggregates. From 2025 onward, the yearbooks are published in line with the SNA 2025 standards.

The values provided in the UN national accounts yearbooks are cited in the national currency. The same data in US dollar equivalents may however be available from other agencies such as the IMF, OECD, World Bank, Eurostat or other UN agencies etc. The IMF publishes the most comprehensive SNA-based Balance of Payments statistics for the world's countries. The OECD and the World Bank publish a lot of SNA-based comparative economic statistics and country reports. To make the comparisons, the data series have to be converted to a common currency.

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

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. Because national accounts data is notoriously prone to revision (since it involves a very large number of different data sources, entries and estimation procedures that have impact on the totals), discrepancies can occur between the totals cited for the same accounting period in different publications issued in different years. The "first final figures" may in fact be retrospectively revised several times, because of necessary corrections, new data sources and methods, or conceptual changes. The revisions may be quantitatively slight, but cumulatively across e.g. ten years they could sometimes alter a trend significantly. This is something the researcher has to bear in mind in seeking to obtain a consistent data set. Usually, it's best to check out first what the most recent data releases and the latest revisions are. Often it is possible to link old and new data series using some some suitable technique.

Quality and coverage

In general, SNA data quality is usually quite good, because the data are regularly checked and controlled by several agencies, and not just by the data producers. Nevertheless, the quality and comprehensiveness of national accounta data that are available can differ between countries. Among the reasons are that:

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

Although the United Nations has rather little power to enforce the actual production of statistics to a given standard in member countries, even if international conventions are signed, some of the world's states are part of international unions (for example the European Union, the OECD, or the United States), which oblige member states of the union to supply standardized data sets, for the purpose of inter-state or international comparisons and coordination. In exchange for supplying data, countries also receive foreign data and expert scientific advice. So there are incentives and benefits for countries to cooperate, for the sake of obtaining more comprehensive, 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 decision-making.

The main accounts in the SNA system

SNA traditionally includes the following main accounts:

• the production account (components of gross output)
• the primary distribution of income account (incomes generated by production)
• the transfers (redistribution) account (including social spending)
• the household expenditure account
• the capital account
• the (domestic) financial transactions account ("flow of funds")
• the changes in asset values account
• the assets and liabilities account (balance sheet)
• the external transactions account (balance of payments)

These basic accounts are complemented with various annexes, sub-accounts, satellite accounts or supplementary tables, and standards are also provided for input-output tables showing transactions between production sectors within each nation.

Almost all member countries of the United Nations provide income and product accounts, but they do not necessarily provide a complete set of SNA standard accounts, or a complete set of data. For example, standardized assets and liabilities accounts for households hardly exist, and remain to be developed. In some countries, it is practically or technically not yet feasible to produce many ancillary accounts, or it is too costly for them to do that.

A recent development was the attempt to create standard accounts of strategic stocks of natural resources.^[4]

Developments

SNA continues to be developed further. International conferences are regularly held to discuss various conceptual and measurement issues, and proposed revisions. The proposed SNA 2025 features many new standards for supplementary SNA tables on different topics.^[5] 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 labour use, natural resources, productivity, health etc.).

There are many ongoing projects, such as developing standard accounts for environmental resources, the measurement of the trade in various services and of capital stocks, the treatment of insurance payments, the grey economy, employee compensation in the form of non-wage income, intangible capital, cryptocurrencies, labour economics etc.

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.^[6]

Discussions and updates are reported in the news bulletin SNA News and Notes.^[7] Official SNA Revisions are always documented at the UN Statistics Division site.^[8]

For the 2008 SNA Revision, the full final text is available online.^[9] For the 2025 Revision, only the proposed document is available so far; the final text still has to be approved.^[10]

Achievements of SNA

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

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

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

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

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

Debates

The SNA data is used by tens of millions of public servants, private data professionals, businesspeople and academics worldwide. Without SNA data (whether published by the UN, or published by other agencies), they would not have internationally comparable data on the economy of different countries. So the data users appreciate that the information is available. But SNA has also been criticized for its shortcomings, which is to be expected.

With so many users of SNA data worldwide, and given the limits of what the SNA accounts can provide, 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.^[11] 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. For example, there are the following sorts of criticism:

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

The 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.

• Many concerns about the data needs of particular sectors of society are being addressed via the design of supplementary standard tables, which provide modified SNA aggregates for special uses, or integrate SNA accounts data with social or environmental data. 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 needs.

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

• There are now more and more different ways to make data available to users, and much more attention is given to information design to make data understandable. Data means nothing, if it is not communicated in an effective way so that people can understand it.

Criticism of GDP

The most popular criticism of national accounts concerns the concept of gross domestic product (GDP). GDP is criticized for what it does not measure, or because it allegedly mismeasures the national economy. Economists like Joseph Stiglitz have argued that a measure of "well-being" is needed to balance a measure of output growth.^[12] Such measures have already been designed, but so far they have not been widely included in SNA accounts. However, SNA 2025 broadens the national accounts framework, to account beter for elements affecting wellbeing and sustainability, for the purpose of informing various policy goals of governments and international organizations.

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

The main response by statistical authorities to such criticism and abuse has not been to abandon or abolish GDP data, but instead to provide additional, complementary data about phenomena which GDP does not measure, and cannot measure. With this approach, most data users can get the data that they want, most of the time, without denying the data needs of other users. There are human restrictions on the types 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 criticised as biased by feminist economists such as Marilyn Waring^[13] and Maria Mies^[14] 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 the accounts do include things like the "imputed rental value of owner-occupied dwellings"^[15] and the "nominal bank charge".^[16] This SNA omission is said to obscure the reality that market production depends to a large extent on non-market labour being performed. In turn, that lacuna in the data promotes a distorted picture of economic life (which includes both paid and unpaid work).

However, such criticism raises several technical questions for the statisticians who would have to produce the data:

• whether an international standard method of comparing the value of household services is technically feasible, given e.g. that the conditions under which the market equivalents for unpaid household services are supplied vary greatly between countries. ^{[citation needed]};
• whether making imputations for women's voluntary work would result in truly meaningfu and uniform measures.^{[citation needed]};
• 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.^{[citation needed]}

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

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

When she was the head of the International Monetary Fund, Christine Lagarde claimed at an IMF/World Bank annual meeting in Tokyo (October 2012) that women could rescue Japan's stagnating economy, if more of them took paid jobs instead of doing unpaid care work. A 2010 Goldman Sachs report had calculated that Japan's GDP would rise by 15 percent, if the participation of Japanese women in the paid labour force was increased from 60 percent to 80 percent, matching that of men.^[17] The difficulty with this kind of argument is, that domestic and care work would still need to be done by someone, meaning that either women and men would need to share household responsibilities more equally, or that parents would have to rely on child and eldercare supplied by paid caregivers from the public sector or the private sector. The majority of young people with young children cannot afford to hire caregivers themselves. According to the ILO, there were in 2013 more than 52 million domestic workers in the world, who mostly work for little pay, and with little legal protection.^[18] They are mainly servants of the wealthy and the middle class.

Marxist critique

Marxian economists have criticized SNA concepts also from a different theoretical perspective on the new value added or value product.^[19] On this view, the distinctions drawn in SNA to define income from production and property income are rather capricious or eclectic, obscuring thereby the different components and sources of realised surplus value; the categories are said to be based on an inconsistent view of newly created value, conserved value, and transferred value (see also double counting). The result is that the true profit volume is underestimated in the accounts – since true profit income is larger than operating surplus – and workers' earnings are overestimated since the account shows the total labour costs to the employer rather than the "factor income" which workers actually get. If one is interested in what incomes people actually get, how much they own, or how much they borrow, national accounts often do not provide the required information.

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

US government statisticians admit frankly that "Unfortunately, the finance sector is one of the more poorly measured sectors in national accounts".^[20] The oddity of this is, that the finance sector nowadays dominates international transactions, and strongly influences the developmental path of the world economy. So, it is precisely the leading sector in the world economy for which systematic, comprehensive, and comparable data are not available.

Statisticians' critical views

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

For example, Jochen Hartwig provides evidence to show that "the divergence in growth rates [of real GDP] between the U.S. and the EU since 1997 can be explained almost entirely in terms of changes to deflation methods that have been introduced in the U.S. after 1997, but not – or only to a very limited extent – in Europe".^[21]

The "magic" of national accounts is that they provide an instant source of detailed international comparisons, but, critics argue, on closer inspection, the numbers are not really so comparable as they are made out to be. The effect 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 untenable (or at the very least rather dubious).

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

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

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

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

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

See also

• Capital formation
• China GDP – Dr. Fengbo Zhang introduced the Western economics, GDP, and SNA system to China, and replaced Soviet Union's MPS system.
• Compensation of employees
• European System of Accounts
• Gross fixed capital formation
• Human Development Index – an alternative way of measuring progress.
• Intermediate consumption
• Macroeconomics
• Material Product System
• Measures of national income and output
• National agencies responsible for GDP measurement
• National income and product accounts
• Productive and unproductive labour